Test Case Review

中文版： 见技能 test-case-reviewer 。

Prompts: see prompts/test-case-reviewer_EN.md in this directory.

When to Use

• User mentions test case review, case review, or test case quality

• Need to review existing test cases for quality, identify missing scenarios, and provide improvement suggestions

• Trigger: e.g. "Please review these test cases" or "Find gaps and risks in the cases"

Output Format Options

This skill defaults to Markdown output. For other formats, specify at the end of your request.

How to Use

• Open the relevant file in this directory's prompts/ and copy the content below the dashed line.

• Append your requirements and context (business flow, environment, constraints, acceptance criteria).

• If you need non-Markdown output, append the request sentence from output-formats.md at the end.

Reference Files

• prompts/test-case-reviewer_EN.md — Test case review prompts

• output-formats.md — Format specifications

Code Examples

• Test Case Review Standards (Planned) - Review checklists and standards

Common Pitfalls

• ❌ Only surface-level issues → ✅ Deep analysis of coverage and quality

• ❌ Criticism without suggestions → ✅ Provide specific improvement recommendations

• ❌ Ignoring maintainability → ✅ Assess long-term maintenance costs

• ❌ Missing priorities → ✅ Mark issue severity levels

Best Practices

1. Review Dimensions

Completeness:

• Requirements coverage

• Scenario coverage

• Boundary value coverage

• Exception scenario coverage

Clarity:

• Clear steps

• Specific data

• Verifiable results

• No ambiguity

Maintainability:

• Independent test cases

• Separated data

• Modular design

• Easy to update

Efficiency:

• Reasonable execution time

• No redundant steps

• Automation potential

• ROI assessment

2. Review Checklist

Test Case Review Checklist

Basic Information

• Unique test case ID
• Clear title
• Priority marked
• Type marked

Preconditions

• Complete preconditions
• Achievable preconditions
• Clear dependencies

Test Steps

• Detailed and specific steps
• Repeatable steps
• Clear step numbering
• No missing steps

Test Data

• Specific and clear data
• Obtainable data
• Boundary values covered
• Exception data included

Expected Results

• Clear results
• Verifiable results
• Complete results
• No vague descriptions

Coverage

• Normal scenarios
• Exception scenarios
• Boundary conditions
• Permission validation

3. Review Report Template

Test Case Review Report

Review Date: 2024-02-06 Reviewer: John Doe Case Count: 50 Review Scope: Login Module

Review Summary

• Overall Quality: Good
• Main Issues: Insufficient boundary value coverage
• Improvement Suggestions: Add exception scenarios

Issue Statistics

Detailed Issues

Critical Issues

1. TC-001: Missing SQL injection test
   • Impact: Security risk
   • Suggestion: Add special character tests

High Issues

2. TC-005: Incomplete boundary value testing
   • Impact: May miss defects
   • Suggestion: Add boundary value cases

Missing Scenarios

• Concurrent login testing
• Session timeout testing
• Password complexity validation

Improvement Suggestions

1. Add boundary value tests
2. Supplement exception scenarios
3. Optimize case descriptions
4. Add automation markers

Troubleshooting

Issue 1: Don't know how to review

Solution: Use the review checklist and check item by item.

Issue 2: Low review efficiency

Solution:

• Use review tools

• Batch review similar cases

• Focus on high-priority cases

Related Skills: test-case-writing-en, test-strategy-en, requirements-analysis-en.

Target Audience

• QA engineers and developers executing this testing domain in real projects

• Team leads who need structured, reproducible testing outputs

• AI users who need fast, format-ready deliverables for execution and reporting

Not Recommended For

• Pure production incident response without test scope/context

• Decisions requiring legal/compliance sign-off without expert review

• Requests lacking minimum inputs (scope, environment, expected behavior)

Critical Success Factors

• Provide clear scope, environment, and acceptance criteria before generation

• Validate generated outputs against real system constraints before execution

• Keep artifacts traceable (requirements -> test points -> defects -> decisions)

Output Templates and Parsing Scripts

• Template directory: output-templates/

• template-word.md (Word-friendly structure)

• template-excel.tsv (Excel paste-ready)

• template-xmind.md (XMind-friendly outline)

• template-json.json

• template-csv.csv

• template-markdown.md

• Parser scripts directory: scripts/

• Parse (generic): parse_output_formats.py

• Parse (per-format): parse_word.py , parse_excel.py , parse_xmind.py , parse_json.py , parse_csv.py , parse_markdown.py

• Convert (generic): convert_output_formats.py

• Convert (per-format): convert_to_word.py , convert_to_excel.py , convert_to_xmind.py , convert_to_json.py , convert_to_csv.py , convert_to_markdown.py

• Batch convert: batch_convert_templates.py (outputs into artifacts/ )

Examples:

python3 scripts/parse_json.py output-templates/template-json.json python3 scripts/parse_markdown.py output-templates/template-markdown.md python3 scripts/convert_to_json.py output-templates/template-markdown.md python3 scripts/convert_output_formats.py output-templates/template-json.json --to csv python3 scripts/batch_convert_templates.py --skip-same