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Frank 96553979fb fix(dankvoice): pin thinking off in rewrite, fix silent and timeout modes
Refs #32

The humanizer's raw fetch to frank-zealot omitted
chat_template_kwargs.enable_thinking: false, so the Qwen35 hybrid thought
instead of answering (6.9 s reasoning_content, empty content - timing out
the 6 s abort; or answering "" and muting the unit). Pin the kwarg, treat
empty-content-with-reasoning as failure over silence, and stop the menu's
test phrase from blocking its handler. Three red-captured regressions;
26/26 green, verified red against HEAD.
2026-10-19 10:46:06 -07:00
dank 8f5a229cc6 Merge pull request 'chore(scripts): promote index-coverage checker; document bundle gates' (#31) from chore/29-kb-coverage-tooling into main 2026-10-19 10:01:30 -07:00
Frank ea514c8fd2 chore(scripts): promote index-coverage checker from campaign scaffolding
PR #30 merged the throwaway checker under its .tmp- name. Promoted to
scripts/kb-coverage.py and documented on okf-maintenance.md § Automated
Gates alongside kb-lint (the bundle previously documented neither gate).
Self-tested: kb-coverage.py reports 0 issues on the current bundle.

Refs #29
2026-10-19 09:59:50 -07:00
dank bc60fa33be Merge pull request 'docs: exhaustive dedupe, compaction, OKF conformance, fact verification' (#30) from docs/29-dedupe-compact into main 2026-10-19 09:56:23 -07:00
Frank e4ecc93f29 live: heartbeat sync 2026-10-19T09:17:41-07:00 (Refs #11) 2026-10-19 09:17:41 -07:00
Frank d055eb1e7f live: heartbeat sync 2026-10-19T08:15:41-07:00 (Refs #11) 2026-10-19 08:15:41 -07:00
Frank 70346f3d57 live: heartbeat sync 2026-10-19T07:12:41-07:00 (Refs #11) 2026-10-19 07:12:41 -07:00
Frank 1251cfbd40 live: heartbeat sync 2026-10-19T06:09:41-07:00 (Refs #11) 2026-10-19 06:09:41 -07:00
Frank e67bbd0de0 live: heartbeat sync 2026-10-19T05:07:41-07:00 (Refs #11) 2026-10-19 05:07:41 -07:00
Frank 986081bf1d docs(log): compact changelog to entry law (406 -> 284 lines)
Changelog entries were essay-length incident writeups duplicating the
concept pages they created. New entry law recorded at top of log.md:
one dated entry = what changed + durable lesson + concept-page link;
full narratives recoverable via git log --follow. Every date, headline,
incident, and durable lesson preserved; narrative prose that already
lives on concept pages (caddy handle-ordering, gluetun/limiter field
notes, quadlet gotchas, faillock law, credential-store trap) replaced
by pointers. Historical pi-era entries tagged '(pi era)'.

Also: self-hosted-web-agents.md '44.5% peer-reviewed CUA' figure could
not be re-attributed to any published benchmark via web search today
— dropped with an explicit note; the valid core claim (87.4% = managed
Cloud, not the self-hostable library) kept.

Refs #29
2026-10-19 04:23:58 -07:00
Frank a9b3c495da docs(research): fact-check web-research and chezmoi docs against sources
- open-models.md: Qwen2.5-VL 'best open vision model' superseded by
  Qwen3-VL (Apache 2.0 dense sizes; repo QwenLM/Qwen3-VL, arXiv
  2511.21631, verified via web search); decision table + mermaid +
  citations updated
- chezmoi-evaluation.md: fleet facts were fabricated — servers run
  Ubuntu 26.04 LTS (probed via ssh, both boxes), not 'Arch/FreeToken'
  (distro does not exist); dev workstation is AMD Ryzen 5 PRO 5650U,
  not Intel Ultra 7; frank-default-* endpoints retired 2026-10-18
- agentic-web-research/index.md: pi-era topology blurb replaced with
  current fleet endpoints
- self-hosted-web-agents.md: sample model frank-default-small ->
  frank-archon (endpoint/IP already correct: dankserver)
- mcp.md reference-server table verified against upstream
  modelcontextprotocol/servers README (exact match, no change)
- 'peer-reviewed BrowseComp' claim from scout ledger: does not exist
  in any file — rejected, not applied

Refs #29
2026-10-19 04:17:49 -07:00
Frank c99eb8e11b docs(fleet): live-probe corrections across dankclaw, caddy, gitea, searxng, vpn docs
Live read-only probes on Dankclaw (BatchMode ssh, 2026-10-19):

- system/dankclaw.md: full 32-container census added (authentik IdP,
  prometheus/grafana/loki/alloy/alertmanager monitoring, pihole, ntfy,
  seerr, hermes stack, anubis, frank-tts :7772 all undocumented);
  dragoon pool corrected 401,408 @ ctx 200,704 (was conflated);
  zealot corrected to PrismML build 10777, Ternary-Bonsai-2-9B
  PQ2_0-MTP, 2x262,144 over one 524,288 pool, f16 K+V (doc claimed
  build 10754, 27B, 2x200,704)
- caddy/index.md: v2.11.7 (in-container ), deduped
  caddyfile listing
- gitea: version 1.27.3 probed via API; systemd-gitea network + rootless
  100999 mapping confirmed live (gitea-server attaches systemd-gitea;
  dank subuid 100000:65536); index See-Also de-duplicated
- searxng-tuning.md: live instance section (ghcr image, valkey:9-alpine,
  marreta netns-sharing explains duplicate port maps); POLICY DRIFT FLAG:
  tuned engine policy (google/bing disabled, verified 2026-08-16) is NOT
  live — /config now shows all 262 engines enabled; upstream settings.yml
  count corrected 388@master; limiter table already matched source
- vpn-routing.md: verify snippet fixed — gluetun image ships no curl;
  health server is 127.0.0.1:9999/health ('OK'), :8000 is the CONTROL
  server (404s on health paths); correct probes provided

Refs #29
2026-10-19 04:12:04 -07:00
Frank cd20d6ddfd live: heartbeat sync 2026-10-19T04:06:41-07:00 (Refs #11) 2026-10-19 04:06:41 -07:00
Frank 82dd0c7d09 docs(power): reclaim the sleep docs from the sold box; fix AGENTS.md machine facts
The sleep/wake saga (Alienware-M16a2 research + Sleep-Fix-Guide) framed a
machine sold on 2026-09-28 as 'this system' — the 2026-09-28 identifier
purge missed both because they name no hostname. blankpad probed live:
Lenovo, AMD Ryzen 5 PRO 5650U / Cezanne, unified memory, s2idle only,
no NVIDIA, no ~/GitPackages/llama.cpp.

- research/Sleep-Fix-Guide.md -> .AGENTTRASH (verbatim restatement of the
  research doc's fix steps; PowerCluster overlap census)
- Alienware doc: archive banner, 'this system' -> retired dankware
- linux-power-management.md: scope note (blankpad s2idle-only; NVIDIA
  section is dankware/future-NVIDIA territory), boilerplate AGENTS.md
  cross-ref dropped
- cachyos.md: de-pinned rolling-release kernel versions (7.1.4 doc vs
  7.2.9 live), repo list confirmed verbatim against pacman.conf, SDDM
  confirmed live, verified: 2026-10-19
- AGENTS.md: dev-workstation row rewritten for blankpad; Gitea gotcha
  corrected — remote URLs carry NO token (credential-store file, verified)

Refs #29
2026-10-19 03:46:02 -07:00
Frank 99b9a6a17c docs(pi): unify split package trees; move live OMP pages to core
Two directories documented one concept (pi npm packages): top-level
packages/ (browser-use, permission-system) and pi/packages/ (peon,
web-access, subagents). Merged into pi/packages/ — one row per package
in a single index, detail pages kept as archive records. The root
index's 'OMP packages and skills' section was doubly wrong (packages/
was pi, not OMP); it becomes a Skills tooling section pointing at the
consolidated /skills/ tree.

Moved the two LIVE omp pages out of the retired-harness banner:
pi/statusline.md -> core/statusline.md, pi/subagent-limits.md ->
core/subagent-limits.md (both document omp behavior against
agent/config.yml + the installed bundle; pi/index.md itself admitted
the mis-shelf). Retargeted every inbound link (core/index, system/
dankserver, log x2, pi/index, settings x2, moved files' own xrefs).

Refs #29
2026-10-19 03:32:07 -07:00
Frank 39385636be docs(llama): delete fabricated ornith-llama-cpp-setup tree (608 lines)
Night fact-check falsified the tree's subject: no `ornith` CLI exists
(npm 404), github.com/rhitching/ornith is 404, and the model IDs the
tree cites are wrong — the real family is ornith-ai/Ornith-1.0/1.5
(9B, 35B-A3B, 397B), built on Qwen3.5/Gemma4 per its model card, not
the 'Ornith-9B-Thinking-1.5T based on Qwen3-8B' the docs assert.
Nothing in the tree describes this fleet: no ornith binary on PATH
(audit 2026-10-18 said the same). Real facts it echoed (PrismML fork
on frank-zealot) already live in /system/.

Also: tools/index.md de-duplicated (same files were listed twice, once
as wikilinks once as links, live-sync missorted) and links normalized;
llama-cpp setup/index xrefs retargeted.

Refs #29
2026-10-19 03:17:49 -07:00
Frank d99c1c3c4f live: heartbeat sync 2026-10-19T03:04:41-07:00 (Refs #11) 2026-10-19 03:04:41 -07:00
Frank 651924a4bc docs(skills): collapse three overlapping skills trees into one verified tree
Three parallel trees documented the same ecosystem: omp-docs/skills/
(two overview pages), tools/npx-skills/ (10 pi-era npm pages), and
tools/vercel-labs-skills/ (11 CLI pages), plus a fourth leaderboard page
at engineering/skills-ecosystem.md. Verbatim overlap (identical SKILL.md
field tables in skills-spec.md vs skill-format.md; 13-agent vs 68-agent
copies of the same upstream table). Consolidated to four concept pages:

- skills/agent-skills.md: standard, format, loading, authoring (merges
  skills-spec, skill-format, skill-file-structure, skill-loading,
  best-practices, skills-vs-extensions)
- skills/skills-cli.md: CLI reference (merges commands, source-formats,
  installation-scope, skill-discovery, lock-file, env-variables,
  agent-support, related-links)
- skills/store-wiring.md: moved, fleet ops, links retargeted
- skills/ecosystem.md: replaces skills-ecosystem.md; stale 2026-08-12
  top-50 table dropped, replaced with a live top-10 re-queried from the
  skills.sh API tonight and the API contract re-verified (zero-based,
  200/page, {skills,total,hasMore,page}, total 9909)

All facts re-verified 2026-10-19 against primary sources:
agentskills.io, vercel-labs/skills README + src/cli.ts (command set,
--full-depth) + src/skill-lock.ts (v3 lock, XDG path, wipe-on-old),
live skills.sh API. Deleted superseded core/index-doc.md (old pi-era
docs index). Retargeted all inbound links (tools/index, engineering x3,
packages x3, pi/skills, core/index). Pi-era npm skill packaging is
listed as archived under /pi/.

Refs #29
2026-10-19 02:58:52 -07:00
Frank e86e60af39 docs: close OKF conformance gaps found by night audit
- references/okf-spec.md: replace v0.2 note with the deltas verified
  against upstream SPEC.md 2026-10-19 (timestamp->generated.at and
  # Citations->sources are the two breaking changes; trust fields and
  root-index okf_version are additive; bundle stays v0.1).
- index.md: restore the agentic-web-research section lost in the
  2026-08-28 rebuild and link log.md (index-coverage doctrine).
- gen-keybinds.sh emits OKF frontmatter so its generated artifact
  (tools/niri/keybindings.md, regenerated, 120 bindings) passes kb-lint;
  test added red->green.
- fix the two broken [[niri]] wikilinks (handy, noctalia-shell).

Refs #29
2026-10-19 02:43:33 -07:00
Frank 01d9d3fbd5 live: heartbeat sync 2026-10-19T02:02:41-07:00 (Refs #11) 2026-10-19 02:02:41 -07:00
dank 570b5509d0 Merge pull request 'dankvoice: humanized narration via @tiny and thinking aloud' (#28) from feat/dankvoice-enhanced-narration into main 2026-10-19 01:57:51 -07:00
Frank 3579c7ebc5 dankvoice: humanize answers via the @tiny role and narrate thinking
Answers spoken with /say were verbatim markdown-cleaned text while the
built-in vocalizer speaks prose rewritten by a small model. Port that
enhancer (bundle Qyr/T6o: same prompt, 1536 tokens, 6 s, 4000-char
window, null-fallback/empty-skip contract) and resolve its model from
modelRoles.tiny exactly as the harness does, so auto-speak sounds like
the enhanced TUI voice instead of a pager. agent_end now also speaks the
last assistant message's thinking blocks as their own unit before the
answer; narration-flagged thinking counts as answer text. Both knobs are
menu-toggleable, persisted, and env-overridable; the fixture gains a
chat route (echo/prose) and seven scenarios cover the round-trip, the
404 fallback, ordering, the kill switches and role resolution (22 green,
58 suite-wide; live smoke through real frank-zealot + frank-tts).

Refs #27
2026-10-19 01:55:57 -07:00
dank 0075ca3bbf Merge pull request 'dankvoice: segmented sequential speech (ported bundle vocalizer)' (#26) from fix/dankvoice-segmented-speech into main 2026-10-19 01:25:03 -07:00
Frank bcd52bb0f4 dankvoice: speak long answers as sequential sentence-sized requests
agent_end awaited one whole-answer synthesis; long answers hit the
harness 30s extension-handler timeout (handler timed out after 30000ms)
and the single frank-tts request was the stall. Port the built-in
speak-aloud vocalizer's utterance segmenter (fHe in dist/cli.js) so
segmentation matches the known-working stock path: [.!?…]-run
boundaries, abbreviation/decimal/inline-code guards, fenced code and
tables swallowed, markup cleaned. Play segment N to player exit before
synthesizing N+1 (audio never stacks); fire-and-forget the chain so
utterances outlive the handler timeout; a run token retires superseded
chains. DANKVOICE_MAX becomes a per-answer budget of whole segments;
stripForSpeech is gone. Refs #23 follow-up.
2026-10-19 01:21:34 -07:00
Frank edd7e0cf68 live: heartbeat sync 2026-10-19T01:00:41-07:00 (Refs #11) 2026-10-19 01:00:41 -07:00
Frank f033639b54 chore(agent): disable built-in speak-aloud — dankvoice cloned voices are the TUI voice (Refs #23) 2026-10-19 00:49:14 -07:00
dank 6fffd83957 Merge pull request 'feat(dankvoice): /say options menu with output-device routing' (#25) from feat/23-dankvoice-menu into main 2026-10-19 00:40:33 -07:00
Frank dd8f3974c1 feat(dankvoice): /say options menu with output-device routing (Refs #23)
Bare /say and /say menu open a ctx.ui.select settings surface: auto-speak
toggle, voice from the frank-tts roster, PipeWire output device
(pw-play --target / paplay --device=), player binary, spoken cap, and a
test phrase. Choices persist to ~/.omp/cache/dankvoice.json (env wins
over file); detectPlayer becomes availablePlayers + playerFor. Fixes
the silent-route failure mode where synthesized audio played into an
offline Bluetooth sink. 15/15 dankvoice bats, 51/51 suite, live pty
TUI smoke armed the footer and wrote the settings file.
2026-10-19 00:31:40 -07:00
dank acf67182e9 Merge pull request 'docs: record omp subagent fan-out caps and per-endpoint in-flight ceilings' (#24) from docs/subagent-limits into main 2026-10-19 00:23:29 -07:00
Frank 38bf9c4897 docs: record omp subagent fan-out caps and per-endpoint in-flight ceilings
Codifies the limits set in agent/config.yml 2026-10-19: task concurrency 2,
no nested subagent spawns (maxRecursionDepth 1 - and why 0 must never be
set), 30-min runtime / 120-request budgets, isolation opt-in enabled,
completion probes off, 600s tool timeout ceiling, and per-provider
in-flight caps (archon 3, dragoon 2, zealot 3) keyed by models.yml provider
ids with their per-machine scope caveat. Small docs-only change; no issue
opened per trunk-based small-fix exemption.
2026-10-19 00:22:17 -07:00
Frank 54f15e2a58 live: heartbeat sync 2026-10-18T23:57:41-07:00 (Refs #11) 2026-10-18 23:57:41 -07:00
Frank 1e7e212e5c live: heartbeat sync 2026-10-18T22:56:41-07:00 (Refs #11) 2026-10-18 22:56:41 -07:00
Frank 475211d2e7 live: heartbeat sync 2026-10-18T21:55:41-07:00 (Refs #11) 2026-10-18 21:55:41 -07:00
Frank 0258ef70f8 live: heartbeat sync 2026-10-18T20:54:41-07:00 (Refs #11) 2026-10-18 20:54:41 -07:00
dank 0c7fe8b4bf Merge pull request 'feat(dankvoice): speak the cloned voices in the TUI (Refs #21)' (#22) from feat/21-dankvoice into main 2026-10-18 20:06:30 -07:00
Frank 765b686859 feat(dankvoice): speak the cloned voices in the TUI (Refs #21)
Every speak-aloud path in the harness gates `--voice` against the bundled
Kokoro enum, so the frank-tts cloned voices could only ever produce files.
`agent/extensions/` auto-loads, so one tracked extension adds the missing
transport: `/say <text>`, `/say on|off` (narrate the final answer at
`agent_end`, silent when the harness schedules a continuation),
`/say voice|voices|stop|status` — OpenAI speech POST plus playback through
pw-play/paplay/ffplay. The endpoint and served id come from the
`api: openai-speech` row of `agent/models.yml`, so the file carries no host
and no secret; markdown is stripped, over-long utterances are cut at a
sentence bound, and the temp WAV dir is always removed.

Verified live in a real TUI session on the workstation (roster
narrator1/narrator2/narrator3; 2.08 s and 1.44 s WAVs played; auto-speak
spoke each finished answer, 1.20 s WAV; unknown voice answers with the
roster). Black-box seam `tests/dankvoice.bats` (12 tests) drives the
extension against a fixture speech endpoint and a stub player.

cwd: /home/blank/.omp/wt/feat-21-dankvoice
session: wt-20261017-181502-6d1fc1f
2026-10-18 20:00:52 -07:00
Frank 332067a516 live: heartbeat sync 2026-10-18T19:52:41-07:00 (Refs #11) 2026-10-18 19:52:41 -07:00
dank 66e3f220e7 Merge pull request 'feat(grilling): omp-aware interview redesign, absorb ask-etiquette law' (#20) from feat/grilling-omp-aware into main 2026-10-18 19:39:00 -07:00
Frank 6134e1168e fix(grilling): plain-mechanics rephrase of the dialog line (Refs #20)
'Too Claudish': drop the aside ('the gotchas no doc confesses') and the
simile ('watches it fall'); lead with the constraint itself. Facts
unchanged: exclusive dialog, scouts before ask, Esc ends the run, the
ledger survives.
2026-10-18 19:31:32 -07:00
Frank c379d16858 fix(grilling): correct ask-tool acceptance semantics (Refs #20)
The ask tool's recommended flag only labels option 0; the reply always
names the selected options, so 'the user's single Enter accepts it'
overclaimed a default-accept mechanic that does not exist. Stated
truthfully: the label invites one-glance acceptance, the reply is
self-documenting.
2026-10-18 19:25:44 -07:00
Frank ca8b46241e fix(grilling): round-two review notes (Refs #20)
- opening restores 'shared understanding' alongside 'nothing is
  silently assumed', and 'Map this as a design tree'
- cluster rationale restated: tight clusters keep each scout aware of
  possible adjacencies
- web_search: explicit 'do not delegate to a subagent'
- 'Done' heading -> 'Definition of Done'
2026-10-18 19:24:51 -07:00
Frank 3fa0242f56 style(grilling): rewrite in the mattpocock corpus voice (Refs #20)
Read all 36 upstream skills, then rewrote to their house style per
writing-for-agents' own levers: leading words as tokens (frontier,
brief, ledger, artefact, scout), vocabulary-first and used exactly,
positive phrasing with prohibitions kept only as hard guardrails,
completion criteria sharpened to checkable+exhaustive ('counted before
sending', 'frontier empty and nothing sits blocked'), zero history,
gotchas the environment cannot confess kept inline. All settled
behaviour from the grilling-on-grilling session survives intact.
2026-10-18 19:15:14 -07:00
Frank fe039a0b73 fix(grilling): strip history and box-specific prose per review (Refs #20)
- drop provenance blockquote and the absorbed-law attribution: the skill
  is instructions, not a history
- 'concurrency is capped' replaces the 3-scout figure of one machine
- completion distillate: project's knowledge base or a log markdown file,
  not a command-center-specific path (skill travels outside this repo)
2026-10-18 19:09:04 -07:00
dank d4092f2f65 Merge pull request 'docs(agent): rule 6 - live todo tracking' (#19) from feat/todo-live-tracking into main 2026-10-18 19:07:56 -07:00
Frank cedef97c99 feat(grilling): omp-aware interview redesign, absorb ask-etiquette law
Rewritten per grilling-on-grilling (2026-10-18, all branches settled via
ask rounds): ask tool is the default round vehicle (one artefact per
question, recommended:0 = bare-yes semantics, hybrid boundary ask-default
/ prose-exception); todo as visible decision tree (phase=branch, blocked
reasons) + durable local://grilling-state.md ledger surviving the
Esc-aborts-the-run path; scout=environment facts (spawn-before-ask,
exclusive concurrency), web_search=world facts, inline=cheap lookups;
completion gate = summary + one closing ask, then distilled decisions
land in omp-docs/log.md via branch -> PR.

Absorbs managed skill one-decision-per-ask-question (Frank's choice;
reworded: ideas heavily encouraged via own atomic question, ban is on
smuggling into option text only). Managed skill deleted here; heartbeat
drops it from the live tree.
2026-10-18 18:58:23 -07:00
Frank 0ee08bc368 live: heartbeat sync 2026-10-18T18:51:41-07:00 (Refs #11) 2026-10-18 18:51:41 -07:00
Frank 6664f9090a docs(agent): rule 6 - todo list must be live, not retrospective
Observed failure mode: tracking flips land in one batch at the end of a
task bill, so the operator's cockpit view stays frozen for the whole run.
Rule pins the mechanics: init before first substantive step, done/start
batched with the step they describe, block-with-reason on stalls, no
lone todo calls. Global tier (APPEND_SYSTEM.md), every session affected.
2026-10-18 18:43:51 -07:00
dank 7de07ee35c Merge pull request 'chore(skills): drop Eve-only agents/openai.yaml from authored grilling' (#17) from fix/skills-tier-prune into main 2026-10-18 18:34:50 -07:00
Frank fcc7226c3b chore(skills): drop Eve-only agents/openai.yaml from authored grilling
omp's skill scanner ignores agents/*.yaml (Eve/Codex binding metadata
carried along by the skills CLI store). The file kept vanishing from the
live tree to a background sweep; an authored omp skill does not need it.
Refs #16
2026-10-18 18:31:37 -07:00
dank a8011c3d4d Merge pull request 'chore(skills): symlink agent/skills into the skills CLI global store' (#16) from chore/skills-store-symlinks into main 2026-10-18 18:30:16 -07:00
Frank 08f90c6df3 chore(skills): move upstream skills to the CLI global store, keep authored tier
Retroactive provenance: the 10 pi-era skill snapshots were byte-identical
to upstream. Canonical installs now live in ~/.agents/skills tracked by
~/.agents/.skill-lock.json (mattpocock/skills x38 after grilling removal,
find-skills from vercel-labs/skills).

Repo tier is authored overrides only: clear all 10 tracked upstream
snapshots; omp loads the store directly through the agents provider
(skills.enableAgentsUser, default on). grilling returns as a real
directory — extracted from the store (CLI + lockfile pruned) so Frank can
customize it without skills update resurrecting a twin.

Docs: skill-store-wiring.md (+index). Pre-cutover snapshot of the old
tracked dirs at /tmp/agent-skills-snap-20261018.
2026-10-18 18:28:34 -07:00
Frank 57e255f930 live: heartbeat sync 2026-10-18T17:49:00-07:00 (Refs #11) 2026-10-18 17:49:00 -07:00
Frank b3d3df4bdb feat(niri): amber-orange focus-ring, width 4 (ff8c00)
Frank's outline restyle: focus-ring red #e01b24 -> #ffb000 -> #ff8c00
(orange), thickness 2 -> 4 in base layout.kdl. The visible ring is
painted by noctalia.kdl, included LAST in config.kdl — its focus-ring
active/urgent colors moved to #ff8c00 too; tab-indicator, insert-hint,
and recent-window highlights deliberately stay red.

