Rocket.Chat Code Analyzer

This tool helps AI agents understand the Rocket.Chat codebase. It scans TypeScript files and creates compressed "skeletons" (summaries) of the code. This allows you to analyze large parts of the application without using too many tokens.

Features

• Smart Scanning: Finds relevant files based on your question.
• Skeleton Generation: Removes function bodies to save space, keeping only structure and types.
• Module Scoping: Can focus on specific Rocket.Chat modules to reduce noise.

Test & Benchmark Results

Tests

• Status: ✅ Passing (Core scanner, Scope enforcement, Benchmarks)

Benchmarks

Tested on Rocket.Chat (apps/meteor) with real-world queries (Messaging, Auth, E2E):

Metric	Result
Token Reduction (vs Full Scan)	~96.5%
Token Reduction (vs Top-N)	~78.2%
Average Execution Time	~1.2s

Usage

Option 1: CLI (Direct Usage)

You can run the tool using npm run cli.

Basic Example

npm run cli -- --question "how are messages sent?"

Using Modules (Recommended)

To get better results, tell the tool which part of Rocket.Chat to look at:

npm run cli -- --question "permission checks" --modules authorization

Available Modules:

• lib-server-functions
• authorization
• e2e
• file-upload

All Options

• --question: (Required) The question you want to answer.
• --root: The folder to scan (default: current folder).
• --limit: How many files to return (default: 10).
• --modules: Comma-separated list of modules to filter by.
• --with-mapping: Creates a map of symbols to find definitions later.
• --skip-cache: Force full analysis without caching.

Caching

The tool caches analysis results for faster repeated queries. Cache is stored in .code-analyzer-cache/.

Cache management:

# View cache statistics
npm run cli -- --cache-stats

# Clear cache
npm run cli -- --cache-clear

# Skip cache for current query
npm run cli -- --question "how are messages sent?" --skip-cache

Cache Details:

• Strategy: Hybrid (in-memory + persistent disk cache)
• Invalidation: MD5 file hashing (detects changes automatically)
• TTL: 24 hours
• Location: .code-analyzer-cache/

Option 2: Gemini CLI Integration (MCP Server)

Use this tool as an MCP (Model Context Protocol) server with Gemini CLI for AI-powered code analysis and benchmarking.

Setup

1. Build the extension:

   npm run build
   cd gemini-extension && npm install && npm run build

2. Configure Gemini CLI:

   Create or update ~/.gemini/config.json:

   {
     "mcpServers": {
       "rc-code-analyzer": {
         "command": "node",
         "args": ["/path/to/code-analyzer/gemini-extension/dist/server.js"]
       }
     }
   }

3. Run Gemini CLI:

   cd /path/to/code-analyzer
   gemini

Example Queries with Gemini CLI

How are messages sent in Rocket.Chat?
How does user authentication work?
How are permissions checked?
What is the E2E encryption flow?

Gemini CLI will automatically use the scan_codebase tool to analyze relevant files and provide insights with token savings metrics.

Benefits

• AI-Powered Analysis: Gemini CLI provides context-aware insights and suggestions.
• Token Efficiency: Skeletons reduce token usage by ~96.5% vs full scans.
• Easy Integration: Works seamlessly with Gemini CLI's MCP protocol.
• Benchmarking: Track token stats and performance across queries.

Install

npm install
npm run build

For Gemini CLI integration:

cd gemini-extension
npm install
npm run build

Testing

Run Tests

npm test

Test MCP Server (Optional)

To verify the Gemini CLI extension works correctly:

npm run build && node test-gemini-server.mjs

This tests tool discovery and the scan_codebase tool without requiring Gemini CLI.