Scans the codebase for technical debt and generates trackable GitHub issues to manage code quality.
Install
mkdir -p .claude/skills/tech-debt && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5393" && unzip -o skill.zip -d .claude/skills/tech-debt && rm skill.zipInstalls to .claude/skills/tech-debt
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Technical debt management - scan codebase for bad smells and create tracking issuesKey capabilities
- →Finds files exceeding 1000 lines
- →Detects ESLint/oxlint suppression comments
- →Identifies unsafe TypeScript 'any' type usages
- →Locates risky mock patterns in test files
- →Flags improper timer usage in tests
- →Generates structured GitHub issues for debt remediation
How it works
It runs targeted shell commands (find, grep, awk) to pattern-match anti-patterns and code smells within the specified directory structure.
Inputs & outputs
When to use tech-debt
- →Scanning for large files over 1000 lines
- →Finding suppressed linting errors
- →Identifying risky code patterns
- →Creating tracking issues for technical debt
About this skill
Technical Debt
Operations
research [scope]: inspect the requested scope, defaulting toturbo/, and report verified findings. This operation is read-only.issue [report]: create an English GitHub issue from current, verified findings. If no report exists, research first. Create or comment on an issue only when the caller requested that operation.
The tech-debt-research and tech-debt-issue commands remain aliases for these
operations. A report is evidence at its recorded revision, not a standing
instruction to change code.
Research
- Record the repository, HEAD, scope, and date. Read code quality and use the index for the affected surfaces.
- Use
rgto find candidates and inspect matching files and consumers. Exclude dependencies, generated/vendor content, and historical migrations from generic cleanup recommendations. Preserve permanent migration records. - Check type/lint suppressions, dynamic imports, environment configuration, error handling, fallback ownership, and unused dependencies against actual contracts. Use testing guidance for tests and ccstate guidance for signal/React code.
- Validate each candidate. File length, a relative import, a
catch, or an ESLintoff/ Oxlintallowsetting is not proof of a defect. Read override scope, replacement enforcement, generated-code boundaries, and documented exceptions. In particular, do not replace every floating promise withdetach()or assume every parentlessresetSignal()leaks. - Report the concrete consequence, file/line, applicable rule, evidence, proposed remedy, and uncertainty. Use severity based on demonstrated impact. Distinguish static inspection from executable or production verification.
Keep the report proportional to the findings: scope and revision, confirmed issues, dismissed candidates when useful, and next actions. Save detailed evidence when it is too long for the response. Do not invent schedules or effort estimates from match counts.
Issue
Recheck the report against current source and existing issues before posting. Use an English title describing the concrete problem; include affected paths, evidence, impact, and actionable acceptance criteria in the body. Use only existing relevant labels and include source links pinned to the inspected SHA.
Write the body to a temporary file and pass gh issue create --repo okou-ai/okou --body-file <file> the exact Markdown. Keep the report focused enough to fit one
issue; add detailed comments only when needed for the requested tracking task.
Verify the created issue and return its URL. If posting fails, retain the report
and state which action failed.
When not to use it
- →Projects not using TypeScript or ESLint
- →Quick prototyping phases where code quality is intentionally deprioritized
- →Filesystems lacking a 'turbo' structure
Limitations
- →Dependent on specific directory naming conventions
- →May generate noise from intentional lint suppressions
- →Limited to the predefined set of search patterns
How it compares
It systematically codifies code quality standards rather than relying on subjective ad-hoc reviews.
Compared to similar skills
tech-debt side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| tech-debt (this skill) | 1 | 3mo | Review | Beginner |
| reviewing-nextjs-16-patterns | 11 | 10mo | Review | Intermediate |
| dependency-upgrade | 0 | 6mo | Review | Advanced |
| fix-dependabot-alerts | 18 | 8mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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