Knowledge Graph Integration
SkillFiles & storageKnowledge graph integration for token-efficient codebase understanding. Uses codebase-memory MCP for AST indexing, dependency graphs, and smart context selection. 6-71x token savings vs raw file reading.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Knowledge Graph Integration skill
What this skill tells your AI
The instructions your AI receives, as published by vibeeval/vibecosystem in skills/knowledge-graph/SKILL.md and read by ahel’s review.
Overview
Transform any codebase into a queryable knowledge graph using codebase-memory MCP server. Instead of reading entire files, query the graph for exactly the context you need.
Token savings: 6-71x reduction compared to raw file reading.
Setup
Prerequisites
- codebase-memory MCP server installed (
~/bin/codebase-memory-mcpor via npm) - MCP config in
~/.mcp.json:
{
"mcpServers": {
"codebase-memory": {
"command": "/path/to/codebase-memory-mcp",
"args": []
}
}
}
Core Operations
1. Index a Repository
mcp__codebase-memory__index_repository
project_name: "my-project"
repo_path: "/path/to/repo"
First index takes 30-120s depending on repo size. Subsequent updates are incremental.
2. Check Index Status
mcp__codebase-memory__index_status
project_name: "my-project"
3. Search Code
mcp__codebase-memory__search_code
project_name: "my-project"
query: "authentication middleware"
Returns relevant code snippets without reading entire files.
4. Get Architecture Overview
mcp__codebase-memory__get_architecture
project_name: "my-project"
Returns high-level architecture: modules, dependencies, entry points.
5. Trace Call Paths
mcp__codebase-memory__trace_call_path
project_name: "my-project"
from_symbol: "handleLogin"
to_symbol: "validateToken"
6. Query Dependency Graph
mcp__codebase-memory__query_graph
project_name: "my-project"
query: "what depends on auth module?"
When to Use
| Scenario | Without Graph | With Graph |
|---|---|---|
| Code review | Read all changed files + imports | Query impact of changes |
| Bug investigation | Read 10-20 files manually | Trace call path to bug |
| Refactoring | Read entire module | Query all dependents |
| Architecture review | Read project top-down | Get architecture overview |
Integration with Agents
code-reviewer
Before reviewing, query the graph for the blast radius of changes:
search_code("functions that call {changed_function}")
architect
Get architecture overview before proposing changes:
get_architecture("project")
sleuth
Trace call paths to understand bug propagation:
trace_call_path("buggy_function", "entry_point")
Token Savings Examples
| Operation | Raw Reading | Graph Query | Savings |
|---|---|---|---|
| Find all callers of function | ~50K tokens | ~700 tokens | 71x |
| Architecture overview | ~200K tokens | ~3K tokens | 67x |
| Impact analysis for PR | ~30K tokens | ~2K tokens | 15x |
| Find related tests | ~20K tokens | ~1.5K tokens | 13x |
Signals
- GitHub stars
- 530
- Forks
- 44
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
knowledge-graph-vibeeval- Source
- github.com/vibeeval/vibecosystem