/understand-knowledge

/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)

The parse script in Phase 1 already performed the deterministic scan. The scan-manifest.json contains:

• Article nodes (one per wiki .md file) with extracted wikilinks, headings, frontmatter
• Source nodes (one per raw/ file)