code-review-graph

Skill by ara.so — Daily 2026 Skills collection.

code-review-graph

builds a persistent structural map of a codebase using Tree-sitter, stores it in a local SQLite graph, and exposes it to Claude via MCP. Instead of re-reading entire projects on every task, Claude queries the graph and reads only the files in the blast radius of a change — averaging 6.8× fewer tokens on code reviews and up to 49× on daily coding tasks in large monorepos.

Installation

Claude Code Plugin (recommended)

bash

claude plugin marketplace add tirth8205/code-review-graph
claude plugin install code-review-graph@code-review-graph

Restart Claude Code after installation.

pip

bash

pip install code-review-graph
code-review-graph install   # registers the MCP server with Claude Code

Requires Python 3.10+ and uv.

Optional: semantic search support

bash

pip install code-review-graph[embeddings]

Enables vector embeddings via

sentence-transformers

for

semantic_search_nodes_tool

Initial Setup

After installation, open your project in Claude Code and run:

Build the code review graph for this project

Or use the slash command:

/code-review-graph:build-graph

The first build parses the full codebase (~10 seconds for 500 files). After that, the graph updates incrementally on every file save and git commit (under 2 seconds for a 2,900-file project).

CLI Reference

bash

# Register MCP server with Claude Code
code-review-graph install

# Parse entire codebase into the graph (first run)
code-review-graph build

# Re-parse only changed files (subsequent runs)
code-review-graph update

# Show graph statistics: node count, edge count, language breakdown
code-review-graph status

# Auto-update the graph as you save files (continuous watch mode)
code-review-graph watch

# Generate an interactive D3.js HTML visualisation of the graph
code-review-graph visualize

# Start the MCP server manually (Claude Code does this automatically)
code-review-graph serve

Slash Commands in Claude Code

Command	What it does
`/code-review-graph:build-graph`	Build or rebuild the code graph from scratch
`/code-review-graph:review-delta`	Review changes since the last commit
`/code-review-graph:review-pr`	Full PR review with blast-radius analysis

MCP Tools (used automatically by Claude)

Once the graph is built, Claude calls these tools without manual prompting:

Tool	Purpose
`build_or_update_graph_tool`	Build or incrementally update the graph
`get_impact_radius_tool`	Find all files/functions affected by a change
`get_review_context_tool`	Return a token-optimised structural summary for review
`query_graph_tool`	Query callers, callees, tests, imports, inheritance
`semantic_search_nodes_tool`	Search code entities by name or meaning
`embed_graph_tool`	Compute vector embeddings for semantic search
`list_graph_stats_tool`	Graph size and health statistics
`get_docs_section_tool`	Retrieve documentation sections
`find_large_functions_tool`	Find functions/classes over a line-count threshold

Configuration: Ignoring Paths

Create

.code-review-graphignore

in the repository root:

generated/**
*.generated.ts
vendor/**
node_modules/**
dist/**
__pycache__/**
*.pyc
migrations/**

The graph will skip these paths during build and update.

Python API

The graph can be queried programmatically for custom tooling or scripts.

Build and update the graph

python

from code_review_graph import GraphBuilder

builder = GraphBuilder(repo_path="/path/to/your/project")

# Full build (first time)
stats = builder.build()
print(f"Nodes: {stats['nodes']}, Edges: {stats['edges']}")

# Incremental update (subsequent runs — only parses changed files)
update_stats = builder.update()
print(f"Re-parsed: {update_stats['files_updated']} files")

Query the graph

python

from code_review_graph import GraphQuery

query = GraphQuery(repo_path="/path/to/your/project")

# Find all callers of a function
callers = query.get_callers("authenticate_user")
print(callers)
# ['api/views.py::login_view', 'tests/test_auth.py::test_login']

# Find all callees (functions called by a function)
callees = query.get_callees("process_payment")
print(callees)

# Find tests that cover a file
tests = query.get_tests_for("payments/processor.py")
print(tests)

# Get inheritance chain for a class
parents = query.get_inheritance("AdminUser")
print(parents)
# ['BaseUser', 'PermissionMixin']

Blast-radius analysis

python

from code_review_graph import ImpactAnalyzer

analyzer = ImpactAnalyzer(repo_path="/path/to/your/project")

# What is affected if this file changes?
impact = analyzer.get_impact_radius("auth/models.py")
print(impact)
# {
#   "direct_callers": ["api/views.py", "middleware/auth.py"],
#   "transitive_dependents": ["api/tests/test_views.py", "integration/test_flow.py"],
#   "test_files": ["tests/test_auth.py"],
#   "blast_radius_size": 7
# }

# Multiple changed files (e.g., from a git diff)
changed_files = ["auth/models.py", "payments/processor.py"]
combined_impact = analyzer.get_impact_radius(changed_files)

Semantic search

python

from code_review_graph import SemanticSearch

# Requires: pip install code-review-graph[embeddings]
search = SemanticSearch(repo_path="/path/to/your/project")

# Embed the graph (one-time, cached)
search.embed()

# Search for code entities by concept
results = search.search("rate limiting middleware", top_k=5)
for r in results:
    print(r["node"], r["file"], r["score"])

Find large functions

python

from code_review_graph import GraphQuery

query = GraphQuery(repo_path="/path/to/your/project")

# Find functions/classes over 50 lines (good for refactoring targets)
large = query.find_large_functions(threshold=50)
for item in large:
    print(f"{item['name']} in {item['file']}: {item['lines']} lines")

Common Patterns

Pattern: Review only what changed in the current branch

bash

# In Claude Code, after making changes:
/code-review-graph:review-delta

Claude will:

Call
```
build_or_update_graph_tool
```
to sync the graph with your edits
Call
```
get_impact_radius_tool
```
on changed files
Call
```
get_review_context_tool
```
to get a compact structural summary
Review only the relevant ~15 files instead of the full codebase

Pattern: Continuous watch during development

bash

# Terminal 1: keep the graph fresh as you code
code-review-graph watch

# Terminal 2: your normal development workflow

Any file save triggers an incremental re-parse of only that file and its dependents.

