chore(skills): promote runbook skills to managed-skills; drop superseded SKILL.md

- 31 new managed skills (anubis/arr/authentik/hermes/freetoken/podman/llm-swap
  runbooks etc.) now tracked.
- Removed superseded skills: omp_harness_config, peon_ping_integration
  (replaced by user-authored peon-ping-* managed skills),
  rocmfp4-strix-benchmark-orchestration.
- New memory-root skills: niri_compositor_ops, omp_git_workflow,
  omp_model_config, quadlet-media-migration, homelab-service-triage,
  hermes-dankclaw-ops, frank-default-large-ops, caddy-auth-dns-playbook.

agent/managed-skills/freetoken-dankclaw-build/SKILL.md

@@ -0,0 +1,39 @@
+---
+name: freetoken-dankclaw-build
+description: "Build FreeToken on Dankclaw (Dankware) — installs CUDA toolkit, sets CUDA_HOME, handles nvcc/CUDA version mismatch"
+---
+
+## Build FreeToken on Dankclaw
+
+### Prerequisites
+- CUDA toolkit: `sudo apt install nvidia-cuda-toolkit` (gives nvcc at /usr/bin, libcudart at /usr/lib/x86_64-linux-gnu/)
+- uv: installed at /home/dank/.local/bin/uv (or install via `curl -LsSf https://astral.sh/uv/install.sh | sh`)
+- CMake, git, Python >= 3.10 — all present
+
+### Build steps
+```bash
+cd /home/dank
+git clone https://github.com/FlashML-org/FreeToken.git  # or cd into existing
+cd FreeToken
+uv venv && source .venv/bin/activate
+export CUDA_HOME=/usr
+export FREETOKEN_ALLOW_CUDA_MISMATCH=1  # nvcc 12.4 + torch cu130 is safe
+uv pip install -e ".[accel]"
+```
+
+### Verification
+```bash
+ft --version
+python3 -c "
+from freetoken.checkpoint import ftw
+import torch
+t = torch.randn(3,4,dtype=torch.float16)
+print(ftw._dtype_str(t.dtype), ftw._elsize(t.dtype))
+"
+```
+
+### Key notes
+- FTW format is dtype-agnostic: FP16, BF16 (default), FP32, FP8 all work
+- GGUF support: only Gemma4GGUFForCausalLM
+- GGML types: F32/F16/BF16 (native views), Q4_0/Q6_K (dequant), Q8_0 (listed, no dequant)
+- The NVIDIA driver modules may not be loaded at build time (NVML warning) — not a problem for the build itself