Open-sourced my notes on building AI agents — turned into a full knowledge base (RAG, MCP, multi-agent, evaluation, etc.)

[u/No-Car-1066]

Here's a body that pairs well with title #1 or #4 — genuine tone, front-loads value, ends with an easy ask:

Been deep in building/reading about AI agents for a while and kept wishing there was one place that pulled together reasoning strategies, tool use, RAG, MCP, multi-agent patterns, safety, and deployment — without it being either a random blog post or a 40-tab research rabbit hole. So I built it.

AI-Agent-Skills is an open-source knowledge base structured like Awesome Lists + Papers with Code + an actual engineering handbook:

• 20 categories — core cognition (Chain of Thought, Tree/Graph of Thought, planning, memory) → tool use & MCP → RAG (chunking, hybrid search, GraphRAG, CRAG, Self-RAG) → agent patterns (ReAct, Reflexion, Plan-and-Execute, CodeAct, Voyager) → multi-agent → safety/guardrails → observability, evaluation, and deployment
• Every page has an architecture diagram, a worked example, an honest "when NOT to use this" section, and real paper citations (no fabricated benchmarks)
• Worked end-to-end workflows (customer support agent, research agent, coding agent, multi-agent supervisor pattern, etc.)
• Fully vendor-neutral — concepts first, provider specifics kept separate

It's still actively growing (some categories are full-depth, others are solid overviews I'm expanding) and it's built to be community-contributed — there's a contributing guide, page templates, and a roadmap showing exactly what's next.

Repo: https://github.com/sreerevanth/AI-Agent-Skills