Context Graph

context-graph

Use when storing decision traces, querying past precedents, or implementing learning loops. Load in COMPLETE state or when needing to learn from history. Covers semantic search with Voyage AI embeddings, ChromaDB for cross-platform vector storage, and pattern extraction from history.

ingpoc/SKILLS·0installs9stars

SKILL.md

Full skill instructions

Context Graph

Living records of decision traces with semantic search. Find similar past decisions by meaning, not keywords.

Setup

MCP Server (recommended):

The context-graph MCP server provides the same functionality via tools:

context_store_trace - Store decisions with embeddings
context_query_traces - Semantic search
context_get_trace - Get by ID
context_update_outcome - Mark success/failure
context_list_traces - List with pagination
context_list_categories - Category breakdown

Configure in .claude/mcp.json:

{
  "mcpServers": {
    "context-graph": {
      "command": "uv",
      "args": ["--directory", "context-graph-mcp", "run", "python", "server.py"],
      "env": {"VOYAGE_API_KEY": "your_key_here"}
    }
  }
}

CLI Scripts (alternative):

# 1. Install dependencies
pip install voyageai chromadb

# 2. Set Voyage AI key
export VOYAGE_API_KEY="your_key_here"

# 3. Store/query traces
python scripts/store-trace.py "DECISION"
python scripts/query-traces.py "similar situation"

Instructions

Store trace after decisions with category + outcome
Query precedents when facing similar situations
Update outcome to success/failure after validation

Quick Commands (MCP)

context_store_trace(decision="Chose FastAPI for async", category="framework")
context_query_traces(query="web framework choice", limit=5)
context_update_outcome(trace_id="trace_abc...", outcome="success")

Quick Commands (CLI)

# Store a decision trace
python scripts/store-trace.py "Chose FastAPI over Flask for async support" --category framework

# Find similar past decisions
python scripts/query-traces.py "web framework selection"

# Query by category
python scripts/query-traces.py "database choice" --category architecture --limit 3

# Output JSON for parsing
python scripts/query-traces.py "error handling" --json

Trace Schema

Field	Description
`id`	Unique trace identifier
`timestamp`	When stored
`category`	Grouping (framework, api, error, etc.)
`decision`	What was decided (text)
`outcome`	pending / success / failure
`state`	State machine state when decided
`feature_id`	Related feature (if any)
`embedding`	1024-dim vector (Voyage AI)

When to Use

Situation	Action
Made a technical decision	Store trace with category
Facing similar problem	Query traces before deciding
Session complete	Query category → extract patterns
Repeating error	Query traces for that error

Install skill

Copy and run in your terminal

npx -y skills add https://github.com/ingpoc/SKILLS --skill context-graph

View on GitHub

context-graph/SKILL.md

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