docs: OKF v0.1 compliance pass + fact-check + 3 research briefs

- Migrate all 127 non-reserved docs to OKF v0.1 frontmatter (type/description/tags/timestamp); fix 13 YAML issues, 2 duplicate-FM blocks, strip reserved-page FM
- Restructure log.md to OKF (## YYYY-MM-DD, newest-first)
- Fact-check against scripts/AGENTS.md ground truth: fix 6 false 'Active' banners on retired runbooks, 96->114 GiB GTT, deployment.md vs deploy-plan.py/deploy-remote.sh, Deployment Flow frank-medium=Quadlet, Calibre 9.9.0->9.15.0 + CVE-2025-7404 conflation, Copyparty v1.20.24, RomM 5.3.0 breaking change
- Move *arr docs to new FrankBook-Pro/ section (git mv, link-safe)
- Write active runbook bodies from ground truth (frank-large, frank-small)
- Add 3 research briefs + HTML report: Local TTS and Voice Cloning, AI Job Search and Resume Tools, Most Popular Self-Hosted AI Apps (Jun-Sep 2026)
- Add upstream-version rows to ComfyUI/OpenWebUI/Hermes app docs
- All 336 tests pass; 136 pages, 0 unresolved wikilinks

serverAppConfigs-docs/LLM/Shared Memory Architecture Dankclaw.md

@@ -1,3 +1,11 @@
+---
+type: reference
+description: "Dankclaw uses AMD Strix Halo APU with unified memory architecture."
+tags:
+  - llm
+timestamp: 2026-08-28
+---
+
 # Shared Memory Architecture Dankclaw
 
 ## Overview
@@ -142,7 +150,7 @@ Unified memory has lower bandwidth than dedicated VRAM:
 
 ### ROCm Overcommit
 
-ROCm reports 96 GiB GPU memory on Strix Halo APU. Physical RAM is 64 GiB (61 GiB visible; corrected 2026-08-17, the box was upgraded from 32 GB). The GPU can address more than physical RAM exists. vLLM will see 96 GiB and try to allocate accordingly. Set `--gpu-memory-utilization` to 0.80 or lower to prevent OOM.
+ROCm reports ~114 GiB of GPU memory on Strix Halo APU (the GTT aperture, `gtt_total=122402963456` bytes = 114 GiB; `llama-server --list-devices` shows 116,732 MiB — the 2026-08-17 "96 GiB" figure was stale). Physical RAM is 64 GiB (61 GiB visible; the box was upgraded from 32 GB). The GPU can address more than physical RAM exists because the GTT aperture maps over the shared LPDDR. vLLM will see ~114 GiB and try to allocate accordingly. Set `--gpu-memory-utilization` to 0.80 or lower to prevent OOM.
 
 Lower bandwidth means slower inference. Plan for lower throughput.