ai-generated-test-review

v2026.09.25

Use this skill when reviewing AI-generated unit, functional, API, or end-to-end tests for false confidence, weak assertions, missing risks, or unsafe test behavior; triggers include AI-generated test review and functional test review.

GitHub
安装命令
npx skhub add naodeng/ai-generated-test-review
Markdown
SKILL.md

AI-Generated Test Review

Determine whether AI-generated tests prove real behavior instead of merely raising coverage or producing green builds.

When to Use

  • Reviewing, changing, or accepting AI-generated unit, functional, API, or E2E tests.
  • A test passes but its assertions, isolation, data, or coverage value is doubtful.

Workflow

  1. Inventory test types and files actually present in scope: unit, functional test, API, E2E, or a combination. Review only discovered or user-specified types.
  2. Establish the behavior, risk, and available requirement or implementation evidence. Mark missing evidence; do not invent findings.
  3. Read prompts/review-test.md and report actionable findings by severity, tied to a test, risk, and repair direction.
  4. Load rules only for discovered layers: unit, functional test, API, or E2E. Load more than one only for cross-layer concerns; do not perform a global review just because multiple rule files exist.
  5. Separate merge-blocking faults from improvements; do not call an effective test defective because of style preference.

Core Constraints

  • Judge observable behavior, failure signals, and risk coverage—not line coverage, test names, or mock-call counts alone.
  • When a broken implementation could still pass, state the smallest break and the assertion needed to catch it.
  • Never recommend deleting assertions, swallowing errors, loosening timeouts, or changing production behavior merely to obtain green tests.
  • Do not expose credentials, personal data, or production write operations in tests, logs, or examples.

Progressive Disclosure

  • Always read prompts/review-test.md before reviewing; its test-type routing precedes per-test review.
  • For fake tests, excessive mocks, or ineffective assertions, read references/fake-test-patterns.md.
  • Read references/unit-test-rules.md, references/functional-test-rules.md, references/api-test-rules.md, or references/e2e-test-rules.md for the applicable layer.
  • Read related material under examples/good/ or examples/bad/ when an example is useful.

Pre-delivery Checklist

  • States scope, evidence, and open questions
  • Ranks findings and includes location, impact, and repair direction
  • Reviews real assertions, negative paths, boundaries, isolation, and repeatability
  • Does not present speculation as fact
发现
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版本
最新版本元数据

版本

v2026.09.25

发布时间

2026年9月25日

分类

未分类

许可证

NOASSERTION

源路径

skills/en/testing-types/ai-generated-test-review

默认分支

main

最新提交

c44b892

Tree SHA

7de02e4