Why clrd?

Traditional dead code tools blindly flag unused code. But modern codebases are complex—dynamic imports, barrel files, and framework magic create false positives everywhere.

clrd is different. Built for the Agentic era, it combines:

• Rust Speed — Oxc parser + Rayon parallelism for instant analysis
• AI Intelligence — Confidence scoring lets LLMs make the final call
• Context Awareness — Generates AI context files so agents understand your codebase

# Find dead code in seconds, not minutes
$ clrd scan

  Found 23 issues in 1,847 files (142ms)

  src/utils/legacy.ts
    ├─ unusedHelper (unused_export) — 0 references [confidence: 0.95]
    └─ deprecatedFn (unused_export) — 0 references [confidence: 0.87]

  src/components/Button.tsx
    └─ OldButtonProps (unused_type) — 0 references [confidence: 0.92]

Installation

Via npm (Recommended)

npx clrd scan

Or install globally:

npm install -g clrd

Via Cargo

cargo install clrd

From Source

git clone https://github.com/relkimm/clrd.git
cd clrd
cargo build --release

Quick Start

1. Initialize

Create clrd.md with usage instructions for AI agents:

clrd init

This creates clrd.md and adds references to existing claude.md, agent.md, or .cursorrules.

2. Scan for Dead Code

# Pretty output (default)
clrd scan

# JSON output for LLM consumption
clrd scan --format json

# Interactive TUI
clrd scan --format tui

# Filter by confidence
clrd scan --confidence 0.8

3. Let AI Clean Up

Tell your AI agent: "Clean up dead code"

The AI will:

1. Read clrd.md for instructions
2. Run clrd scan --format json
3. Remove dead code based on confidence scores

4. Manual Fix (Optional)

# Preview changes (dry run)
clrd fix --dry-run

# Comment out instead of delete
clrd fix --soft

# Actually remove (requires clean git)
clrd fix --force

Features

Dead Code Detection

Confidence Scoring

Not all dead code is equal. clrd assigns confidence scores to minimize false positives:

Factors that lower confidence:

• Dynamic imports (import(), require())
• Test files
• Entry points (index.ts, main.ts)
• Public API markers

AI Integration

clrd is designed to work seamlessly with AI agents:

# Output JSON schema for LLM tool use
clrd schema

# The JSON output is perfect for AI consumption
clrd scan --format json --output dead-code.json

CLI Reference

clrd - AI-native code maintenance tool

USAGE:
    clrd <COMMAND>

COMMANDS:
    init     Create clrd.md with AI agent instructions
    scan     Scan for dead code
    fix      Remove or comment out dead code
    schema   Output JSON schema for LLM integration

OPTIONS:
    -v, --verbose         Enable verbose output
    -C, --directory <DIR> Working directory
    -h, --help            Print help
    -V, --version         Print version

clrd scan

OPTIONS:
    -f, --format <FORMAT>      Output format [default: pretty]
                               [values: pretty, json, compact, tui]
    -e, --extensions <EXT>     File extensions (comma-separated)
    -i, --ignore <PATTERN>     Patterns to ignore (comma-separated globs)
        --include-tests        Include test files in analysis
        --confidence <FLOAT>   Minimum confidence threshold [default: 0.5]
    -o, --output <FILE>        Output file (for json format)

clrd fix

OPTIONS:
        --dry-run              Preview changes without modifying files
        --soft                 Comment out code instead of deleting
        --force                Force removal (requires clean git status)
        --confidence <FLOAT>   Only fix items above threshold [default: 0.8]
    -f, --files <FILES>        Specific files to fix

Configuration

Supported File Types

By default, clrd scans: .ts, .tsx, .js, .jsx, .mjs, .cjs

# Scan only TypeScript
clrd scan --extensions ts,tsx

Ignore Patterns

Default ignores: node_modules, dist, build, .git

# Add custom ignores
clrd scan --ignore "**/*.test.ts,**/*.spec.ts,**/fixtures/**"

How It Works

┌─────────────────────────────────────────────────────────────────┐
│                         clrd Pipeline                           │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│   1. COLLECT         2. ANALYZE          3. DETECT              │
│   ┌──────────┐      ┌──────────┐       ┌────────────┐           │
│   │FileWalker│─────▶│   Oxc    │──────▶│ Reference  │           │
│   │ (rayon)  │      │  Parser  │       │   Graph    │           │
│   └──────────┘      └──────────┘       └────────────┘           │
│        │                 │                   │                  │
│        ▼                 ▼                   ▼                  │
│   1,847 files      AST Analysis       Dead Code Items           │
│     in 50ms        with exports/      with confidence           │
│                    imports            scores                    │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

1. FileWalker — Parallel file traversal using rayon, respects .gitignore
2. Oxc Parser — Lightning-fast JavaScript/TypeScript AST parsing
3. Reference Graph — Cross-file analysis to find unused exports/imports

Benchmarks

Tested on a large TypeScript monorepo (50,000+ files):

Benchmarks run on Apple M2, 16GB RAM

Programmatic API

Rust

use clrd::Scanner;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let scanner = Scanner::new("./src")
        .with_extensions(vec!["ts".into(), "tsx".into()])
        .with_confidence_threshold(0.8);

    let result = scanner.scan().await?;
    println!("Found {} issues", result.dead_code.len());
    Ok(())
}

Comparison

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

# Clone the repo
git clone https://github.com/relkimm/clrd.git
cd clrd

# Install dependencies
cargo build

# Run tests
cargo test

# Run locally
cargo run -- scan --format pretty

License

MIT License - see LICENSE for details.