Install & Quick Start

Install

pip install my-llm-wiki

Optional extras:

pip install my-llm-wiki[all]   # PDF + .docx/.xlsx + better clustering

Build a graph

cd your-project
llm-wiki .

Output goes to wiki-out/:

wiki-out/
  graph.html       ← open in browser
  graph.json       ← persistent graph data
  WIKI_REPORT.md   ← analysis report
  wiki/            ← Wikipedia-style articles
  vault/           ← Obsidian-compatible vault ([[wikilinks]] + YAML frontmatter)

Open in Obsidian: Point Obsidian at wiki-out/vault/ (Open folder as vault) — graph view, backlinks, tag pane, and Properties all work out of the box. Community colors are pre-configured via .vault/graph.json.

Query

llm-wiki query gods                      # most connected nodes
llm-wiki query search "authentication"   # keyword search
llm-wiki query node UserService          # details + doc comment
llm-wiki query neighbors UserService     # what connects to it?
llm-wiki query path Auth Database        # shortest path
llm-wiki query community 0              # largest community
llm-wiki query stats                     # summary

Health check

llm-wiki lint    # orphan nodes, tiny communities, confidence breakdown

Keep the wiki alive

llm-wiki watch .                               # auto-rebuild on changes
llm-wiki add https://interesting-article.com   # ingest URL
llm-wiki .                                     # rebuild (cache skips unchanged)

Claude Code skill (optional)

For deep extraction of DOCX, scanned PDFs, and images:

mkdir -p ~/.claude/skills/my-llm-wiki
cp "$(python -c 'import my_llm_wiki; print(my_llm_wiki.__path__[0])')/SKILL.md" ~/.claude/skills/my-llm-wiki/

Then in Claude Code, run /wiki . for the full pipeline with agent-mode semantic extraction.

Ignore files

Create .wikiignore in project root (gitignore syntax):

vendor/
node_modules/
dist/
*.generated.py

Supported languages

Python, JavaScript, TypeScript, Go, Rust, Java, C, C++, Ruby, C#, Kotlin, Scala, PHP, Swift, Lua, Zig, PowerShell, Elixir