Identify, categorize, and prioritize technical debt. Trigger with "tech debt", "technical debt audit", "what should we refactor", "code health", or when the user asks about code quality, refactoring priorities, or maintenance backlog.
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill tech-debt
Systematically identify, categorize, and prioritize technical debt.
| Type | Examples | Risk |
|------|----------|------|
| Code debt | Duplicated logic, poor abstractions, magic numbers | Bugs, slow development |
| Architecture debt | Monolith that should be split, wrong data store | Scaling limits |
| Test debt | Low coverage, flaky tests, missing integration tests | Regressions ship |
| Dependency debt | Outdated libraries, unmaintained dependencies | Security vulns |
| Documentation debt | Missing runbooks, outdated READMEs, tribal knowledge | Onboarding pain |
| Infrastructure debt | Manual deploys, no monitoring, no IaC | Incidents, slow recovery |
Score each item on:
Priority = (Impact + Risk) x (6 - Effort)
Produce a prioritized list with estimated effort, business justification for each item, and a phased remediation plan that can be done alongside feature work.
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Take anthropics/tech-debt from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.