Knowledge Graph Integration

SkillFiles & storage

Knowledge 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.

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-mcp or 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

ScenarioWithout GraphWith Graph
Code reviewRead all changed files + importsQuery impact of changes
Bug investigationRead 10-20 files manuallyTrace call path to bug
RefactoringRead entire moduleQuery all dependents
Architecture reviewRead project top-downGet 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

OperationRaw ReadingGraph QuerySavings
Find all callers of function~50K tokens~700 tokens71x
Architecture overview~200K tokens~3K tokens67x
Impact analysis for PR~30K tokens~2K tokens15x
Find related tests~20K tokens~1.5K tokens13x

Signals

GitHub stars
530
Forks
44
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
knowledge-graph-vibeeval
Source
github.com/vibeeval/vibecosystem