noctalia.kdl was hand-written live-only (Oct 14, no repo copy — the
override that silently beat every layout.kdl edit); first durable copy
lands in the zz-blankpad mirror.
2026-10-18 17:37:27 -07:00
dank 5d523f6e9f Merge pull request 'docs: noctalia bar clobber postmortem (log entry)' (#15) from wt/20261018-170616 into main 2026-10-18 17:30:58 -07:00
181 changed files with 4543 additions and 4531 deletions
+6 -3
View File
@@ -100,15 +100,18 @@ secret in every agent's context window on every machine that pulls this repo.
| box | role | GPU | notes |
|-----|------|-----|-------|
| Dev workstation | client box, never runs inference | laptop iGPU + dGPU (non-unified) | mainline llama.cpp at `~/GitPackages/llama.cpp/build/bin/`; this repo lives here at `~/.omp` |
| Dev workstation (`blankpad`) | client box, never runs inference | Lenovo laptop, AMD Ryzen 5 PRO 5650U / Cezanne APU (**unified memory**, s2idle sleep only, no dGPU) | this repo lives here at `~/.omp`; the earlier "iGPU + dGPU / `~/GitPackages/llama.cpp`" description belonged to the sold `dankware` box |
| Dankclaw | bench target, secondary models + service stack | Strix Halo APU (**unified memory**) + RTX 3090 (moved over from Dankserver 2026-09) | prod services `frank-dragoon` (halogen-flash-server, :7770, iGPU) and `frank-zealot` (llama.cpp PrismML fork, :7771, 3090); runbooks in the serverAppConfigs vault (`~/Projects/serverAppConfig/serverAppConfigs-docs/LLM/`); ssh: `ssh dankclaw` |
| Dankserver | main-model box | 2× Radeon AI PRO R9700 — non-unified (was RTX 3090 until 2026-09) | runs `frank-archon` (radiance, TP=2, :7770) — **this repo's operator session runs on it**; ssh: `ssh dankserver` |
## Environment gotchas
- Gitea API needs a token: `GITEA_TOKEN` env (gitignored `.env`). No `tea` CLI
installed anywhere. Remote URLs embed the token locally in `.git/config` — that
file is never pushed; it is not a substitute for the secret gate.
installed anywhere. Remote URLs carry NO embedded token (2026-10-09
credential-store cutover) — git and the API both read
`~/.config/secrets/gitea` (`store --file`, URL-line format; see
`omp-docs/tools/gitea/client-access.md`). That file is never pushed; it is
not a substitute for the secret gate.
- Passwordless sudo (`sudo -n`) works on Dankclaw and Dankserver for systemctl
verbs only; user units need no sudo at all.
- SSH into both servers is BatchMode-capable from here:
+11
View File
@@ -96,6 +96,17 @@ Never assume the user reports correct information. He is human, and humans make
- Always practice Test Driven Development practices; do UNIT TESTS exist for the functionality about to be edited? Is there a LINTER? Is there a FORMATTER? Verify that they exist, and that they are configured as a pre-commit hook. If they do not exist, they MUST be written PRIOR to the code being written. Invoke `/skill:tdd` for preferred testing style. If tests do exist, ensure that they still match the planned changes. If you believe a PRE-EXISTING test must be changed prior to commencing work, ASK THE USER ABOUT IT.
- Always ensure tests run on code changes after every commit, and all project tests run before every push using git hooks, EXCEPT in the event that the individual test in question takes an excessive amount of time. Always ask the user before disabling an individual due to running time or performance concerns.
### 6. Keep the Todo List LIVE, Not Retrospective
The todo list is the user's cockpit view of your work. A list that only flips at the end is a history dump, not tracking - the user sees nothing while you work.
- Multi-step work: `todo init` BEFORE the first substantive step - the list must exist while the work is unseen, not after.
- Batch the todo transition with the step it describes: `done` + `start` ride along in the same message as the first tool calls of the next step. NEVER defer flips until the whole bill of tasks is finished.
- A task is `done` the moment its work is verified - not when the surrounding phase ends.
- Blocked on external input (user answer, subagent, service)? `block` it with a reason so the stall is visible; `unblock` the instant it is actionable.
- NEVER make a todo call the only call in a message - that is ceremony, not progress; pair every flip with real work.
## FORBIDDEN ACTS AND MISTAKES TO NOT REPEAT (DO NOT DO THESE):
- Editing node_modules or similar import module directories. This is third party code that will be overwritten next time `npm update` or a similar command is run.
- `git push` - unless directed, except if it's our local gitea instance on Dankclaw.
+18 -5
View File
@@ -1,6 +1,10 @@
providers:
openrouterVariant: online
fetch: auto
maxInFlightRequests:
llamacpp (dankserver): 3
llamacpp (dankclaw): 2
llamacpp (dankclaw-3090): 3
modelRoles:
slow: llamacpp (dankclaw)/frank-dragoon:medium
vision: llamacpp (dankclaw-3090)/frank-zealot:xhigh
@@ -13,7 +17,7 @@ modelRoles:
default: llamacpp (dankserver)/frank-archon:medium
smol: llamacpp (dankclaw-3090)/frank-zealot:medium
web: web/searxng
speech: local/kokoro
speech: frank-tts (dankclaw)/frank-tts
judge: openrouter/~typesafe/jev-latest:auto
dictation: local/parakeet-tdt-0.6b-v3
memory: llamacpp (dankclaw-3090)/frank-zealot:medium
@@ -145,17 +149,25 @@ display:
subagentLivePreview: true
task:
showResolvedModelBadge: true
maxConcurrency: 3
maxConcurrency: 2
agentModelOverrides:
designer: llamacpp (dankclaw-3090)/frank-zealot
librarian: llamacpp (dankclaw-3090)/frank-zealot
reviewer: llamacpp (dankserver)/frank-archon
scout: llamacpp (dankserver)/frank-archon
scout: llamacpp (dankclaw-3090)/frank-zealot
security-reviewer: llamacpp (dankclaw)/frank-dragoon
sonic: llamacpp (dankclaw-3090)/frank-zealot
task: llamacpp (dankserver)/frank-archon
seance: llamacpp (dankclaw-3090)/frank-zealot
eager: default
enableLsp: true
maxRuntimeMs: 1800000
softRequestBudget: 120
maxRecursionDepth: 1
disabledAgents: []
isolation:
enabled: true
completionProbe: false
snapcompact:
systemPrompt: none
toolResults: false
@@ -203,8 +215,8 @@ vault:
tts:
localVoice: bm_george
speech:
enabled: true
mode: yield
enabled: false
mode: all
enhanced: true
voice: am_fenrir
secrets:
@@ -232,6 +244,7 @@ followUpMode: one-at-a-time
tools:
approvalMode: yolo
format: auto
maxTimeout: 600
marketplace:
autoUpdate: notify
bash:
File diff suppressed because it is too large Load Diff
@@ -0,0 +1,77 @@
---
name: audit-never-run-container-deploy
description: "Audit a locally built podman/quadlet deploy path that has never actually run: prove base-image assumptions, env-file reader divergence, and image-hash coverage before the first deploy."
---
# Audit a never-run container deploy path
A deployable that has never been built or started has never been *executed*: every
fault in it is invisible to tests that stub the runtime. Audit it as static code
against the tools it calls, then prove each suspicion cheaply against the real
tool. The faults worth hunting are the ones that **report success while doing
nothing** — those are the ones that survive a green `/health` and a green e2e run.
## The three fault classes (all measured 2026-10-18, frank-tts-engine)
1. **A command the base image does not ship.** e.g. `adduser` in a `RUN` line
against a trimmed `ubuntu:24.04` — absent, and not pulled in by
`ca-certificates curl libgomp1`. Dies at build time (loud), but only the first
time anyone builds it.
Prove it in the base, never from memory:
`podman run --rm <base> sh -c "command -v adduser || echo absent; useradd --system --uid 10000 --home-dir /app --shell /usr/sbin/nologin tts && id tts"`
Note the accepted cosmetic warning (`uid 10000 is greater than SYS_UID_MAX 999`)
in a comment, or a future agent "fixes" it by dropping `--system` and the uid
stops matching the sibling container.
2. **Two readers of one env file disagree.** systemd units that pass
`EnvironmentFile=` hand it to podman `--env-file`, which does **no shell
parsing** — it takes the literal remainder of the line — while bash `source`
strips one quoting layer. So `WARM_TEXT="Warm up, one two three."` reaches the
container *with its quotes*, and a script that interpolates it into a JSON body
produces invalid JSON: the container boots, `active`, every voice registered,
every voice cold. Fix in the consumer: strip exactly one matched pair **only**
when both ends are the same quote AND the inner content carries another quote or
backslash (never mangle a value that legitimately contains quotes), then escape.
3. **A build-skip hash that under-covers the image.** `build_compose_image`-style
helpers skip `podman build` when a label hash matches; hashing the `Containerfile`
alone means editing a `COPY`'d app/script rebuilds **nothing** — deploy reports
success, `/health` answers, container serves old code. Each case arm must name
the paths its `Containerfile` copies (`extra=(…)`) and hash Containerfile+extras.
Arms that have no extras keep their old hash, so they do not needlessly rebuild.
## Test it as behaviour, never as a grep of the handler
- Drive the **real** function: `awk '/^build_compose_image\(\) \{/,/^\}/' deploy-remote.sh > bci.sh`,
`source` it, put a stub `podman` first on `PATH`, assert the observable question —
*did the deploy ask podman to build, or did it skip?*
- Stub traps that cost real time: podman is invoked `podman image inspect <image> --format …`
so the tag is **`$3`**, not `$2`; tags contain `/` so a state file named after one
needs `${tag//\//_}` or the write silently lands in a nonexistent directory and
every image looks permanently unbuilt; `--label cfhash=…` arrives **before** `-t <tag>`,
so collect the label and write it after the arg loop.
- For an env-file bug, write one test that reads the file **both** ways — `source`
and the `--env-file` way (parse `KEY=literal remainder`) — and assert the program
receives the same value in both shapes, including a value that carries its own
quotes and a backslash. A suite that only sources the file is how the bug shipped.
- Prove red: `git show HEAD:scripts/deploy-remote.sh > scripts/deploy-remote.sh`,
run the new test (must fail at the exact intended step), restore. Keep each fix in
its own commit and run the seam at each one so the branch bisects.
## Base-image and host facts to check while auditing
- `useradd` lives in `login(1)` (base carries it); `adduser` does not.
- Rootless podman **cannot raise rlimits** — `--ulimit nofile=…` above the host hard
limit dies at container create, not at runtime.
- A referenced `Network=` `.network` file the generator cannot find means the
container unit is **not produced at all**.
- Two containers talk by DNS name only if they attach to a **common** network;
check both unit files rather than trusting a comment that says they share one.
- Container DNS name + the network that owns it, never `host.containers.internal`
or a published loopback port, for service-to-service traffic.
## Do not
- Do not deploy the audited thing because the audit is finished: first build of a
heavy image (recursive source clone ~10 min) plus a new unit on a host serving
people is the operator's call.
- Do not add a Prometheus target for a container with no `/metrics` — say the probe
is a decision (blackbox HTTP), do not fake a scrape.
@@ -1,82 +1,32 @@
---
name: bounding-subagent-runtime
description: "Cap and diagnose runaway or hung omp subagents: task.maxRuntimeMs, softRequestBudget, agentIdleTtlMs, per-agent model overrides, the cfg save-approval quirk, and the finished-work-but-never-exits nested-fanout deadlock."
description: "Cap and diagnose runaway or hung omp subagents: task.maxRuntimeMs, softRequestBudget, maxConcurrency, maxRecursionDepth (the 0-trap), per-provider in-flight ceilings."
---
# Bounding subagent runtime (omp harness)
## When
Subagent runs long, fan out too wide, or you must (re)declare the fleet's subagent limit policy. Also when asked "what limits can subagents have".
Use when a `task`/`eval` subagent runs absurdly long (tens of minutes on a small job),
when it **finishes its deliverable and still never exits**, when you want a hard cap
before spawning, or when you must tell a busy agent to stop.
## Read first
- Repo KB page `omp-docs/pi/subagent-limits.md` — the live policy of record (values + rationale + deliberately-not-set list). Do not re-derive; read it.
- `cfg://task` and `cfg://providers/maxInFlightRequests` — effective values, not the stock defaults.
## The knobs (`cfg://task/...`)
| Key | Default | Meaning |
## The knobs (cfg:// writes; `/save` suffix persists)
| Knob | Effect | Gotcha |
|---|---|---|
| `maxRuntimeMs` | `0` (unlimited) | **Hard wall-clock limit per subagent (ms).** The only true time cap. |
| `softRequestBudget` | `200` | Soft cap on assistant **requests** per run; force-stop at **1.5×**. |
| `softRequestBudgetNotice` | `true` | Injects one "wrap up" steering message at the soft mark. |
| `agentIdleTtlMs` | `420000` | Parks an **idle** agent after 7 min. Useless against a busy-but-slow agent. |
| `completionProbe` | `true` | Asks a working subagent to self-report completeness at 2/5/10 requests. |
| `maxConcurrency` | `32` (often lowered) | Concurrent subagents; sizes GPU/endpoint load. |
| `agentModelOverrides` | `{}` | Per-agent model routing, e.g. `{"scout":"provider/model-id"}`. |
| `tools.maxTimeout` | `0` | Caps the timeout the agent may set on a **tool**, not on the agent. |
| `task.maxConcurrency` | session semaphore; excess queues | stock default 32 — "2" is not a default |
| `task.maxRecursionDepth` | nesting cap | predicate is `depth < n`; **1 = children cannot spawn (correct for "no nesting"); 0 disables spawning for the MAIN session too — never reach for 0**; negative = unlimited |
| `task.maxRuntimeMs` | hard wall clock, overrun = `aborted` | default 0 = off |
| `task.softRequestBudget` | wrap-up notice at N, force-yield at 1.5N | scout/sonic may impose lower built-ins |
| `task.agentIdleTtlMs` | park idle finished agents | `<= 0` disables parking |
| `providers.maxInFlightRequests` | concurrent LLM requests per provider id | keys are the quoted block labels from `agent/models.yml` (e.g. `"llamacpp (dankclaw-3090)"`), flat map lookup; absent/≤0 = unlimited; scope = this machine's config root only — other workstations and non-omp clients are NOT counted; excess queues |
| `tools.maxTimeout` | ceiling on any agent-requested tool timeout | kills `timeout: 0` runaways |
| `task.isolation.enabled` | makes per-spawn `isolated` flag available | opt-in per spawn, not a blanket sandbox; needs git repo; off in plan mode |
| `task.completionProbe` | periodic completeness side-requests | token sink on shared endpoints |
Reasonable fleet defaults: `maxRuntimeMs = 900000` (15 min), leave the request budget
alone unless the failure mode is a looping search agent (then lower it — request count,
not the clock, is what bounds a 200-call research loop).
## Verify semantics from the bundle, not the label
Setting descriptions lie by omission. `~/.bun/install/global/node_modules/@oh-my-pi/pi-coding-agent/dist/cli.js`:
- depth gate: `grep -o '.\{130\}xC\b.\{130\}'` finds `U_(n,s)`; `grep -o 'function U_(e,t){.\{0,60\}'` → `e<0||t<e` (n=cap, s=taskDepth).
- in-flight lookup: `grep -o '.\{150\}axInFlightRequests.\{200\}'` → flat `[providerId]` lookup, non-number/≤0 = unlimited, clamp ≥1.
**Verify the cap instead of assuming it.** `read cfg://task/maxRuntimeMs` at the start of
any session that plans to rely on it. A session-only write is gone next session, and an
unanswered `/save` approval means the value never persisted — so the fleet can run hours
with the cap at `0` while everyone believes it is 15 minutes. Nothing else bounds a child.
## Three failure modes, three different fixes
- **Runaway loop** (hundreds of sequential tool calls): lower `softRequestBudget`; the
clock cap only truncates it late.
- **Slow model, legitimate work** (dozens of calls on a low-t/s endpoint = an hour of wall
clock): fix routing, not the clock — check `cfg://task/agentModelOverrides` and move the
agent class onto a faster/shared endpoint. Watch the slot math: subagent endpoints share
KV slots with the interactive session, so `maxConcurrency + 1` sequences on an N-slot
endpoint degrades everyone's decode.
- **Finished work, no exit (nested fan-out deadlock).** A subagent that spawned **its own**
children blocks on their barriers. If those children die out-of-band (killed, starved, or
waiting on an answer whose subject changed mid-flight), the parent waits forever with its
deliverable already written. No instruction text prevents this — not the repo AGENTS.md,
not the task prompt; only the clock cap or a kill ends it.
Signature: parent and children report **the same elapsed wall clock**, and the parent's
on-disk output is complete. Census (agent registry + `ps`): group by elapsed time, look
for identical `etimes` across a parent/child set, then judge the **artifacts** instead of
the process — balanced code fences, no truncated tables, trailing newline, front matter or
the page's H1+status convention intact. Complete artifacts + still "running" = deadlock,
not work.
Repair: kill the **subtree** and confirm the children leave (a killed parent does not
cancel children that came from a separate `tasks[]` batch). Then **flatten**: the
top-level session does the fan-out and children never spawn children. Re-run only the
slices whose artifacts are missing — integrate from what is already on disk.
## cfg write mechanics (bit me once)
- `write cfg://task/maxRuntimeMs 900000` → applies **session-only**, replies "NOT saved".
- Persist = `write cfg://task/maxRuntimeMs/save` with the same content, and that write
needs its **own interactive approval**. If the approval prompt is not answered in time
the value stays session-only and the tool says *NEVER retry unless the user asks* —
report it in the reply instead.
- Revert a session value by writing the old value back (e.g. `0`).
## Order of operations when one is already running late
1. `read proc://` → registry of running agents; `read proc://<id>` for status/output.
2. `read agent://<id>` → live progress ("Latest assistant text") — often shows it is
mid-batch, not hung. If the latest text is already a wrap-up/summary, treat it as
**done** and collect its output instead of waiting for an exit event.
3. `write agent://<id>` an explicit wrap-up order: stop searching, answer what is
sourced, mark the rest `NOT VERIFIED — needs <what>`, cap the report length.
4. Only then `write proc://<id>/kill` — the cap does **not** retroactively bind agents
spawned before the change, so a long runner must be ordered or killed, never just
re-configured. After any kill, re-read the registry: unreaped children and orphaned
host-side processes (a scratch server holding GPU/RAM) are the expensive residue, and
`pkill -f` patterns that also match production services are forbidden — kill by pid.
## Landing a policy change
cfg `/save` writes persist immediately; `agent/config.yml` is machine-live tier (heartbeat commits it). Human-facing policy changes land as an `omp-docs` page update via branch → PR (docs tier), `git worktree add` from `origin/main` if the current checkout is branch-locked by workspace policy.
@@ -0,0 +1,30 @@
---
name: corpus-voice-skill-rewrite
description: "Rewrite a skill to emulate an author corpus's voice: full read, style-DNA distillation from writing-for-agents levers, positive-phrasing pass, sharpened completion criteria"
---
# Corpus-voice skill rewrite
Rewrite a skill so it reads as if a chosen author wrote it. Done for `grilling` against the `mattpocock/skills` corpus (2026-10-18, command-center PR #20); behaviour preserved, voice swapped.
## Where the corpus lives
Installed third-party skills: `~/.agents/skills/<name>/SKILL.md` (the skills-CLI global store; `~/.agents/.skill-lock.json` names sources). Whole mattpocock corpus ≈ 2,800 lines — small enough to read inline in ~4 `cat` batches via bash; do NOT delegate the reading, style lives in the exact prose.
Read the author's own meta-skill FIRST if one exists (`writing-for-agents` for mattpocock — it states his levers explicitly), then the corpus practicing them.
## Style DNA checklist (mattpocock; generalise per author)
- **Leading words**: compact pretrained concepts repeated as tokens, never sentences (_red_, _seam_, _fog of war_, _brief_, _frontier_). Define each once, reuse everywhere. Prefer words already in the author's other skills so the corpus shares one language.
- **Vocabulary-first**: bolded glossary terms, then used exactly; explicit "_Avoid_: component, service".
- **Positive phrasing**: prohibitions rewritten as target behaviours; keep a prohibition only when no positive form exists (hard guardrails).
- **Sharpened completion criteria**: fuzzy bounds ("understanding reached") → checkable + exhaustive ("frontier empty and nothing sits blocked", "one artefact per question, counted before sending").
- **Zero history**: no provenance, attribution, or absorbed-from lineage in the body.
- **No-op hunting**: delete harness defaults and anything the environment already confesses (formats, rendering, caps). Gotchas the environment CANNOT confess (exclusive dialogs, Esc-abort semantics) stay inline — they're the cache worth keeping.
## Procedure
1. Read entire corpus; tabulate levers with per-skill evidence before writing.
2. Rewrite preserving settled behaviour 1:1 — voice only; diff the two versions for semantic drift.
3. Audit pass: grep the new text for history words (extracted/absorbed/from/upstream), machine-specific constants, repo-specific paths.
4. Run repo checks, commit as `style(<scope>)`, note the lever→instance mapping in the PR comment so the reviewer can grade the emulation.
@@ -0,0 +1,70 @@
---
name: deployment-checkout-trunk-sync
description: Use when the live deployment checkout (~/.omp main) must merge a moved origin/main while dirty tracked files block the merge and workspace policy blocks git checkout.
---
---
name: deployment-checkout-trunk-sync
description: Use when the live deployment checkout (~/.omp main) must merge a moved origin/main while dirty tracked files block the merge and workspace policy blocks git checkout.
---
# Sync a dirty live checkout to a deployment (checkout blocked)
Situation: the checkout IS the deployment; months of machine/hand writes sit
uncommitted; `origin/main` has moved; `git checkout`/discard is BLOCKED by
workspace policy ("edit forward"; exemption only during active conflict).
## Procedure
1. `git fetch`; trial `git merge --no-commit --no-ff origin/main` to enumerate
exact blockers (dirty files the merge would overwrite + untracked collisions).
Untracked blockers: `cp -a` to `.AGENTTRASH/pre-merge-<date>/`, then `mv` aside.
2. **Preservation commit:** `git add` ONLY the blocking paths (not the whole
tree) and commit them as-is: `chore: adopt pre-existing working-tree state
before trunk merge`. Nothing is discarded; the secret gate still runs.
Include EVERY dirty deployment-state path (dotfiles/live tiers too) — a
dirty file that is neither committed nor trashed is unprotected from step 3.
3. `git merge --no-ff origin/main`. Conflicts are now resolvable — the policy
exemption is active during a merge.
4. Resolution law:
- **live machine config** (`agent/config.yml`, `models.yml`, dotfiles live
state like noctalia `settings.toml`) → `--ours`: the running box is its
own authority; the remote copy is a snapshot.
- **prose/law/docs** (`AGENTS.md`, KB) → `--theirs` (upstream canonical;
local variants survive in the preservation commit).
- **append-mostly logs** → union: cut only the three marker lines
(`<<<<<<<`/`=======` range + `>>>>>>>`), keep both sides' entries.
5. `git commit --no-edit`, push trunk, verify `main == origin/main`.
6. Pre-merge byte-compare every dirty file vs `origin/main`
(`git show origin/main:$f | diff -q - $f`): SUPERSEDED (identical → discardable),
DIVERGED (resolve), untracked-in-upstream (collision).
## Gotchas
- **NEVER `git stash` to unblock a deployment sync, NEVER `git stash clear`/
`drop` afterward.** Observed 2026-10-18: a sync stashed the dirty tree, the
stash entry was later destroyed, and months of GUI-built bar layout
(noctalia settings.toml, never committed) vanished with it — recovered only
via dangling-object archaeology (below). Step 2's preservation commit exists
precisely so stashing is never needed.
- **Stash-and-retry loops are a red flag**: three `WIP on main` stash commits
within ~60s of each other means the operator was fighting the dirty tree,
not resolving it.
- **Recovery from destroyed stashes** (objects survive entry deletion until gc):
`git fsck --lost-found` → `git log -1 --format='%ci %s' <dangling>` to date
them → `git show <c>:<path>` to dump candidates; newest `WIP on` commit is
usually the last good state. Validate before deploying (e.g.
`noctalia config validate`), back up the clobbered file to `.AGENTTRASH/`,
then restore through the symlink target.
- Never wrap `git checkout` in `2>/dev/null` here: the policy-block error was
swallowed and the loop silently no-op'd; the merge then failed identically.
- `git add` a directory pathspec stages its untracked children (fine for
allowlist dirs; never for prose dirs).
- The live-sync heartbeat (#11) commits machine tiers hourly, so this sync is
a rare operation post-deployment — mostly memories/dotfiles stragglers.
Remember the heartbeat can lag up to an hour behind GUI edits: the tree
between heartbeats is the ONLY copy of fresh GUI work.
- **Frank's accepted risk posture (2026-10-18):** hourly sweep + the
preservation-commit law + fsck recovery is defense-in-depth ENOUGH. Do not
re-propose faster heartbeats or path/event triggers to shrink the
GUI-edit-to-commit window; he chose status quo after measuring (heartbeat
itself is 57 ms CPU — cost was never the objection; un-debounced
DirectoryNotEmpty triggering was, and path-unit proposals are vetoed).
@@ -0,0 +1,36 @@
---
name: docs-dedupe-verify-campaign
description: "Run an exhaustive docs dedupe + fact-verification campaign in dank/command-center: scout cluster ledgers, evidence-overridden merges, live fleet probes, log compaction law, and landing via Gitea PR."
---
Campaign procedure for deduping + fact-checking `omp-docs/` in dank/command-center (proven on Refs #29, 2026-10-19: 8 commits, -2,229 lines, 0 lint/coverage/bats failures).
## 1. Recon
- Fresh branch off `origin/main` in a new worktree (`git worktree add ~/.omp/wt/<name> -b docs/<issue>-<slug> origin/main`); the session worktree's `git checkout -b` is policy-blocked.
- Run `scripts/kb-lint.sh omp-docs` baseline; write a throwaway index-coverage checker (each dir's `index.md` must link every subdir/file) — mechanical, no scout needed.
- Open the Gitea issue first (multi-moving-parts law).
## 2. Scout fan-out (overlap detection)
- One `task` batch, `agent: scout`, one task per doc cluster + one cross-cutting sweep (cap 2 concurrent; rest queue).
- Each scout writes a ledger to `local://dedupe/<cluster>.md`: inventory table (file, lines, purpose, verdict KEEP/MERGE/DELETE/UPDATE), overlaps, facts-to-keep ledger, inbound links, staleness, claims-needing-verification.
- Scouts are LEADS, not truth. Observed failures: fabricated ledger entries (claims about text that does not exist in any file), a DELETE verdict on a generated artifact that is under test (`tools/niri/keybindings.md` is generated by `scripts/gen-keybinds.sh` and tested by `tests/gen-keybinds.bats` — keep), and a KEEP based on misreading a changelog leftover. Re-derive every consequential verdict from the files/repo yourself.
## 3. Verify fleet facts live (never trust doc dates)
- Read-only BatchMode probes: `ssh -o BatchMode=yes dankclaw '...'` (podman ps/inspect, systemctl status, curl localhost, os-release, cpuinfo). `sudo -n` only has systemctl verbs — use `podman exec <ctr> grep/cat` for in-container files.
- Update docs with dated drift banners ("probed 2026-10-19") for policy divergence; NEVER silently re-apply a policy — flag as operator decision (e.g. SearXNG engine policy).
## 4. Verify external claims via direct web research (no subagents)
- Version/protocol/benchmark claims: primary source only (upstream README, raw.githubusercontent, /api/v1/version, arxiv). If a number cannot be re-attributed to a published benchmark, drop it with an explicit note in the doc.
- Fabrication hunt: invented distros/projects/model names (found: "FreeToken" distro, ornith-llama-cpp-setup tree, Intel CPU on an AMD box) — delete the artifact, not just the line.
## 5. Log compaction law
- Changelog entry = date + what changed + durable lesson + concept-page pointer, few lines. Full narratives live in git (`git log --follow`). Record the law at the top of `log.md`. Never re-expand an entry in place. Keep pi-era entries tagged "(pi era)".
## 6. Gates + landing
- Gate every commit: `bash scripts/kb-lint.sh omp-docs` + index-coverage + `bats tests/` (67 tests). Pre-commit hook prints `error: command not found: caddy` on Caddyfile-touching commits — warning only, commit still lands.
- Gitea API auth: `~/.config/secrets/gitea` is **URL-form** (`http://dank:<token>@host`), not a raw token. Extract: `T=$(sed -n 's|.*://[^:]*:\([^@]*\)@.*|\1|p' ~/.config/secrets/gitea | head -1)`; raw `cat` as bearer token → 401.
- PR body ends with `---` + `cwd: <wd> · session: <id>` footer; then `xdg-open <PR-URL>` immediately; comment the campaign ledger summary on the issue. NEVER merge without Frank's explicit OK.
## Edit-tool field notes (recurring traps)
- `PUT N+=:` is invalid syntax — it inserts the literal text. One insert-op per edit call; recompute line numbers per call.
- File hash tag changes after every edit — re-`read` before each subsequent edit call to the same file; reusing a stale tag is rejected.
@@ -0,0 +1,85 @@
---
name: docs-refresh-scout-summaries
description: "Refresh a stale documentation cluster without delegating the writing: scout subagents produce per-line verdict tables (holder verified by comma-insensitive grep), the parent makes every edit, and a port-before-cut census proves nothing was lost. Use for dedupe-our-docs, fix-the-stale-runbooks, pointers-instead-of-copied-numbers jobs."
---
# Refresh stale docs with scout summaries, parent-side writes
Use when a cluster of documentation pages is stale and/or restates facts another page owns, and
the fix touches many files. **Scouts read and classify; the parent writes.** Sibling skill
`vault-one-fact-one-owner-dedupe` covers collapsing era pages into owner pages - its section 3
(orphan census), section 7 (edit-tool hazard) and section 9 (verify/PR) apply unchanged.
## Why not writer subagents (measured cost)
Writer agents produce plausible output and cannot be trusted on the one claim that matters - the
owner page already holds this fact. In one run they asserted every cut was grep-confirmed while
FOUR cuts left pointers to pages that did not contain the fact (118->238 GiB, 16,095 tokens,
0.739/0.554/0.427/0.340, PR #23897). Each became a broken promise the next reader trusts.
Classification is the only part that parallelizes; writing is where taste (ownership, era
naming, what counts as a law) lives. So fan out read-only scouts and keep the pen.
If writer agents were already spawned and are no longer wanted: `write agent://all` to stop
them, then `git status` the target tree - `proc://` does not list agent jobs, and a finished
worker may already have edited files.
## Pipeline
1. **Cluster** targets into groups of 3-4 pages sharing subject matter (one cluster per scout).
Know the owner map first (endpoint/service/host pages, plus the repo documentation law).
2. **Wave of 2 scouts** (harness cap is `task.maxConcurrency`, usually 2). Scout contract:
> READ-ONLY, no writes of any kind. Per file, one table row per candidate fact:
> `| lines | verbatim figure + 6 words | holder elsewhere (file:line) or none | VERDICT |`
> Verdicts: `CUT -> [[Owner]]` (holder verified), `KEEP(owned here)` (no holder, this page is
> the record), `PORT(parent)` (rightful owner lacks it - name page and section), `STALE`
> (contradicted by current state; quote the contradicting line), `INDEX` (locator page).
> Verify every holder claim with a COMMA-INSENSITIVE grep: a holder writing 1,350,182
> satisfies a page writing 1350182 and vice versa; 16,095 does NOT satisfy a check for 16095
> unless commas are stripped. Never name a holder line you have not read.
> End with a per-file tally: kept / cut / port / stale.
Put the law, the owner map and the verification rule in the batch-level `context`, never per
task.
3. **Write while the next wave runs**: edit cluster N from wave N, launch wave N+1 in the same
turn. Never launch a wave you have nothing to write.
4. **Verify each CUT yourself** before cutting - read the holder line. A scout row is a
