Guard code quality with AI (translated)
Skills used in this guide (3)
使用 Playwright 与本地 Web 应用交互并测试的工具集。支持验证前端功能、调试 UI 行为、截取浏览器截图、查看浏览器日志。
npx skills add anthropics/skills -g当完成任务、实现主要功能，或在合并前验证工作是否符合需求时使用。
npx skills add obra/superpowers -g写新功能、修 bug 或重构时使用：强制测试驱动开发，单元、集成与端到端测试合计覆盖率 80% 以上。
npx skills add affaan-m/ECC -g
AI writes fast, but the quality gate matters more. Community consensus in three: reverse TDD (AI writes tests, then minimal impl), zero-warning gate (--max-warnings=0, warnings silently become the new baseline), review as a gate (every change through the same gate). Make AI output verifiable and gated, not fast and wild.
Who this is for / not for
For: teams using AI to code, wanting quality not to drop. Not for: those merging untested / unreviewed AI code.
Step-by-step
1. Reverse TDD
Spec in natural language → AI writes tests → AI writes minimal impl to pass:
From this spec, write tests first (cover edges and errors), then minimal impl to go green. Don't over-build.2. Zero-warning gate
ESLint --max-warnings=0, pre-commit for the mechanical layer; accumulated warnings become the baseline — only zero holds.
eslint . --max-warnings=03. Review as gate
Every change goes through requesting-code-review; auto checks block a batch first, humans only judge "does the standard hold cross-scene".
Review this change against team standards: issues, severity, fix; judge if the standard holds cross-scene.Pitfalls
| Pit | Symptom | Fix |
|---|---|---|
| No tests | Regress | Reverse TDD |
| Warning pile | Rot baseline | Zero warnings |
| No gate | Miss defects | Pre-commit |
| Blind trust | Incident | Human final call |
FAQ
TDD with AI?
Tests before impl.
Manage warnings?
Yes, zero-warning gate.
Who reviews?
Auto + human final.
Team uniform?
Same gate for all.
相关源码
- Quality Assurance in AI-Assisted Development (yushi91)
- Test-Driven Development with AI (Kinde)
- Making AI Coding Agents Follow True TDD (brgr.one)
- Keep Consistent Coding Standards with AI Code (exceeds.ai)
一句话结论
结论：AI 写代码要把质量门做硬——反向 TDD、零警告门禁、审查当关卡，让 AI 产出可验证可守门，你做最终判断。
References
Related Scenes
Write test cases and automation scripts with AI
The biggest value of testing isn't "high coverage" — it's "catching the paths that actually break". The point of AI-generated tests: give it the implemented code or a clear behavior contract, then have it add edge cases. Don't let it invent the thing under test; a test that passes on a fake object p
Get an AI code review worth reading
The classic failure mode is twenty "suggestions" where eighteen are style preferences. A useful review contains only two kinds of information: what will break, and what will confuse the next reader. So the job is not to make AI say more. It is to forbid everything else.