Skills

Knowledge Base Graph

Turns an LLM wiki knowledge base into an entity and topic knowledge graph.

Install

npx skills add Egonex-AI/Understand-Anything --skill understand-knowledge -g -a claude-code -y
Category
Data and ML
Updated
10d ago
License
MIT
Context cost
Lightabout 1,481 tokens
Runs scripts
Yes, review before use

What it does

Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.

/understand-knowledge

Analyzes a Karpathy-pattern LLM wiki, a three-layer knowledge base with raw sources, wiki markdown, and a schema file, and produces an interactive knowledge graph dashboard.

What It Detects

The Karpathy LLM wiki pattern (see https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f):

  • Raw sources, immutable source documents (articles, papers, data files)
  • Wiki, LLM-generated markdown files with wikilinks ([[target]] syntax)
  • Schema, CLAUDE.md, AGENTS.md, or similar configuration file
  • index.md, content catalog organized by categories
  • log.md, chronological operation log

Detection signals: has index.md + multiple .md files with wikilinks. May have raw/ directory and schema file.

Instructions

Phase 1: DETECT

  1. Determine the target directory:

    • If the user provided a path argument, use that
    • Otherwise, use the current working directory
    • Resolve the data directory $UA_DIR once, and reuse it for every read and write below: UA_DIR="<TARGET_DIR>/$([ -d "<TARGET_DIR>/.understand-anything" ] && echo .understand-anything || echo .ua)", this selects the legacy .understand-anything/ when it already exists, otherwise the new .ua/.
  2. Run the format detection script bundled with this skill:

    python3 "<SKILL_DIR>/parse-knowledge-base.py" "<TARGET_DIR>"
    
    • If the script exits with an error, tell the user this doesn't appear to be a Karpathy-pattern wiki and explain what was expected
    • If successful, proceed. The script writes scan-manifest.json to $UA_DIR/intermediate/
  3. Read the scan-manifest.json and announce the results:

    • "Detected Karpathy wiki: N articles, N sources, N topics, N wikilinks (N unresolved)"
    • List the categories found from index.md

Phase 2: SCAN (already done)

Read the whole SKILL.md on GitHub

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