docs: distill the managed skill library into the vault (waves 1-7)

All ~173 managed skills read in full and merged, one polished reference
page per skill-cluster:

- LLM cross-cutting (17 pages): GGUF Compatibility, Llama Cpp Serving
  Sizing, Llama Cpp Multi-Device Splits, PCIe Link and Atomics, RDNA4
  Container Serving, RDNA4 MoE Expert Offload VRAM Budget, vLLM Boot
  Forensics, vLLM Porting and Compile Triage, LLM Bench Windows, LLM
  Performance Diagnosis, Model Swap and Rollback, Tcclaviger Fork Ops,
  Heterogeneous Split Triage, FreeToken Builds + deltas folded into the
  retired runbooks (GLM DFlash2 port laws, Lucebox dual-R9700, R9V
  qualification pipeline, FLM pack registration, ik hybrid envelope,
  frank-medium split rebalance, llama.cpp GGUF preflight, batch-ubatch
  split section, bench-window D-state/stale-read notes, second-endpoint
  bring-up).
- Architecture (3): Stale Signal Audit, Quadlet Lifecycle, Deploy State
  Triage.
- Operations (6 + index): Remote Job Runner, Payload and Disk Reclaim,
  Container Host Reachability, Fleet Ops Playbook, Fleet Audit and
  Posture, SSH and Remote Access.
- Infrastructure: Observability Provisioning + Homepage Status Probes;
  updates to Authentik, Anubis, LAN-DNS (per-client DoH bypass, Porkbun
  zone ops), Swap Configuration, OpenWebUI, Hermes (pre-existing page
  preserved and extended).
- FrankBook-Pro: ARR-Stack filled (API split, schema-first probing,
  auth-posture, auth-config trap); qBittorrent E2E verification.
- Desktop/Agent/Research: Noctalia and Niri, OMP Harness, Agent Docs and
  Edits, Command Center Dotfiles, PICO-8 Asset Standards.
- Indexes: LLM Cross-Cutting References section, Operations/ and Agent/
  index pages, root-index Skill Distillation section, AGENTS.md pointer.
- log.md carries the wave plan.

check-vault-links.py 0 unresolved (185 pages); ./tests/run.sh 366/366.

serverAppConfigs-docs/LLM/frank-large-ik-uncensored.md

@@ -123,3 +123,27 @@ Stop and disable the root unit, trash it, restore the halogen quadlet from
 `~/.AGENTTRASH/20260915-ik-swap/halogen-quadlet` to
 `~/.config/containers/systemd/`, `systemctl --user daemon-reload`, start;
 the .hgn checkpoint and the kingjones STRIX llama.cpp payload remain on disk.
+
+## Hybrid campaign envelope (2026-09-16, 3090 + Strix Halo)
+
+Why this deployment could not be tuned into a production endpoint: decode
+3.8–4.3 tok/s flat across thread counts (T1 ≈ T16); prefill ~192 tok/s at
+1.8k–32k prompts = the **CPU AVX512-VNNI compute ceiling** for CPU experts.
+The decode root cause is structural: ~100 CPU↔GPU backend splits per token
+with the GPU at 5 % SM during decode — launch/sync-bound over the PCIe x4
+dock, not compute- or memory-bound. T16 profiling shows ~90 % of cycles in
+`pause` (ggml_barrier spin): threads wait on the serial critical path.
+Memory placement (mmap/anon/THP/deferred) does not matter — all variants
+landed 3.8–4.6.
+
+- CUDA-graph capture aborts: qwen4exp's hyper-connection broadcasts use
+  per-layer `ggml_repeat_4d`, whose CUDA path is capture-illegal; until ik
+  gains capture-safe repeat/hc ops (mainline PR #28901 direction), graphs
+  stay dead.
+- Mainline llama.cpp itself runs 1.0 tok/s on this model (CPU MoE kernels
+  4× slower than ik's iqk) — do not switch engines for speed.
+- MTP/speculative decoding is impossible for mradermacher i1 GGUFs: the
+  NextN head is stripped (no `blk.48` tensors).
+- Tuning lever ranked first: `-ncmoe 42` (6 layers' experts on the 3090) →
+  decode 4.54, small-prompt prefill 32 — but VRAM 22/24.6 GiB at 262k ctx,
+  an operator OOM-margin decision, and it needs `GGML_CUDA_NO_PINNED_WEIGHTS=1`.