ai-generated-test-review · v1.0.0 · 2026-10-29 · sha256 939962b4fbecb1d2
ai-generated-test-review v1.0.0A
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--- name: ai-generated-test-review description: 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. license: PolyForm-Noncommercial-1.0.0 metadata: version: "1.0.0" compatibility: "" author: "Awesome QA Skills contributors" language: "en" category: "testing-types" source: "https://github.com/naodeng/awesome-qa-skills" license-url: "https://polyformproject.org/licenses/noncommercial/1.0.0" --- # 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. ## Domain Execution Essentials 1. Evaluate assertions against the actual contract; mock, snapshot, or status-only syntax alone does not imply WEAK/FAKE. 2. A boundary mock may replace a confirmed external dependency while real production logic executes. Mocking the subject itself and asserting its preset return offers no protection. 3. A reviewed, independent snapshot of stable business structure can detect meaningful mutations. A snapshot that discards all business fields cannot. A status assertion can be STRONG when status fully expresses the supplied contract; persistence obligations require business postconditions. 4. Support each classification with a concrete escaping/detected mutation and contract source. Retain confidence/gaps when evidence is missing, using the same bilingual rationale. ## 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 - When calibrating domain outcomes, valid controls, or evidence gaps, read [references/domain-decision-example.md](references/domain-decision-example.md) for sanitized input, per-item oracles, and reproducible calculations. - 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