Requirements Analysis (English)

中文版： See skill requirements-analysis .

Prompt: this directory's prompts/requirements-analysis_EN.md .

When to Use

• User mentions requirements analysis, test point identification

• Need to extract test points from requirement documents

• Trigger examples: "Analyze test points for this requirement" or "Identify boundary conditions in requirements"

Output Format Options

This skill defaults to Markdown. To get another format, add 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/requirements-analysis_EN.md — Requirements analysis prompt

• output-formats.md — Format instructions

Code Examples

• Requirements Analysis Templates (Planned) - Requirements analysis examples and templates

Common Pitfalls

• ❌ Only looking at surface functionality → ✅ Deeply analyze implicit requirements and boundary conditions

• ❌ Ignoring non-functional requirements → ✅ Focus on performance, security, usability, etc.

• ❌ Missing exception scenarios → ✅ Identify all possible exception cases

• ❌ Lacking priority → ✅ Mark test point priorities

Best Practices

1. Requirements Analysis Framework (5W1H)

What (What is it)

• Feature description
• Business goals
• User value

Who (Who uses it)

• Target users
• User roles
• Permission requirements

When (When)

• Trigger conditions
• Time constraints
• Frequency requirements

Where (Where)

• Usage scenarios
• Environment requirements
• Platform limitations

Why (Why)

• Business reasons
• Problem solving
• Value proposition

How (How to implement)

• Implementation approach
• Technical solution
• Interaction flow

2. Test Point Identification

Test Point Types:

• Functional test points

• UI test points

• Data test points

• Performance test points

• Security test points

• Compatibility test points

Identification Methods:

• Equivalence partitioning

• Boundary value analysis

• Decision table

• State transition diagram

• Use case analysis

• User story mapping

3. Boundary Condition Analysis

Boundary Types:

• Input boundaries (min/max values, length limits)

• Output boundaries (result ranges, data formats)

• Time boundaries (timeout, expiration, scheduling)

• Quantity boundaries (count limits, capacity)

• Permission boundaries (role-based access control)

Analysis Techniques:

• On-point testing (exact boundary value)

• Off-point testing (just inside/outside boundary)

• Edge case testing (extreme values)

4. Dependency Analysis

Dependency Types:

• Data dependencies (input/output relationships)

• Functional dependencies (feature interactions)

• System dependencies (external services, APIs)

• Environmental dependencies (OS, browser, device)

5. Risk Assessment

Risk Categories:

• High: Critical business impact, high probability

• Medium: Moderate impact or probability

• Low: Minor impact, low probability

Risk Factors:

• Complexity of implementation

• Frequency of use

• Business criticality

• Technical uncertainty

Troubleshooting

Detailed troubleshooting steps were moved to references/troubleshooting.md. Load it on demand to keep the main skill concise.

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