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tech-debt

Identify maintenance problems across code, architecture, tests, dependencies, documentation, and infrastructure. Rank them by impact, risk, and effort, then produce a prioritized backlog with business reasons and a phased improvement plan alongside feature development.

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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.

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适用场景

  • Deciding which parts of the codebase to refactor first
  • Organizing maintenance issues across technical areas
  • Explaining the business reasons for technical improvements
  • Planning maintenance alongside feature development

包含的文件(1)

  • SKILL.md1.4 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Tech Debt Management

Systematically identify, categorize, and prioritize technical debt.

Categories

TypeExamplesRisk
Code debtDuplicated logic, poor abstractions, magic numbersBugs, slow development
Architecture debtMonolith that should be split, wrong data storeScaling limits
Test debtLow coverage, flaky tests, missing integration testsRegressions ship
Dependency debtOutdated libraries, unmaintained dependenciesSecurity vulns
Documentation debtMissing runbooks, outdated READMEs, tribal knowledgeOnboarding pain
Infrastructure debtManual deploys, no monitoring, no IaCIncidents, slow recovery

Prioritization Framework

Score each item on:

  • Impact: How much does it slow the team down? (1-5)
  • Risk: What happens if we don't fix it? (1-5)
  • Effort: How hard is the fix? (1-5, inverted — lower effort = higher priority)

Priority = (Impact + Risk) x (6 - Effort)

Output

Produce a prioritized list with estimated effort, business justification for each item, and a phased remediation plan that can be done alongside feature work.

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中文简介正在准备中。当前显示英语简介。

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