dead-code

Detect and categorize dead code across Python, JavaScript, and TypeScript codebases.

1|Updated May 5, 2026
One-click install
npx skills add https://github.com/kollaborai/kollab --skill dead-code-kollaborai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dead-code
Source: https://github.com/kollaborai/kollab/tree/main/bundles/skills/dead-code
Command: npx skills add https://github.com/kollaborai/kollab --skill dead-code-kollaborai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually hunting for unused, obsolete, or unreachable code across a codebase is time-consuming, error-prone, and often leads to bloated projects with unnecessary technical debt and higher maintenance costs.

Core Features & Use Cases

  • Multi-Language Static & Dynamic Analysis: Detects unused imports, functions, classes, variables, commented-out code blocks, and unreachable code paths across Python, JavaScript, TypeScript, and other common programming languages.
  • Severity-Based Prioritization: Categorizes findings by risk level, flags uncertain items for manual review, and identifies safe-to-delete candidates to minimize cleanup risk.
  • Actionable Reporting: Generates structured markdown reports with code snippets, line numbers, removal recommendations, and automated cleanup script templates to streamline technical debt reduction.
  • Use Case: Before a major refactoring or production deployment, run this skill to get a full inventory of dead code, prioritize low-risk cleanup tasks, and reduce bloat without breaking existing functionality.

Quick Start

Use the dead-code skill to analyze your project's codebase and generate a full dead code report with prioritized cleanup recommendations.

Frequently Asked Questions about dead-code

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect dead code and unused functions across a Python or TypeScript codebase?

To detect dead code across Python or TypeScript codebases, you can run static analysis to identify unused imports, functions, classes, and variables. This process cross-references dynamic usage and generates markdown reports with severity-based prioritization for safe removal.

What is dead code analysis and how does it help reduce technical debt?

Dead code analysis is the automated identification of unreachable code paths and obsolete variables to reduce technical debt. By categorizing unused code by risk level, it flags safe-to-delete candidates and uncertain items for manual review, improving project maintainability without breaking functionality.

Can I generate cleanup reports for unused imports and variables before a major code refactoring?

Yes, you can generate cleanup reports for unused imports and variables before code refactoring. The analysis produces structured markdown reports containing code snippets, line numbers, removal recommendations, and automated cleanup script templates to streamline technical debt reduction workflows.

Does static analysis for dead code work with both Python and JavaScript projects?

Static analysis for dead code works with Python, JavaScript, TypeScript, and other common programming languages. It applies multi-language static and dynamic cross-referencing to accurately identify unused code blocks and commented-out code across diverse software codebases.

How do I prioritize dead code cleanup to minimize the risk of breaking existing functionality?

To prioritize dead code cleanup and minimize risk, the analysis categorizes findings by severity-based risk levels. It identifies safe-to-delete candidates separately from uncertain items requiring manual review, ensuring you reduce codebase bloat without breaking existing functionality.