Pattern: Pre-commit hook

bash

# .git/hooks/pre-commit
#!/bin/sh
code-review-graph update

Makes the graph always current before Claude sees a commit.

Pattern: Visualise the dependency graph

bash

code-review-graph visualize
# Opens an interactive D3.js force-directed graph in your browser
# Toggle edge types: calls, imports, inheritance, test coverage
# Search nodes by name

Pattern: Check graph health

bash

code-review-graph status
# Example output:
# Graph: .code-review-graph/graph.db
# Nodes: 4,821 (functions: 2,103 | classes: 487 | files: 312)
# Edges: 11,204 (calls: 7,891 | imports: 2,108 | inherits: 205 | tests: 1,000)
# Languages: Python (180), TypeScript (98), JavaScript (34)
# Last updated: 2026-03-26 01:22:11 (3 files changed)

Supported Languages

Python, TypeScript, JavaScript, Vue, Go, Rust, Java, C#, Ruby, Kotlin, Swift, PHP, Solidity, C/C++

Each language has full Tree-sitter grammar support for: functions, classes, imports, call sites, inheritance chains, and test detection.

Adding a New Language

Edit

code_review_graph/parser.py

python

# 1. Add file extension mapping
EXTENSION_TO_LANGUAGE = {
    # ... existing entries ...
    ".ex": "elixir",
    ".exs": "elixir",
}

# 2. Add AST node type mappings for the new language
_CLASS_TYPES["elixir"] = {"defmodule"}
_FUNCTION_TYPES["elixir"] = {"def", "defp"}
_IMPORT_TYPES["elixir"] = {"alias", "import", "use", "require"}
_CALL_TYPES["elixir"] = {"call"}

Then add a test fixture in

tests/fixtures/elixir/

and open a PR.

Where the Graph Is Stored

The graph is stored locally in

.code-review-graph/graph.db

(SQLite). There is no external database, no cloud dependency, and no data leaves your machine. Add it to

.gitignore

if you don't want it committed:

bash

echo ".code-review-graph/" >> .gitignore

Or commit it to share the pre-built graph with your team (saves the ~10-second initial build for each developer).

Troubleshooting

Graph is stale / not reflecting recent changes

bash

code-review-graph update    # incremental re-parse of changed files
# or, if something seems wrong:
code-review-graph build     # full rebuild from scratch

MCP server not connecting to Claude Code

bash

# Re-register the MCP server
code-review-graph install

# Verify it's registered
claude mcp list

Then restart Claude Code.

uv

not found

bash

# Install uv (required by the MCP server runner)
curl -LsSf https://astral.sh/uv/install.sh | sh
# or
pip install uv

Semantic search not working

bash

# Install the embeddings extra
pip install "code-review-graph[embeddings]"

# Compute embeddings (required once after install)
code-review-graph embed    # or call embed_graph_tool via Claude

A language isn't being parsed

Check that the file extension is in

EXTENSION_TO_LANGUAGE

and the corresponding Tree-sitter grammar is installed. Run

code-review-graph status

to see which languages were detected in your project.

Build is slow on first run

Expected — Tree-sitter parses every file. A 500-file project takes ~10 seconds. All subsequent

update

calls complete in under 2 seconds because only changed files are re-parsed (detected via SHA-256 hash comparison).

How the Token Reduction Works

On every review or coding task:

Graph query: Claude calls
```
get_impact_radius_tool
```
with the changed files
Blast-radius tracing: the graph follows call edges, import edges, and test edges to find every affected node
Compact summary:
```
get_review_context_tool
```
returns a 156–207 token structural summary (callers, dependents, test coverage gaps, dependency chains)
Targeted reading: Claude reads only the ~15 files in the blast radius, not the full codebase

In the Next.js monorepo (27,732 files): without the graph Claude reads ~739K tokens; with the graph it reads ~15K tokens — a 49× reduction.

code-review-graph

NPX Install

Tags

SKILL.md Content

code-review-graph

Installation

Claude Code Plugin (recommended)

pip

Optional: semantic search support

Initial Setup

CLI Reference

Slash Commands in Claude Code

MCP Tools (used automatically by Claude)

Configuration: Ignoring Paths

Python API

Build and update the graph

Query the graph

Blast-radius analysis

Semantic search

Find large functions

Common Patterns

Pattern: Review only what changed in the current branch

Pattern: Continuous watch during development

Pattern: Pre-commit hook

Pattern: Visualise the dependency graph

Pattern: Check graph health

Supported Languages

Adding a New Language

Where the Graph Is Stored

Troubleshooting

Graph is stale / not reflecting recent changes

MCP server not connecting to Claude Code

`uv`
not found

Semantic search not working

A language isn't being parsed

Build is slow on first run

How the Token Reduction Works