Identify and prioritize technical debt across codebases with parallel analyses.
npx skills add https://github.com/MitchellX/awesome-skills --skill techdebt-mitchellx
Please help me install this Agent Skill. Skill: techdebt Source: https://github.com/MitchellX/awesome-skills/tree/main/skills/techdebt Command: npx skills add https://github.com/MitchellX/awesome-skills --skill techdebt-mitchellx
Identify and prioritize technical debt across a codebase by running parallel analyses to surface duplication, code smells, architecture issues, and maintenance risks.
Invoke the /techdebt command in Claude Code to scan your repository and generate a prioritized technical debt report.
High-intent search queries and answers about installing and using this skill.
You can identify technical debt in a large codebase by running parallel analyses that scan for duplication, code smells, architecture issues, and maintenance risks simultaneously, generating a categorized and prioritized report.
Yes, you can scan specific directories for code smells and duplication by applying optional scope and category filtering before the parallel analysis begins, targeting only the areas you want to audit.
The best way to prioritize technical debt for quick fixes is to use a scanning tool that ranks issues by severity and highlights the top three easy fixes at the end of every consolidated report.
Yes, parallel code quality scanning works for maintenance risks by deploying specialized subagents that categorize findings into areas like architecture and maintenance, ranking their severity for actionable results.
You generate a technical debt report with severity ranking by invoking the scan command, which triggers parallel analyses to surface issues and rank them as High, Medium, or Low with actionable suggestions.
Automated codebase scanning for technical debt relies on static analysis to categorize issues like duplication and maintenance risks, meaning it may not capture runtime behaviors or dynamic architectural dependencies.
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