LeanKG GEMINI.md

LeanKG - AI Agent Context

Project Overview

LeanKG is a lightweight knowledge graph for codebase understanding. It indexes code, builds dependency graphs, calculates impact radius, and exposes everything via MCP for AI tool integration.

Tech Stack: Rust + PostgreSQL/pgvector + tree-sitter + MCP

Quick Start

# Index a codebase
cargo run -- init
cargo run -- index ./src

# Calculate impact radius
cargo run -- impact src/main.rs 3

# Start MCP server
cargo run -- serve

Development Workflow

When implementing features, follow: docs/workflow-opencode-agent.md

Pattern: Update Docs -> Implement -> Test -> Commit -> Push -> Bump Version -> Tag

1. Update docs first - PRD (docs/requirement/prd-leankg.md) -> HLD (docs/design/hld-leankg.md) -> README
2. Implement - Follow patterns in docs/workflow-opencode-agent.md
3. Build & test - cargo build && cargo test
4. Commit - git commit -m "feat: description" (one feature per commit)
5. Push - git pull --rebase && git push
6. Bump version - Update version in Cargo.toml
7. Tag - git tag -a v<version> -m "Release v<version>" && git push origin v<version> (after version bump)

Key Commands

cargo build      # Build project
cargo test       # Run tests
cargo run -- <cmd>  # Run CLI commands

Important Files

File	Purpose
src/lib.rs	Module exports
src/db/models.rs	Data models (CodeElement, Relationship, BusinessLogic)
src/graph/query.rs	Graph query engine
src/mcp/tools.rs	MCP tool definitions
src/mcp/handler.rs	MCP tool handlers
src/indexer/extractor.rs	Code parsing with tree-sitter

Data Model

• CodeElement - Files, functions, classes with qualified_name (e.g., src/main.rs::main)
• Relationship - imports, calls, tested_by, references, documented_by
• BusinessLogic - Annotations linking code to business requirements

MCP Tools

Core tools: query_file, get_dependencies, get_dependents, get_impact_radius, get_review_context, find_function, get_call_graph, search_code, generate_doc, find_large_functions, get_tested_by