llm
Installation
SKILL.md
llm · experimental
Context skill for LLM engineering: agent frameworks, document/image processing, open-weight model serving, retrieval-augmented generation, and evaluation tooling.
When to load recipes
| You are working on... | Load recipe |
|---|---|
| Agent with Vercel AI SDK or Anthropic SDK | references/recipes/agents-ai-sdk.md |
| Agent with LangChain or LangGraph | references/recipes/agents-langgraph.md |
| Tool calling in any SDK | references/recipes/tool-calling.md |
| PDF text extraction, OCR, or document chunking | references/recipes/document-processing.md |
| Image tiling for Vision APIs or PDF rasterization | references/recipes/image-tiling.md |
| Serving open-weight models on AWS | references/recipes/serving-aws.md |
| Serving open-weight models on GCP | references/recipes/serving-gcp.md |
| RAG pipeline on AWS (OpenSearch, Bedrock) | references/recipes/rag-aws.md |
| RAG pipeline on GCP (Vertex AI, BigQuery) | references/recipes/rag-gcp.md |
| RAG with OSS vector stores (Qdrant, Chroma) | references/recipes/rag-oss.md |
| LLM evaluation, RAGAS, LangSmith, regression testing | references/recipes/llm-eval.md |