# LLM Wiki Agent

[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)

**A coding agent skill.** Drop source documents into `raw/` and type `/wiki-ingest` — the agent reads them, extracts knowledge, and builds a persistent interlinked wiki. Every new source makes the wiki richer. You never write it.

> Most knowledge tools make you search your own notes. This one reads everything you've collected and writes a structured wiki that compounds over time — cross-references already built, contradictions already flagged, synthesis already done.

```
/wiki-ingest raw/papers/attention-is-all-you-need.md
```

```
wiki/
├── index.md          catalog of all pages — updated on every ingest
├── log.md            append-only record of every operation
├── overview.md       living synthesis across all sources
├── sources/          one summary page per source document
├── entities/         people, companies, projects — auto-created
├── concepts/         ideas, frameworks, methods — auto-created
└── syntheses/        query answers filed back as wiki pages
graph/
├── graph.json        persistent node/edge data (SHA256-cached)
└── graph.html        interactive vis.js visualization — open in any browser
```

## Install

**Requires:** [Claude Code](https://claude.ai/code), [Codex](https://openai.com/codex), [Gemini CLI](https://github.com/google-gemini/gemini-cli), or any agent that reads a config file.

```bash
git clone https://github.com/SamurAIGPT/llm-wiki-agent.git
cd llm-wiki-agent
```

Open in your agent — no API key or Python setup needed:

```bash
claude      # reads CLAUDE.md + .claude/commands/
codex       # reads AGENTS.md
opencode    # reads AGENTS.md
gemini      # reads GEMINI.md
```

## Usage

```
/wiki-ingest raw/papers/my-paper.md          # ingest a source into the wiki
/wiki-ingest raw/articles/my-article.md      # works on any markdown file

/wiki-query "what are the main themes?"      # synthesize answer from wiki pages
/wiki-query "how does X relate to Y?"        # with [[wikilink]] citations

/wiki-lint                                   # find orphans, contradictions, gaps
/wiki-graph                                  # build graph.html from all wikilinks
```

Plain English also works with any agent:
```
"Ingest this paper: raw/papers/llama2.md"
"What does the wiki say about attention mechanisms?"
"Check for contradictions across sources"
"Build the knowledge graph and tell me the most connected nodes"
```

Works with any markdown source — articles, papers, book chapters, meeting notes, journal entries, research summaries.

## What You Get

**Persistent wiki** — structured markdown pages that accumulate across sessions. Unlike chat, nothing is lost.

**Entity pages** — auto-created for every person, company, or project mentioned across sources. Updated each time a new source references them.

**Concept pages** — auto-created for every key idea or framework. Cross-referenced to every source that discusses them.

**Living overview** — `wiki/overview.md` is revised on every ingest to reflect the current synthesis across everything you've read.

**Contradiction flags** — when a new source contradicts an existing claim, it's flagged at ingest time, not buried until query time.

**Knowledge graph** — `graph.html` shows every wiki page as a node, every `[[wikilink]]` as an edge, and Claude-inferred implicit relationships as dotted edges. Community detection clusters related topics.

**Lint reports** — orphan pages, broken links, missing entity pages, data gaps with suggested sources to fill them.

## Use Cases

### Research

Going deep on a topic over weeks — reading papers, articles, reports.

```
/wiki-ingest raw/papers/attention-is-all-you-need.md
/wiki-ingest raw/papers/llama2.md
/wiki-ingest raw/papers/rag-survey.md

# Wiki builds entity pages (Meta AI, Google Brain) and
# concept pages (Attention, RLHF, Context Window) automatically.

/wiki-query "What are the main approaches to reducing hallucination?"
/wiki-query "How has context window size evolved across models?"

/wiki-lint
# → "No sources on mixture-of-experts — consider the Mixtral paper"
```

By the end you have a structured, interlinked reference — not a folder of PDFs you'll never reopen.

---

### Reading a Book

File each chapter as you go. Build out pages for characters, themes, arguments.

```
/wiki-ingest raw/book/chapter-01.md
/wiki-ingest raw/book/chapter-02.md

# Wiki creates entity and theme pages automatically.

/wiki-query "How has the protagonist's motivation evolved?"
/wiki-query "What contradictions exist in the author's argument so far?"

/wiki-graph   # → graph.html shows every character/theme and how they connect
```

Think fan wikis like Tolkien Gateway — built as you read, with the agent doing all the cross-referencing.

