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-primary-llamacpp-qwen38-flash-next-q8.md

@@ -110,6 +110,32 @@ retires the lucebox user quadlet to dated home trash
 truly free, relinks + enables + restarts the root unit, and waits up to
 1800 s for `/health` (cold start page-ins ~175 GiB and builds the graphs).
 
+### Preflight the GGUF without downloading it
+
+GGUF metadata lives in the header and HF honours ranged GETs, so a few MB
+answers every sizing question before a 13 GB transfer
+(`Range: bytes=0-8000000`). Parse: magic `GGUF`, u32 version, u64
+n_tensors, u64 n_kv, then key/value pairs (string = u64 len + bytes; ARRAY
+= u32 elem type + u64 count; BOOL is 1 byte — the type hand-written parsers
+forget). Walk arrays by byte size even for a summary: a naive parser
+desynchronises on `tokenizer.ggml.tokens` and lands gigabytes off. Read:
+`general.architecture`, `<arch>.block_count`, `<arch>.context_length`,
+`<arch>.nextn_predict_layers` (MTP is a property of the FILE — the `-mtp`
+build carries `blk.<n>.nextn.*`; `--spec-type draft-mtp` then loads the
+head against the MAIN model's weights, and `--model-draft` would load the
+file twice), `<arch>.head_count_kv`, `<arch>.key_length`/`value_length`,
+`<arch>.full_attention_interval`, `<arch>.ssm.state_size`/`group_count`/
+`time_step_rank`, and for the projector `clip.projector_type` +
+`clip.has_vision_encoder`.
+
+KV arithmetic for the hybrid (16 × (3 Gated DeltaNet + 1 Gated Attention)):
+only full-attention layers take KV
+(`attn_layers × n_head_kv × head_dim × 2 × bytes_per_elem`; f16 = 2 B,
+q8_0 = 1.0625 B, q4_0 = 0.5625 B); DeltaNet state is a fixed per-slot
+buffer (~0.16 GiB/sequence at 48 layers/128 d_state/48 v-heads f32); the
+MTP draft context costs ≈ 4 KiB/token. `--parallel N` DIVIDES `--ctx-size`
+between slots — it does not multiply.
+
 ## Verification (2026-09-26 deploy)
 
 - `/v1/models` reports `frank-primary`.