autowiki

AutoWiki

Your LLM Compiles a Knowledge Base. You Just Read and Ask.
_{Implementing Karpathy's LLM Knowledge Base vision — raw sources in, Obsidian wiki out.
By AlphaLab-USTC}

English · 中文

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The Idea

Good survey papers don't just list references — they identify milestones, trace how ideas evolved, and organize the field into a coherent structure. AutoWiki does the same thing, automatically.

Drop papers in. The LLM identifies milestone nodes (conceptual breakthroughs), clusters papers around them, builds a hierarchical file tree that mirrors the field's structure, and writes deep analysis with temporal links between sources. You get a survey-quality knowledge graph maintained in Obsidian — not a folder of disconnected notes.

 You drop PDFs            LLM compiles                    You browse in Obsidian
─────────────    ──────────────────────────    ──────────────────────────────────
 raw/new/    →    Identify milestones          kb/topics/  (milestone nodes)
                  Cluster papers               kb/sources/ (deep analysis pages)
                  Trace temporal evolution      kb/journal/ (cognitive timeline)
                  Write cross-linked wiki       index.md    (survey-style tree)

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🚀 Quick Start

1. Clone & Install

git clone https://github.com/AlphaLab-USTC/AutoWiki-skill.git
pip install PyMuPDF

2. Add as Skill

In Claude Code or OpenClaw, just ask:

> "Add /absolute/path/to/AutoWiki-skill/skills to my global skillSources"

3. Initialize Your Wiki

cd your-wiki-project
mkdir -p raw/new raw/compiled kb/{sources,topics,journal} output
touch kb/index.md kb/log.md

4. Start Using

Open the project root as an Obsidian vault, then in Claude Code / OpenClaw:

> "Ingest the paper in raw/new/"
> "How does X compare across the Y papers?"
> "Lint the wiki"

Prerequisites: Claude Code or OpenClaw + Obsidian + Python 3.12+

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How It Works

raw/new/  ──→  LLM (Claude Code)  ──→  kb/  ──→  Obsidian
  you drop       reads, analyzes,       sources/    you browse
  PDFs here      links, writes          topics/
                                        journal/

Layer	Role	Who owns it
raw/	Source archive (PDFs + figures)	You drop files; agent organizes
kb/	Living wiki (markdown + wikilinks)	Agent writes & maintains everything

Three operations: Ingest (PDF → analysis page), Query (ask questions → synthesize → write back), Lint (25+ auto-checks).

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What Makes It Different

🧠 Deep Analysis	Not summaries. CRGP factors from the author's Introduction. Critical analysis with prior/update contrastive structure. Anti-patterns prevent generic filler.
🔗 Temporal Graphs	Every source positioned in the field's timeline. Evolutionary chains, cross-domain links, temporal tensions — all automatic.
🏠 Self-Healing	Three-tier autonomy: Silent (fix links) → Notify (record insights) → Confirm (restructure). 25+ lint checks.
🎯 Smart Classification	3-question fitness check before every topic assignment. Auto-scaling: <5 inline, ≥5 split, >8 sub-cluster.

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📂 Showcase: 80-Paper Wiki

We built a real wiki on Agent Self-Evolution — 80 papers, 13 milestones, 2 hours. Here's what the LLM compiled (compiling 80 papers in Claude Code with Opus 4.6 cost ~150 🔪 of quota):