---

### Personal Knowledge Base

Track goals, health, habits, self-improvement — file journal entries, articles, podcast notes.

```
/wiki-ingest raw/journal/2026-01-week1.md
/wiki-ingest raw/articles/huberman-sleep-protocol.md
/wiki-ingest raw/articles/atomic-habits-summary.md

/wiki-query "What patterns show up in my journal entries about energy?"
/wiki-query "What habits have I tried and what was the outcome?"
```

The wiki builds a structured picture over time. Concepts like "Sleep", "Exercise", "Deep Work" accumulate evidence from every source filed.

---

### Business / Team Intelligence

Feed in meeting transcripts, project docs, customer calls.

```
/wiki-ingest raw/meetings/q1-planning-transcript.md
/wiki-ingest raw/docs/product-roadmap-2026.md
/wiki-ingest raw/calls/customer-interview-acme.md

/wiki-query "What feature requests have come up most across customer calls?"
/wiki-query "What decisions were made in Q1 and what was the rationale?"

/wiki-lint
# → "Project X mentioned in 5 pages but no dedicated page"
# → "Roadmap contradicts customer interview on priority of feature Y"
```

The wiki stays current because the agent does the maintenance no one wants to do.

---

### Competitive Analysis

Track a company, market, or technology over time.

```
/wiki-ingest raw/competitors/openai-announcements.md
/wiki-ingest raw/market/ai-funding-report-q1.md

/wiki-query "How do OpenAI and Anthropic differ on safety approach?"
/wiki-query "Which companies announced multimodal models in the last 6 months?"
/wiki-query "Competitive landscape summary as of today" --save
```

## The Graph

Two-pass build:

1. **Deterministic** — parses all `[[wikilinks]]` across wiki pages → edges tagged `EXTRACTED`
2. **Semantic** — agent infers implicit relationships not captured by wikilinks → edges tagged `INFERRED` (with confidence score) or `AMBIGUOUS`

Louvain community detection clusters nodes by topic. SHA256 cache means only changed pages are reprocessed. Output is a self-contained `graph.html` — no server, opens in any browser.

## CLAUDE.md / AGENTS.md

The schema file tells the agent how to maintain the wiki — page formats, ingest/query/lint/graph workflows, naming conventions. This is the key config file. Edit it to customize behavior for your domain.

| Agent | Schema file |
|---|---|
| Claude Code | `CLAUDE.md` |
| Codex / OpenCode | `AGENTS.md` |
| Gemini CLI | `GEMINI.md` |

## 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 |

## Obsidian Integration

The wiki is designed to be browsed seamlessly in [Obsidian](https://obsidian.md). Since the agent maintains consistent `[[wikilinks]]`, you get a naturally growing knowledge graph in your vault.

### Vault Symlink Pattern
If you want to keep the LLM Wiki Agent repository separate from your main personal vault, use symlinks:
1. Keep your working agent repository at e.g., `~/llm-wiki-agent`
2. Create a symlink from your main Obsidian vault:
   ```bash
   ln -sfn ~/llm-wiki-agent/wiki ~/your-obsidian-vault/wiki
   ```
3. Use the [Obsidian Web Clipper](https://obsidian.md/clipper) or write directly to `raw/` in the agent repo to queue items for ingestion.

> **Note:** If you ever move your local repo directory, remember to update the symlink, otherwise the `wiki/` directory will appear missing in Obsidian.

### Recommended .obsidian Config
- **Graph View:** Filter out `index.md` and `log.md` (e.g. `-file:index.md -file:log.md`) to avoid them becoming gravity wells in your Obsidian graph.
- **Dataview:** Use the community plugin [Dataview](https://blacksmithgu.github.io/obsidian-dataview/) to query the YAML frontmatter the agent automatically injects (e.g., `type: source`, `tags: [diary]`).

## Tips

- File good query answers back with `--save` — your explorations compound just like ingested sources
- The wiki is a git repo — version history for free
- Standalone Python scripts in `tools/` work without a coding agent (require `ANTHROPIC_API_KEY`)

## Tech Stack

NetworkX + Louvain + Claude + vis.js. No server, no database, runs entirely locally. Everything is plain markdown files.

## Related

- [graphify](https://github.com/safishamsi/graphify) — graph-based knowledge extraction skill (inspiration for the graph layer)
- [Vannevar Bush's Memex (1945)](https://en.wikipedia.org/wiki/Memex) — the original vision this resembles

## License

MIT License — see [LICENSE](LICENSE) for details.