mini-context-graph
Best for document-heavy domainsWorks with GitHubLow risk
⌘source
- author
@github- language
- Python
★32kstars
3.9kforks
May 5, 2026
✦overview.md
Key Features
- ·Persistent wiki layer
- ·Navigable knowledge graph
- ·Raw source provenance
- ·Compounding knowledge accumulation
- ·Structured entity/relation extraction
Use Cases
- →Building a persistent knowledge base from a document collection
- →Supporting queries that require cross-referencing multiple documents
- →Answering structural questions about relationships between entities
Best for
- ✓document-heavy domains
- ✓long-running projects with evolving knowledge
Not ideal for
- !one-off queries
- !ephemeral conversations without persistence
FAQs
name
mini-context-graph
description
A persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern
with a structured knowledge graph. Ingest documents once — the LLM writes wiki
pages, extracts entities/relations into the graph, and stores raw content for
evidence retrieval. Knowledge accumulates and cross-references; it is never
re-derived from scratch.
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 |
| Wiki | wiki/ (markdown) | Writes/updates pages | Manages index.md + log.md |
| Graph | data/graph.json | Extracts entities + relations | Persists, deduplicates, traverses |
⚡ Quick Start for Agents
$install
1-click copynpx skills add github/awesome-copilot --skill mini-context-graphSafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
4/ 5
very goodClear and well structured, with only minor parts that might need a second read.
◎
Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
4/ 5
highMostly actionable with clear steps; only a few small gaps remain.