ai-assisted-testing

AI-Assisted Testing

Chinese version： See the corresponding Chinese skill.

When to Use

Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).
Add only project context that changes the result: scope, environment, constraints, risks, dependencies, expected deliverable.
If input is incomplete, return a usable first draft and explicitly mark assumptions and gaps.
Default to Markdown; switch formats only when the user asks.

Record input classification, sanitization, and allowed use. Replace identities, tokens, and personal data with non-reversible placeholders while retaining schema/business constraints.
Trace input snapshot→model/prompt version→AI draft ID→Human review→adopted version ID→acceptance evidence. Drafts do not automatically become execution assets.
Name the reviewers of business oracles, assertions, privacy, and high-risk tradeoffs. Unreviewed work remains draft, unexecuted work NOT_RUN; AI does not accept on behalf of Human.
Compare equal tasks/complexity/windows: manual baseline versus AI generation+review+rework+acceptance time. Track defects/rework separately; generation time alone cannot prove productivity gains.

Prioritize by risk / business impact — do not treat everything equally.
Separate confirmed facts from current assumptions.
Do not invent endpoints, fields, environments, or root causes the user did not provide.
Keep output executable: concrete scenarios, clear priority, clear next steps.

When calibrating domain outcomes, valid controls, or evidence gaps, read references/domain-decision-example.md for sanitized input, per-item oracles, and reproducible calculations.
Before producing output, read and follow prompts/ai-assisted-testing.md (minimum coverage, output structure, quality bar).
When Excel/CSV/JSON/Word is requested: read output-formats.md and honor the format.
When a ready-made template fits: use matching files under output-templates/.
For format conversion or helper checks: prefer existing scripts/ over reinventing.
For evaluating/regressing this skill: use evals/ with skill-up.

Followed the main prompt's output structure
Minimum coverage focus: task scope, best AI-assisted opportunities, human verification points, high-risk areas that need manual judgment, draft artifacts to generate, review and approval steps, quality gates, time-saving opportunities, ... (details in main prompt)
Covered the minimum checklist, or explained omissions
High-risk items have explicit priority
Did not invent details the user did not provide
Assumptions and gaps are marked