praneybehl/llm-wiki-plugin
80 stars · Last commit 2026-07-20
Andrej Karpathy's LLM Wiki pattern as a skill & Claude Code plugin — turn accumulated sources into a self-maintaining, scalable markdown knowledge base.
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# LLM Wiki — a second brain for AI agents Turn PDFs, articles, transcripts, and notes into a shared wiki that your AI agents can search, cite, and keep up to date. Add a source once. Ask questions later. Keep the useful answers. Works with Claude Code, Codex, Cursor, Gemini CLI, OpenCode, OpenClaw, Pi, and OMP. [Read the documentation](https://praneybehl.github.io/llm-wiki-plugin/). ## What is LLM Wiki? AI agents are good at the task in front of them, but a new session starts with limited context. LLM Wiki gives them a shared memory that lives inside your project. When you add a source, the agent turns it into linked Markdown pages. Later, it can find the right section and answer with citations. Useful answers can be saved back into the wiki, so the knowledge grows instead of being rebuilt from scratch. Everything canonical stays in readable Markdown. Default semantic search is local—no hosted vector database or embedding service. ## What's new in v3.0.0 - **Local semantic search by default.** FastEmbed runs `BAAI/bge-small-en-v1.5` on-device; sqlite-vec stores derived vectors in each wiki's cache. - **Hybrid precision and recall.** BM25 exact-term ranks and semantic ranks are fused with RRF. - **Incremental indexing.** Content hashes limit re-embedding to new or changed sections and remove deleted sections. - **Zero provider surface.** No OpenAI-compatible endpoint, API key, remote text transfer, provider consent, or per-query charge.