Scan backend and frontend code for technical debt patterns and append findings to TECH_DEBT.md.
npx skills add https://github.com/wesuuu/runbook --skill tech-debt-wesuuu
Please help me install this Agent Skill. Skill: tech_debt Source: https://github.com/wesuuu/runbook/tree/main/.agent/skills/tech_debt Command: npx skills add https://github.com/wesuuu/runbook --skill tech-debt-wesuuu
Analyze the codebase for technical debt and append findings to TECH_DEBT.md. Use when the user asks to "find tech debt", "audit code quality", "log technical debt", "what needs refactoring", or runs /tech_debt. Scans backend and frontend code for common debt patterns and documents them for future development.
Run the tech_debt skill to scan the repository and append findings to TECH_DEBT.md.
High-intent search queries and answers about installing and using this skill.
To find technical debt in your codebase, you can scan source files for long functions, high cyclomatic complexity, and duplicate logic. This process surfaces code smells and architecture issues, appending structured refactoring candidates to a documentation file.
Common code smells include long functions, high cyclomatic complexity, duplicate logic, and missing tests. Identifying these refactoring candidates helps prioritize development efforts by documenting architecture issues and patterns that degrade code quality.
You can audit code quality across both frontend and backend repositories by analyzing source files for debt patterns. The scan applies to both environments to surface code smells, missing tests, and architecture issues for unified documentation.
To document technical debt, scan your repository to identify code smells and append structured findings to a markdown file. This log captures refactoring candidates and architecture issues, providing actionable guidance to prioritize development efforts.
The best way to log static analysis findings is to append structured results directly into a repository root file. This documents missing tests, architecture issues, and code smells, creating a persistent record to guide future refactoring.
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