command-center/agent/managed-skills/bench-arm-provenance-recovery/SKILL.md

name, description

name	description
bench-arm-provenance-recovery	Before calling a leftover LLM bench drop-in a rogue/hijack, reconstruct whether Frank ordered and measured that arm: omp archive prompt timestamps + journald print_timing for the exact pid, then land the verdict in the repo.

Use when a live service boots a payload you did not configure (stale systemd drop-in / *_ENV_FILE arm env) and the docs — or your own compaction-inherited context — call it "unfinished", "armed but never measured", or "hijack". Do NOT report that until proven: the arm may be an ordered, measured, approved configuration whose record lived only in /tmp + journald.

Why this exists

2026-10-18 frank-zealot: a frank-zealot.service.d/ptq1.conf drop-in made the cutover deploy boot a different model at a different shape. I reported it as an unfinished experiment. It was actually the 27B PTQ1_0 arm Frank ordered at 02:36, that served production 03:14:39→03:38:57, and whose numbers existed only in tool output that context compaction later dropped.

Step 1 — recover the ORDER (the harness archive, not memory)

eval with the archive prelude:

ps = await archive.prompts()          # searchable prompt history, survives compaction
# filter for the payload name / repo URL keywords, print p['at'] + p['text'][:90]
r = await archive.session("<sessionId>")   # full session record
recaps = await archive.recaps()             # recap stamps — check they postdate the window

archive.prompts() keeps user prompts with ISO timestamps even when the middle of the transcript was dropped. Timestamp every instruction: ordered → measured → superseded. Convert to local (UTC−7 here) before quoting. A recap older than the instruction proves the recap layer never covered the window.

Step 2 — recover the MEASUREMENT (journal, per pid)

The engine's own per-request timings are the record; they outlive /tmp env files.

ssh dank@<host> 'journalctl -u <svc> --no-pager' | grep -F 'serve-<svc>.sh[<PID>]' \
  | grep -E 'prompt eval time|eval time' | awk '... median per task ...'

• Pin the pid (sh[NNNN]): --since windows alone pull the previous process's numbers too.
• llama.cpp format: prompt eval time = 1234.56 ms / 100 tokens (…, 81.03 tokens per second); decode rows are eval time = … ms / N tokens (…). Multiple spaces between task/eval break naive regexes — match task\s+(\d+)\s+prompt eval time exactly, or parse both labels separately.
• Filter pathological rows: generations running concurrently on other slots, or ending in a 4-byte EOS, read ~4× low. Report clean single-stream probes (≥200 generated tokens) and label the rest.
• Cross-check the boot banner for the payload identity (type ptq1_0: 402 tensors, KV ledger, slot/ctx lines) — that proves which shape that pid served.

Step 3 — adjudicate, then land it in the repo

Write the verdict in the same session you derive it: runbook deploy-ledger section, log.md dated section, the arm script's header comment, and the AGENTS.md law. /tmp and journald are not records — that absence is what makes the next agent misread an approved arm as a rogue one.

Traps

• mask fails on a relinked unit; never systemctl disable; retire drop-ins to ~/.AGENTTRASH/<date>-<topic>/ + daemon-reload (recoverable, not deleted).
• /health 200, /v1/models echoing the alias, and a green e2e gate all fail to read the payload — check systemctl show <svc> -p DropInPaths (must be empty), then tr '\0' ' ' </proc/$(pidof llama-server)/cmdline, then the boot ledger.
• Verification sequence that is honest: correction commit must quote commands you ran; state [INFERENCE] for anything the journal does not show.