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CLAUDE.md

code-review-graph CLAUDE.md

From tirth8205

code-review-graph is a persistent, incrementally updated, local-first knowledge graph for token-efficient code review through MCP and the CLI. It parses codebases using Tree-sitter and targeted fallba

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tirth8205/code-review-graph
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CLAUDE.md

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# CLAUDE.md - Project Context for Claude Code

## Project Overview

**code-review-graph** is a persistent, incrementally updated, local-first knowledge graph for token-efficient code review through MCP and the CLI. It parses codebases using Tree-sitter and targeted fallbacks, builds a structural graph in SQLite, and exposes compact context to AI coding tools including Claude Code, Codex, Cursor, Windsurf, Zed, Continue, OpenCode, Gemini CLI, Qwen, Kiro, Qoder, and GitHub Copilot.

## Graph Tool Usage (Token-Efficient)
When using code-review-graph MCP tools, follow these rules:
1. First call: `get_minimal_context(task="<description>")` — costs ~100 tokens, gives you the full picture.
2. All subsequent calls: use `detail_level="minimal"` unless you need more.
3. Prefer `query_graph_tool` with a specific target over broad `list_*` calls.
4. The `next_tool_suggestions` field in every response tells you the optimal next step.
5. Target: ≤5 tool calls per task, ≤800 total tokens of graph context.

## Architecture

- **Core Package**: `code_review_graph/` (Python 3.10+)
  - `parser.py` — Tree-sitter multi-language AST parser plus targeted fallbacks for broad source-language and notebook support
  - `custom_languages.py` — Config-driven custom language support (`.code-review-graph/languages.toml`, see docs/CUSTOM_LANGUAGES.md)
  - `graph.py` — SQLite-backed graph store (nodes, edges, B
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