- Description truncated to 60 chars in system prompt (extract_skill_description),
so the 500-char HF workflow description never reached the agent; shortened to
'llama.cpp local GGUF inference + HF Hub model discovery.' (56 chars).
- Restore llama-cpp-python section (basic, chat+stream, embeddings,
Llama.from_pretrained) and frontmatter dependencies entry.
- Fix broken 'Authorization: Bearer ***' curl line (missing closing quote;
llama-server doesn't require auth by default).
Three tightly-scoped built-in skill consolidations to reduce redundancy in
the available_skills listing injected into every system prompt:
1. gguf-quantization → llama-cpp (merged)
GGUF is llama.cpp's format; two skills covered the same toolchain. The
merged llama-cpp skill keeps the full K-quant table + imatrix workflow
from gguf and the ROCm/benchmarks/supported-models sections from the
original llama-cpp. All 5 reference files preserved.
2. grpo-rl-training → fine-tuning-with-trl (folded in)
GRPO isn't a framework, it's a trainer inside TRL. Moved the 17KB
deep-dive SKILL.md to references/grpo-training.md and the working
template to templates/basic_grpo_training.py. TRL's GRPO workflow
section now points to both. Atropos skill's related_skills updated.
3. guidance → optional-skills/mlops/
Dropped from built-in. Outlines (still built-in) covers the same
structured-generation ground with wider adoption. Listed in the
optional catalog for users who specifically want Guidance.
Net: 3 fewer built-in skill lines in every system prompt, zero content
loss. Contributor authorship preserved via git rename detection.