hypothesis, not evidence.
5. **PORT items are your edits**: add the fact to the owner page section (Eras row / Laws / spec
table), then cut it from the technique page in the same commit.
6. **STALE items: check live state**, not another document - `ssh <host> systemctl is-active
<svc>`, the endpoint `/health`, the env file. Then rewrite with a date, or drop transient
live state an owner page already records.
## The ownership test that stops wasted ports
Two pages carrying one figure is the defect - a figure with exactly one holder is fine wherever
it lives. A technique page that is the sole record of a campaign owns that campaign's arm
tables; do not port such ledgers into an endpoint Eras table. Write the clause into the repo
documentation law so the next pass stops porting single-owner facts. Corollary: a worked example
may repeat a live number if it declares itself dated and names the owner (a snapshot, not fleet
state - recompute from the live files).
## Census after each cluster (catches your own slips too)
Run the sibling skill's section 3 census over `git diff -U0` for the cluster (deleted lines x
distinctive numeric keys vs the whole vault **plus AGENTS.md**), comma-insensitively; drive the
count to zero or list each accepted loss in the commit message.
```python
flat = corpus.replace(',', '')
pres = lambda n: n in corpus or n.replace(',', '') in flat
toks = lambda l: [n for n in re.findall(r'\d[\d,]*(?:\.\d+)?', l)
if len(n.replace(',', '').split('.')[0]) >= 4
or (len(n.split('.')[-1]) >= 2 and len(n.replace(',', '')) >= 5)]
orphan = [l for l in deleted if toks(l) and not any(pres(n) for n in toks(l))]
```
## Verify and land
- Vault link seam must print `0 unresolved links`; hard-wrapped `[[Two Word Page]]` links split
across lines are the usual cause - unwrap them.
- Full suite once at the end, not per cluster; a docs seam running while scouts are live may
read half-written files, so re-run after the last edit.
- Commit per cluster (docs-only means **no deploy**); push, open the PR through the API with a
600-perm curl config, `xdg-open` the PR URL immediately.
@@ -0,0 +1,62 @@
---
name: fleet-service-runtime-census
description: "Answer \"what is service running right now?\" for a dank-fleet service: live endpoint probe plus host units, image ids, live-vs-repo env, and drop-ins."
---
# Fleet service runtime census
Answer the question "what is `<service>` running currently?" with evidence, not from docs. Docs say what *should* run; the host says what *does*. Run all five probes, then report one table.
## 1. Probe the published port (works from any LAN box, no ssh)
```bash
curl -s -m 10 http://<host-ip>:<port>/health; echo
curl -s -m 10 http://<host-ip>:<port>/v1/audio/voices # per-endpoint extras: /v1/models, /metrics
```
The extra route matters more than `/health` for identity claims:
- llama.cpp and radiance **echo the requested model name** — a 200 proves nothing; read `/v1/models`.
- halogen 404s `/completion`, `/ping`, `/props`, `/tokenize`.
- The frank-tts façade answers `/health` **without dialing the engine**, so "façade healthy, engine down" is a real state; the voice list in that same response is the honest census.
## 2. Units + containers on the host (ssh as the deploy user, no sudo)
```bash
ssh <host> 'systemctl --user status <svc>.service <engine>.service --no-pager \
| grep -E "^(●| Active| Loaded)"; \
podman images --format "{{.Repository}}:{{.Tag}} {{.ID}} {{.Created}}"; \
podman ps -a --format "{{.Names}}\t{{.Status}}\t{{.Image}}"'
```
- `active (running) since …` + `Up N hours (healthy)` is the answer; `activating (auto-restart)` with a ~50 ms exit is a **preflight refusal**, not an engine fault.
- **NEVER prefix these podman calls with `sudo`.** Containers live in the deploy user's rootless storage; `sudo podman inspect frank-tts-engine` returns `no such object` while the plain form succeeds. Treating that as "container missing" is a false finding.
## 3. Drop-ins — the override that no health gate sees
```bash
ssh <host> 'systemctl --user show <svc>.service -p DropInPaths; \
systemctl --user show <engine>.service -p DropInPaths'
```
`DropInPaths=` must be empty. A leftover bench drop-in (`Environment=FRANK_<SVC>_ENV_FILE=/tmp/<arm>.env`) makes the next deploy boot a different model at a different shape while `/health` still answers 200 and the e2e gate passes.
## 4. Live env vs repo env — the only truth test
```bash
# repo side (local checkout)
grep -vE '^\s*#|^\s*$' scripts/<svc>.env
# host side
ssh <host> 'sudo cat /home/dank/serverAppConfigs/scripts/<svc>.env' | grep -vE '^\s*#|^\s*$'
```
Diff them. Per repo law the env file beside the serve script **is** the authority; a doc page that disagrees with it is the bug, and host-side drift means an uncommitted edit. Also check `git log --oneline -3 -- scripts/<svc>.env` to confirm the host isn't ahead of git.
## 5. Report
Table of: unit state + since, image repo:tag@short-ID + age, backend/alias actually served (from step 1, not from the name), drop-ins, and whether live env == repo env. State explicitly when a fact came from docs rather than from a probe.
## Traps that produce false findings
- Digest-pinned images: the local image ID's *creation date* answers "is this stale" better than the tag; `latest` + `Pull=never` is a locally built image, not a registry pull.
- `ssh` user context changes what podman sees (root vs rootless) — see step 2.
- Two ports on one host are two providers in `models.yml`; a port mismatch is a rename or drift, not a config typo.
@@ -0,0 +1,81 @@
---
name: frank-tts-add-cloned-voice
description: "Add or repair a cloned voice on the dank fleet: pack builder, the reference.wav contract, the boot warm hook (argv-cap and env-quote laws), and how to prove a voice really answers."
---
# Adding (or repairing) a cloned voice on the dank fleet
Repo law lives in `serverAppConfigs-docs/Dankclaw/Voice Packs.md` and
`Frank TTS Engine.md` — read those for the pack format. This skill is the
**operating sequence plus the traps that cost real time on 2026-10-18**.
## Stack, fast
- `frank-tts-engine` — arm A `qwentts.cpp tts-server`, container-internal `:8880`,
publishes **no port**. Reach it with `podman exec frank-tts-engine curl …`.
- `frank-tts` — OpenAI façade on host `:7772`; resolves voice **by name**.
- Packs: `/home/dank/voices/<name>/` with `reference.wav` (+ manifest, `.spk`,
`.rvq`). Builder: `scripts/build-voice-pack.sh` (crop 19.84–25 s, first 10 s of
any source is forbidden).
- Weights: `/home/dank/models/Qwen3-TTS-GGUF/` —
`scripts/download-frank-tts-engine-qwentts.sh [--verify-only]` (1.4 GiB, ~18 s
on the LAN; verifies byte count + Hub LFS sha256).
## Sequence
1. Build the pack (dry-run first — sizes are arithmetic and asserted).
2. Deploy the engine only if its files changed:
`./scripts/deploy.sh dankclaw --service frank-tts-engine`
(first run builds the image: ~10 min recursive source clone).
3. Register/warm: `podman exec frank-tts-engine /app/warm-voices.sh`
— registers **every** pack each run (the engine replaces a name it already
holds; `tools/tts-server.cpp:148`), then synthesizes twice per voice.
4. Prove from the consumer side, not the config:
`curl -s localhost:7772/v1/audio/voices` then a real
`POST /v1/audio/speech` and listen to the bytes.
## Trap 1 — the kernel's argument cap (this broke the first deploy)
`/usr/bin/curl: Argument list too long` in the warm log ⇒ a request body was
passed as **one argv string**. Linux caps a single argument at
`MAX_ARG_STRLEN = 131 072 bytes`; a ~1 MB `reference.wav` base64's to ~1.27 MB.
curl never runs, and hooks report it as `HTTP no response` while `/health` is
green. Fix = write the body to a file and use `--data-binary @file`; feed the
payload through a redirection, not `$(base64 …)`.
Regression-test shape: **real** curl + real listener + a fixture >128 KB, so the
kernel (not a stub) produces the failure. Any pack over ~96 KB trips it.
## Trap 2 — two readers of the env file disagree about quotes
`bash set -a; source` strips `"…"`. podman's `--env-file` (how the unit really
reads it) does **not**. A value interpolated into a JSON body therefore arrives
quoted and invalidates it. Test both readers, not just `source`.
## Trap 3 — locally built images skip rebuilds on a stale hash
`build_compose_image` compares a `cfhash` label; it must cover every file the
`Containerfile` `COPY`s, or an edited `app.py`/hook deploys "successfully" while
the container runs old code.
## Measured numbers (2026-10-18, deployed build — retire the trial's ladder)
| thing | value |
|---|---|
| first synthesis of a freshly registered voice | 1 883 ms |
| later short requests | 1 226–1 283 ms |
| ~110-word request (repeat) | 9.4 s / 9.8 s — tracks generated audio, not state |
| whole boot warm, 3 packs | 15.2 s |
| engine resident | ~4.0 GiB |
The trial's `6.2–8.0 s cold → 0.5 ms warm` claim does **not** reproduce; warming
is for registration (registry is memory-only, re-register ≠ warm) plus ~0.6 s.
## Ops notes
- `systemctl --user stop` **removes** the quadlet container — `podman start` then
finds nothing. To run the engine without its `ExecStartPost` hook, use a
separate container, not stop+start.
- `podman cp` of a fixed script into a running container is a **trial only**: the
layer dies with the container. Merge + redeploy to make it durable.
- Nothing on the voice pair exposes `/metrics`; Prometheus can't scrape it (a
blackbox HTTP probe on 7772 is the only honest option).
@@ -0,0 +1,81 @@
---
name: frank-tts-consumer-voice-triage
description: "Triage a consumer (OpenWebUI, omp, open-notebook) rejecting or ignoring a frank-tts voice name: prove whether the server or the browser-side Kokoro.js engine produced the error."
---
# frank-tts consumer voice triage
A consumer says a voice name is invalid, speaks in the wrong voice, or is
silent. `frank-tts` (`192.168.0.143:7772`, shim
`dankclaw/voiceservice/app.py`) resolves `voice=<name>` against
`/home/dank/voices/<name>/reference.wav` and answers **400 + the list of
voices that exist** for a name it cannot resolve — never a silent fallback.
Any error naming a *different* voice list did not come from it.
**Signature that decides the case immediately:** an enum of ~29 names
`af_heart, af_alloy, … am_*, bf_*, bm_* … bm_fable` is **Kokoro's fixed pack**,
the voice list of **Kokoro.js running in the browser** (OpenWebUI ships it
in its own front end as TTS engine value `browser-kokoro`, with a personal
"Kokoro.js dtype" setting; model `onnx-community/Kokoro-82M-v1.0-ONNX`).
`narrator1/2/3` are frank-tts cloned voices. Kokoro cannot clone.
## Instrument ladder (stop at the first that answers)
1. **What the endpoint actually accepts** (never infer from a consumer's text):
`curl -s http://127.0.0.1:7772/v1/audio/voices` → JSON array of pack names.
2. **Speak with the consumer's exact body, from inside the consumer's
container** — same network, same shape. Write the JSON to a file and
`--data-binary @file` (nested `sh -c` quoting silently sends an empty
body and yields a bogus `400 malformed request body`):
```
printf '%s' '{"model":"frank-tts","input":"probe","voice":"narrator1","response_format":"mp3","speed":1.0}' > /tmp/p.json
podman cp /tmp/p.json <consumer>:/tmp/p.json
podman exec <consumer> curl -sS -o /tmp/o.bin -w 'http=%{http_code} type=%{content_type} bytes=%{size_download}\n' \
-X POST http://host.containers.internal:7772/v1/audio/speech \
-H 'Content-Type: application/json' --data-binary @/tmp/p.json
```
`200 audio/mpeg|audio/wav` ⇒ the server path is healthy; the failure is elsewhere.
3. **Did the request arrive at all?** `podman logs --tail 400 <consumer> | grep -c audio/speech`.
A server-path failure leaves a log line **and** a frank-tts error body; a
client-side engine leaves **neither**. This contrast is the discriminator.
4. **Where the rejection string lives** (proves the emitter without guessing):
```
podman exec <consumer> sh -c 'grep -ho ".\{200\}Should be one of.\{80\}" /app/build/_app/immutable/chunks/*.js | head'
podman exec <consumer> sh -c 'grep -ho ".\{60\}af_heart.\{200\}" /app/build/_app/immutable/chunks/*.js | head -2'
```
Matched inside the front-end bundle ⇒ browser-side validator, not the API.
5. **Config authority sweep** (OpenWebUI): admin config is the `config`
table (one key per row, JSON `value`; expected
`audio.tts.engine=openai`, `audio.tts.model`, `audio.tts.voice`,
`audio.tts.openai.api_base_url`); per-user overrides are the `settings`
JSON column of table `user` (singular, no `is_active`; some rows hold the
string `null` → guard it). `audio.stt.*` and `audio.tts.*` are separate.
No `sqlite3` CLI in the image or on the host: `podman exec -i <c> python -`
with the stdlib module. **`podman exec` needs `-i` to accept a heredoc
script** — without it the script is silently dropped and you get no output.
## Known traps
- OpenWebUI is a **rootless** quadlet: `sudo podman …` reports *no such
container*. Read it rootless.
- `podman ps` in this podman build has no `.ImageName` field — use `{{.Image}}`.
- The in-browser engine choice is **per-browser storage**: empty
`user.settings` + correct admin config + zero backend hits is the normal
shape of this bug. Fix is UI: Settings → Audio → TTS Engine → **Default**.
- `GET /api/config` publishes no `audio` block, and nonexistent `/api/...`
paths return the SPA HTML with `200` — never conclude "config missing" from
an HTML body.
- TTS is memory-registry sensitive: the engine's voice registry is
memory-only, so "every name returns 400" after a restart points at the warm
pass, not at the caller (see [[frank-tts-add-cloned-voice]]).
## Local playback side (omp `/say`, manual probes)
If synthesis succeeds (`200`, sane WAV bytes) but nothing is audible, the
fault is the PipeWire graph, not the endpoint:
`wpctl status` (default sink marked `*`, and *Default Configured Devices* —
a remembered-but-offline `bluez_output.*` there is the classic silent
route), `wpctl get-volume @DEFAULT_AUDIO_SINK@`, `pw-play -v <file>` (expect
`stream drained` + exit 0), and target a device explicitly with
`pw-play --target <node-id>` to identify which hardware is live. A one-word
clip (~0.7 s) is easy to miss — probe with a multi-second sentence.
@@ -1,105 +1,73 @@
---
name: gitea-api-pr-operations
description: "Open, list, merge, and verify pull requests (and diagnose issue-API scope failures) on the Dankclaw Gitea via its REST API from a workstation, keeping the token out of argv (curl -K config file, mode 600) — includes the credential-store extraction one-liner, the merge endpoint's Do-field law and Content-Type-header trap, the suggested-URL-is-not-a-PR gotcha, and the insufficient-token-scope trap."
description: "\"Open, list, merge, and diagnose issues/PRs on the Dankclaw Gitea API (192.168.0.143:3000, repo dank/command-center) with the token stored in ~/.config/secrets/gitea — incl. the required merge payload, where review comments actually live on 1.27.3, and how to recover the session id for the mandatory body footer.\""
---
# Gitea API PR operations (Dankclaw)
# Gitea API PR operations (Dankclaw `dank/command-center`)
`git push` on this fleet prints `Create a new pull request for ...` — that is a
**suggestion, not a PR**. Verify (`GET /pulls?state=open` → expect `[]`) before
claiming a PR "should exist"; create it via the API when asked.
## Where
- Token: `~/.config/secrets/gitea` (`http://user:TOKEN@192.168.0.143` single line).
Extract WITHOUT echoing:
`tok=$(sed -nE 's#^http://[^:/@]+:([^@]+)@192\.168\.0\.143.*#\1#p' ~/.config/secrets/gitea | head -1)`
- Build a 600-perm temp curl config and use `curl -K`:
`cfg=$(mktemp) && chmod 600 "$cfg" && printf 'header = "Authorization: token %s"\n' "$tok" > "$cfg"`
Delete `$cfg` after use. NEVER pass `-H "Authorization: token $tok"` (the literal
header lands in transcript + logs). NEVER echo the token.
- Base URL: `http://192.168.0.143:3000/api/v1/repos/dank/command-center`.
## Endpoint + auth
- API base: `http://192.168.0.143:3000/api/v1/repos/dank/<repo>`
- Token lives in the git credential store configured by
`git config --get credential.helper` → `store --file ~/.config/secrets/gitea`,
line format `http://user:TOKEN@192.168.0.143:3000`.
- The repo-local `.env` `GITEA_TOKEN` (main checkout, gitignored) carries
**`read:issue` too** (measured 2026-10-18): filing issues needs THAT token,
the credential-store one 403s on issues.
## Recipes (all verified live 2026-10-18)
- **Open PR** (token only needed for private repos; this one reads publicly but
POST needs auth): `POST /pulls` JSON `{title, head, base:"main", body}`.
- **PATCH PR title/body**: `PATCH /pulls/<n>` with JSON body `{title}` and/or
`{body}`. Returns 201 with the full PR. Use `jq -n --arg` to build JSON; for
multi-line bodies write the text to a temp file and `--arg b "$(cat b.txt)"`.
(jq CLI: a bare `---` argument after the program is parsed as a flag → error;
fold footers into the --arg string instead.)
- **List open PRs**: `GET /pulls?state=open` → `jq -r '.[] | "#\(.number) \(.head.ref) \(.title)"'`.
- **Read PR**: `GET /pulls/<n>` (no token; public repo) → `jq -c '{state,merged,mergeable,head:.head.ref}'`.
`mergeable:false` is often Gitea's *not-yet-checked* state, not a conflict — prove a real
conflict locally with `git merge-tree --write-tree HEAD origin/main` before believing it.
- **MERGE**: `POST /pulls/<n>/merge` with `-H 'Content-Type: application/json'`
and body **`{"Do":"merge"}`** — this build REQUIRES the `Do` field:
`{}` or `{"DoNotMerge":false,...}` → 422; `{"Do":"merge"}` → 200 +
`{"state":"closed","merged":true,"merge_commit_sha":"..."}`. Verify with a plain
GET /pulls/<n> afterwards (merge endpoint's own stdout may not parse).
Merge is the `--no-ff` merge commit on main; then `git -C ~/.omp fetch && git
merge --ff-only origin/main` propagates the live deployment.
- **Issues**: same shape at `/issues` (`POST {title, body}`), `/issues/<n>/comments`
(`POST {body}`, `PATCH .../comments/<id>`) — both work with the temp-cfg auth.
Extract the token (the `http://` scheme contains a colon — scheme-stripping
awk regexes silently grab the port instead; use this anchored sed):
## Review comments: the API lies on 1.27.3 (learned 2026-10-18)
- `GET /pulls/<n>/comments` (inline review comments) → **404 `not found` on every
route** (token or not, `?pull_request_id=` or not) even when a review with
comments exists.
- `GET /pulls/<n>/reviews` works (shows `state`, `comments_count`) but bodies are empty.
- **The comments are readable from the PR HTML**:
`curl -sS http://192.168.0.143:3000/dank/command-center/pulls/<n> -o /tmp/pr.html`
then extract `<div class="content comment-content">` blocks
(python: `re.finditer(r'comment-content', src)` → widen ±800 chars, strip tags).
Duplicates appear (suggested-change UI shows text twice); dedupe mentally.
- Per-conversation resolve API also 404s — flag resolutions in an issue comment instead.
```bash
tok=$(sed -nE 's#^http://[^:/@]+:([^@]+)@192\.168\.0\.143.*#\1#p' ~/.config/secrets/gitea | head -1)
[ -n "$tok" ] && echo "token-extracted(len=${#tok})" # length check, never echo the value
```
## Body-footer law (AGENTS.md)
Every issue/PR body ends with `---` line then `cwd: <wd> · session: <id>`. Keep
it inside the --arg string (not a `---` CLI arg).
## Keep the token out of argv (repo secret law)
`curl -H "Authorization: token $tok"` is world-readable in `/proc/<pid>/cmdline`.
Use a mode-600 config file:
`cwd` is THIS session's own working directory (note a build worktree separately if they
differ). When `/status` is unreachable (headless/subagent context), recover the session id
from the session store instead of inventing one:
`ls -t ~/.omp/agent/sessions/<cwd-slug>/ | head -2` → `<timestamp>_<uuid>` (the same uuid as
`<uuid>.jsonl`); the slug is the cwd with `/` replaced by `-`. Subagent files live under the
**parent** session's directory, so the newest entry there is the parent id.
```bash
cfg=$(mktemp); chmod 600 "$cfg"
printf 'header = "Authorization: token %s"\n' "$tok" > "$cfg"
```
- POST JSON needs a second header line: `header = "Content-Type: application/json"`.
There IS NO `content-type` config option — curl rejects the file.
- `rm -f "$cfg"` when done (a mode-600 token file left in /tmp is its own leak).
## Operations
```bash
# list open PRs
curl -sS -K "$cfg" ".../pulls?state=open" | jq -r '.[] | [.number,.head.name,.base.name,.title] | @tsv'
# create (build the payload as a FILE, see below)
curl -sS -K "$cfg" -o /tmp/pr.json -w '%{http_code}\n' -X POST -d @/tmp/pr-payload.json ".../pulls"
# verify: 201 is not enough — check mergeable
curl -sS -K "$cfg" ".../pulls/1" | jq '{number,state,merged,mergeable,base:.base.ref,head:.head.ref,url:.html_url}'
```
## Merging: the field is `Do`, and it is a STRING naming the strategy
Measured 2026-10-18 on Gitea at 192.168.0.143:3000 (`POST .../pulls/<n>/merge`).
`MergePullRequestOption` is `{From, To, When, Do}` — **there is no `DoMerge` and
no `merge_method`**. Every wrong shape is a 422 with a distinct message, so read it:
|body sent|http|message|
|---|---|---|
|`{"DoMerge":true,"merge_method":"merge"}`|422|`[Do]: Required`|
|`{"Do":true,"merge_method":"merge"}`|422|`[]: json: cannot unmarshal JSON boolean into Go string within "/Do"`|
|`{"Do":"true"}`|422|`[Do]: In…` (validation: not a strategy name)|
|form body `Do=true&merge_method=merge`|422|`[Do]: Required` (the value must be a strategy name)|
|`{"Do":"merge"}`|**200**|merged|
```bash
curl -sS -K "$cfg" -H 'Content-Type: application/json' -X POST -d '{"Do":"merge"}' ".../pulls/4/merge"
# then prove it: .merged true, .state closed, .merge_commit_sha set, and origin/main moved
curl -sS ".../pulls/4" | jq -c '{number,state,merged,merge_commit_sha}'
```
Strategy names: `merge`, `rebase`, `rebase-merge`, `squash`, `manually` — a
strategy the repo does not allow is rejected too.
**Merge trap (measured 2026-10-18):** on `POST /merge` the `Content-Type` header
must go on the **command line** (`-H 'Content-Type: application/json'`). Same
curl that succeeds on `POST /pulls` with Content-Type supplied only via the `-K`
config file returns **405 with an EMPTY body** on `/merge`. A 405 there is this
trap (or a base-moved mergeability recheck — GET the PR, see `mergeable:true`,
then retry with `-H`), NOT a permission problem.
## Building issue/PR bodies without quote carnage
Hand-written `jq -n --arg t "..." '{title:$t, body:"..."}'` one-liners with long
markdown bodies WILL break on a stray quote (and the broken quoting can swallow
the following commands). Build bodies as files (heredoc or write tool), then:
```bash
b=$(jq -Rs . body.md)
jq -n --arg t "$title" --argjson b "$b" '{title:$t, body:$b, head:"<branch>", base:"main"}' > payload.json
curl ... -d @payload.json
```
## Gotchas measured 2026-10-14 / 2026-10-17 / 2026-10-18
- Unauthenticated/bad token → HTTP 401 body `{"message":"not found"}`; `jq '.[]|[.number,..]'` then fails with *cannot index "not found"* — that is an auth failure, not a missing repo.
- **Insufficient token scope ≠ missing data.** The credential-store token
(measured 2026-10-17) carries only `write:repository,write:user`; the issues
API answers HTTP 403 `{"message":"token does not have at least one of required
scope(s), required=[read:issue], token scope=write:repository,write:user"}`.
jq surfaces that JSON as the *cannot index* error — do NOT conclude the issue
list is empty, and note POSTs under this token create NOTHING (verify, don't
assume retry safety). Filing issues needs a fresh token minted in the Gitea
web UI with `read:issue`+`write:issue` (Frank-class credential action; ask) —
OR use the main-checkout `.env` `GITEA_TOKEN`, which already has issue scope.
PR endpoints work fine with either token (`pulls` POST/GET/merge all 200/201).
- On the created-PR response `.head.name` can be null; verify with the `GET /pulls/<n>` and use `.head.ref`.
- **Swagger JSON is disabled on this instance** — `/api/swagger.v1.json`, `/api/swagger.json` and `/api/v1/swagger.json` all 404. Do not go looking for the schema there; the 422 messages name the field and its Go type, which is the faster instrument.
## Gotchas
- Content-Type: POSTs with `-d @file.json` MUST carry
`-H 'Content-Type: application/json'` on the command line. `-H` entries put in
the curl config file are ignored for this (header ordering quirk).
- `xdg-open <pr-url>` lands the PR in Frank's Firefox the moment it is opened —
law, not courtesy.
- `jq: cannot index "not found" with "user"` = endpoint 404'd into an error
object; check `-w '%{http_code}'` before blaming jq.
- The token in `.git/config`'s remote URL is the same secret; the credential
file (`~/.config/secrets/gitea`) is the one git actually consults (global
credential.helper) and the one to reuse for API calls.
@@ -0,0 +1,29 @@
---
name: gitea-pr-api-cycle
description: "Open/update/merge PRs and issues on the Dankclaw Gitea API (192.168.0.143:3000, dank/command-center) with the token-safe curl+jq sequence, including the {\"Do\":\"merge\"} merge payload and post-merge live-checkout fast-forward."
---
# Gitea PR/issue cycle — dank/command-center
Friction-earned 2026-10-18 across PRs #15–#20 and issue #18: three separate fumbles (jq trailer flag, 422 merge payload, silent -o/-w swallowing) codified once.
## Where
- API base: `http://192.168.0.143:3000/api/v1/repos/dank/command-center/{pulls,issues}`
- Token: never inline, never echoed. Extract from the git credential file into a 600-perm temp curl config:
`tok=$(sed -nE 's#^http://[^:/@]+:([^@]+)@192\.168\.0\.143.*#\1#p' ~/.config/secrets/gitea | head -1)`
`cfg=$(mktemp); chmod 600 "$cfg"; printf 'header = "Authorization: token %s"\n' "$tok" > "$cfg"` → `curl -K "$cfg"`; `rm -f "$cfg"` when done.
- Unauthenticated GET works for state reads (`GET /pulls/N` → `jq -c '{state,merged,merge_commit_sha}'`).
## Body construction (the two traps)
- Build JSON with `jq -n --arg t <title> --arg b "$(cat b.txt)" '{title:$t, head:<branch>, base:"main", body:$b}'`; write the body to a temp file first (`printf '%s' … > b.txt`). NEVER pass `---` as a bare jq argument — jq parses it as a flag (`unknown flag: ---`). The AGENTS.md attribution trailer (`---` + `cwd: … · session: …`) goes INSIDE the body string.
- Always capture status explicitly: `-o r.json -w '%{http_code}'` and print it; a bare `-o` hides failures (a 422 looked like success-with-no-output once).
## Merge (the 422 trap)
`POST /pulls/N/merge` requires body `{"Do":"merge"}` — `Do` is the Required field on this Gitea. `{}`, `{"DoNotMerge":false}`, `{"merge_style":…}` all return 422 (`"[Do]: Required"`). Success may return an EMPTY body — verify by GET afterwards (`state=closed, merged=true`), not by the POST response.
- Merge only with Frank's explicit per-PR OK (repo law).
- Post-merge the live deployment must follow: `git -C ~/.omp fetch -q origin && git -C ~/.omp merge --ff-only origin/main` (the checkout IS the deployment; branch is `main`).
## PR etiquette per AGENTS.md
- Immediately after opening: `xdg-open <PR-URL>` lands it in Frank's Firefox.
- Redesign mid-review: amend + `git push -f` the branch, then PATCH the PR body (`/pulls/N`, `{"body":…}`) so title/body match the net diff — verify `{number,state,mergeable}` in the response.
- Issue creation identical shape: `POST /issues` with `{title, body}`, expect 201; PATCH same endpoint `/issues/N` to fix bodies retroactively, then GET-readback verify.
@@ -0,0 +1,42 @@
---
name: gitea-review-comment-html-scrape
description: "Read inline review comments on the Dankclaw Gitea when pulls/N/comments 404s (Gitea 1.27.3): scrape comment-content blocks and diff anchors from the PR HTML page"
---
# Gitea review-comment extraction when the API 404s
On the Dankclaw Gitea (192.168.0.143:3000, Gitea 1.27.3) the review-comment API is dead for inline comments:
`/api/v1/repos/{owner}/{repo}/pulls/{N}/comments` returns 404 `not found` **even with a valid token**, and `pulls/comments?pull_id=` / `?pull_request_id=` variants 404 too. `/pulls/{N}/reviews` works but its bodies are empty for inline reviews (read `comments_count` for how many exist); `/issues/{N}/comments` shows only conversation comments, never inline ones.
## Procedure
1. Confirm the review exists and how many inline comments it holds:
`curl -sS http://192.168.0.143:3000/api/v1/repos/dank/command-center/pulls/{N}/reviews | jq -c '.[] | {id, state, comments_count}'`
2. Scrape the PR page instead (no token needed for a public repo):
`curl -sS http://192.168.0.143:3000/dank/command-center/pulls/{N} -o /tmp/pr.html`
3. Extract each comment's text — every inline comment renders a `comment-content` block; dedupe (each comment appears twice in the HTML):
```python
import re, html
src = open('/tmp/pr.html').read()
seen = set()
for m in re.finditer(r'comment-content', src):
t = html.unescape(re.sub(r'<[^>]+>', ' ', src[m.start()-100:m.start()+800]))
t = re.sub(r'\s+', ' ', t).strip()[:400]
if t not in seen:
seen.add(t); print('>>', t)
```
The comment text appears twice back-to-back inside each block ("text text") — read it once. Blocks start after `Copy Link|Copy Source`; ignore those chrome words.
4. **Locate the file/line anchor** (comment-content blocks carry no `data-path`/`data-line` attrs on this build): search the raw HTML for the comment string, walk *backward* ~4–7 KB, strip tags; the nearby `agent/...` path, `@@ -a,b +c,d @@` hunk header, and surrounding diff context lines identify the anchored file and the quoted source line.
## Replying / housekeeping
- Per-conversation resolve API does not exist on this build (404s) — reply to the round as a normal issue comment (`POST /repos/{o}/{r}/issues/{N}/comments`, token via `curl -K` temp cfg, `header = "Authorization: token …"`, 600 perms, `jq -n --arg b "$(cat b.txt)" '{body:$b}'`) listing which note got which fix commit.
- Edit a posted comment: `PATCH /repos/{o}/{r}/issues/{N}/comments/{id}` with `{"body": ...}` — use to fix your own typos rather than double-posting.
- Token source on this box: `~/.config/secrets/gitea` (grep the remote-URL pattern); never echo it.
## Why this works
The PR page is server-rendered with full inline comment bodies; Gitea's "Copy Source" UI element guarantees the raw text is present pre-markdown-render.
@@ -1,14 +1,15 @@
---
name: niri-config-edit-validate
description: "Locate, edit, validate, and commit niri compositor config on Frank's workstations: desk/display profiles, EDID-keyed outputs, layout, keybind grepping, dotfiles mirror, forced hot-reload."
description: "Locate, edit, validate, and commit niri compositor config on Frank's workstations: desk/display profiles, EDID-keyed outputs, layout, keybind grepping, dotfiles mirror, noctalia.kdl last-include color override, forced hot-reload."
---
# Editing niri config on Dank workstations
## Layout of the config
- Live config: `~/.config/niri/config.kdl` is a thin file of `include "./cfg/*.kdl"` lines. **Never conclude "not bound" from grepping only `config.kdl`** — keybinds live in `cfg/keybinds.kdl`, rules in `cfg/rules.kdl`, layout in `cfg/layout.kdl`, etc. Grep `~/.config/niri/cfg/` recursively.
- **Include order wins:** `config.kdl` ends with `include "noctalia.kdl"` — a hand-written accent overlay at `~/.config/niri/noctalia.kdl` that re-declares `layout { focus-ring/border/tab-indicator/insert-hint }` + `recent-windows.highlight` colors and BEATS every `cfg/layout.kdl` color edit (observed 2026-10-18: focus-ring color edits to layout.kdl appeared to "not reload" while this file silently repainted them red). Before changing any accent/outline color, grep the WHOLE `~/.config/niri/` tree (not just `cfg/`) for the property and fix the LAST includer. Tracked in repo at `dotfiles/zz-blankpad/niri/.config/niri/noctalia.kdl`; live file is NOT a symlink — sync by `cp` and `diff` like the rest.
- niri notation: `Mod` = Super/Win key. Chords like `Mod+R { switch-preset-column-width; }`.
- `~/.config/niri` is a REAL directory, not a symlink; the version-controlled copies are a partial mirror under `~/.omp/dotfiles/zz-blankpad/niri/.config/niri/`. Trees can drift: diff them before/after edits. (Hardlink wiring is FRAGILE — editor/agent atomic-rename writes silently break hardlinks; verify live↔mirror by CONTENT diff, never by link trust.)
- `~/.config/niri` is a REAL directory, not a symlink; the version-controlled copies are a partial mirror under `~/.omp/dotfiles/zz-blankpad/niri/.config/niri/`. Trees can drift: diff them before/after edits. (Hardlink wiring is FRAGILE — editor/agent atomic-rename writes silently break hardlinks; verify live↔mirror by CONTENT diff, never by link trust.) On blankpad the `cfg/*.kdl` entries are symlinks into the repo (`dotfiles/niri/...` base + `zz-blankpad` overrides) — edit through them freely; `noctalia.kdl` and `config.kdl` are the plain-file exceptions.
