Test Case Reviewer
Published by naodeng in awesome-qa-skills
No known issues199 installs
What this skill does
Use this skill when you need to review test cases for completeness, clarity, maintainability, and missing scenarios; triggers include test case review and test case QA.
Add Test Case Reviewer to your agent
Review the source and files first. When you are ready, copy the prompt instruction or use the CLI command supported by your environment.
Install with a prompt
Paste this into a compatible coding agent:
add this skill "test-case-reviewer" from https://github.com/naodeng/awesome-qa-skillsInstall with the CLI
Run this command in a controlled environment after reviewing the repository:
npx skills add https://github.com/naodeng/awesome-qa-skills --skill test-case-reviewerSkill instructions
Test Case Review
Chinese version： See the corresponding Chinese skill.
When to Use
- Need help with test case reviewer in a real project context.
- Need an output that can be used directly for execution, review, or follow-up.
Workflow
- 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.
Core Constraints
- 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.
Progressive Disclosure
- Before producing output, read and follow
prompts/test-case-reviewer.md(minimum coverage, output structure, quality bar). - When Excel/CSV/JSON/Word is requested: read
output-formats.mdand 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.
Pre-delivery Checklist
- Followed the main prompt's output structure
- Minimum coverage focus: coverage gaps, missing positive scenarios, missing negative scenarios, missing boundary scenarios, traceability to requirements, step clarity, expected result quality, data quality, ... (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
Common Pitfalls
- Do not pretend completeness when scope/context is missing.
- Do not treat every item as equally important.
- Do not skip assumptions and information gaps.
- Do not dump generic theory unrelated to the current toolchain.
Files included
- README.md
- SKILL.md
- agents/openai.yaml
- evals/cases/basic-success.yaml
- evals/cases/edge-risk-priority.yaml
- output-formats.md
- evals/eval.yaml
- evals/cases/edge-incomplete-input.yaml
- evals/cases/review-located-case-defects.yaml
- evals/cases/review-correct-case-control.yaml
- output-templates/template-csv.csv
- output-templates/template-word.md
- output-templates/template-json.json
- output-templates/template-excel.tsv
- output-templates/template-markdown.md
- quick-start.md
- scripts/batch_convert_templates.py
- output-templates/template-xmind.md
- prompts/test-case-reviewer.md
- scripts/convert_output_formats.py
- scripts/convert_formats.py
- scripts/convert_to_excel.py
- scripts/convert_to_json.py
- scripts/convert_to_csv.py
- scripts/convert_to_xmind.py
- scripts/convert_to_markdown.py
- scripts/convert_to_word.py
- scripts/parse_excel.py
- scripts/parse_formats.py
- scripts/parse_csv.py
- scripts/parse_output_formats.py
- scripts/parse_json.py
- scripts/parse_pdf.py
- scripts/parse_markdown.py
- scripts/parse_word.py
- scripts/xlsx_reader.py
- scripts/parse_xmind.py