Mini Context Graph

What it does

When your agent uses it

• Tasks that involve LLM wikis
• Tasks that involve Knowledge graphs
• Tasks that involve Knowledge bases

Example prompts

• “/mini-context-graph”

Requirements

• Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

1. 1Wiki layer — The LLM writes and maintains persistent markdown pages (summaries, entity pages, topic syntheses). Cross-references are…
2. 2Graph layer — Entities and relations are extracted once and stored as a navigable knowledge graph. BFS traversal answers structural…
3. 3Raw source layer — Original documents are stored immutably with chunks. Provenance links tie every graph node and edge back to the exact…

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 10 files in scripts/ (Python), which the agent can run.

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Mini Context Graph loads about 2k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 89 tokens; SKILL.md has 654 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~89

When it runs · the whole SKILL.md, loaded when a task matches

~2k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~6.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 654 words, ~2,028 tokens.

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.

from scripts.contextgraph import ContextGraphSkill
from scripts.tools import wiki_store

skill = ContextGraphSkill()

# ===== INGEST WITH FULL RAG + WIKI =====
# 1. Read references/ingestion.md and references/ontology.md first
# 2. Extract entities and relations (LLM reasoning step)
entities = [
    {"name": "memory leak",   "type": "issue",  "supporting_text": "memory leaks cause crashes"},
    {"name": "system crash",  "type": "issue",  "supporting_text": "system crashes due to memory leaks"},
]
relations = [
    {"source": "memory leak", "target": "system crash", "type": "causes",
     "confidence": 1.0, "supporting_text": "System crashes due to memory leaks."},
]

result = skill.ingest_with_content(
    doc_id="doc_001",
    title="System Crash Analysis",
    source="/docs/incident_report.pdf",
    raw_content="System crashes due to memory leaks. Memory leaks occur when objects are not released.",
    entities=entities,
    relations=relations,
)
# result = {"doc_id": "doc_001", "chunk_count": 1, "nodes_added": 2, "edges_added": 1}

# 3. Write a wiki summary page for this document
wiki_store.write_page(
    category="summary",
    title="System Crash Analysis Summary",
    content="""---
title: System Crash Analysis
source_document: doc_001
tags: [summary, incident]
---

# System Crash Analysis

**Source:** incident_report.pdf

## Key Claims

- [[memory-leak]] causes [[system-crash]] (confidence: 1.0)

## Entities

- [[memory-leak]] (issue)
- [[system-crash]] (issue)
""",
    summary="Incident report: memory leaks cause system crashes.",
)

# ===== QUERY WITH EVIDENCE =====
result = skill.query_with_evidence("Why does the system crash?")
# Returns: {"query": ..., "subgraph": ..., "supporting_documents": [...], "evidence_chain": ...}

# ===== WIKI SEARCH (read wiki before answering) =====
pages = wiki_store.search_wiki("memory leak")
# Returns: [{slug, category, path, snippet}, ...]

from scripts.tools import wiki_store
issues = wiki_store.lint_wiki()
# Returns: {orphan_pages, missing_pages, broken_wikilinks, isolated_pages}

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 14 other files (scripts, references) in skills/mini-context-graph of github/awesome-copilot.

• SKILL.md
• references/ingestion.md
• references/lint.md
• references/ontology.md
• references/retrieval.md
• scripts/config.py
• scripts/contextgraph.py
• scripts/template_agent_workflow.py
• scripts/tools/__init__.py
• scripts/tools/documents_store.py
• scripts/tools/graph_store.py
• scripts/tools/index_store.py
• scripts/tools/ontology_store.py
• scripts/tools/retrieval_engine.py
• scripts/tools/wiki_store.py

Open the folder on GitHubat commit 727ff2e

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

• boshi-xixixi/TraeSkill.trae/Skills/.agents/skills/mini-context-graph