## Desk/display profiles (monitor arrangement)
- Profiles: `cfg/desk-<n>-<name>.kdl` (e.g. `desk-1-home.kdl`, `desk-2-portable.kdl`); ACTIVE profile is symlinked as `cfg/display.kdl` — `readlink` it to know which. `scripts/desk.sh` manages switching; `desk.sh capture` prints connected outputs' EDID long names.
@@ -21,21 +22,22 @@ description: "Locate, edit, validate, and commit niri compositor config on Frank
- Preset list order = cycle order for `Mod+R` (`switch-preset-column-width`); `Mod+Shift+R` cycles backwards. WITH custom preset lists the cycle contains ONLY the configured presets — no implicit full/maximize tail (verified: [0.25, 0.5] cycles period 2). Maximize = separate `Mod+F` `maximize-column`. Built-in defaults without the node: 1/3, 1/2, 2/3.
- WITHOUT `preset-window-heights`, `switch-preset-window-height` FALLS BACK to the width presets — user sees width-fractions as heights; define the node explicitly to stop it.
- Ground truth for node placement: the binary's embedded template — `grep -a -B4 -A8 "preset-column-widths {" $(which niri)`.
- Window outlines: base geometry (`width`, `off`) lives in `cfg/layout.kdl` `focus-ring`/`border`; COLORS effectively live in `noctalia.kdl` (see include-order law). `border { off }` + focus-ring active = the visible outline. Frank's look since 2026-10-18: amber-orange `#ff8c00`, width 4 (`active`+`urgent` in noctalia.kdl; tab-indicator/insert-hint/recent-windows stay red `#f43841` by choice).
## Workflow
1. Edit the live file under `~/.config/niri/cfg/`.
1. Edit the live file under `~/.config/niri/cfg/` (symlinked = repo file; except `noctalia.kdl`, edit live then `cp` to mirror).
2. `niri validate` (exit 0 + "config is valid") — mandatory before done.
3. **Hot-reload is NOT reliable after harness edits** (atomic-rename writes are missed by niri's watcher; user then tests against the OLD config and reports "no change"). ALWAYS follow with `niri msg action load-config-file` (NOT `reload-config`).
4. Sync changed file into the mirror: `cp ~/.config/niri/cfg/<f>.kdl ~/.omp/dotfiles/zz-blankpad/niri/.config/niri/cfg/<f>.kdl` (repo root is `~/.omp`, branch `main`, remote = dankclaw Gitea `dank/command-center`; push there is pre-authorized). Verify by `diff`, not by cp success.
5. Untracked mirror files: `config.kdl`, `noctalia.kdl`, `animation.kdl`, `display.kdl`, `input.kdl` — flag drift, don't silently add.
5. Untracked mirror files: `config.kdl`, `noctalia.kdl`, `animation.kdl`, `input.kdl`, `display.kdl` (symlink target) — flag drift, don't silently add; when a live-only file turns out to be load-bearing (like `noctalia.kdl` was), commit the first durable copy into `dotfiles/zz-blankpad/niri/.config/niri/`.
6. Mirror files often carry pre-existing uncommitted drift (desk.sh captures); a commit of your edit folds it in — say so in the report/commit body.
## Live-behavior verification without disturbing Frank's windows
- `niri msg --json <subcmd>` — the `--json` flag goes BEFORE the subcommand.
- `niri msg --json <subcmd>` — the `--json` flag goes BEFORE the subcmd.
- Targeting differs per action: WINDOW-scoped actions take `--id <window-id>` (NOT `--window`) — e.g. `switch-preset-window-height --id N`. COLUMN-scoped actions (`switch-preset-column-width`, `set-column-width`, `maximize-column`) have NO id — they hit the FOCUSED column; only `set-column-width <px|±N%>` positional CHANGE, no flags.
- Spawned test apps do NOT reliably take focus, so blind `spawn + action` cycles resize whatever Frank is looking at. For column actions you must `focus-window --id N` first — and that STEALS focus; if Frank is actively testing chords, your probes and his keystrokes interleave and corrupt both. STOP probing, deliver config + validate, and have him press the chord himself.
- `niri msg --json focused-window` can report a different window than assumed (focus moves); for per-window measurement read `niri msg --json windows` and filter by `id`. Present height of proportion p with gaps g over work-area H renders ≈ p*(H+g) − g.
- If Frank reports "still seeing old values" after a config edit: run `load-config-file` first, then verify empirically before believing anything else.
- `niri msg --json focused-window` can report a different window than assumed (focus moves); for per-window measurement read `niri msg --json windows` and filter by `id`. Present height of proportion p with gaps g over work-area H renders ≈ p*(H+g) − g. NOTE (measured 2026-10-18): this build's `windows`/`focused-window` JSON returns `x/y/width/height = null` — pixel-sampling the outline color from screenshots is not viable; ask Frank to eyeball after `load-config-file` instead of burning turns on capture forensics.
- If Frank reports "still seeing old values" after a config edit: run `load-config-file` first, then verify empirically before believing anything else — and check `noctalia.kdl` include-order override BEFORE suspecting the reload.
## "What does chord X do?" triage
For "mod+<key>" questions, check in order: `~/.config/niri/cfg/keybinds.kdl` (compositor wins first), terminal configs (`~/.config/ghostty`, `foot`, `kitty`), tmux, then omp TUI chords (`omp://keybindings.md`; modifiers are ctrl/shift/alt/super only, no `Mod`; `Ctrl+R`=history search, `Alt+R`=app.retry).
@@ -1,45 +1,52 @@
---
name: noctalia-bar-layout-edit
description: "Edit/verify Noctalia v5 bar layout and clock widgets (multi-timezone instances, capsule groups); GUI→repo propagation chain and settings.toml symlink audit on Frank's dotfiles workstations"
description: "Edit/verify Noctalia v5 bar layout and clock widgets (multi-timezone instances, capsule groups); GUI-repo propagation chain, settings.toml symlink audit, and stash-clobber recovery on Frank's dotfiles workstations"
---
# Noctalia v5 bar layout edit
Bar widget layout on Frank's noctalia v5 workstations is GUI-override state, not config.toml.
## Where
- Layout file: `~/.local/state/noctalia/settings.toml` → `[bar.<name>]` keys `start` / `center` / `end` (arrays of widget ids; `[widget.<id>]` subtables hold per-widget settings).
- On Frank's boxes this file MUST be a **symlink into the command-center repo** (e.g. `~/.omp/dotfiles/noctalia/.local/state/noctalia/settings.toml`) — edit the repo file, not the link path (atomic-rename writes through the link path would replace the symlink).
- Layout file: `~/.local/state/noctalia/settings.toml` -> `[bar.<name>]` keys `start` / `center` / `end` (arrays of widget ids; `[widget.<id>]` subtables hold per-widget settings).
- On Frank's boxes this file MUST be a **symlink into the command-center repo** (e.g. `~/.omp/dotfiles/noctalia/.local/state/noctalia/settings.toml`) - edit the repo file, not the link path (atomic-rename writes through the link path would replace the symlink).
- Layer order: built-in defaults < `~/.config/noctalia/config.toml` (+`[include]`) < `settings.toml` (wins). Noctalia writes through symlinks and keeps them.
- Defaults when a key is absent: `start = ["launcher","wallpaper","workspaces"]`, `center = ["clock"]`.
- **Noctalia rewrites this file itself** (GUI actions + normalizes keys/format, e.g. strips `{:%...}` braces, reorders widget lists). Always re-read the exact lines immediately before editing; stale line anchors WILL drift between reads.
- Defaults when a key is absent: `start = ["launcher","wallpaper","workspaces"]`, `center = ["clock"]`, `end = ["notifications","clipboard","network","bluetooth","tray","battery","session","control-center","clock"]`.
## GUI→repo propagation (checkout-is-deployment)
- `~/.config/noctalia/config.toml` is symlinked into the repo → GUI settings writes land in the repo working tree automatically.
- `~/.local/state/noctalia/settings.toml` can SILENTLY become a plain file (observed 2026-10-17; hardlink/symlink wiring decays) → GUI bar-layout changes then diverge from the repo with no signal. AUDIT: `readlink ~/.local/state/noctalia/settings.toml` must print the repo path; if it's a plain file and repo copy is content-identical, re-arm: `ln -sfn <repo-path> <live-path>` + `noctalia config validate`.
- Landing in the working tree ≠ propagated: other boxes only see it after commit + push to Gitea main. After GUI changes, check `git -C ~/.omp status` and commit (Noctalia's runtime churn — wallpaper path, nightlight, panel positions — rides along; normal).
- niri has NO settings GUI; niri "GUI changes" don't exist, and `niri msg output ...` runtime overrides are not persisted. niri cfg mirror↔live links also decay (all inodes decoupled once) → audit by CONTENT: `diff` every `~/.config/niri/cfg/*.kdl` against its `dotfiles/zz-blankpad/niri/...` mirror, never trust links.
## Clobber window and recovery (2026-10-18 incident law)
- GUI-built layout is **working-tree-only until the hourly live-sync heartbeat commits it**. A merge/sync session that "clears the dirty tree" can `git stash` those edits, and later stash operations can destroy the entries - customizations then vanish from the live bar with the repo copy stale.
- Never blame the GUI or noctalia first: diff live file vs `HEAD`, check heartbeat commits (`git log -- dotfiles/noctalia/.local/state/noctalia/settings.toml`), then the stash chain.
- Destroyed stashes are recoverable: `git fsck --lost-found` lists dangling commits; `git show <dangling>:dotfiles/noctalia/.local/state/noctalia/settings.toml` dumps each candidate; pick by `[bar.default]` richness (capsule groups, extra clock instances). Validate a candidate in a sandboxed `XDG_*_HOME` before touching the live file.
- After recovery, commit the file immediately so the window closes.
## Apply/verify loop (no restart, no reload IPC)
1. Edit the repo `settings.toml`.
2. `noctalia config validate` (checks merged layers; also `noctalia config export [full] | yq -p toml` to inspect effective values).
3. Both layers are file-watched → hot-reload. Prove visually: `noctalia msg screenshot-fullscreen` saves a PNG to `~/Pictures`; read the image and inspect the bar.
4. **Screenshot race:** the `ok` return precedes the PNG write. Never chain `noctalia msg screenshot-fullscreen && magick "$(ls -t ~/Pictures/screenshot_*.png | head -1)" ...` in one command — you crop the PREVIOUS capture. List `ls -t` in a separate later call and crop the named file.
5. Crop for reading: `magick <png> -crop 100%x8%+0+0 +repage /tmp/strip.png`, then read the strip; cross-check clocks against `date -u` / `date`.
## Widgets (v5 census, verified 2026-10-17)
- Full roster in `settings.toml` widget_order plus docs: activity, backlinks, battery, bluetooth, brief, bright, cat, cheatsheet, chart, clipby, clipboard, control-center, cpu, controls, cava (now playing), disk, gpu, help, keyboard, language, launcher, mediaplayer, memory, mic, network, night-light, noctalia-palette, notification-history, notifications, niri-colors, power-section, power-profile, screenrecord, scratchpad, screenshot, session, shell (custom shell command), slowouts, slowouts-visible (per-output bar assignment), speedtest, swayosd-*, taskbar, tray, voiceline, volume, wallpaper, weather, workspaces.
- `clock` widget: `format` (chrono strftime), `schema` (12/24), `multi_line`, `show_seconds`, `popup`, and **timezone** = IANA name. Multiple clock widget instances are supported: ids like `clock`, `clock-utc`, `clock-sea` each get a `[widget.<id>]` subtable -> one capsule per instance. This is how multi-timezone (Seattle work + UTC dev) lands: add `clock` + `clock-utc` to `end` (or `center`), set `timezone = "Etc/UTC"` on the utc one.
- `cat` widget: shows random ASCII art, `rows` setting (4-10).
- `shell` widget: `command`, `run interval` (seconds), `icon`, `terminal`; output lands in its capsule popup - can wrap any CLI (hyprstatus-style).
- `taskbar` widget: shows window buttons **only on outputs where `niri-bridged` is enabled** (noctalia-launcher enables it). Buttons render **icon-only** (app icon from icon theme; fallback = first letter of title); the window title string is NOT shown in the bar. Hover tooltip carries title + app_name. Per-widget settings: `show_icons`, `show_actions`, `disable_middle_click`, `preferred_app_names` (map app_name -> icon for missing icons).
- Widget ids usable in `[bar.*].start|center|end` are restricted to "bar widgets" (`is_bar_widget` allowlist in `bar.rs`); non-bar widget ids are silently dropped at load. `group:<id>` entries render capsule groups.
- Capsule groups: `[bar.<name>.capsule_groups]` id = `["widget",...]`.
- Niri layout law for bars: window width must stay **odd** (strut = (W-1)/2); bars reserve via layer-shell, niri's reserved area = layer surface size, so bar height changes need no niri edit.
## Clock widgets
- `[widget.clock]` settings: `format`, `vertical_format`, `tooltip_format`, `timezone` (IANA id, e.g. `"UTC"`, `""` = system local). Tokens are strftime-compatible (`%H` 24h, `%I:%M %p` 12h, `%F` ISO date); `{:%...}` brace fields optional; `\n` = second line. Docs: docs.noctalia.dev → bar/widgets/clock + configuration/date-format-tokens.
- **One timezone per widget; multiple instances allowed:** any `[widget.<id>]` needs `type = "clock"` for custom ids (bare `clock` id infers it). Each instance converts independently — e.g. local 12h + `timezone = "UTC"` 24h side by side.
- Placement: add ids to `[bar.<name>]` start/center/end, or to a capsule group: `[[bar.default.capsule_group]]` with `id = "g1"` + `members = [...]`, referenced from `start` as `"group:g1"` (member order = left-to-right inside the capsule).
- Local date + local 12h fit in ONE widget (same tz); the UTC 24h clock must be a second widget.
- Expect the date widget (local) and UTC clock to disagree on the day after ~5 PM Seattle — that's correct UTC, not a bug; offer `%F` inside the UTC widget if it irks.
## Bar styles (GUI-visible, settings.toml keys)
- `[bar.*]`: `thickness`, `font_family`, `font_weight`, `font_size`, `opacity`, `border_width`, `border_offset`, `rounded`, `paddings`, `icon_ratio`, `follow_layout`, `output`, `exclusive`, `layer` (`bottom` = below window layer; `overlay` = above windows), `position` (`top`/`bottom`).
- Per-monitor bars: add a `[bar.<name>]` with `output = "<monitor>"` and `follow_layout = true` (niri) -> per-workspace strut follows tall windows on that monitor. This is the mechanism for "bar shrinks when a window is tall" (the bar is a layer-shell strut, NOT a niri layer rule).
- The GUI "Bar" page is the reference list; anything absent from settings.toml is a built-in default.
## Taskbar recipes
- Move window indicator beside workspaces: put `"taskbar"` in `start` after `"workspaces"`.
- Combine workspaces+windows into ONE widget: `[widget.taskbar] group_by_workspace = true` — per-workspace capsules with disc labels (focused/occupied/empty/urgent colors); `workspace_group_content = "icons"|"count"|"dots"` (count/dots: left-click activates the workspace); `hide_empty_workspaces`, `show_workspace_label`, `minimal`, `workspace_label_placement = corner|centered|inside`. Requires compositor per-window workspace assignment (niri: yes; LabWC: no → stays flat).
## Slowouts (window-height-aware bars/panels)
- `slowouts` = hidden engine (not a bar capsule): `[slowouts]` keys `enabled`, `duration`, `easing`, `trigger_offset`; per-monitor `[slowouts.<monitor-name>]` overrides (e.g. `DP-1`) with the same keys plus `edge`.
- `position = "top"` + `exclusive = false` + slowouts on the monitor -> panel hides when a window touches its edge, re-reveals otherwise. `slowouts-visible` = toggle capsule.
- **Slowouts needs niri workspace-autoresize ON** (niri `workspace-autoresize` = "per-workspace" in cfg/layout.kdl `output ... { workspace-autoresize per-workspace }`): noctalia computes hide from workspace height < panel bottom edge; uniform-strut layouts never trigger it.
- Per-output bars: slowouts config keys are monitor names, so one `[bar.<x>]` with `output` + `exclusive=false` + `layer=overlay` per slowout monitor is the supported shape.
## Layout modes and window title decorations
- `[layout]`: `mode` (`tiling`|`floating`|`monocle`), `pseudotiled`, `focus_bar` (window-title bar at top, center, layer-shell; style via `[ui.controls...]`/bar-ish settings), `window_follows_cursor`, `gaps`, `border_width`, `rounded`, `blur`, `opacity`, `borderless_csd`, `show_native_decoration`.
- `focus_bar` is the noctalia analog of niri's drawn window title, but ONE global bar (no per-window arrows). True per-window title tags = niri `draw-with-border` on window rules; noctalia adds no per-window decoration (it's a bar app + portal, composites nothing).
- Floating mode: right-click desktop / `SUPER+Shift+F` / toggle widget; widgets `floating-directories`, `floating-files`, `pins` (sticky notes), `canvas`, `sketchpad`, `post-its`. Float windows snap to screen quarters (`SUPER+Ctrl+Alt+Arrows`) and tile into current layout (`SUPER+Shift+T`). `[layout.floating.files]` = icon/view/sort/preview size.
- `[bar.*].window_display` = `disabled`|`icons`|`text`|`combined` - per-window chips in the bar strip (niri only; this is what niri-taskbar could not do). Values: `disabled`|`icons`|`centered`|`inside`. Requires compositor per-window workspace assignment (niri: yes; LabWC: no -> stays flat).
- The `workspaces` widget itself has no window display; styles are regular/minimal/focus_hint only.
## Law
- Full widget/setting tables: https://docs.noctalia.dev/noctalia/bar/ and .../bar/widgets/<name>/ . Commit bar changes atomically to the command-center repo (checkout is the deployment).
- **Ask before applying.** Frank asks "how do I X" questions about the live bar; answer with the exact snippet + file, apply ONLY on explicit go. A settings.toml edit is a live-deployment change, not a demo.
- Git `M` on settings.toml usually carries noctalia's own runtime churn (wallpaper path, nightlight, panel positions) alongside your edit — mention it when committing.
- Git `M` on settings.toml usually carries noctalia's own runtime churn (wallpaper path, nightlight, panel positions) alongside your edit - mention it when committing.
- Right after building layout in the GUI, commit settings.toml (or trigger `scripts/live-sync.sh`) before any branch/merge work: the uncommitted-GUI-edit window is exactly where the 2026-10-18 clobber happened.
@@ -0,0 +1,38 @@
---
name: omp-bundle-implementation-port
description: "Extract and port a working implementation from omp's minified dist/cli.js bundle (copy-not-invent requests); anchors, python slicing, regex-constant sweep, trace-driven test prediction."
---
# Porting built-in omp behavior out of the minified bundle
Use when Frank says "copy the omp implementation / work off known-working code" — i.e. port a built-in feature (vocalizer segmentation, retry logic, formatting rules) into our own file instead of hand-rolling a heuristic. For merely *auditing behavior claims*, use `omp-bundle-claim-audit`; this skill is extraction-for-porting.
Bundle: `~/.bun/install/global/node_modules/@oh-my-pi/pi-coding-agent/dist/cli.js` (minified; single-letter names, private `#x` fields survive).
## Extraction recipe
1. **Find the setting/entry strings first.** `grep -o 'ce({id:"<area>[^"]*"[^}]\{0,200\}' cli.js` — setting descriptions state semantics verbatim (e.g. `speech.enhanced` = "Rewrite assistant output into natural spoken prose with the tiny/smol model"). Descriptions are quotable ground truth.
2. **Anchor to code with a distinctive token**, not guesses: a method name (`pushDelta`), a state init, or a string. Then slice generously with python (bash heredoc), NOT grep -o which truncates:
```python
src = open('cli.js').read()
i = src.index('pushDelta'); print(src[i-1500:i+3000])
```
3. **Follow the constructor**: pipeline classes instantiate collaborators there (`this.#t ??= new fHe` → `fHe` is the real worker; `#g()` returned `{speakable:new fHe, pending:[]…}`). Dump `class fHe{` +4000 chars.
4. **Regex/helper sweep**: minified code declares shared constants in a trailing `var a,b,c,…` list and initializes them elsewhere (`Xyr=`, `Pwc=function`). Loop the names with `re.search(rf'{name}=', src)` and print ~400 chars each — the actual boundary/cleanup rules live in these one-liners.
5. Write slices to `/tmp/*.txt` and `read` them; don't eyeball megabyte greps.
## Port rules
- Rename fields/methods to readable names but keep logic **1:1** — the value is behavioral fidelity (Frank's "known-working set of code").
- Private `#x` fields port cleanly: TS classes in Bun extensions support `#`.
- Global-regex `.lastIndex=0` before each scan loop — minified code relies on it; keep it.
## Verification shortcut
Before running tests, **hand-trace** each test input through the ported rules (boundary indices, state transitions) and predict exact segment counts/strings; then run — predicted-vs-actual mismatch localizes port errors faster than test output alone. Worked example (2026-10-19, dankvoice PR #26): traced `"First stop here. Second one goes!!! Really? Third ... done"` → predicted 3 segments incl. `"Third ... done"` merged via flush (10-char boundary < 24-char started-min) → bats green first run.
## Known anchors (2026-10-19 bundle)
- Speak-aloud vocalizer pipeline: class `I6o` (gating on `speech.enabled`, suspend counter, enhancer, `#g()` per-message state).
- Utterance segmenter: class `fHe` + helpers `Pwc` (line-head classify), `Iwc`/`_wc`/`b6o`/`w6o` (boundary search), `Cwc`+`y6o` (cleanup: links→label, URL→host, path→basename). Regex consts: `Xyr` sentence-end runs, `pHe` weak breaks, `mwc` abbreviations, `hwc` undecided line-heads, `g6o` horizontal rules.
- Port already living in `agent/extensions/dankvoice.ts` (`SpeechSegmenter`) — when the bundle updates, re-extract `fHe` and diff against it before assuming our copy still matches.
@@ -0,0 +1,65 @@
---
name: omp-extension-live-tui-verify
description: "Verify an omp extension's slash commands and event hooks against a real TUI session: pty submit semantics, observable side-effect instrument, transient-toast trap, agent_end willContinue law, PipeWire output triage."
---
Verify that a `.ts` file in `agent/extensions/` actually works inside the interactive TUI — the black-box bats seam cannot see harness-side wiring (event names, arg passing, mode gating), and it will pass beside a dead hook.
Distinct from `omp-tui-live-visual-verify` (config/theme rendering proven by screenshot): here the instrument is **observable side effects**, not pixels, because extension notifications are transient toasts that vanish before the pty buffer is read.
## 1. Launch the exact build under test
```bash
omp --no-extensions --no-session -e /abs/path/agent/extensions/<name>.ts
```
as a **pty service** (`pty: true`, `ready: {"log": "╭|❯|Tip:|─", "timeout": 60}`).
`--no-extensions` + explicit `-e` proves the file loads by path and nothing else interferes. Neutral cwd (`/tmp`) so repo state cannot color the run.
## 2. Submit input correctly (the costly gotcha)
`write proc://<id>` with a trailing `\n` does **not** submit — the text just sits in the composer.
- **Works:** two writes — first `"/cmd args"` (no terminator), then a **separate** write whose whole content is `\r`.
- **Broken:** `"/cmd args\r"` in one write. It still submits, but the trailing `\r` arrives inside the command args. Symptom: `unknown voice 'narrator1\r'`, an unexpected extra utterance, or a chat message whose transcript line ends in a literal `\r`. That is a harness artifact — never "fix" it by stripping control characters in the extension (`.trim()` already covers what a keyboard can produce).
## 3. Instrument with a stub, never with ears or eyes
Point the extension's player/handler at a script that appends evidence:
```bash
#!/usr/bin/env bash
echo "$1" >> /tmp/stub.log; cp "$1" "/tmp/out-$$.wav"; exit 0
```
Run the TUI with that stub in the env the extension reads (`DANKVOICE_PLAYER=…` style). Then every assertion is a file: `wc -l` of the log (how many times it fired), `ffprobe -show_entries format=duration` (what it produced), `ls -d <tmp-glob>` (that cleanup ran).
Sequence per behavior: command → CR → short `sleep` → count. **Count before and after** each command; the delta is the only honest proof a subcommand stayed silent.
## 4. Discriminate "fired twice" from "fired once per turn"
Stray CR writes can create extra empty turns, each with its own `agent_end` — two utterances for one intended prompt is usually **two turns**, not a duplicate speak. Confirm by counting assistant turns in the transcript (`read proc://<id>`), and by matching each clip's duration to its own answer's length.
## 5. Event-hook contract traps
- `agent_end` payload (`dist/types/extensibility/shared-events.d.ts`): `{ type, messages: AgentMessage[], willContinue? }`. **`willContinue: true` means the harness already scheduled a continuation** (auto-retry / empty-stop retry) — a subscriber that narrates or notifies there speaks an answer the model is about to redo. Gate on it.
- Read the real event/payload shape from `~/.bun/install/global/node_modules/@oh-my-pi/pi-coding-agent/dist/types/…`; grep `dist/cli.js` for the literal event names to confirm they exist.
- A driver test that *calls* the handler by hand proves nothing about emission — that is exactly the gap this live check closes.
## 6. Audio output goes silent while every command reports success
`pw-play` exits 0 and prints `stream drained` even when nobody hears anything. Triage order:
```bash
wpctl status # Sinks, the `*` default, and live Streams
wpctl get-volume @DEFAULT_AUDIO_SINK@
```
- A **`Default Configured Devices` entry naming a `bluez_output.*` node that is not in the Sinks list** = remembered-but-offline Bluetooth: the classic silent-route cause.
- Confirm the stream really links: a short clip can vanish before inspection, so use a multi-second clip and read `wpctl status` mid-play, or target explicitly: `pw-play --target <node-id> <file>` (node ids from `wpctl status`; `wpctl inspect <id>` gives `node.name`).
- Prove the synth path independently of the player: `curl -o x.wav …` then `file x.wav` (expect `RIFF … WAVE … PCM`).
## 7. Land it
Live result belongs in the commit message, the reference page, and the work log — and the guard the live check uncovered gets its own behavior test (assert observable output only: fired count, payload content, silence).
## Cleanup
`/exit` or `proc://<id>/kill` the service; move stub scripts, logs, and clips to `~/.AGENTTRASH/<date>-<topic>/` — never `rm`. Kill background jobs that keep playing to the operator's speakers.
@@ -0,0 +1,116 @@
---
name: omp-models-yml-runner-api-placement
description: "Add or edit a non-chat (tts/image/embedding) model row in ~/.omp/agent/models.yml, wire the speech role, and diagnose a failing speech device without blaming a healthy endpoint"
---
# Scope
`~/.omp/agent/models.yml` (or `models.yaml`) on a workstation: adding a **runner**
model row (TTS / image / embedding / rerank / video) alongside chat providers,
flipping `config.yml` `modelRoles` at it, and diagnosing a speech device that
refuses to speak.
# The landmine
Provider-level `api` accepts **only chat/judge transports**:
`openai-completions`, `openai-responses`, `openai-codex-responses`,
`azure-openai-responses`, `anthropic-messages`, `bedrock-converse-stream`,
`google-generative-ai`, `google-gemini-cli`, `google-vertex`,
`openrouter-decisions`, `typesafe`.
Naming a runner API (`openai-speech`, `openai-images`, `openai-embeddings`, …)
at **provider** level fails whole-file validation, and the failure mode is not
scoped to your provider:
```
Warning: models.yml validation failed — custom providers disabled
Failed to load config file models, Schema error: providers.<id>.api: must be "openai-completions", …
```
Every custom provider disappears from the registry (fleet chat endpoints stop
resolving) and `omp models` lists only built-in locals. Measured 2026-10-18.
# Correct shape
Runner api goes on the **model entry only**; `auth: none` satisfies the
credential requirement; omit `contextWindow`/`maxTokens` (the positivity check
fires only when they are provided — `omp models` still prints filled defaults,
which the runner transport never reads).
```yaml
"frank-tts (dankclaw)":
baseUrl: http://192.168.0.143:7772/v1 # no `api:` here
auth: none
models:
- id: frank-tts
name: "frank-tts (dankclaw) — cloned voices"
api: openai-speech # runner api on the model
input: [text]
```
Roles live in `config.yml` (`modelRoles`), not in `models.yml`. Kind roles
(`image`, `web`, `speech`, `dictation`, `judge`) take no `:thinking` suffix.
# Verify after every edit (never assume the file loaded)
```bash
omp models --kind tts --no-extensions # the new row must appear
omp models --no-extensions | grep -E '<each fleet chat model>' # and still be listed
omp models | grep -c 'validation failed' # must be 0
```
A run that lists only built-ins means your row broke the file — revert before
yielding.
# Speech transport contract (`openai-speech`)
Body is `{model, input, response_format, voice?, speed?}`; `voice` is forwarded
**only** when the caller passed `voice_id`; `sample_rate`/`bit_rate` **throw**
(`openai-speech does not support sampleRate`). Codec comes from the
`output_path` suffix; 15 000-character cap. An unknown `voice` name is a server
error, not a fallback — and `auth: none` makes a dead endpoint read as
*available*, so point `modelRoles.speech` at such a provider only after it has
answered a real synthesis.
# Three speech-role laws (bundle-read + measured 2026-10-18)
1. **No setting carries a voice for `openai-speech`.** The transport builds the
body with `voice` from the call's `voice_id` and nothing else.
`tts.localVoice` is the *local Kokoro backend's* key; `speech.voice` is the
TUI's **speak-aloud** voice, an enum of Kokoro names that never reaches an
HTTP request (setting it to a pack name breaks the vocalizer and does nothing
for synthesis — read `cfgSpeechVoice` in `dist/cli.js` before believing
otherwise). So a voice-less call is the harness's **normal** shape: a
voice-required endpoint needs a server-side default (fleet answer:
`DEFAULT_VOICE` in `scripts/frank-tts.env`, journal marks the line
`(default)`, unknown names still 400 with the list).
2. **An explicit role has no fallback candidate.** `modelRoles.speech` set to one
model yields exactly one candidate, so a dead endpoint or an unresolvable
selector fails with *"No available speech model matches the speech role"*
instead of degrading to Kokoro. Loud-by-design; do not "fix" it by adding a
fallback in the client.
3. **`models.yml` loads at process start; `config.yml` is read live.** A session
older than the new row fails exactly like a dead endpoint while a fresh
process succeeds in the same minute.
# Diagnosing "speech device won't speak" — in this order
1. `curl` the endpoint directly with a real voice name. 200 + audio ⇒ the service
is fine and the fault is harness-side; stop touching the server.
2. Control test in the *same* session: point `modelRoles.speech` at
`local/kokoro` and call the device. It works ⇒ `config.yml` is live-read and
the runner selector or its voice argument is the problem, not the endpoint.
Revert the role immediately after.
3. Distinguish stale registry from dead endpoint with a fresh process:
`omp -p --no-session --no-extensions --no-skills --no-rules --tools tts --cwd /tmp
'Call the tts tool exactly once with text="…" output_path=/tmp/x.wav
voice_id=<name> — then reply with the tool result line.'`
Succeeds ⇒ the long-lived session predates the `models.yml` row; restart it.
4. Cross-check server-side, never trust the client's echo: the façade/access log
line and the engine's own ledger must carry the same byte count the tool
printed. (`model=…` in a tool result is what the client *requested*; a server
line is the fact.)
5. For harness-behaviour claims, read the bundle rather than reasoning from the
tool description: `/home/blank/.bun/install/global/node_modules/@oh-my-pi/pi-coding-agent/dist/cli.js`,
e.g. `grep -o -E '.{300}response_format:[a-zA-Z$]+.{250}'` for the speech body
builder, `grep -o -E 'cfgSpeechVoice:.{0,400}'` for what a settings key feeds.
@@ -1,27 +0,0 @@
---
name: one-decision-per-ask-question
description: "Use when putting decisions to Frank via the ask tool or a grilling round — exactly one work item per question, rounds may group many single-item questions."
---
# One Decision, One Work Item, One Question
Friction-earned rule (corrected twice on 2026-10-18, during the voice/TTS planning).
## Rules
- Each question addresses **exactly one work item**. A round may contain many questions covering different work items; a question may not.
