llm-wiki-agent/README.md

LLM Wiki Agent

A personal knowledge base that builds and maintains itself. Drop in source documents — articles, papers, notes — and the LLM reads them, extracts the knowledge, and integrates everything into a persistent, interlinked wiki. You never write the wiki. Claude does.

Unlike RAG systems that re-derive knowledge from scratch on every query, LLM Wiki Agent compiles knowledge once and keeps it current. Cross-references are pre-built. Contradictions are flagged at ingest time. Every new source makes the wiki richer.

How It Works

You drop a source → Claude reads it → wiki pages are created/updated → graph is rebuilt

You ask a question → Claude reads relevant wiki pages → synthesizes answer with citations

Three layers:

• raw/ — your source documents (immutable, you own this)
• wiki/ — Claude-maintained markdown pages (Claude writes, you read)
• graph/ — auto-generated knowledge graph visualization

Quick Start — Any Coding Agent (no API key needed)

Works with Claude Code, Codex, OpenCode, Gemini CLI, and any agent that reads a config file from the repo root.

Agent	Config file read automatically
Claude Code	CLAUDE.md + .claude/commands/
OpenAI Codex	AGENTS.md
OpenCode / Pear AI	AGENTS.md
Gemini CLI	GEMINI.md
Any other agent	Point it at AGENTS.md or README.md

git clone https://github.com/SamurAIGPT/GPT-Agent.git
cd GPT-Agent

claude          # Claude Code
codex           # OpenAI Codex
opencode        # OpenCode
gemini          # Gemini CLI

Each agent reads its config file and follows the same workflows. Then talk to it:

# Claude Code slash commands:
/wiki-ingest raw/articles/my-article.md
/wiki-query what are the main themes across all sources?
/wiki-lint
/wiki-graph

# Any agent (plain English):
"Ingest this paper: raw/papers/my-paper.md"
"What does the wiki say about X?"
"Check for contradictions"
"Build the knowledge graph"

Quick Start — Standalone Python (requires API key)

pip install -r requirements.txt
export ANTHROPIC_API_KEY=your_key_here

python tools/ingest.py raw/articles/my-article.md
python tools/query.py "What are the main themes?"
python tools/query.py "How does X relate to Y?" --save
python tools/build_graph.py --open
python tools/lint.py --save

Architecture

raw/                    ← your sources (never modified by LLM)
wiki/
  index.md              ← catalog of all pages (updated on every ingest)
  log.md                ← append-only operation log
  overview.md           ← living synthesis across all sources
  sources/              ← one page per source document
  entities/             ← people, companies, projects
  concepts/             ← ideas, frameworks, methods
  syntheses/            ← answers to queries, filed back as pages
graph/
  graph.json            ← node/edge data (SHA256-cached)
  graph.html            ← interactive vis.js visualization
tools/
  ingest.py             ← process a new source
  query.py              ← ask a question
  lint.py               ← health-check the wiki
  build_graph.py        ← rebuild the knowledge graph
CLAUDE.md               ← schema and workflow instructions for the LLM

Commands

Claude Code (primary — no API key)

Slash command	What it does
/wiki-ingest <file>	Read a source, update wiki pages, append to log
/wiki-query <question>	Search wiki, synthesize answer with citations
/wiki-lint	Check for orphans, broken links, contradictions, gaps
/wiki-graph	Build knowledge graph (graph.json + graph.html)

Or describe what you want in plain English — Claude Code follows CLAUDE.md and does the right thing.

Standalone Python (optional — requires ANTHROPIC_API_KEY)

Command	What it does
python tools/ingest.py <file>	Ingest a source
python tools/query.py "<question>"	Query the wiki
python tools/query.py "<question>" --save	Query and file answer back
python tools/lint.py	Lint the wiki
python tools/build_graph.py	Build graph
python tools/build_graph.py --no-infer	Build graph (skip inference, faster)
python tools/build_graph.py --open	Build and open in browser

The Graph

build_graph.py runs two passes:

1. Deterministic — parse all [[wikilinks]] in every page → explicit edges tagged EXTRACTED
2. Semantic — Claude infers implicit relationships not captured by wikilinks → edges tagged INFERRED (with confidence) or AMBIGUOUS

Community detection (Louvain) clusters nodes by topic. The output is a self-contained graph.html — open it in any browser. SHA256 caching means only changed pages are reprocessed.

CLAUDE.md

CLAUDE.md is the schema document — it tells the LLM how to maintain the wiki. It defines page formats, ingest/query/lint workflows, naming conventions, and log format. This is the key configuration file. Edit it to customize behavior for your domain.

What Makes This Different from RAG

RAG	LLM Wiki Agent
Re-derives knowledge every query	Compiles once, keeps current
Raw chunks as retrieval unit	Structured wiki pages
No cross-references	Cross-references pre-built
Contradictions surface at query time (maybe)	Flagged at ingest time
No accumulation	Every source makes the wiki richer

Use Cases

• Research — go deep on a topic over weeks; every paper/article updates the same wiki
• Reading — build a companion wiki as you read a book; by the end you have a rich reference
• Personal knowledge — file journal entries, health notes, goals; build a structured picture over time
• Business — feed in meeting transcripts, Slack threads, docs; LLM does the maintenance no one wants to do

Tips

• Use Obsidian to read/browse the wiki — follow links, check graph view
• Use Obsidian Web Clipper to clip web articles directly to raw/
• The wiki is a git repo — you get version history for free
• File good query answers back with --save — your explorations compound just like ingested sources

License

MIT License — see LICENSE for details.

Related

• graphify — graph-based knowledge extraction skill (inspiration for the graph layer)
• Vannevar Bush's Memex (1945) — the original vision this is related to in spirit