mini-context-graph
Mini Context Graph Skill
The Core Idea
Standard RAG re-discovers knowledge from scratch on every query. This skill is different:
- Wiki layer — The LLM writes and maintains persistent markdown pages (summaries, entity pages, topic syntheses). Cross-references are already there. The wiki gets richer with every ingest.
- Graph layer — Entities and relations are extracted once and stored as a navigable knowledge graph. BFS traversal answers structural queries without re-reading sources.
- Raw source layer — Original documents are stored immutably with chunks. Provenance links tie every graph node and edge back to the exact text that supports it.
The LLM writes; the Python tools handle all bookkeeping.
Three Layers
| Layer | Where | What the LLM does | What Python does |
|---|---|---|---|
| Raw Sources | data/documents.json |
Reads (never modifies) | Stores chunks + metadata |
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