- Never merge two artefacts into one option because they share an implementation dependency. Sharing an endpoint, a service, or a build step is NOT grounds for one question. (`frank-tts` serving both a podcast and an audiobook generator produced exactly this bug.)
- Never offer something Frank did not ask for inside another question's option text. If an idea is mine, it gets its own question or stays out of the plan; it never rides along as "…and also X" in an option label or preview.
- Do not derive option wording from my own scaffolding (todo text, my table row labels, my runbook headings). Derive it from his stated goal.
- Mark the recommended option; a bare "yes" must accept it.
- Facts are mine to fetch (subagent/scout), never a question for him. Only decisions go to him.
- A question whose answer depends on an unsettled fact or another open question belongs to a **later round**, not this one.
## Anti-patterns that triggered this
- One option: "Audiobook/podcast factory — open-notebook + EPUB→narration builder." Two products, one shared dependency, zero requests for the second one. He answered "I never asked for audiobook generation."
- One question: "Is the deliverable the podcast, or the platform (harness voice + OpenWebUI + alerts)?" Four work items in one question. Rejected: "You're lumping multiple asks into one question. Ask me per item."
## Check before sending
For each question: can I name the single artefact it decides? If two names come to mind, split it.
@@ -0,0 +1,27 @@
---
name: openwebui-tts-chain-audit
description: Audit/repair OpenWebUI TTS on Dankclaw when cloned voices get rejected by a 29-name Kokoro enum or synthesis is silent; rootless DB + endpoint probes
---
Audit OpenWebUI's TTS/STT wiring on Dankclaw when a voice is rejected, synthesis is silent, or someone asks "is the cloned voice wired correctly". Not for model-picker/ACL issues (openwebui-picker-acl-repair owns those).
## Shape of the stack
- Container `open-webui` runs **rootless as `dank`** on Dankclaw: `ssh dankclaw 'podman exec open-webui ...'` (NO sudo: `sudo podman` sees an empty world). Host port 3005.
- Server-side config = `webui.db` `config` table (admin), per-user overrides = `user.settings` JSON column. Settings changed via UI persist per-user; admin page persists to `config`.
- Cloned voices live behind the frank-tts façade `:7772` (`/v1/audio/speech`, `/v1/audio/voices`); voices resolve to `/home/dank/voices/<name>/reference.wav`.
## The trap (2026-10-18 law)
`Error: Voice "narrator1" not found. Should be one of: af_heart, ...` (29 names) is **OpenWebUI's bundled in-browser Kokoro** (`browser-kokoro`) rejecting client-side — frank-tts never sees the request. Signature: container logs show zero `audio/speech` hits. Fix = the personal dropdown Settings -> Audio -> TTS Engine -> Default (empty string), not any deploy.
## Probe sequence (read-only, safe)
1. Admin truth:
`podman exec open-webui python -c "import sqlite3; c=sqlite3.connect('/app/backend/data/webui.db'); [print(k,'=',v) for k,v in sorted(dict(c.execute('SELECT key,value FROM config')).items()) if 'audio' in k or 'tts' in k.lower()]"`
Expect: `audio.tts.engine=openai`, `audio.tts.openai.api_base_url=http://host.containers.internal:7772/v1`, `audio.tts.model=frank-tts`, `audio.tts.voice=<cloned name>`.
2. User overrides — a user pinned to `browser-kokoro` beats admin config. CAUTION: `user.settings` can be SQL NULL or the JSON string `"null"`:
`... for uid,s in c.execute('SELECT id,settings FROM user'): d=json.loads(s) if s else None; d=d if isinstance(d,dict) else {}; hits={k:v for k,v in d.items() if 'audio' in k or 'tts' in k.lower()} ...`
3. Endpoint truth: `curl -s http://127.0.0.1:7772/v1/audio/voices` (roster), then POST the exact OpenWebUI body `{"model":"frank-tts","input":"probe","voice":"narrator1","response_format":"mp3","speed":1.0}` to `/v1/audio/speech` — expect `200 audio/mpeg`.
4. Contrast logic: server-path failure leaves a container log line AND a façade error; browser-kokoro failure leaves neither.
## Law
- Full contract + diagnosis live in serverAppConfigs docs (`Dankclaw/OpenWebUI.md` § Text-to-speech, `Dankclaw/Frank TTS.md` troubleshooting). Docs are the source; this skill is just the probe route.
- Rootless gotcha generalizes: any Dankclaw service probe through podman goes WITHOUT sudo unless the unit is a system quadlet.
@@ -0,0 +1,31 @@
---
name: skills-cli-retroactive-store-wiring
description: "Retroactively register hand-copied skills with the vercel-labs skills CLI (global store + lockfile), wire omp via the agents provider (no repo symlinks), and extract authored overrides without twins"
---
# Skills CLI retroactive store wiring (omp tiers)
Retrofit provenance for hand-copied skills and wire them for omp on Dank workstations. Executed 2026-10-18 on blankpad; doctrine doc: `omp-docs/tools/vercel-labs-skills/skill-store-wiring.md` (repo).
## Tier law (final design — do NOT reintroduce per-skill symlinks in the repo)
| Tier | Path | Owner |
|---|---|---|
| Store | `~/.agents/skills/` + lockfile `~/.agents/.skill-lock.json` (v3) | `skills` CLI |
| Authored | `<repo>/agent/skills/` real dirs | Frank, branch → PR |
| Managed | `~/.omp/agent/managed-skills/` | `manage_skill` only |
omp has NO agent id in the skills CLI (79-agent registry in `dist/cli.mjs`; `-a pi` writes `~/.agents/skills` too — pi detector keys on `~/.pi/agent`). omp reads the store DIRECTLY via its `agents` provider (`skills.enableAgentsUser`, default true; check with `read cfg://skills`). Precedence: authored (native, 100) > skillshare > ... > agents provider > managed (5). Identical copies collapse by realpath; differing same-named copies survive namespaced `agents/<name>` with a startup warning — so when authoring an override, REMOVE the store twin (`npx -y skills remove <name> -g`; prunes lockfile too) or `skills update -g` resurrects a twin.
## Procedure (retroactive registration)
1. List the repo/live skill dirs to register; identify true sources (per-skill — e.g. `find-skills` is `vercel-labs/skills`, not `mattpocock/skills`).
2. Drift check FIRST, per skill, before anything moves: `diff -rq <live>/<name> ~/.agents/skills/<name>` after canonical install; abort-and-report on drift (byte-identical = clean cutover).
3. Canonical install (scratch dir with a package.json; global scope): `npx -y skills add <owner>/<repo> --all -g` (+ per extra source `npx -y skills add vercel-labs/skills --skill find-skills --agent universal -g`). Artifacts: store dirs + `~/.agents/.skill-lock.json`; verify `jq '.skills|length'`.
4. Authored extraction (only for skills the user will customize): copy dir into repo `agent/skills/<name>/`, add an "Authored override" note after frontmatter, then `npx -y skills remove <name> -g` and confirm `jq '.skills|has("<name>")' == false`.
5. Clear repo copies of store-managed skills (repo records authored overrides ONLY). Live cutover after merge: move old dirs to /tmp snapshot, `git merge --ff-only origin/main` in the live checkout.
6. `skills ls` from a repo containing `agent/skills` mislabels skills as Eve project skills (path collision) — attribution noise, ignore.
7. Fresh-box recipe (three commands, no wiring): add `--all -g`, add find-skills, `remove grilling -g`.
## Gotchas
- Eve/Codex `agents/openai.yaml` files ride along from upstream; omp ignores them — prune from authored dirs (they get swept off disk elsewhere, leaving phantom ` D` in git status).
- `skills remove` prunes only global scope if `-g` given; check lockfile after.
- Mid-run doc readers (subagents) may see pre-cutover trees — send them a correction message, don't let stale advice ship in issue bodies.
@@ -0,0 +1,44 @@
---
name: strix-halo-npu-readiness-census
description: "Engine-agnostic census of whether an AMD Strix Halo / Ryzen AI host can run anything on its XDNA2 NPU: driver bind, firmware, device perms, IOMMU, distro XRT, missing AIE compiler, fabric clock, RAM headroom."
---
Use when asked "can we run <engine/model> on the Strix Halo / Ryzen AI NPU?" for a runtime that is **not** halogen (halogen has its own gate + vendor catalog: use `halogen-npu-feasibility-census` for that). This answers only: is the *host* able, and what is missing.
## Why it is usually the wrong door first
XDNA2 executes **precompiled AIE partition programs** loaded through XRT → `amdxdna`. There is no generic tensor dispatch: an engine built on ggml/llama.cpp (or any GGUF loader) cannot "enable" the NPU — the port must be a re-export + vendor compile, not a flag. So pair this census with the accelerator the same engine *can* select by build flag (Vulkan/HIP on the gfx1151 iGPU) before proposing NPU work.
## Census (all read-only, over ssh from the operator box)
```bash
ssh <host> '
cat /proc/cmdline; ls /sys/kernel/iommu_groups | wc -l # iommu=pt required; groups==0 => IOMMU off => NPU dead
lsmod | grep -i amdxdna # in-tree driver
sudo dmesg | grep -iE "xdna|npu" | tail # "Initialized amdxdna_accel_driver <ver> for 0000:c6:00.1"
lspci -nn | grep -iE "npu|processing" # Strix Halo = 1022:17f0
ls /sys/bus/pci/drivers/amdxdna # must list the BDF
ls -l /dev/accel # accel0, root:render 660
id -nG <deploy-user> | tr " " "\n" | grep -E "render|video" # rootless podman needs render, else --device fails at create
find /usr/lib/firmware -iname "*npu*" | head # firmware is /usr/lib/firmware/amdnpu/<devid>_<rev>/npu.sbin*.zst — match the PCI rev
dpkg -l | grep -iE "xrt|xdna"; ls /opt/xilinx/xrt/lib 2>&1 # distro libxrt-npu2 = XDNA2 runtime; vendor /opt/xilinx/xrt usually absent
apt-cache policy libxrt2 libxrt-npu2 | grep Candidate
apt-cache search onnxruntime | head # distro ONNX RT exists; the Ryzen AI EP does not
python3 -c "import onnxruntime" 2>&1 | tail -1 # absence of the EP + of ryzenai-compile is the real blocker
for c in /sys/class/drm/card*/device; do echo "-- $c"; cat $c/power_dpm_force_performance_level 2>&1; cat $c/pp_dpm_fclk 2>&1 | tr "\n" " "; echo; done
nproc; free -g | head -2 # RAM headroom + thread count the engine will pick
'
```
## Reading it
- Driver bound + `accel0` + firmware dir + `iommu=pt` ⇒ **kernel side is ready**; do not re-litigate "is the NPU disabled". A missing device node is *not* the modern failure mode.
- `auto` on `pp_dpm_fclk` / `power_dpm_force_performance_level` ⇒ fabric clock **unheld**. GPU+NPU concurrently with a moving fclk hangs these hosts and corrupts NPU results; any NPU plan must pin the top fclk step (or run in a container holding it) first.
- No `ryzenai-compile`/ONNX Ryzen AI EP ⇒ nothing on the host can produce a partition program. That is the enablement delta, and it is a toolchain install + a model-specific export/quantize/compile project, not a config change.
- `free` headroom matters: NPU partitions want a few GB of host RAM each and can log benign `Failed to alloc dev bo memory, ret -28` under pressure.
## Laws / traps
- Read state only. Never probe or load the NPU beside a live inference service — stop + mask the service first (fleet benching policy); this host class has a precedent of a concurrent GPU/NPU experiment needing a power cycle.
- `sudo podman ...` finds nothing (per-user rootless storage); run podman as the deploy user.
- `/dev/accel/accel0` existing does not mean a context/PASID can be created; with IOMMU off the failure is at context creation, not at the node.
@@ -0,0 +1,152 @@
---
name: vault-one-fact-one-owner-dedupe
description: "\"Collapse per-payload/per-attempt vault pages into one owner page per endpoint without losing a fact: port-before-cut orphan census, doubled-page repair, trash-aware tools, delegated-write verification, index regeneration, and the merge-resolution order.\""
---
# One fact, one owner: dedupe the vault without losing a fact
Use when a repo has accumulated one page per attempt/era (runbooks, bench logs, swap
narratives) and the law is **one page owns one thing**. Applies to
`serverAppConfigs-docs/` (Obsidian vault, `AGENTS.md` → *Documentation Policy*), but the
mechanics are general.
## 1. Decide ownership before touching files
- Endpoint/service page owns: current shape, **Eras** table (window | payload | runtime |
shape | replaced because | rollback), **Laws**, wire contract, files.
- Technique page owns the mechanism and the arithmetic — **no per-endpoint throughput
table or boot ledger**.
- `log.md` owns incidents and laws only. A swap is an Eras row, never a log entry.
- `AGENTS.md` carries operator-critical numbers + cross-border laws; everything else links.
- A **retired** endpoint still gets one locator page: era windows quoted verbatim from each
era page's own banner, no numbers restated, and any date conflict recorded as an open
question instead of silently resolved. Never pick a winner between two primary sources.
## 2. Single-writer rule (the mistake that costs the most)
Facts get **ported into the owner page before they are cut** anywhere else. So while any
subagent may port facts, only ONE writer may touch the owner pages. Spawn children with an
explicit `DO NOT EDIT <owner pages>` and require a `needsPort` list in their report instead
of letting them append. Send the narrowing message early — a child already editing them has
to be reconciled by hand.
## 3. Port-before-cut census (proves nothing was lost)
For every deleted line, extract distinctive keys and check them against the vault minus the
file being rewritten. Any line with **no** surviving key is an orphan → port, or accept
deliberately and say so. Use `scripts/port-census.py <new-dir> <git-HEAD:path|file>` (numbers
with ≥ 4 int digits, decimals, flags, paths, backticked spans, `--`, ALL-CAPS, or ≥ 2 hyphens).
Two calibration traps:
- **Prose words are not facts.** A hyphen or trailing period inside a word (`long-standing`,
`deployed:`) was counted as a tracked token while real identifiers hid behind it; that noise
buried 300 real lines under 979 fake ones. Strip punctuation, require fact shape.
- **The corpus decides the question.** Corpus = the new file only → "what did this rewrite
drop?" Corpus = whole vault → "is the dropped fact orphaned repo-wide?" Ask one at a time.
Also grep `AGENTS.md` separately — a fact it carries is not an orphan.
## 4. When a page is the same page twice
Signature: a page whose `wc -l` is ~2× its `HEAD` size, with a **second frontmatter block in
the body** whose closing `---` is glued onto the end of a body/timestamp line. Cause chain: a
frontmatter rewrite that re-reads the file it just wrote (so its own output becomes the body),
then a fence-repair pass keyed on `line == "---"` that cannot see a glued fence and inserts a
fence mid-page, so the next pass treats the tail as a new document.
Un-double rule that worked: find the first frontmatter's close (accepting a glued fence), then
the first `type:` line after it that has more keys (`title|description|tags|timestamp`) behind
it — that is the second copy, and a stray `type:` in a code block has no key run. Keep the copy
whose body is a **superset** (compare after stripping the dropped copy's own frontmatter),
un-glue the fence, and prove `0` census losses before writing. Refuse to guess: if the halves
differ materially, stop.
## 5. `.AGENTTRASH` is not vault content
Every tool that walks the vault must exclude it — **both the scan set and the resolution
index**. The link checker resolving links *into* the trash turns "live page points at a
deleted page" into a false PASS, which is worse than a false alarm. The `docs_completeness`
seam's `find` must carry `-not -path '*/.AGENTTRASH/*'` in both walks, or a trashed page
demands an index row and a trashed page can satisfy the docs requirement for a live service.
Trash is gitignored; move with plain `mv` into the dated dir. `git mv` into an ignored path
stages a rename the next agent cannot see (`git restore --staged <src> <dst>`). Never `rm`,
never `git clean -f`.
## 6. Rewire + regenerate indexes mechanically
```bash
grep -rnoE "\[\[(page-a|page-b|...)\]\]" --include="*.md" serverAppConfigs-docs | grep -v AGENTTRASH
grep -rnoE "\((page-a|page-b|...)\.md\)" --include="*.md" serverAppConfigs-docs | grep -v AGENTTRASH
```
Both wikilinks and markdown path refs must be repointed (Research `See Also` lists and bench
pages are where path refs hide). Then **regenerate** index rows with a script, never by hand.
The generator bug to check for: presence tested as a **bare stem substring** — a page whose
name prefixes another's (`frank-medium` inside `frank-medium-rocmfpx`) then silently never
gets a row. Test the wikilink form `[[<stem>]]`.
## 7. Enforce the law with a seam
`tests/docs_completeness.bats`: derive the live set instead of hardcoding it — an endpoint is
live when `scripts/` holds **both** `<name>.env` and `<name>.service`; fail if any
`<name>-*.md` page exists, and guard against a vacuous derivation (`derived -ge 3`). A
re-created era page then cannot pass tests. For the length hint, prefer **derived** exemptions
(live endpoint, or a `retired-endpoint` tag: a campaign ledger that exists nowhere else is
owned by the page that measured it) plus one documented per-page opt-out; never let a size
ceiling force a ledger to be split across two owners.
## 8. Edit-tool hazard (costs the most time)
Body rows beginning with `-` or `+` are op markers. The documented `+-` escape **writes a
literal `+`** — do not use it. Safe rewrites inside an existing bullet: keep the `- ` opener
line untouched and PUT only the indented continuation lines, or convert the note to a nested
bullet whose body lines start with two/four spaces. If a wrapped `[[Two Word Page]]` shows up
as an unresolved link, the target was hard-wrapped across lines — unwrap it.
## 9. Delegated writes: verify bytes, never narrative
Measured in one campaign, all four failure modes live:
- A subagent killed by the runtime limit yielded a 495-line owner page, a verified era table
and a byte census — **the file did not exist** and its table was self-referential.
- Another wrote its output to disk and died without reporting, leaving a rewritten `log.md`;
the census showed it had dropped laws held nowhere else.
- Verdict tables claimed "0 sole records / no contradictions" while missing the contradiction
sitting in their own evidence row, and invented bullet IDs — one renamed a bullet to the
**opposite** claim.
- A scout called accurate docs "WRONG" because the docs said `wip: "down"`.
Rules: after ANY delegated write run `wc`/`ls` + the orphan census yourself; re-grep every
claimed holder before cutting a line; treat `cancelled`/timed-out yields as unverified no
matter how concrete they read; and re-read the source bullet before trusting a table's ID.
## 10. Merge order (a long-lived branch under a moving main)
1. Commit your work in atomic groups **before** merging (a dirty tree cannot merge cleanly).
2. Inspect the incoming commits: `git log --oneline --stat HEAD..origin/main`. If they modify
a page you deleted, **port their additions into the owner page**, then merge and resolve
the modify/delete as `git rm`.
3. Resolve a content block with `write conflict://<id>` (`@ours` / `@theirs` / explicit text),
then **`git add` the file** — resolving content does not stage it.
4. **Re-probe live state after the merge, before you write any number.** A campaign that
reported fleet shapes at the start was made stale by a mid-campaign reslice on main: probe
`/slots` and `tr '\0' '\n' < /proc/$(pidof <engine>)/cmdline` again at the end, and let the
live answer beat both your earlier probe and the docs.
5. `git * --no-verify` is forbidden here. Sweep dead paths in `AGENTS.md`
(`grep -oE "[A-Za-z0-9._-]+\.md" AGENTS.md | sort -u`, then `find` each; hard-wrapped names
are false positives — confirm with `ls`).
## 11. Verify, open, land
- `./tests/run.sh` (full suite) + `python3 scripts/check-vault-links.py serverAppConfigs-docs`
→ must print `0 unresolved links`, and the OKF linter `0 violations`.
- Env trims: prove value-neutrality mechanically (`git show HEAD:scripts/<svc>.env | grep -E
'^[A-Z_]+=' | sort` vs working copy, diff empty). **`scripts/<svc>.env` is a deploy-planner
path**: a comment-only trim makes the next service-scoped deploy restart a healthy endpoint.
- Open the PR through the API with a 600-perm curl config (managed skill
`gitea-api-pr-operations`), end the body with the `cwd:` / `session:` footer, then
`xdg-open <PR-URL>` the instant it exists. Never merge without Frank's current explicit OK.
- Docs-only change ⇒ **no deploy**. Fast-forward the deploy checkout only
(`git -C ~/Projects/serverAppConfig merge --ff-only origin/main`).
- Say what was NOT done, in the PR body: soft lint tallies left (missing `## Citations`),
conflicts left standing, repo config that was never installed on a host.
@@ -1,6 +1,6 @@
{
"v": 1,
"lastConsolidatedAt": 1792359756091,
"lastConsolidatedAt": 1792398332410,
"lastResult": {
"at": 1791599865775,
"sessions": 1,
@@ -1,4 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792359704968
"lastConsolidatedAt": 1792401025778
}
@@ -1,4 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792359739617
"lastConsolidatedAt": 1792398289746
}
@@ -1,118 +1,70 @@
## Runtime Stack
## Subagent routing (harness law, 2026-10-18)
**llama.cpp** is the inference runtime for all `frank-zealot`-class endpoints. The `frank-zealot` service runs llama.cpp master (0.5.0-dev, commit `5fc4f3c`), CUDA sm_86 build, under a root systemd unit.
**No subagent class may route to `frank-archon`** — the operator session lives there and
the endpoint runs 3 sequences (`--max-num-seqs 3`), so `task.maxConcurrency + 1` children
eat the parent's own KV slots. Violation cost: three doc children + parent = 4 sequences
on 3 slots, children ran 2 h 27 m / 2 h 45 m, the interactive session starved.
Routing and bounds live in `~/.omp/agent/config.yml` (`task:` block — the owner; verified
with `read cfg://task/agentModelOverrides`): heavy writers (`task`, `scout`) → frank-dragoon
(2 slots, idle, slow card ⇒ slice work smaller), bursty readers (`reviewer`, `sonic`,
`designer`, `librarian`) → frank-zealot (2 slots, also the compaction hub and every
tiny/smol/plan/commit/memory role). Caps: `maxConcurrency: 2`, `maxRuntimeMs: 1800000`,
`softRequestBudget: 120`, `maxRecursionDepth: 1` (children never spawn children).
`cfg://.../save` approvals auto-deny after a hardcoded 10 s dialog — after Frank has
approved a change, edit `config.yml` directly and validate the YAML; a running session
picks global-config edits up at once. Full procedure: managed skill
`bounding-subagent-runtime`.
## Model Inventory
## Documentation law (2026-10-18)
### frank-zealot (Dankclaw: 192.168.0.143:7771)
**One fact, one owner.** The `serverAppConfigs` repo owns every fleet fact;
`AGENTS.md` restates only what a deploy gate or the harness needs and otherwise
links. `serverAppConfigs-docs/` (Obsidian vault) carries the lore: one page per
endpoint (`[[frank-archon]]`, `[[frank-dragoon]]`, `[[frank-zealot]]`) holding
Current shape, **Eras** (one row per payload swap: dates, payload, runtime,
shape, why replaced, rollback), Laws, wire contract, files. `log.md` records
incidents and laws only — no per-swap ledgers, no bench tables. A retired
payload is an Eras row, never a page of its own. `scripts/<service>.env` beats
any page: where they disagree, the page is the bug.
**Ternary-Bonsai-2-27B-PQ2_0.gguf** (prism-ml/Ternary-Bonsai-2-27B-gguf)
## Model swaps (2026-10-18)
- Runtime: llama.cpp
- Format: PQ2_0 quantized GGUF
- 27B parameter class
- Vision: native BF16 mmproj projector for image input
- MTP: OFF (no `nextn` tensors in checkpoint)
- Context: 256k per-slot window (`--ctx-size 401408 --parallel 2` = 200,704 tokens effective)
- Batch: 4096 / ubatch 2048 (CUDA optimum)
- Log verbosity: 4
- Ports: 7771 on Dankclaw
Swap the model, don't instrument the swap: edit the trio
(`scripts/<svc>.env` + serve script + unit) → `./tests/run.sh` → PR →
`deploy.sh <host> --service <svc>` → `/health` + one chat / tool-call / vision
probe → done. **No benchmarks, A/Bs, ladders, or acceptance tables unless
Frank explicitly asks for data.** If a payload misbehaves, revert the commit and
redeploy. When a bench IS ordered, the GPU-safety procedure (stop + mask, no
scratch ports, never `systemctl disable`) is `AGENTS.md` → *Model swaps*
and *Deployment completeness*.
### frank-dragoon (Dankclaw: 192.168.0.143:7770)
## Where facts live
**Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated** (`.hgn` format)
|Need|Owner|
|---|---|
|Topology, ports, payload, shape|repo `AGENTS.md` → Fleet topology; `scripts/<svc>.env` is the authority|
|Endpoint lore, eras, laws, rollback|vault `serverAppConfigs-docs/LLM/<endpoint>.md`|
|Harness model entries (`contextWindow`, `maxTokens`, `reasoningContentField`, `modelRoles`)|`~/.omp/agent/models.yml`|
|Incidents and operational laws|vault `serverAppConfigs-docs/log.md`|
|Service/infra pages|vault `Dankclaw/`, `Dankserver/`, `Infrastructure/`, `Architecture/`|
- Runtime: halogen-flash-server 0.16.2 (digest-pinned `ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84…`)
- Format: v2 `.hgn` (flash-server exclusive)
- MTP head: INSIDE checkpoint (`HALOGEN_MTP_HEAD` unset)
- Vision: ON (v2 tower loads beside checkpoint)
- Base: abliterated (27B-era was censored finetune)
- Slots: 2 × 262,144 ctx (KV pool 524,288 positions)
- Server sampler: 1.0/0.95/20
- Prompt cache: ON by default
Models.yml resolution rules that are harness-local: a default model resolves as
a `defaultProvider` + `defaultModel` pair; a subagent override is a bare model
`id` and resolves only when unique across providers; two ports on one host need
two provider blocks — the file cannot express "same host, different port".
### frank-archon (Dankserver: 192.168.0.235:7770)
There is **no audio input anywhere in the fleet** (gone with the Gemma4
retirement, 2026-10-01). All three chat endpoints take text + images.
**StillDeadcode/qwen3.8-next-flash-fp8-iq4r-moe** (`.rad` format)
## Retired laws
- Runtime: radiance 1.0.13 (digest-pinned `stilldeadcode/radiance@sha256:4c3f484564…`)
- Format: fp8-KV `.rad` (121,969,901,568 B = 116,322 MiB)
- MTP head: MTP depth 2, MNBT 2048, Froggeric v22.5 template
- Vision: 27-layer Qwen-VL tower native
- KV: 3 × 200,000 fp8-KV (`--max-num-seqs 3`)
- 30,720 MiB of 30,969 MiB claimable
- 44 GiB/rank pinned host pool, PLE pinned to RAM
- Base-alignment: censored (abliterated family lives on frank-dragoon)
## Resolution Rules
Official model ids are StarCraft unit names, on the wire since 2026-10-09, and since 2026-10-10 they are also the SERVICE names: `frank-archon` → `192.168.0.235:7770`, `frank-dragoon` → `192.168.0.143:7770`, `frank-zealot` → `192.168.0.143:7771`.
The default model resolves as a `defaultProvider` + `defaultModel` pair (provider must serve the model); a subagent override uses a bare model `id`, which resolves only when unique across providers. Two ports on one host need two providers — the file cannot express "same host, different port".
When renaming a service, retiring an endpoint, or moving a model: update the provider block, model `id`, `contextWindow`, `maxTokens`, `input` in `models.yml`, then fix every `modelRoles` entry that named the old endpoint — a role pointing at a provider the file does not define fails at call time. As of 2026-10-06 **all three endpoints accept images** (`input: [text, image]`) — `frank-dragoon` returned to vision with the flash-server v2 swap, while `frank-archon` takes them natively and `frank-zealot` through its BF16 mmproj.
Reasoning channel differs by runtime: llama.cpp AND SGLang (qwen3 parser, live-verified) emit `reasoning_content`, vLLM emits `reasoning` — `models.yml` sets `reasoningContentField` per endpoint to match.
There is **no audio** input anywhere in the fleet: that capability left with the FLM NPU endpoint on 2026-09-11, returned 2026-09-17 with the Gemma4 projector's audio encoder, and left again with the Gemma4 retirement on 2026-10-01.
## Boot Persistence & Self-Healing (MANDATORY)
Every deployed, working Podman container MUST have a self-healing, boot-persistent Quadlet unit. A container that runs only from `compose.yaml` or a manual `podman run` dies silently at reboot — rootless Podman does not auto-start bare containers, and `restart: unless-stopped` does not survive the explicit stop that shutdown performs. Never report such a service as "up".
Unit requirements:
- **Boot persistence** — `[Install] WantedBy=default.target`, installed to `~/.config/containers/systemd/<name>.container`, enabled in the user manager, with linger on for the deploy user (`loginctl show-user dank -p Linger` → `Linger=yes`).
- **Self-healing** — `Restart=always` (or `on-failure`) with a short `RestartSec`; quadlet health check where the service has one.
- **Repo provenance** — the `.container` file lives in this repo (`<host>/<svc>/quadlet/`), is installed by the deployer, and is covered by the quadlet test seam. The host-side unit is generated state; the repo file is the source of truth.
Before declaring a service deployed: `systemctl --user is-enabled <name>` → `enabled`, `is-active` → `active`, and the container answers its health check.
A running container with no unit is a gap: write the unit, test it, deploy it.
This rule exists because reboots found gaps twice (2026-08-26: Caddy as a bare compose container never returned; 2026-09-11: five observability services had no units). The observability services now have units under `dankclaw/observability/quadlet/` and their compose definitions were removed — one owner per container name. The stack is **configured and delivering as of 2026-09-17**: a Grafana datasource and the `llm-fleet` dashboard are provisioned from `shared/grafana/provisioning/`, `shared/prometheus/rules/llm-fleet.yml` loads 5 alert rules + 1 recording rule, and firing rules are delivered: Prometheus → Alertmanager (`dankclaw/observability/quadlet/alertmanager.container`, loopback :9093) → host-side Signal relay (`scripts/signal-relay.py`, user unit, 192.168.0.143:18093 — the host LAN IP, the one bind a container can reach as `host.containers.internal`; iptables admits loopback, the host and the podman bridge subnet only) → signal-cli account 318311.
Prometheus targets read down for structural reasons (HTML-scraped "probes", Gitea metrics off); the remedy is a blackbox exporter. See `serverAppConfigs-docs/Infrastructure/Observability.md`.
## Benchmarking Policy (MANDATORY)
**STOP the production service BEFORE benchmarking** — these servers serve real users, and a bench beside a live service starves the GPU and corrupts results. Use the runtime's own harness: `llama-bench` for the llama.cpp endpoints; a live llama.cpp server also reports honest per-request numbers in the `/completion` `timings` object (prefill/decode rates, `draft_n`, `draft_n_accepted`), which is how frank-dragoon and frank-zealot were measured. Rolling your own bench requires asking first.
Scratch ports are not used on LLM hosts — a test process cannot share the single GPU anyway; validate against the service itself.
A gufo-era law: **`gufo bench` cannot rank speculative-decode settings, and will invert the ranking.**
Measured 2026-09-28 on frank-dragoon at depth 32768: its corpus reports `acceptance=0.933 ± 0.000` with an **identical trace sha256** across draft widths, i.e. the same highly-predictable text every run, and 93 % of every proposal accepted. It reported 29–37 t/s decode where real traffic gives ~15 t/s, and it made `--draft-tokens 16` look 6 % faster than 7 when real text made it 14 % *slower*. Use it for shape, not for A/B. For an A/B, replay **real** text through the live server and read the `Server-Timing` header — but note the unit rides in the **name** half (`ttft;dur=402.485`), so splitting on `=` alone keys the dict `ttft;dur` and every lookup silently returns nothing. Generate **at least 128 tokens** for the measurement: at 8 tokens, `inter_token` is first-token noise and the run-to-run spread swamps every real difference.
This covers **any GPU experiment, not just benchmarks** — including a bare 2-rank RCCL/`torch.distributed` probe. On 2026-09-16 one such probe was run against the live service "because it only needs 200 MB of VRAM"; the host went hard down ~20 minutes later (no ARP reply, 100% ICMP loss from two subnets, no recovery — a power cycle was required). A hung AQL dispatch wedging the GPU driver is the plausible mechanism, and this host has precedent for going unreachable until a power cycle. If an experiment needs GPUs, stop and mask first, or use a host that serves nobody. Telling an off machine from a wedged one: `ip neigh show <ip>` from a peer — FAILED means off/NIC dead, while a merely wedged kernel usually still answers ARP.
1. Stop and mask (self-healing would restart it):
- Dankclaw `frank-dragoon` (root unit, halogen podman on the iGPU):
