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technical-debt-visualizer

technical-debt-visualizer

github.com/jorgealvesTesting & quality2170 installsUpdated 4d ago
Repository

About technical-debt-visualizer

technical-debt-visualizer analyzes code structure and change history to surface complex, frequently modified files. It helps developers and engineering leads prioritize refactoring, using a local static scan that does not execute the code.

Key features

  1. 01Complexity analysis
  2. 02Change-frequency analysis from Git history
  3. 03Hotspot reports in Markdown
  4. 04Local in-memory static analysis
  5. 05Flags unsupported file types with lower confidence

Use cases

  1. 01Select refactoring targets before a sprint
  2. 02Review legacy code impact on codebase health
  3. 03Assess a repository during due diligence

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/jorgealves/agent_skills --skill technical-debt-visualizer

After installing, type/technical-debt-visualizerin Claude Code to confirm it loaded.

Bundled filesskill.yaml

Details

From the project README

Technical Debt Visualizer

Purpose and Intent

The technical-debt-visualizer provides a data-driven view of software quality. It helps engineering leaders and developers prioritize refactoring work by identifying files that are both complex and frequently changed—the "high-interest" technical debt.

When to Use

  • Sprint Planning: Run this before a dedicated refactoring sprint to identify the best "ROI" targets.
  • Architectural Reviews: Use to visualize the impact of legacy systems on the overall codebase health.
  • Due Diligence: Quickly assess the health of a new or acquired repository.

When NOT to Use

  • Performance Benchmarking: This tool measures code structure and maintainability, not runtime performance.
  • Absolute Complexity Rating: Metrics like cyclomatic complexity are indicators, not absolute rules; some complex logic is unavoidable.

Input and Output Examples

Input
source_path: "./src"
output_format: "markdown"
Output

A markdown report highlighting "Hotspots"—files that have high complexity and low test coverage.

Error Conditions and Edge Cases

  • No Git History: If run on a non-git directory, the "change frequency" metric will be unavailable.
  • Unsupported Languages: Complexity analysis is language-dependent; unknown extensions will be reported with a lower confidence score.

Security and Data-Handling Considerations

  • Local Scan: The analysis is performed entirely in memory on the local machine.
  • No Execution: The tool uses static analysis; it never runs the code it is analyzing.

Comments

Markdown supported