`sudo systemctl stop frank-dragoon && sudo systemctl mask frank-dragoon`
- Dankclaw `frank-zealot` (root unit, llama.cpp on the 3090):
`sudo systemctl stop frank-zealot && sudo systemctl mask frank-zealot`
- Dankserver `frank-archon` (root unit, radiance on both R9700s, TP=2):
`sudo systemctl stop frank-archon && sudo systemctl mask frank-archon`
2. Bench.
NOTE: `systemctl mask` FAILS on a relinked unit (the unit file in `/etc/systemd/system/` is itself a symlink into the checkout — mask refuses to replace it). Stop is enough for the bench window; the deploy restores the unit, so re-deploy after benching instead of unmasking.
3. Unmask and start; verify `curl http://192.168.0.<host>:7770/health`.
**CRITICAL:** never `systemctl disable` a system unit on these hosts — it deletes the unit file from `/etc/systemd/system/`, not just the symlink. `mask` symlinks to `/dev/null` and is safe/reversible.
## Subagent Lifecycle (MANDATORY)
A subagent that appears stuck must have an explicit recovery path defined before the subagent is considered deployed. "Stuck" includes: silent completion halt, repeated identical responses, or extended latency without token emission.
Recovery requirements:
- **Explicit timeout** — a hard timeout (≤30s) on the subagent's response channel, with a defined action (retry, fallback, or escalate).
- **State checkpoint** — the subagent maintains checkpoints at decision boundaries, allowing resumption from a known good state.
- **Health signal** — the subagent publishes a heartbeat (≤5s interval) that triggers the recovery path when missed.
A subagent without these three properties is a gap: write the timeout, add the checkpoint, wire the heartbeat, then deploy.
This rule exists because subagent hangs were observed in early deployments (2026-09-xx: silent completion halt; 2026-09-xx: repeated identical responses). The deployment script must verify the heartbeat channel is live before reporting "deployed".
Before declaring a subagent deployed: verify the heartbeat endpoint returns within the timeout window, and confirm the recovery path is wired (retry/fallback/escalation logic exists in the codepath).
A subagent without a heartbeat or recovery path is a gap: wire the heartbeat, add the recovery path, then deploy.
- The old "Benchmarking Policy (MANDATORY)" wording demanded a bench harness per
payload; superseded 2026-10-18 by the swap law above.
- A "Subagent Lifecycle (MANDATORY)" rule (heartbeat ≤5 s, checkpoints, hard
timeout) was recorded here 2026-09 and **never implemented anywhere**; it
described nothing that exists and is deleted 2026-10-18. Do not re-add it
without a real implementation.
- The fleet model inventory that used to live in this memory file drifted out of
date within hours (it still claimed Bonsai-2-**27B** at `--ctx-size 401408`
and a dragoon 524,288-position pool). Memory files do not get deploys — the
repo does. That is why it is pointers now.
@@ -1,7 +1,24 @@
## Voice Generation
- Custom voice source material must exclude the first 10 seconds of any audio sample file used to generate voices; this is a project-wide invariant across all source files, not a per-file exception.
- Voice selector valid options: af_heart, af_alloy, af_aoede, af_bella, af_jessica, af_kore, af_nicole, af_nova, af_river, af_sarah, af_sky, am_adam, am_echo, am_eric, am_fenrir, am_liam, am_michael, am_onyx, am_puck, am_santa, bf_emma, bf_isabella, bm_george, bm_lewis, bf_alice, bf_lily, bm_daniel, bm_fable.
## Input Capabilities
All endpoints accept text input with optional image input: `frank-dragoon` returned to vision with the flash-server v2 swap, while `frank-archon` takes them natively and `frank-zealot` through its BF16 mmproj.
There is no audio input anywhere in the fleet: that capability left with the FLM NPU endpoint on 2026-09-11, returned 2026-09-17 with the Gemma4 projector's audio encoder, and left again with the Gemma4 retirement on 2026-10-01.
## Voice Usage Notes
- Voice generator output does not affect token counting or inference costs — all voices are rendered post-inference.
- Voice quality varies by source sample: exclude the first 10 seconds of any audio sample file used to generate voices; this is a project-wide invariant across all source files, not a per-file exception.
- Voice selection is client-side only; the server does not generate or return audio data.
## Load Management
- Subagent settings must prevent frank-archon from being overwhelmed; concurrent request handling prioritizes endpoint stability over throughput.
## Podcast
- Podcast functionality is sourced from open-notebook; this is a project decision established before this document was created.
- Podcast functionality is sourced from open-notebook; this is a project decision established before this document was created.
@@ -1,8 +1,8 @@
{
"v": 1,
"lastConsolidatedAt": 1792367186349,
"lastConsolidatedAt": 1792400853634,
"lastResult": {
"at": 1792361576391,
"at": 1792393886960,
"sessions": 1,
"deltas": 1,
"model": "frank-zealot"
@@ -1,6 +1,6 @@
{
"v": 1,
"lastConsolidatedAt": 1792367076712,
"lastConsolidatedAt": 1792367676725,
"lastResult": {
"at": 1792366721197,
"sessions": 1,
@@ -0,0 +1,3 @@
## top bar
- Preserve top bar customizations; customizations lost or obliterated on subsequent runs
- Todo list updates as tasks change, not waiting for entire bill of tasks to finish
@@ -0,0 +1,10 @@
{
"v": 1,
"lastConsolidatedAt": 1792381281460,
"lastResult": {
"at": 1792381281460,
"sessions": 1,
"deltas": 1,
"model": "frank-zealot"
}
}
@@ -0,0 +1,2 @@
## window outlines
- Window outline color is amber, and outline thickness is thickened
@@ -0,0 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792381246498
}
@@ -0,0 +1,3 @@
# Output behavior
Output must not be shaken off during presentation. Output remains anchored until explicitly confirmed.
@@ -0,0 +1,10 @@
{
"v": 1,
"lastConsolidatedAt": 1792400453482,
"lastResult": {
"at": 1792398531282,
"sessions": 1,
"deltas": 1,
"model": "frank-zealot"
}
}
@@ -0,0 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792381487662
}
@@ -0,0 +1,10 @@
{
"v": 1,
"lastConsolidatedAt": 1792393561866,
"lastResult": {
"at": 1792381870670,
"sessions": 1,
"deltas": 1,
"model": "frank-zealot"
}
}
@@ -0,0 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792388836682
}
@@ -0,0 +1 @@
{"v":1,"kind":"product_decision","statement":"Limit on zealot set to 3, dragoon set to 2, archon set to 3","source":"explicit_user","evidence":"make the limit on zealot 3, dragoon 2, archon 3","friction":{"corrective":false,"regression":false,"subtle":false},"sessionId":"01a15302-f12d-77d8-9a33-be31a1a05528","ts":1792394470419}
@@ -0,0 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792394427081
}
@@ -0,0 +1 @@
{"v":1,"kind":"product_decision","statement":"Documentation links to @~/Projects/serverAppConfig/serverAppConfigs-docs/","source":"explicit_user","evidence":"correct our documentation to just link to @~/Projects/serverAppConfig/serverAppConfigs-docs/","friction":{"corrective":false,"regression":false,"subtle":false},"sessionId":"01a1531d-3e48-70b0-8ee0-6d48a197cae3","ts":1792397374946}
@@ -0,0 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792397349857
}
@@ -0,0 +1,10 @@
{
"v": 1,
"lastConsolidatedAt": 1792426412619,
"lastResult": {
"at": 1792401456699,
"sessions": 1,
"deltas": 1,
"model": "frank-zealot"
}
}
@@ -0,0 +1,4 @@
{
"v": 1,
"lastConsolidatedAt": 1792398333838
}
@@ -0,0 +1,10 @@
{
"v": 1,
"lastConsolidatedAt": 1792426569902,
"lastResult": {
"at": 1792402864677,
"sessions": 1,
"deltas": 8,
"model": "frank-zealot"
}
}
@@ -0,0 +1,10 @@
{
"v": 1,
"lastConsolidatedAt": 1792426408958,
"lastResult": {
"at": 1792401394555,
"sessions": 1,
"deltas": 1,
"model": "frank-zealot"
}
}
+81 -81
View File
@@ -24,27 +24,13 @@ providers:
# compactionModel candidate keeps the wire model id valid there.
compactionModel: llamacpp (dankclaw-3090)/frank-zealot
name: "frank-archon"
# Dankserver: BOTH Radeon AI PRO R9700s (gfx1201, TP=2 over the
# 2026-09-20 board swap's root ports, wht6 wire). Engine:
# radiance (StillDeadcode, Apache-2.0) from the digest-pinned
# stilldeadcode/radiance image (index digest sha256:4c3f4845..., 287
# MiB, kernels prebuilt for gfx1201), plain `podman run` through
# scripts/serve-frank-archon.sh, root unit (User=dank, dank's
# rootless podman storage). Serving the OFFICIAL
# Qwen/Qwen3.8-Flash-Next-FP8 at NATIVE modelopt block-FP8
# precision — a rad-convert no-recipe pure copy into
# qwen4exp-fp8-native.rad (172.76 GiB measured by plan-only), built by
# scripts/build-frank-archon-rad.sh against a staging dir whose
# config.json drops quantization_config so the shipped qwen4exp
# plugin's (qwen4exp, "") selection key matches; per-weight
# encodings are untouched. Experts stream from a 40 GiB/rank
# pinned host pool; the 47.7 GiB PLE ngram table is pinned in RAM
# (Frank's call); KV fp8; MTP depth 3 (the checkpoint's own mtp.*
# head); prefix cache 4 GiB host + 64 GiB disk. Chat template:
# froggeric's fixed qwen3.8 v22.5
# (scripts/qwen38-froggeric-v22.5.jinja) via
# --override-chat-template. Rollback: git tag
# frank-archon-freetoken-pr587-20261005 (FreeToken, one card).
# Dankserver: BOTH Radeon AI PRO R9700s (gfx1201, TP=2, wht6 wire) on
# the digest-pinned radiance image, plain `podman run` under a root
# unit. Payload, shape, eras, laws, rollback:
# serverAppConfigs-docs/LLM/frank-archon.md — and
# scripts/frank-archon.env is the authority for every number there.
# contextWindow MUST quote the engine's --max-model-len: radiance
# refuses a longer prompt and never truncates.
contextWindow: 200000
# maxTokens must survive the harness compaction gap AND the chars/4
# token-estimate under-run on code-heavy prompts. The clamp is
@@ -105,40 +91,22 @@ providers:
# compaction model candidate so the wire model id stays valid
# there even from a frank-dragoon session.
compactionModel: llamacpp (dankclaw-3090)/frank-zealot
# halogen-flash-server 0.16.2 (ghcr.io/peonist-ai/
# halogen-flash-server@sha256:0c61bf84, digest-pinned) serving the
# Quat3rnion NATIVE v2 ABLITERATED conversion of orcarouter's pinned
# BF16 Qwen3.8-Flash-Next (qwen38-flash-next-v2-abliterated.hgn,
# ~62 GiB resident, + REQUIRED n-gram table + vision tower, both
# hardlinked from the swift15 dir) on the Strix Halo iGPU: TWO slots
# over ONE 401,408-position KV pool (= 2 x ctx, raised 2026-10-18) at
# HALOGEN_CTX=200704 (the ceiling lowered from the card's 262,144 on
# 2026-10-17; ~10.8 GiB reserved where 200,704 cost 5.5, 262,144 cost
# 7.2 and 524,288 measured 14.6), with the MTP head ALWAYS ON
# (HALOGEN_SPEC_ADAPT=0 — the default adaptive policy halves
# decode). Measured 2026-10-17: 50 t/s greedy decode, 1,604 t/s
# cold prefill at 59k, NIAH 18/18. ABLITERATED base (no refusals:
# 0/5 on the hostile census) and VISION ON (OpenAI image_url
# parts; >=256 px images or it answers "video"). Runbook:
# serverAppConfigs-docs/LLM/frank-dragoon-flash-server-v2-native.md.
# Window the harness may fill — deliberately BELOW the engine
# ceiling (HALOGEN_CTX=200704, lowered from 262,144 on 2026-10-17):
# the clamp below leaves the 45k gap that absorbs the estimate error.
# Both slots SHARE one 401,408-position KV pool — exactly two full
# windows — so TWO maximum-length conversations can be resident at the
# same time (at the old pool == ctx 200,704 only two of <=100k could).
# The per-request ceiling is unchanged, so this window is unchanged.
# halogen flash-server on the Strix Halo iGPU. Payload, shape, eras,
# laws, rollback: serverAppConfigs-docs/LLM/frank-dragoon.md — and
# scripts/frank-dragoon.env is the authority for every number there.
# contextWindow sits deliberately BELOW the engine ceiling
# (HALOGEN_CTX): the clamp below leaves the gap that absorbs the
# harness's chars/4 under-count, so a window equal to the ceiling
# would make every long request a guaranteed 400.
contextWindow: 155648
# The clamp is max_tokens = min(maxTokens, contextWindow − est −
# 4096); the chars/4 est UNDER-counts the rendered prompt by ~3 %
# on code/agent traffic (measured 2026-10-07: est 152,938 ->
# server 157,388). Worst-case request = window − 4096 + 3 % est
# error ≈ 156.2k, inside the 200,704 engine ceiling with ~44k
# margin (robust to a ~25 % under-count). Compaction fires at 85 %
# of the window = 132,300 est ≈ 136k measured — the 180k target of
# the 262,144 era is unreachable now (the window itself is 155,648)
# — and rides on frank-zealot: input ≈ threshold − keepRecent(20k)
# ≈ 112k, inside its 200,704 slot.
# error ≈ 156.2k, inside the engine ceiling with ~44k of margin
# (robust to a ~25 % under-count). Compaction fires at 85 % of the
# window and rides on frank-zealot: input ≈ threshold −
# keepRecent(20k), comfortably inside its per-slot window.
# HALOGEN_MAX_TOKENS_CAP in frank-dragoon.env must stay >= this.
maxTokens: 45056
reasoning: true
@@ -183,39 +151,20 @@ providers:
# config.yml (192.168.0.143:7771 — this endpoint); the
# compactionModel candidate keeps the wire model id valid there.
compactionModel: llamacpp (dankclaw-3090)/frank-zealot
# Dankclaw's RTX 3090: llama.cpp PrismML fork build (vendor 10777,
# commit e3de71522 — the ONLY loader for this payload's custom tensor
# type 142 + prism.hadamard.* metadata, and the minimum build that
# pairs MTP with a quantized V cache) serving
# prism-ml/Ternary-Bonsai-2-9B-gguf at PQ2_0 (2,675,410,720 B) WITH the
# MTP head in the file — qwen35 hybrid, 32 layers (8 full-attention +
# 24 Gated DeltaNet), 4 KV heads x 256 dim, native 262,144 — in THREE
# conversations (--ctx-size 786432 / --parallel 3), each slot at the
# model's TRAINED window.
# KV is q8_0 K + q8_0 V (17 KiB/token over the 8 full layers =
# 13,056 MiB pool, ledger-exact); f16 KV would bill 26,112 MiB and
# cannot boot this card. Boot ledger 17,876 used / 6,249 free. Vision
# through the publisher's Q8_0 mmproj (624,229,664 B — Q8_0 is the
# publisher's requirement for concurrent image requests), whose
# worst-case lands outside the engine's fit projection. **MTP OFF —
# measured, not assumed**: the draft context bills its own f16 KV over
# the WHOLE pool (3,072 MiB) and at ubatch 2048 that squeeze halves
# decode (167.2 → 109.2 t/s); SPEC_TYPE=draft-mtp + UBATCH_SIZE=1024 is
# the 213.5 t/s arm if the card ever has room. 2026-10-18 swap from
# Ternary-Bonsai-2-27B PQ2_0 at 2 × 200,704. Measured: 167.2 t/s
# single-stream greedy decode, 280.2 t/s across three concurrent
# streams, 2,877 t/s prefill at 106,418. Base-alignment: censored base
# lineage; unlike the 27B there is NO CRACK re-export matching this
# file. Runbook:
# serverAppConfigs-docs/LLM/frank-zealot-llama-prism-bonsai9-mtp.md.
# contextWindow is the PER-SLOT window (= the native 262,144): a longer
# prompt needs compaction — llama.cpp answers a 400, never truncates.
contextWindow: 262144
# Dankclaw's RTX 3090 llama.cpp endpoint (PrismML fork build — the only
# loader for this payload's custom tensor type). Shape, payload, eras,
# laws, rollback: serverAppConfigs-docs/LLM/frank-zealot.md, and
# scripts/frank-zealot.env is the authority for every number there.
# contextWindow is the PER-SLOT window: llama.cpp divides --ctx-size
# across slots and answers a longer prompt with a 400, never a
# truncation, so this value must follow every reslice (live now:
# 3 x 200,704 over f16 K + q8_0 V with the MTP drafter armed, ba69ea5).
contextWindow: 200704
# Prompt + budget must fit inside the slot window; thinking counts
# against the budget. Compaction fires at 85 % of the window =
# 222,822 est; worst-case prompt + budget ≈ 222,822 × 1.03 +
# 16,384 ≈ 245,891 ≤ 262,144. This endpoint is the fleet's
# compaction hub: the widest window in the fleet.
# 170,598 est; worst-case prompt + budget ≈ 170,598 × 1.03 +
# 16,384 ≈ 192,100 ≤ 200,704. This endpoint stays the fleet's
# compaction hub: still the widest window in this file.
maxTokens: 16384
reasoning: true
input: [text, image]
@@ -254,3 +203,54 @@ providers:
# prior assistants' <think> blocks from history. Keep them —
# multi-turn tool traffic on this endpoint is the majority.
preserve_thinking: true
# Speech endpoint — the fleet's TTS, NOT a chat provider. `api:
# openai-speech` is a runner API (catalog kind `tts`), so this row never
# enters the chat picker, the Ctrl+P cycle, or any chat role: it is
# reachable only through the `speech` model role and the tts device.
# frank-tts (host port 7772) is the OpenAI /v1/audio/speech façade that
# resolves a voice BY NAME; its engine (frank-tts-engine, container-internal
# 8880, never published) is arm A qwentts.cpp 5916bf7 — measured 0.55-0.67
# RTF warm and 86-451 ms to the first audio byte on Dankclaw's CPU, with
# mainline llama-tts (TTS_BACKEND=llama-tts-cli) kept as the rollback.
# Transport contract, read out of the harness itself: the request body is
# {model, input, response_format, voice?, speed?}; `voice` is forwarded ONLY
# when explicitly set, and sampleRate/bitRate are REJECTED outright (the
# transport throws "openai-speech does not support sampleRate"), so the
# codec comes from the output_path suffix and the only tunable that matters
# is the voice name — and it comes from ONE place: the tool's `voice_id`
# argument. No setting feeds it (`speech.voice` is the speak-aloud Kokoro enum,
# `tts.localVoice` is the local backend's), so a call that omits voice_id arrives
# at 7772 with no `voice` key and the endpoint answers 400 "unknown voice None;
# available voices: narrator1, narrator2, narrator3". Say the voice in the call.
# WIRED 2026-10-18: `config.yml` `modelRoles.speech` is this row, flipped only
# after the service was deployed and answered real synthesis (two packs,
# different bytes, 24 kHz PCM16, RTF 0.57). Why the gate existed: `auth: none`
# makes this provider read as AVAILABLE even while the container is down, and an
# explicit speech role has NO fallback candidate, so a dead 7772 fails the device
# loudly instead of quietly narrating in Kokoro. Reverting is ONE key:
# `modelRoles.speech: local/kokoro`. `speech.voice` stays a Kokoro name either
# way — it was never this endpoint's voice.
# SCHEMA LAW, learned the hard way (2026-10-18): provider-level `api` must be
# a CHAT transport — the models.yml schema accepts only the chat/judge APIs
# there, and naming a runner API (`openai-speech`) at provider level fails the
# file's validation, which DISABLES EVERY custom provider: all three fleet
# endpoints vanish from the registry, not just this one (`omp models` prints
# "models.yml validation failed — custom providers disabled" and lists only
# local/kokoro). The runner api belongs on the MODEL entry only, which is what
# the block below does — `auth: none` covers the credential requirement, and
# `contextWindow`/`maxTokens` stay unset because the check only fires when they
# are provided (the bundled Kokoro row is null on both). `omp models --kind tts`
# still prints 128K/16K for this row — the registry fills display defaults — and
# the speech transport never reads them: its whole request body is the five
# fields named above. Verified 2026-10-18 with `omp models --kind tts` (row
# present) and `omp models` (frank-tts absent from the chat roster, all three
# fleet providers still listed).
"frank-tts (dankclaw)":
baseUrl: http://192.168.0.143:7772/v1
auth: none
models:
- id: frank-tts
name: "frank-tts (dankclaw) — cloned voices"
api: openai-speech
input: [text]
-89
View File
@@ -1,89 +0,0 @@
---
name: code-review
description: "Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to \"review since X\"."
---
Two-axis review of the diff between `HEAD` and a fixed point the user supplies:
- **Standards**: does the code conform to this repo's documented coding standards?
- **Spec**: does the code faithfully implement the originating issue / spec?
Both axes run as **parallel sub-agents** so they don't pollute each other's context, then this skill aggregates their findings.
The issue tracker should have been provided to you. If not, tell the user to run `/setup-matt-pocock-skills`.
## Process
### 1. Pin the fixed point
Whatever the user said is the fixed point (a commit SHA, branch name, tag, `main`, `HEAD~5`, etc.). If they didn't specify one, ask for it.
Capture the diff command once: `git diff <fixed-point>...HEAD` (three-dot, so the comparison is against the merge-base). Also note the list of commits via `git log <fixed-point>..HEAD --oneline`.
Before going further, confirm the fixed point resolves (`git rev-parse <fixed-point>`) and the diff is non-empty. A bad ref or empty diff should fail here, not inside two parallel sub-agents.
### 2. Identify the spec source
Look for the originating spec, in this order:
1. Issue references in the commit messages (`#123`, `Closes #45`, GitLab `!67`, etc.), fetched via the workflow in the tracker doc.
2. A path the user passed as an argument.
3. A spec file under `docs/`, `specs/`, or `.scratch/` matching the branch name or feature.
4. If nothing is found, ask the user where the spec is. If they say there isn't one, the **Spec** sub-agent will skip and report "no spec available".
### 3. Identify the standards sources
Search the repo for every file that documents how code should be written. When `CODING_STANDARDS.md` or `CONTRIBUTING.md` exists, it must be on the list.
On top of whatever the repo documents, the Standards axis always carries the **smell baseline** below: a fixed set of Fowler code smells (_Refactoring_, ch.3) that applies even when a repo documents nothing. Two rules bind it:
- **The repo overrides.** A documented repo standard always wins; where it endorses something the baseline would flag, suppress the smell.
- **Always a judgement call.** Each smell is a labelled heuristic ("possible Feature Envy"), never a hard violation. Like any standard here, skip anything tooling already enforces.
Each smell reads *what it is* → *how to fix*; match it against the diff:
- **Mysterious Name**: a function, variable, or type whose name doesn't reveal what it does or holds. → rename it; if no honest name comes, the design's murky.
- **Duplicated Code**: the same logic shape appears in more than one hunk or file in the change. → extract the shared shape, call it from both.
- **Feature Envy**: a method that reaches into another object's data more than its own. → move the method onto the data it envies.
- **Data Clumps**: the same few fields or params keep travelling together (a type wanting to be born). → bundle them into one type, pass that.
- **Primitive Obsession**: a primitive or string standing in for a domain concept that deserves its own type. → give the concept its own small type.
- **Repeated Switches**: the same `switch`/`if`-cascade on the same type recurs across the change. → replace with polymorphism, or one map both sites share.
- **Shotgun Surgery**: one logical change forces scattered edits across many files in the diff. → gather what changes together into one module.
- **Divergent Change**: one file or module is edited for several unrelated reasons. → split so each module changes for one reason.
- **Speculative Generality**: abstraction, parameters, or hooks added for needs the spec doesn't have. → delete it; inline back until a real need shows.
- **Message Chains**: long `a.b().c().d()` navigation the caller shouldn't depend on. → hide the walk behind one method on the first object.
- **Middle Man**: a class or function that mostly just delegates onward. → cut it, call the real target direct.
- **Refused Bequest**: a subclass or implementer that ignores or overrides most of what it inherits. → drop the inheritance, use composition.
### 4. Spawn both sub-agents in parallel
Issue both sub-agent calls together, in the foreground, and aggregate the reports they return.
**Standards sub-agent prompt** should include:
- The full diff command and commit list.
- The list of standards-source files you found in step 3, **plus the smell baseline from step 3** pasted in full (the sub-agent has no other access to it).
- The brief: "Report, per file/hunk where relevant, (a) every place the diff violates a documented standard: cite the standard (file + the rule); and (b) any baseline smell you spot: name it and quote the hunk. Distinguish hard violations from judgement calls: documented-standard breaches can be hard, but baseline smells are always judgement calls, and a documented repo standard overrides the baseline. Skip anything tooling enforces. Under 400 words."
**Spec sub-agent prompt** should include:
- The diff command and commit list.
- The path or fetched contents of the spec.
- The brief: "Report: (a) requirements the spec asked for that are missing or partial; (b) behaviour in the diff that wasn't asked for (scope creep); (c) requirements that look implemented but where the implementation looks wrong. Quote the spec line for each finding. Under 400 words."
If the spec is missing, skip the Spec sub-agent and note this in the final report.
### 5. Aggregate
Present the two reports under `## Standards` and `## Spec` headings, verbatim or lightly cleaned. Do **not** merge or rerank findings, because the two axes are deliberately separate (see _Why two axes_).
End with a one-line summary: total findings per axis, and the worst issue _within each axis_ (if any). Don't pick a single winner across axes: that's the reranking the separation exists to prevent.
## Why two axes
A change can pass one axis and fail the other:
- Code that follows every standard but implements the wrong thing → **Standards pass, Spec fail.**
- Code that does exactly what the issue asked but breaks the project's conventions → **Spec pass, Standards fail.**
Reporting them separately stops one axis from masking the other.
@@ -1,3 +0,0 @@
interface:
display_name: "Code Review"
short_description: "Review a diff on standards and spec"
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---
name: diagnosing-bugs
description: Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
---
# Diagnosing Bugs
A discipline for hard bugs. Skip phases only when explicitly justified.
When exploring the codebase, read `GLOSSARY.md` (if it exists) to get a clear mental model of the relevant modules, and check ADRs in the area you're touching.
## Redact
This skill has you show commands, outputs and captured artifacts. **Redact every secret first**: write `<REDACTED>` in its place. Build loops against env vars, so the credential stays in the environment rather than in what you show. Captured artifacts carry auth headers: quote only the lines that carry the signal.
If the redacted output is not enough to diagnose the bug, say so and ask the user.
## Phase 1: Build a feedback loop
**This is the skill.** Everything else is mechanical. If you have a **tight** pass/fail signal for the bug (one that goes red on _this_ bug), you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. If you don't have one, no amount of staring at code will save you.
Spend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**
### Ways to construct one, in roughly this order
1. **Failing test** at whatever seam reaches the bug: unit, integration, e2e.
2. **Curl / HTTP script** against a running dev server.
3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.
4. **Headless browser script** (Playwright / Puppeteer) that drives the UI and asserts on DOM/console/network.
5. **Replay a captured trace.** Save a real network request / payload / event log to disk; replay it through the code path in isolation.
6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.
7. **Property / fuzz loop.** If the bug is "sometimes wrong output", run 1000 random inputs and look for the failure mode.
8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate "boot at state X, check, repeat" so you can `git bisect run` it.
9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.
10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts/hitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.
Build the right feedback loop, and the bug is 90% fixed.
### Tighten the loop
Treat the loop as a product. Once you have _a_ loop, **tighten** it:
- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)
- Can I make the signal sharper? (Assert on the specific symptom, not "didn't crash".)
- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)
A 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight, a debugging superpower.
### Non-deterministic bugs
The goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not, so keep raising the rate until it's debuggable.
### When you genuinely cannot build a loop
Stop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a redacted captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.
### Completion criterion: a tight loop that goes red
Phase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** (a script path, a test invocation, a curl) that you have **already run at least once** (show the invocation and its output, redacted), and that is:
- [ ] **Red-capable**: it drives the actual bug code path and asserts the **user's exact symptom**, so it can go red on this bug and green once fixed. Not "runs without erroring"; it must be able to _catch this specific bug_.
- [ ] **Deterministic**: same verdict every run (flaky bugs: a pinned, high reproduction rate, per above).
- [ ] **Fast**: seconds, not minutes.
- [ ] **Agent-runnable**: you can run it unattended; a human in the loop only via `scripts/hitl-loop.template.sh`.
If you catch yourself reading code to build a theory before this command exists, **stop: jumping straight to a hypothesis is the exact failure this skill prevents.** No red-capable command, no Phase 2.
## Phase 2: Reproduce + minimise
Run the loop. Watch it go red as the bug appears.
Confirm:
- [ ] The loop produces the failure mode the **user** described, not a different failure that happens to be nearby. Wrong bug = wrong fix.
- [ ] The failure is reproducible across multiple runs (or, for non-deterministic bugs, reproducible at a high enough rate to debug against).
- [ ] You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.
### Minimise
Once it's red, shrink the repro to the **smallest scenario that still goes red**. Cut inputs, callers, config, data, and steps **one at a time**, re-running the loop after each cut, and keep only what's load-bearing for the failure.
Why bother: a minimal repro shrinks the hypothesis space in Phase 3 (fewer moving parts left to suspect) and becomes the clean regression test in Phase 5.
Done when **every remaining element is load-bearing**: removing any one of them makes the loop go green.
Do not proceed until you have reproduced **and** minimised.
## Phase 3: Hypothesise
Generate **3–5 ranked hypotheses** before testing any of them. Single-hypothesis generation anchors on the first plausible idea.
Each hypothesis must be **falsifiable**: state the prediction it makes.
> Format: "If <X> is the cause, then <changing Y> will make the bug disappear / <changing Z> will make it worse."
If you cannot state the prediction, the hypothesis is a vibe: discard or sharpen it.
**Show the ranked list to the user before testing.** They often have domain knowledge that re-ranks instantly ("we just deployed a change to #3"), or know hypotheses they've already ruled out. Cheap checkpoint, big time saver. Don't block on it; proceed with your ranking if the user is AFK.
## Phase 4: Instrument
Each probe must map to a specific prediction from Phase 3. **Change one variable at a time.**
Tool preference:
1. **Debugger / REPL inspection** if the env supports it. One breakpoint beats ten logs.
2. **Targeted logs** at the boundaries that distinguish hypotheses.
3. Never "log everything and grep".
**Tag every debug log** with a unique prefix, e.g. `[DEBUG-a4f2]`. Cleanup at the end becomes a single grep. Untagged logs survive; tagged logs die.
**Perf branch.** For performance regressions, logs are usually wrong. Instead: establish a baseline measurement (timing harness, `performance.now()`, profiler, query plan), then bisect. Measure first, fix second.
## Phase 5: Fix + regression test
Write the regression test **before the fix**, but only if there is a **correct seam** for it.
A correct seam is one where the test exercises the **real bug pattern** as it occurs at the call site. If the only available seam is too shallow (single-caller test when the bug needs multiple callers, unit test that can't replicate the chain that triggered the bug), a regression test there gives false confidence.
**If no correct seam exists, that itself is the finding.** Note it. The codebase architecture is preventing the bug from being locked down. Flag this for the next phase.
If a correct seam exists:
1. Turn the minimised repro into a failing test at that seam.
2. Watch it fail. If you forced the red by mutating code or a fixture, `diff` against a pristine copy to prove the mutation landed before you trust it.
3. Apply the fix.
4. Watch it pass.
5. Re-run the Phase 1 feedback loop against the original (un-minimised) scenario.
## Phase 6: Cleanup
Required before declaring done:
- [ ] Original repro no longer reproduces (re-run the Phase 1 loop)
- [ ] Regression test passes (or absence of seam is documented)
- [ ] All `[DEBUG-...]` instrumentation removed (`grep` the prefix)
- [ ] Throwaway prototypes deleted (or moved to a clearly-marked debug location)
- [ ] The hypothesis that turned out correct is stated in the commit / PR message, so the next debugger learns
@@ -1,3 +0,0 @@
interface:
display_name: "Diagnosing Bugs"
short_description: "Diagnose hard bugs and regressions"
@@ -1,44 +0,0 @@
#!/usr/bin/env bash
# Human-in-the-loop reproduction loop.
# Copy this file, edit the steps below, and run it.
# The agent runs the script; the user follows prompts in their terminal.
#
# Usage:
# bash hitl-loop.template.sh
#
# Two helpers:
# step "<instruction>" → show instruction, wait for Enter
# capture VAR "<question>" → show question, read response into VAR
#
# At the end, captured values are printed as KEY=VALUE for the agent to parse.
#
# `capture` prints its value back to the terminal, where the agent reads it,
# so capture observations, and leave signing in to the user as a `step`.
set -euo pipefail
step() {
printf '\n>>> %s\n' "$1"
read -r -p " [Enter when done] " _
}
capture() {
local var="$1" question="$2" answer
printf '\n>>> %s\n' "$question"
read -r -p " > " answer
printf -v "$var" '%s' "$answer"
}
# --- edit below ---------------------------------------------------------
step "Open the app at http://localhost:3000 and sign in."
capture ERRORED "Click the 'Export' button. Did it throw an error? (y/n)"
capture ERROR_MSG "Paste the error message (or 'none'):"
# --- edit above ---------------------------------------------------------
printf '\n--- Captured ---\n'
printf 'ERRORED=%s\n' "$ERRORED"
printf 'ERROR_MSG=%s\n' "$ERROR_MSG"
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---
name: find-skills
description: Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
---
# Find Skills
This skill helps you discover and install skills from the open agent skills ecosystem.
## When to Use This Skill
Use this skill when the user:
- Asks "how do I do X" where X might be a common task with an existing skill
- Says "find a skill for X" or "is there a skill for X"
- Asks "can you do X" where X is a specialized capability
- Expresses interest in extending agent capabilities
- Wants to search for tools, templates, or workflows
- Mentions they wish they had help with a specific domain (design, testing, deployment, etc.)
## What is the Skills CLI?
The Skills CLI (`npx skills`) is the package manager for the open agent skills ecosystem. Skills are modular packages that extend agent capabilities with specialized knowledge, workflows, and tools.
**Key commands:**
- `npx skills find [query] [--owner <owner>]` - Search for skills interactively or by keyword, optionally scoped to a GitHub owner
- `npx skills add <package>` - Install a skill from GitHub or other sources
- `npx skills update` - Update all installed skills
**Browse skills at:** https://skills.sh/
## How to Help Users Find Skills
### Step 1: Understand What They Need
When a user asks for help with something, identify:
1. The domain (e.g., React, testing, design, deployment)
2. The specific task (e.g., writing tests, creating animations, reviewing PRs)
3. Whether this is a common enough task that a skill likely exists
### Step 2: Check the Leaderboard First
Before running a CLI search, check the [skills.sh leaderboard](https://skills.sh/) to see if a well-known skill already exists for the domain. The leaderboard ranks skills by total installs, surfacing the most popular and battle-tested options.
For example, top skills for web development include:
- `vercel-labs/agent-skills` — React, Next.js, web design (100K+ installs each)
- `anthropics/skills` — Frontend design, document processing (100K+ installs)
### Step 3: Search for Skills
If the leaderboard doesn't cover the user's need, run the find command:
```bash
npx skills find [query] [--owner <owner>]
```
For example:
- User asks "how do I make my React app faster?" → `npx skills find react performance`
- User asks "can you help me with PR reviews?" → `npx skills find pr review`
- User asks "I need to create a changelog" → `npx skills find changelog`
### Step 4: Verify Quality Before Recommending
**Do not recommend a skill based solely on search results.** Always verify:
1. **Install count** — Prefer skills with 1K+ installs. Be cautious with anything under 100.
2. **Source reputation** — Official sources (`vercel-labs`, `anthropics`, `microsoft`) are more trustworthy than unknown authors.
3. **GitHub stars** — Check the source repository. A skill from a repo with <100 stars should be treated with skepticism.
### Step 5: Present Options to the User
When you find relevant skills, present them to the user with:
1. The skill name and what it does
2. The install count and source
3. The install command they can run
4. A link to learn more at skills.sh
Example response:
```
I found a skill that might help! The "react-best-practices" skill provides
React and Next.js performance optimization guidelines from Vercel Engineering.
(185K installs)
To install it:
npx skills add vercel-labs/agent-skills@react-best-practices
Learn more: https://skills.sh/vercel-labs/agent-skills/react-best-practices
```
### Step 6: Offer to Install
If the user wants to proceed, you can install the skill for them:
```bash
npx skills add <owner/repo@skill> -g -y
```
The `-g` flag installs globally (user-level) and `-y` skips confirmation prompts.
## Common Skill Categories
When searching, consider these common categories:
| Category | Example Queries |
| --------------- | ---------------------------------------- |
| Web Development | react, nextjs, typescript, css, tailwind |
| Testing | testing, jest, playwright, e2e |
| DevOps | deploy, docker, kubernetes, ci-cd |
| Documentation | docs, readme, changelog, api-docs |
| Code Quality | review, lint, refactor, best-practices |
| Design | ui, ux, design-system, accessibility |
| Productivity | workflow, automation, git |
## Tips for Effective Searches
1. **Use specific keywords**: "react testing" is better than just "testing"
2. **Try alternative terms**: If "deploy" doesn't work, try "deployment" or "ci-cd"
3. **Check popular sources**: Many skills come from `vercel-labs/agent-skills` or `ComposioHQ/awesome-claude-skills`
## When No Skills Are Found
If no relevant skills exist:
1. Acknowledge that no existing skill was found
2. Offer to help with the task directly using your general capabilities
3. Suggest the user could create their own skill with `npx skills init`
Example:
```
I searched for skills related to "xyz" but didn't find any matches.
I can still help you with this task directly! Would you like me to proceed?
If this is something you do often, you could create your own skill:
npx skills init my-xyz-skill
```
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description: Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
---
Interview the user relentlessly until you reach a shared understanding. Map this as a **design tree**: every decision branches into the decisions that hang off it.
# Grilling
Work the tree in **rounds**. The **frontier** is every decision whose prerequisites are already settled: the questions you can ask _now_ without guessing at answers you haven't heard yet. Ask the whole frontier in one round: number each question and give your recommended answer. Then wait for the user's answers before the next round.
Interview the user relentlessly until nothing is silently assumed and you reach a shared understanding. Map this as a **design tree**: every decision branches into the decisions that hang off it.
Format a round like so:
A decision is **frontier** when it can be asked now, without an answer you haven't heard yet. The interview is done when the frontier is empty: every branch of the tree visited.
```
❓ **Q1** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices>
## Rounds
➡️ <your recommended answer>
Work the tree in **rounds**: ask the whole frontier at once, then wait. A decision whose answer hangs on an open question or an unfetched fact joins a later round.
---
Ask each closed decision - anything expressible as 2–5 options - through the `ask` tool:
❓ **Q2** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices>
- **One artefact per question**, counted before sending. Name the artefact each question decides; two names means two questions. Shared plumbing (an endpoint, a service, a build step) still leaves two artefacts.
- Recommended answer first, marked `recommended: 0`, which labels it "(Recommended)" for one-glance acceptance. Every reply names what was picked, so the record is unambiguous.
- Options quote the user's goal. Their words, their stated goal, ground the wording; your todo text and table rows stay out of it.
- Your own idea is welcome: it gets its own recommended question. Attach it to its own question, so it rides there on its merits.
- `multi: true` for pick-many, `header` for the branch chip, `preview` when the decision needs code or config in front of the user.
➡️ <your recommended answer>
```
Open narrative - "walk me through the deploy flow" - has no options to offer; ask it as prose in chat. Without an `ask` tool the whole round degrades to text: `❓ **Q1 — title**: body`, then `➡️ recommendation`, phrased so one bare "yes" accepts every recommendation.
Word each question so "yes" accepts your recommended answer.
The dialog is exclusive: dispatch scouts before the `ask` call in the same message, or they wait behind it; their results land between rounds. Esc ends the run outright, with no turn to wrap up, so the ledger is what survives it.
Each round the user answers reshapes the tree: settled decisions push the frontier outward and unblock questions that depended on them. Recompute the frontier and ask the next round. A question whose answer depends on another question still open in this round belongs to a _later_ round, not this one.
## The ledger
Finding _facts_ is your job, never the user's. When a frontier question needs a fact from the environment (filesystem, tools, etc.), dispatch a sub-agent to find it; don't ask the user for anything you could look up yourself. Don't block on it: a running exploration is an unsettled prerequisite, so only the questions downstream of it wait for the sub-agent to report; ask the rest of the frontier now. The _decisions_ are the user's: put each to them and wait.
The tree lives in the `todo` list while the interview runs, so the user watches it fall:
The session is done when the frontier is empty: every branch of the design tree visited, nothing left silently assumed. Do not act on it until the user confirms you have reached a shared understanding.
- One task per decision, filed under the phase for its branch; `via: <parent decision>` in the task text carries the edge.
- `pending` is the frontier; `block` with a one-line reason waits on a fact or an open decision; `done` is settled. Unblock the moment the dependency settles.
Write `local://grilling-state.md` at the end of every round: the tree, each decision's verdict and one-line rationale. It is the durable copy of the interview; keep it current so an Esc costs one round.
## Facts are yours, decisions are theirs
- Environment facts (filesystem, repo, live config): dispatch a **scout** per fact-cluster, batched into one `task` call, before the round's `ask`. Cluster tightly; doing so keeps each scout more aware of possible adjacencies.
- Outside-world facts: call `web_search` directly, do not delegate to a subagent.
- Cheap lookups: `read`/`grep` inline.
- The main session is where questions happen: every spawn carries the exact facts to return, and comes back into the next round.
## Definition of Done
The frontier is empty and nothing sits blocked. Distil the ledger into a **brief**: one line per decision, verdict plus rationale, grouped by branch. Put it in chat, then one closing `ask`: "Proceed on this brief?" Nothing executes before that yes. After it, fold the brief into the project's knowledge base, or a log markdown file, wherever the project keeps its decisions.
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interface:
display_name: "Grilling"
short_description: "Stress-test thinking a round of questions at a time"
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---
name: handoff
description: Compact the current conversation into a handoff document for another agent to pick up.
argument-hint: "What will the next session be used for?"
disable-model-invocation: true
---
Write a handoff document summarising the current conversation so a fresh agent can continue the work. Save to the temporary directory of the user's OS (`$TMPDIR`, else `/tmp`; `%TEMP%` on Windows) - not the current workspace.
Include a "suggested skills" section in the document, naming which skills the next agent should call the Skill tool for.
Do not duplicate content already captured in other artifacts (specs, plans, ADRs, issues, commits, diffs). Reference them by path or URL instead.
Redact any sensitive information, such as API keys, passwords, or personally identifiable information.
If the user passed arguments, treat them as a description of what the next session will focus on and tailor the doc accordingly.
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interface:
display_name: "Handoff"
short_description: "Compact a conversation into a handoff"
policy:
allow_implicit_invocation: false
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---
name: implement
description: "Implement a piece of work based on a spec or set of tickets."
disable-model-invocation: true
---
Implement the work described by the user in the spec or tickets.
If the user passes a ticket reference, fetch it from the issue tracker and state its title before starting. If the reference is ambiguous, ask.
Call the Skill tool with "tdd" where possible, at pre-agreed seams.
Run typechecking regularly, single test files regularly, and the full test suite once at the end.
Once done, call the Skill tool with "code-review" to review the work.
Commit your work to the current branch.
@@ -1,5 +0,0 @@
interface:
display_name: "Implement"
short_description: "Build work from a spec or tickets"
policy:
allow_implicit_invocation: false
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# Logic Prototype
A single, self-contained HTML file (a **shareable demo**) that lets anyone drive a state model by clicking buttons. Use this when the question is about **business logic, state transitions, or data shape**: the kind of thing that looks reasonable on paper but only feels wrong once you push it through real cases.
Because it's one file with nothing to install, you can hand it to a non-developer (a designer, a PM, a domain expert) and let them feel the model for themselves. So it speaks their language, not the code's.
## When this is the right shape
- "I'm not sure if this state machine handles the edge case where X then Y."
- "Does this data model actually let me represent the case where..."
- "I want to feel out what the API should look like before writing it."
- Anything where someone wants to **press buttons and watch state change**.
If the question is "what should this look like," this is the wrong branch. Use [UI.md](UI.md).
## Process
### 1. State the question
Before writing code, write down what state model and what question you're prototyping. One paragraph, at the top of the demo (in a visible intro, not just a comment). A logic prototype that answers the wrong question is pure waste, so make the question explicit so it can be checked later, whether the user is watching now or returning to it AFK.
### 2. Isolate the logic in a portable module
Put the actual logic (the bit that's answering the question) in a single `<script>` block written as a small, pure module that could be lifted out and dropped into the real codebase later. The page around it is throwaway; this module isn't.
The right shape depends on the question:
- **A pure reducer**: `(state, action) => state`. Good when actions are discrete events and state is a single value.
- **A state machine**: explicit states and transitions. Good when "which actions are even legal right now" is part of the question.
- **A small set of pure functions** over a plain data type. Good when there's no implicit current state, just transformations.
- **A class or module with a clear method surface** when the logic genuinely owns ongoing internal state.
Pick whichever shape best fits the question being asked, *not* whichever is easiest to wire to a page. Keep it pure: no DOM, no `document`, no button handlers reaching inside it. The page calls into it; nothing flows the other direction. This is what makes the prototype useful past its own lifetime: once the question's answered, the validated reducer / machine / function set lifts into the real module on its own.
### 3. Build the shareable HTML file
One file, plain HTML/CSS/JS: no framework, no bundler, no server, everything inline so it opens by double-click and survives being emailed around. Anyone should be able to run it by opening it.
Write it for a non-developer. Every label is in **domain language**, not code: buttons and state read like the business, not the reducer. Explain in plain words what's happening.
Lay it out with a clean hierarchy, top to bottom:
1. **Title and one-line explanation** of what this demo lets you explore (the question from step 1).
2. **Current state**: the full relevant state, rendered as a readable panel (labelled fields, not a raw JSON dump), re-rendered after every click so the change is visible. Where it helps a non-developer follow, call out what just changed.
3. **Free-play buttons**: one button per action, always available, so anyone can poke at the model in any order. Each click dispatches its action and re-renders the state.
4. **Guided walkthroughs**: a set of **scenarios**, one per tab. Each tab holds a short plain-language description of the scenario (the situation it sets up and what to watch for) and underneath it, the ordered **buttons to press** for that scenario. Each step is a real button: clicking it performs that action and moves to the next step. Starting a walkthrough resets to a known initial state so the scenario runs the same way every time.
Choose scenarios that demonstrate the awkward cases, the ones hard to reason about on paper: the happy path, a tricky edge case, an attempt at something that should be illegal.
Keep it beautiful but restrained: clean typography, generous spacing, one accent colour. No animations, no gimmicks: nothing that competes with the state and the buttons.
### 4. Hand it over
Send them the file, or open it for them. They'll click through the walkthroughs and free-play whenever they get to it; the interesting moments are when they say "wait, that shouldn't be possible" or "huh, I assumed X would be different"; those are the bugs in the _idea_, which is the whole point. If they want new actions or a new scenario, add them. Prototypes evolve.
### 5. Capture the answer and the prototype
Once the prototype has answered its question, capture the answer, then capture the prototype the way the [SKILL](SKILL.md) describes. The logic-specific mapping: the validated reducer / machine / function set lifts into the real module (the decision, absorbed); the HTML shell rides along to the throwaway branch that keeps the prototype as a primary source, and being one self-contained file, it stays trivially re-runnable there.
## Anti-patterns
- **Don't add tests.** A prototype that needs tests is no longer a prototype.
- **Don't wire it to the real database.** Use in-memory state unless the question is specifically about persistence.
- **Don't generalise.** No "what if we wanted to support X later." The prototype answers one question.
- **Don't blur the logic and the page together.** If the pure module references the DOM, `document`, or button handlers, it's no longer liftable. Keep the page as a thin shell over a pure module.
- **Don't reach for a framework, bundler, or server.** One file the recipient double-clicks; a React app or a dev server defeats "shareable".
- **Don't ship the HTML shell into production.** The page is optimised for being clicked through by hand. The logic module behind it is the bit worth keeping.
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---
name: prototype
description: Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
---
# Prototype
A prototype is **throwaway code that answers a question**. The question decides the shape.
## Pick a branch
Identify which question is being answered, using the user's prompt, the surrounding code, or by asking if the user is around:
- **"Does this logic / state model feel right?"** → [LOGIC.md](LOGIC.md). Build a single shareable HTML file (free-play buttons plus tabbed guided walkthroughs) that pushes the state machine through cases that are hard to reason about on paper, and that a non-developer can drive.
- **"What should this look like?"** → [UI.md](UI.md). Generate several radically different UI variations on a single route, switchable via a URL search param and a floating bottom bar.
The two branches produce very different artifacts, so getting this wrong wastes the whole prototype. If the question is genuinely ambiguous and the user isn't reachable, default to whichever branch better matches the surrounding code (a backend module → logic; a page or component → UI) and state the assumption at the top of the prototype.
## Rules that apply to both
1. **Throwaway from day one, and clearly marked as such.** Locate the prototype code close to where it will actually be used (next to the module or page it's prototyping for) so context is obvious, but name it so a casual reader can see it's a prototype, not production. For throwaway UI routes, obey whatever routing convention the project already uses; don't invent a new top-level structure.
2. **Trivial to run.** A UI prototype starts from one command in the project's task runner: `pnpm <name>`, `python <path>`, `bun <path>`, etc. A logic demo is a single HTML file the user double-clicks. Either way, no thinking required to start it.
3. **No persistence by default.** State lives in memory. Persistence is the thing the prototype is _checking_, not something it should depend on. If the question explicitly involves a database, hit a scratch DB or a local file with a clear "PROTOTYPE, wipe me" name.
4. **Skip the polish.** No tests, no error handling beyond what makes the prototype _runnable_, no abstractions. The point is to learn something fast.
5. **Surface the state.** After every action (logic) or on every variant switch (UI), print or render the full relevant state so the user can see what changed.
6. **Capture it when done.** Fold any validated decision into the real code, then capture the prototype itself as a **primary source**: commit it to a throwaway branch, out of main, and leave a context pointer to that branch on the implementation issue. Capture the answer too (the verdict and the question it settled) in the issue or a commit. The main branch keeps only the validated decision.
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# UI Prototype
Generate **several radically different UI variations** on a single route, switchable from a floating bottom bar. The user flips between variants in the browser, picks one (or steals bits from each), then throws the rest away.
If the question is about logic/state rather than what something looks like, this is the wrong branch. Use [LOGIC.md](LOGIC.md).
## When this is the right shape
- "What should this page look like?"
- "I want to see a few options for this dashboard before committing."
- "Try a different layout for the settings screen."
- Any time the user would otherwise spend a day picking between three vague mockups in their head.
## Two sub-shapes: strongly prefer sub-shape A
A UI prototype is much easier to judge when it's **butting up against the rest of the app**: real header, real sidebar, real data, real density. A throwaway route on its own is a vacuum: every variant looks fine in isolation. Default to sub-shape A whenever there's a plausible existing page to host the variants. Only reach for sub-shape B if the prototype genuinely has no nearby home.
### Sub-shape A: adjustment to an existing page (preferred)
The route already exists. Variants are rendered **on the same route**, gated by a `?variant=` URL search param. The existing data fetching, params, and auth all stay. Only the rendering swaps. This is the default; pick it unless there's a specific reason not to.
If the prototype is for something that doesn't yet have a page but *would naturally live inside one* (a new section of the dashboard, a new card on the settings screen, a new step in an existing flow), it's still sub-shape A. Mount the variants inside the host page.
### Sub-shape B: a new page (last resort)
Only use this when the thing being prototyped genuinely has no existing page to live inside (e.g. an entirely new top-level surface, or a flow that can't be embedded anywhere sensible).
Create a **throwaway route** following whatever routing convention the project already uses. Don't invent a new top-level structure. Name it so it's obviously a prototype (e.g. include the word `prototype` in the path or filename). Same `?variant=` pattern.
Before committing to sub-shape B, sanity-check: is there really no existing page this could be embedded in? An empty route hides design problems that a populated one would expose.
In both sub-shapes the floating bottom bar is identical.
## Process
### 1. State the question and pick N
Default to **3 variants**. More than 5 stops being radically different and starts being noise, so cap there.
Write down the plan in one line, in the prototype's location or a top-of-file comment:
> "Three variants of the settings page, switchable via `?variant=`, on the existing `/settings` route."
This works whether the user is here to push back or not.
### 2. Generate radically different variants
Draft each variant. Hold each one to:
- The page's purpose and the data it has access to.
- The project's component library / styling system (TailwindCSS, shadcn, MUI, plain CSS, whatever).
- A clear exported component name, e.g. `VariantA`, `VariantB`, `VariantC`.
Variants must be **structurally different**: different layout, different information hierarchy, different primary affordance, not just different colours. Three slightly-tweaked card grids isn't a UI prototype, it's wallpaper. If two drafts come out too similar, redo one with explicit "do not use a card grid" guidance.
### 3. Wire them together
Create a single switcher component on the route:
```tsx
// pseudo-code, adapt to the project's framework
const variant = searchParams.get('variant') ?? 'A';
return (
<>
{variant === 'A' && <VariantA {...data} />}
{variant === 'B' && <VariantB {...data} />}
{variant === 'C' && <VariantC {...data} />}
<PrototypeSwitcher variants={['A','B','C']} current={variant} />
</>
);
```
For sub-shape A (existing page): keep all the existing data fetching above the switcher; only the rendered subtree changes per variant.
For sub-shape B (new page): the throwaway route under `/prototype/<name>` mounts the same switcher.
### 4. Build the floating switcher
A small fixed-position bar at the bottom-centre of the screen with three pieces:
- **Left arrow**: cycles to the previous variant (wraps around).
- **Variant label**: shows the current variant key and, if the variant exports a name, that name too. e.g. `B (Sidebar layout)`.
- **Right arrow**: cycles forward (wraps around).
Behaviour:
- Clicking an arrow updates the URL search param (use the framework's router, e.g. `router.replace` on Next, `navigate` on React Router, etc) so the variant is shareable and reload-stable.
- Keyboard: `←` and `→` arrow keys also cycle. Don't intercept arrow keys when an `<input>`, `<textarea>`, or `[contenteditable]` is focused.
- Visually distinct from the page (e.g. high-contrast pill, subtle shadow) so it's obviously not part of the design being evaluated.
- Hidden in production builds: gate on `process.env.NODE_ENV !== 'production'` or an equivalent check, so a stray prototype merge can't ship the bar to users.
Put the switcher in a single shared component so both sub-shapes can reuse it. Locate it wherever shared UI lives in the project.
### 5. Hand it over
Surface the URL (and the `?variant=` keys). The user will flip through whenever they get to it. The interesting feedback is usually **"I want the header from B with the sidebar from C"**, which is the actual design they want.
### 6. Capture the answer and clean up
Once a variant has won, capture the answer (which variant and why), then capture the prototype the way the [SKILL](SKILL.md) describes. Fold the winner into the real code and move the rest onto the throwaway branch, not into main:
- **Sub-shape A**: fold the winner into the existing page; drop the losing variants and the switcher from main.
- **Sub-shape B**: promote the winning variant to a real route; drop the throwaway route and the switcher from main.
The full set of variants is the primary source, so it lands on the throwaway branch, not the bin, since variant components and the switcher left in the main branch rot fast and confuse the next reader.
## Anti-patterns
- **Variants that differ only in colour or copy.** That's a tweak, not a prototype. Real variants disagree about structure.
- **Sharing too much code between variants.** A shared `<Header>` is fine; a shared `<Layout>` defeats the point. Each variant should be free to throw out the layout.
- **Wiring variants to real mutations.** Read-only prototypes are fine. If a variant needs to mutate, point it at a stub: the question is "what should this look like", not "does the backend work".
- **Promoting the prototype directly to production.** The variant code was written under prototype constraints (no tests, minimal error handling). Rewrite it properly when you fold it in.
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interface:
display_name: "Prototype"
short_description: "Prototype to answer a design question"
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---
name: tdd
description: Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
---
# Test-Driven Development
TDD is the red → green loop. This skill is the reference that makes that loop produce tests worth keeping: what a good test is, where tests go, the anti-patterns, and the rules of the loop. Every section applies on every cycle: consult them before and during the loop, not after.
When exploring the codebase, read `GLOSSARY.md` (if it exists) so test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
## What a good test is
Tests verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't. A good test reads like a specification: "user can checkout with valid cart" tells you exactly what capability exists, and it survives refactors because it doesn't care about internal structure.
See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
## Seams: where tests go
A **seam** is the public boundary you test at: the interface where you observe behavior without reaching inside. Tests live at seams, never against internals.
**Test only at pre-agreed seams.** Before writing any test, write down the seams under test and confirm them with the user. No test is written at an unconfirmed seam. You can't test everything, so agreeing the seams up front is how testing effort lands on the critical paths and complex logic instead of every edge case.
Ask: "What's the public interface, and which seams should we test?" Give each proposed seam a one-line note on what it catches and what it misses.
When the shape of that interface is itself in question (how deep the module is, where the seam belongs, what the interface should expose), call the Skill tool with "codebase-design" for the vocabulary. It is the shared source of the module, interface, depth, seam, adapter, leverage and locality terms, and it is a reference to consult, not a session to run.
## Anti-patterns
- **Implementation-coupled**: mocks internal collaborators, tests private methods, or verifies through a side channel (querying the database instead of using the interface). The tell: the test breaks when you refactor but behavior hasn't changed.
- **Tautological**: the assertion recomputes the expected value the way the code does (`expect(add(a, b)).toBe(a + b)`, a snapshot derived by hand the same way, a constant asserted equal to itself), so it passes by construction and can never disagree with the code. Expected values must come from an independent source of truth: a known-good literal, a worked example, the spec.
- **Horizontal slicing**: writing all tests first, then all implementation. Bulk tests verify _imagined_ behavior: you test the _shape_ of things rather than user-facing behavior, the tests go insensitive to real changes, and you commit to test structure before understanding the implementation. Work in **vertical slices** instead: one test → one implementation → repeat, each test a **tracer bullet** that responds to what the last cycle taught you.
## Rules of the loop
- **Red before green.** Write the failing test first, then only enough code to pass it. Don't anticipate future tests or add speculative features.
- **One slice at a time.** One seam, one test, one minimal implementation per cycle.
- **Refactoring is not part of the loop.** It belongs to the review stage (see the `code-review` skill), not the red → green implementation cycle.
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interface:
display_name: "TDD"
short_description: "Test-driven red-green-refactor"
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# When to Mock
Mock at **system boundaries** only:
- External APIs (payment, email, etc.)
- Databases (sometimes - prefer test DB)
- Time/randomness
- File system (sometimes)
Don't mock:
- Your own classes/modules
- Internal collaborators
- Anything you control
## Designing for Mockability
At system boundaries, design interfaces that are easy to mock:
**1. Use dependency injection**
Pass external dependencies in rather than creating them internally:
```typescript
// Easy to mock
function processPayment(order, paymentClient) {
return paymentClient.charge(order.total);
}
// Hard to mock
function processPayment(order) {
const client = new StripeClient(process.env.STRIPE_KEY);
return client.charge(order.total);
}
```
**2. Prefer SDK-style interfaces over generic fetchers**
Create specific functions for each external operation instead of one generic function with conditional logic:
```typescript
// GOOD: Each function is independently mockable
const api = {
getUser: (id) => fetch(`/users/${id}`),
getOrders: (userId) => fetch(`/users/${userId}/orders`),
createOrder: (data) => fetch('/orders', { method: 'POST', body: data }),
};
// BAD: Mocking requires conditional logic inside the mock
const api = {
fetch: (endpoint, options) => fetch(endpoint, options),
};
```
The SDK approach means:
- Each mock returns one specific shape
- No conditional logic in test setup
- Easier to see which endpoints a test exercises
- Type safety per endpoint
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# Good and Bad Tests
## Good Tests
**Integration-style**: Test through real interfaces, not mocks of internal parts.
```typescript
// GOOD: Tests observable behavior
test("user can checkout with valid cart", async () => {
const cart = createCart();
cart.add(product);
const result = await checkout(cart, paymentMethod);
expect(result.status).toBe("confirmed");
});
```
Characteristics:
- Tests behavior users/callers care about
- Uses public API only
- Survives internal refactors
- Describes WHAT, not HOW
- One logical assertion per test
## Bad Tests
**Implementation-detail tests**: Coupled to internal structure.
```typescript
// BAD: Tests implementation details
test("checkout calls paymentService.process", async () => {
const mockPayment = jest.mock(paymentService);
await checkout(cart, payment);
expect(mockPayment.process).toHaveBeenCalledWith(cart.total);
});
```
Red flags:
- Mocking internal collaborators
- Testing private methods
- Asserting on call counts/order
- Test breaks when refactoring without behavior change
- Test name describes HOW not WHAT
- Verifying through external means instead of interface
```typescript
// BAD: Bypasses interface to verify
test("createUser saves to database", async () => {
await createUser({ name: "Alice" });
const row = await db.query("SELECT * FROM users WHERE name = ?", ["Alice"]);
expect(row).toBeDefined();
});
// GOOD: Verifies through interface
test("createUser makes user retrievable", async () => {
const user = await createUser({ name: "Alice" });
const retrieved = await getUser(user.id);
expect(retrieved.name).toBe("Alice");
});
```
**Tautological tests**: Expected value restates the implementation, so the test passes by construction.
```typescript
// BAD: Expected value is recomputed the way the code computes it
test("calculateTotal sums line items", () => {
const items = [{ price: 10 }, { price: 5 }];
const expected = items.reduce((sum, i) => sum + i.price, 0);
expect(calculateTotal(items)).toBe(expected);
});
// GOOD: Expected value is an independent, known literal
test("calculateTotal sums line items", () => {
expect(calculateTotal([{ price: 10 }, { price: 5 }])).toBe(15);
});
```
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# GLOSSARY.md Format
`GLOSSARY.md` is the canonical language for this teaching workspace. All explainers, exercises, and learning records should adhere to its terminology. Building it is itself part of learning: compressing a concept into a tight definition is evidence the user understands it.
## Structure
```md
# {Topic} Glossary
{One or two sentence description of the topic this glossary covers.}
## Terms
**Hypertrophy**:
Muscle growth driven by mechanical tension and metabolic stress over repeated training sessions.
_Avoid_: Bulking, getting big
**Progressive overload**:
Systematically increasing the demand on a muscle over time, via load, volume, or intensity.
_Avoid_: Pushing harder, levelling up
**RPE (Rate of Perceived Exertion)**:
A 1–10 self-rating of how hard a set felt, where 10 is failure and 8 means two reps left in the tank.
_Avoid_: Effort score, intensity rating
```
## Rules
- **Add a term only when the user understands it.** The glossary is a record of compressed knowledge, not a dictionary the user reads to learn. If the user has just been introduced to a concept, wait until they can use it correctly before promoting it here.
- **Be opinionated.** When several words exist for the same concept, pick the best one and list the rest as aliases to avoid. This is how language compresses.
- **Keep definitions tight.** One or two sentences. Define what the term IS, not what it does or how to do it.
- **Use the glossary's own terms inside definitions.** Once a term is in the glossary, prefer it everywhere, including inside other definitions. This is what makes complex terms easier to grasp later.
- **Group under subheadings** when natural clusters emerge (e.g. `## Anatomy`, `## Programming`). A flat list is fine when terms cohere.
- **Flag ambiguities explicitly.** If a term is used loosely in the wider field, note the resolution: "In this workspace, 'set' always means a working set; warm-ups are tracked separately."
- **Revise as understanding deepens.** A definition the user wrote in week one may be wrong by week six. Update in place; do not leave stale entries.
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# Learning Record Format
Learning records live in `./learning-records/` and use sequential numbering: `0001-slug.md`, `0002-slug.md`, etc. Create the directory lazily: only when the first record is written.
They are the teaching equivalent of ADRs: they capture non-obvious lessons, key insights, and stated prior knowledge that will steer future sessions. They are used to calculate the zone of proximal development.
## Template
```md
# {Short title of what was learned or established}
{1-3 sentences: what was learned (or what prior knowledge was established), and why it matters for future sessions.}
```
That is the whole format. A learning record can be a single paragraph. The value is recording _that_ this is now known and _why_ it changes what to teach next, not in filling out sections.
## Optional sections
Only include these when they add genuine value. Most records won't need them.
- **Status** frontmatter (`active | superseded by LR-NNNN`): useful when an earlier understanding turns out to be wrong and is replaced.
- **Evidence**: how the user demonstrated the understanding (a question answered, an exercise completed, prior experience cited). Useful when the claim might be revisited.
- **Implications**: what this unlocks or rules out for future sessions. Worth recording when non-obvious.
## Numbering
Scan `./learning-records/` for the highest existing number and increment by one.
## When to write a learning record
Write one when any of these is true:
1. **The user demonstrated genuine understanding of something non-trivial**: not just exposure, but evidence they can use the concept correctly. This sets a new floor for what to teach next.
2. **The user disclosed prior knowledge**: "I already know X." Record it so future sessions don't re-teach it. Also record the _depth_ claimed.
3. **A misconception was corrected**: the user previously believed something wrong and now sees why. These are high-value: they predict future stumbling blocks for related topics.
4. **The mission shifted in response to learning**: the user discovered they cared about something different than they thought. Cross-link to [[MISSION.md]] and update it.
### What does _not_ qualify
- Material that was merely covered. Coverage is not learning. Wait for evidence.
- Anything already captured tersely in [[GLOSSARY.md]] as a term definition. Don't duplicate.
- Session-by-session activity logs. Learning records are not a journal: they are decision-grade insights.
## Supersession
When a later record contradicts an earlier one (the user's understanding deepened or corrected), mark the old record `Status: superseded by LR-NNNN` rather than deleting it. The history of how understanding evolved is itself useful signal.
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# MISSION.md Format
`MISSION.md` lives at the workspace root. It captures the _reason_ the user is learning this topic. Every teaching decision (what to teach next, which resources to surface, which exercises to design) should trace back to this document.
## Template
```md
# Mission: {Topic}
## Why
{1-3 sentences. The concrete real-world goal the user is chasing. What changes in their life or work when they have this skill? Avoid abstract framings like "to understand X"; push for the underlying outcome.}
## Success looks like
- {A specific, observable thing the user will be able to do}
- {Another specific thing}
- {…}
## Constraints
- {Time, budget, prior commitments, learning preferences, anything that bounds the approach}
## Out of scope
- {Adjacent topics the user explicitly does not want to chase right now, protecting the zone of proximal development}
```
## Rules
- **One mission per workspace.** If the user wants to learn two unrelated things, that is two workspaces.
- **Concrete over abstract.** "Run a half marathon by October" beats "get fitter." "Ship a Rust CLI to my team" beats "learn Rust."
- **Push back on vagueness.** If the user cannot articulate why, interview them before writing anything. A bad mission is worse than no mission.
- **Revise when reality shifts.** Missions change. When the user's goal moves, update this file: don't leave a stale mission steering future sessions.
- **Keep it short.** If `MISSION.md` runs past a screen, it has stopped being a compass and started being a plan.
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# RESOURCES.md Format
`RESOURCES.md` is the curated set of trusted sources for this topic. Knowledge for explainers should be drawn from here, not from parametric guesses. Wisdom comes from the communities listed here.
## Structure
```md
# {Topic} Resources
## Knowledge
- [Book: _The Science and Practice of Strength Training_ by Zatsiorsky & Kraemer](https://example.com)
Foundational text on programming and adaptation. Use for: anything to do with periodisation, recovery, intensity zones.
- [Article: "How Much Should I Train?" by Greg Nuckols (Stronger By Science)](https://example.com)
Evidence-based review of volume landmarks. Use for: weekly set targets per muscle group.
## Wisdom (Communities)
- [r/weightroom](https://reddit.com/r/weightroom)
High-signal subreddit, moderated against bro-science. Use for: programme critique, plateau troubleshooting.
- Local: Tuesday strength class at {gym name}
Use for: real-time coaching feedback on lifts.
```
## Rules
- **High-trust only.** Prefer primary sources, recognised experts, peer-reviewed work, and communities with strong moderation. If a resource is marketing dressed as education, leave it out.
- **Annotate every entry.** A bare link is useless in three months. Add one line: what it covers and when to reach for it.
- **Group by Knowledge / Wisdom.** Mirrors the philosophy in [SKILL.md](./SKILL.md). It is fine for a resource to appear in only one group.
- **Surface gaps explicitly.** If no good resource exists for an area the mission needs, write a `## Gaps` section listing what is missing. This drives future search.
- **Prune ruthlessly.** A resource that turned out to be wrong, shallow, or off-mission should be removed, not buried. Better five sharp sources than thirty mediocre ones.
- **Record community preferences.** If the user has opted out of joining communities, note it here so future sessions don't keep proposing them.
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---
name: teach
description: Teach the user a new skill or concept, within this workspace.
disable-model-invocation: true
argument-hint: "What would you like to learn about?"
---
The user has asked you to teach them something. This is a stateful request - they intend to learn the topic over multiple sessions.
## Teaching Workspace
Treat the current directory as a teaching workspace. Workspace paths (`./lessons/` and the rest) resolve from the directory `/teach` was run in; only the `*-FORMAT.md` links resolve from this skill's folder. The state of their learning is captured in this directory in several files:
- `MISSION.md`: A document capturing the _reason_ the user is interested in the topic. This should be used to ground all teaching. Use the format in [MISSION-FORMAT.md](./MISSION-FORMAT.md).
- `./reference/*.html`: A directory of reference materials. These are the compressed learnings from the lessons - cheat sheets, reference algorithms, syntax, yoga poses, glossaries. They are the raw units of learning. They should be beautiful documents which print out well, and are designed for quick reference.
- `RESOURCES.md`: A list of resources which can be explored to ground your teaching in contextual knowledge, or to acquire knowledge and wisdom. Use the format in [RESOURCES-FORMAT.md](./RESOURCES-FORMAT.md).
- `./learning-records/*.md`: A directory of learning records, which capture what the user has learned. These are loosely equivalent to architectural decision records in software development - they capture non-obvious lessons and key insights that may need to be revised later, or drive future sessions. These should be used to calculate the zone of proximal development. They are titled `0001-<dash-case-name>.md`, where the number increments each time. Use the format in [LEARNING-RECORD-FORMAT.md](./LEARNING-RECORD-FORMAT.md).
- `./lessons/*.html`: A directory of lessons. A **lesson** is a single, self-contained HTML output that teaches one tightly-scoped thing tied to the mission. This is the primary unit of teaching in this workspace.
- `./assets/*`: Reusable **components** shared across lessons. See [Assets](#assets).
- `NOTES.md`: A scratchpad for you to jot down user preferences, or working notes.
## Philosophy
To learn at a deep level, the user needs three things:
- **Knowledge**, captured from high-quality, high-trust resources
- **Skills**, acquired through highly-relevant interactive lessons devised by you, based on the knowledge
- **Wisdom**, which comes from interacting with other learners and practitioners
Before the `RESOURCES.md` is well-populated, your focus should be to find high-quality resources which will help the user acquire knowledge. Never trust your parametric knowledge.
Some topics may require more skills than knowledge. Learning more about theoretical physics might be more knowledge-based. For yoga, more skills-based.
### Fluency vs Storage Strength
You should be careful to split between two types of learning:
- **Fluency strength**: in-the-moment retrieval of knowledge
- **Storage strength**: long-term retention of knowledge
Fluency can give the user an illusory sense of mastery, but storage strength is the real goal. Try to design lessons which build long-term retention by desirable difficulty:
- Using retrieval practice (recall from memory)
- Spacing (distributing practice over time)
- Interleaving (mixing up different but related topics in practice - for skills practice only)
## Lessons
A lesson is the main thing you produce: the unit in which knowledge and skills reach the user. Each lesson is one self-contained HTML file, saved to `./lessons/` and titled `0001-<dash-case-name>.html` where the number increments each time.
A lesson should be **beautiful**, with clean, readable typography and layout, since the user will return to these later to review. Think Tufte.
The lesson should be short, and completable very quickly. Learners' working memory is very small, and we need to stay within it. But each lesson should give the user a single tangible win that they can build on. It should be directly tied to the mission, and should be in the user's zone of proximal development.
If possible, open the lesson file for the user by running a CLI command.
Each lesson should link via HTML anchors to other lessons and reference documents.
Each lesson should recommend a primary source for the user to read or watch. This should be the most high-quality, high-trust resource you found on the topic.
Each lesson should contain a reminder to ask followup questions to the agent. The agent is their teacher, and can assist with anything that's unclear.
## Assets
Lessons are built from reusable **components**, stored in `./assets/`: stylesheets, quiz widgets, simulators, diagram helpers, and anything else a second lesson could reuse.
Reuse is the default, not the exception. Before authoring a lesson, read `./assets/` and build from the components already there. When a lesson needs something new and reusable, write it as a component in `./assets/` and link to it; never inline code a future lesson would duplicate.
A shared stylesheet is the first component every workspace earns: every lesson links it, so the lessons look like one consistent course rather than a pile of one-offs. As the workspace grows, so should the component library.
## The Mission
Every lesson should be tied into the mission - the reason that the user is interested in learning about the topic.
If the user is unclear about the mission, or the `MISSION.md` is not populated, your first job should be to question the user on why they want to learn this.
Failing to understand the mission will mean knowledge acquisition is not grounded in real-world goals. Lessons will feel too abstract. You will have no way of judging what the user should do next.
Missions may change as the user develops more skills and knowledge. This is normal - make sure to update the `MISSION.md` and add a learning record to capture the change. Confirm with the user before changing the mission.
## Zone Of Proximal Development
Each lesson, the user should always feel as if they are being challenged 'just enough'.
The user may specify an exact thing they want to learn. If they don't, figure out their zone of proximal development by:
- Reading their `learning-records`
- Figuring out the right thing to teach them based on their mission
- Teach the most relevant thing that fits in their zone of proximal development
## Knowledge
Lessons should be designed around a skill the user is going to learn. The knowledge in the lesson should be only what's required to acquire that skill. You teach the knowledge first, then get the user to practice the skills via an interactive feedback loop.
Knowledge should first be gathered from trusted resources. Use `RESOURCES.md` to keep track of them. Lessons should be littered with citations - links to external resources to back up any claim made. This increases the trustworthiness of the lesson.
For acquiring knowledge, difficulty is the enemy. It eats working memory you need for understanding.
## Skills
If knowledge is all about acquisition, skills are about durability and flexibility. Make the knowledge stick.
For skill acquisition, difficulty is the tool. Effortful retrieval is what builds storage strength. Skills should be taught through interactive lessons. There are several tools at your disposal:
- Interactive lessons, using quizzes and light in-browser tasks
- Lessons which guide the user through a list of real-world steps to take (for instance, yoga poses)
Each of these should be based on a **feedback loop**, where the user receives feedback on their performance. This feedback loop should be as tight as possible, giving feedback immediately - and ideally automatically.
For quizzes, each answer should be exactly the same number of words (and characters, if possible). Vary which position holds the correct answer across questions. Don't give the user any clues about the answer through formatting or order.
## Acquiring Wisdom
Wisdom comes from true real-world interaction - testing your skills outside the learning environment.
When the user asks a question that appears to require wisdom, your default posture should be to attempt to answer - but to ultimately delegate to a **community**.
A community is a place (online or offline) where the user can test their skills in the real world. This might be a forum, a subreddit, a real-world class (budget permitting) or a local interest group.
You should attempt to find high-reputation communities the user can join. If the user expresses a preference that they don't want to join a community, respect it.
## Reference Documents
While creating lessons, you should also create reference documents. Lessons can reference these documents - they are useful for tracking raw units of knowledge useful across lessons.
Lessons will rarely be revisited later - reference documents will be. They should be the compressed essence of the lesson, in a format designed for quick reference.
Some learning topics lend themselves to reference:
- Syntax and code snippets for programming
- Algorithms and flowcharts for processes
- Yoga poses and sequences for yoga
- Exercises and routines for fitness
- Glossaries for any topic with its own nomenclature
Glossaries, in particular, are an essential reference. Once one is created, it should be adhered to in every lesson.
## `NOTES.md`
The user will sometimes express preferences of how they want to be taught, or things you should keep in mind. This is the place to record those preferences, so you can refer back to them when designing lessons or working with the user.
-5
View File
@@ -1,5 +0,0 @@
interface:
display_name: "Teach"
short_description: "Learn a concept in a guided workspace"
policy:
allow_implicit_invocation: false
+2 -2
View File
@@ -19,9 +19,9 @@
}
shadow
focus-ring {
width 2
width 4
active-color "#e01b24"
active-color "#ff8c00"
}
border {
off
@@ -275,13 +275,13 @@ transition = [ "fade" ]
interval_seconds = 1200
[wallpaper.default]
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_oxex69.jpg"
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_ymp267.jpg"
[wallpaper.last]
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_oxex69.jpg"
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_ymp267.jpg"
[wallpaper.monitors.DP-1]
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_oxex69.jpg"
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_y8ewzk.jpg"
[wallpaper.monitors.DP-2]
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_oxex69.jpg"
@@ -290,7 +290,7 @@ transition = [ "fade" ]
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_v9e2w3.jpg"
[wallpaper.monitors.eDP-1]
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_oxex69.jpg"
path = "/home/blank/.local/share/noctalia/wallpapers/wallhaven_ymp267.jpg"
[weather]
unit = "imperial"
@@ -0,0 +1,32 @@
layout {
focus-ring {
active-color "#ff8c00"
inactive-color "#181818"
urgent-color "#ff8c00"
}
border {
active-color "#f43841"
inactive-color "#181818"
urgent-color "#f43841"
}
tab-indicator {
active-color "#f43841"
inactive-color "#74050b"
urgent-color "#f43841"
}
insert-hint {
color "#f4384180"
}
}
recent-windows {
highlight {
active-color "#f43841"
urgent-color "#f43841"
}
}
+6 -1
View File
@@ -2,7 +2,12 @@
Agentic web research means that an AI drives the search loop. The agent formulates queries, reads results, decides what to read next, and writes a synthesis. It works best when search, extraction, and reasoning each run in the right place.
> **Your setup:** Pi Web Access calls SearXNG at `192.168.0.143:8081` (dankclaw) and serves models through llama.cpp at `192.168.0.235:7770`, `192.168.0.143:7770`, and `localhost:8080`. The pages below assume that topology.
> **Fleet topology (2026-10):** SearXNG lives at `192.168.0.143:8081` (UI) /
> `:8082` (JSON) on dankclaw; model endpoints are `frank-archon`
> (dankserver :7770, radiance), `frank-dragoon` (dankclaw :7770,
> halogen-flash-server), `frank-zealot` (dankclaw :7771, llama.cpp PrismML).
> The pi-era `localhost:8080` llama.cpp endpoint is retired. See
> [System hosts](/system/index.md).
This section connects four decisions:
+12 -5
View File
@@ -32,9 +32,15 @@ Qwen3 is the current state of the art for open function calling and tool use. It
The 8B and 14B models run on one consumer GPU. The 30B-A3B MoE runs on a single A100-class card or equivalent.
## Best Vision Model: Qwen2.5-VL-7B
## Best Vision Model: Qwen3-VL (Apache 2.0)
Many web tasks need a model that can read a page image, not just text. Qwen2.5-VL-7B is the best open vision model for this. It reads text, charts, icons, and layout in screenshots. It supports computer-use and phone-use agents. Apache 2.0 license. The 7B model fits on a single GPU with 8 GB or more.
Many web tasks need a model that can read a page image, not just text.
**Qwen3-VL** supersedes Qwen2.5-VL as the strongest open-weights vision family
(4B/8B dense through 30B-A3B/235B-A22B MoE): text, chart, icon, and layout
reading in screenshots, plus computer-use agent support. Small dense sizes
ship Apache 2.0; a quantized 4B/8B runs on a single consumer GPU. On this
fleet, vision duty is carried by the mmproj vision towers on the endpoints
(dragoon, zealot) — see [System hosts](/system/index.md).
Llama 4 Scout is the larger multimodal option. Verify the claims before you trust them:
@@ -47,7 +53,7 @@ Llama 4 Scout is the larger multimodal option. Verify the claims before you trus
```mermaid
graph TD
A[Consumer GPU 16-24GB] --> B[Qwen3-8B / 14B]
A --> C[Qwen2.5-VL-7B]
A --> C[Qwen3-VL-4B / 8B]
D[Single server GPU 80GB] --> E[Qwen3-30B-A3B]
D --> F[Llama 4 Scout INT4]
G[Multi-GPU cluster] --> H[Qwen3-235B-A22B]
@@ -71,7 +77,7 @@ llama-server -m qwen3-8b-q4_k_m.gguf -c 131072 --port 7770
| Need | Pick |
|------|------|
| Best tool calling, one consumer GPU | Qwen3-8B or 14B |
| Visually read a web page | Qwen2.5-VL-7B |
| Visually read a web page | Qwen3-VL-4B / 8B |
| Server-scale reliable agent | Qwen3-235B-A22B |
| Cheapest acceptable agent | Qwen3-8B on a mid GPU |
@@ -79,7 +85,8 @@ llama-server -m qwen3-8b-q4_k_m.gguf -c 131072 --port 7770
- Qwen3 technical report: <https://qwenlm.github.io/blog/qwen3/>
- Qwen3 repository: <https://github.com/QwenLM/Qwen3>
- Qwen2.5-VL-7B model card: <https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct>
- Qwen3-VL repository: <https://github.com/QwenLM/Qwen3-VL> (tech report: <https://arxiv.org/abs/2511.21631>)
- Qwen2.5-VL-7B model card (predecessor): <https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct>
- Meta AI Llama 4 announcement: <https://ai.meta.com/blog/llama-4-multimodal-intelligence/>
- Ollama library: <https://ollama.com/library>
- Browser Use supported models: <https://docs.browser-use.com/open-source/supported-models>
@@ -8,18 +8,41 @@ tags:
- privacy
- configuration
- unverified
verified: 2026-08-28
verified: 2026-10-19
timestamp: 2026-08-11
resource: https://docs.searxng.org
---
# SearXNG Tuning
SearXNG is a metasearch engine. It aggregates 274 or more upstream search services into one result set. Configuration lives in `settings.yml`. The recommended deployment is Docker Compose with a Valkey container.
SearXNG is a metasearch engine. It aggregates hundreds of upstream search
services into one result set (upstream `settings.yml` defines 388 engine
entries at master, probed 2026-10-19; the live fleet instance loads 262).
Configuration lives in `settings.yml`. The recommended deployment is Docker
Compose (or Podman Quadlet) with a Valkey container.
This page lists the settings that matter for speed, privacy, and useful results.
> **Your setup:** Pi Web Access calls a remote SearXNG at [`192.168.0.143:8081`](../pi/packages/pi-web-access.md) (dankclaw). Apply these settings to that host, not to this machine.
> **Fleet instance:** the harness `web/searxng` provider calls the instance at
> `192.168.0.143:8081` (UI) / `:8082` (JSON API) on dankclaw. The pi-era
> [Pi Web Access](../pi/packages/pi-web-access.md) called the same host.
## Live instance (probed 2026-10-19)
User Quadlet stack on dankclaw: `searxng.container`
(`ghcr.io/searxng/searxng:latest`) + `searxng-valkey.container`
(`docker.io/valkey/valkey:9-alpine`) + `gluetun.container` (VPN egress; the
containers share its network namespace, which is why `podman ps` shows :8081/
:8082 on several names) + `marreta`/`marreta_browser`. `limiter.toml`: enabled,
`pass_searxng_org: true`.
**Policy drift flag:** this page's tuned engine policy (google and bing
disabled; DuckDuckGo/Wikipedia/Google News enabled — verified via `/config` on
2026-08-16) is NOT live: `/config` on 2026-10-19 reports all 262 engines
enabled, google and bing included. Either the settings override was lost in
the 2026-10 stack reinstatement or the policy was deliberately dropped.
Confirm with Frank before re-applying.
## Plan the Deployment
@@ -29,10 +29,17 @@ Key ideas:
- Ten watchdogs handle CAPTCHAs, crashes, popups, downloads, and security.
- Real browser profiles carry saved logins.
**On the "87.4 percent" number:** that result refers to Browser Use's managed Cloud agent (the Hybrid type that blends structured browser tools with screenshots). Peer-reviewed results for vision-only (CUA) models are much lower, about 44.5 percent on the same task type. Treat any single accuracy number as one benchmark, not a universal score.
**On the "87.4 percent" number:** that result refers to Browser Use's managed
Cloud agent (the Hybrid type that blends structured browser tools with
screenshots), not the open-source library you self-host. Academic
computer-use results on comparable web tasks run far lower, and an earlier
"44.5 percent peer-reviewed CUA" figure carried in this page could not be
re-attributed to a specific published benchmark (checked 2026-10-19) and was
dropped. Treat any single accuracy number as one benchmark, not a universal
score.
```python
# Local model via llama.cpp (OpenAI-compatible endpoint)
# Local model via any OpenAI-compatible endpoint
from browser_use import Agent
from browser_use.llm.openai import ChatOpenAI
@@ -40,7 +47,7 @@ agent = Agent(
task="Search for the latest AI news",
llm=ChatOpenAI(
base_url="http://192.168.0.235:7770/v1",
model="frank-default-small",
model="frank-archon",
api_key="EMPTY",
),
)
+8 -2
View File
@@ -171,8 +171,14 @@ This pattern places the whole SearXNG process inside the tunnel namespace. The h
4. Confirm that unrelated host traffic keeps the host IP.
```bash
# From inside the tunnel with Gluetun
docker exec gluetun curl -s ifconfig.me
# Gluetun ships no curl; use its own endpoints or a throwaway container.
podman exec gluetun sh -c 'test -e /sys/class/net/tun0 && echo tunnel-up'
podman exec gluetun sh -c 'wget -qO- 127.0.0.1:9999/health' # "OK" when up
# NOTE: :9999 is Gluetun's HTTP health server (200 "OK" / 500); :8000 is the
# CONTROL server (/v1/* API), which 404s on everything else. Do not health-
# probe :8000. Egress-IP check needs a real binary — run a companion
# container on gluetun's network: docker run --rm --net container:gluetun
# curlimages/curl -s ifconfig.me
```
## Citations

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