API Testing (English)

中文版： See skill api-testing.

Prompt: this directory's prompts/api-testing_EN.md.

When to Use

• User mentions API testing, api-testing
• Need to execute this testing type or produce deliverables per Standard-version
• Trigger examples: "Generate/design/write API test cases for the following"

Output Format Options

Markdown by default. For Excel / CSV / JSON, add at the end of your request; see output-formats.md.

How to Use

1. Open the relevant file in this directory's prompts/ and copy the content below the dashed line.
2. Append your requirements and context (business flow, environment, constraints, acceptance criteria).
3. If you need non-Markdown output, append the request sentence from output-formats.md at the end.

Code Examples

1. Postman + Newman REST API Testing

Complete user management API test example with 10 test cases.

Location: examples/postman-rest-api/

Includes:

• Postman collection file (10 test cases)
• Environment variable configuration
• Newman automation run script
• Detailed README documentation

Quick Start:

cd examples/postman-rest-api
npm install -g newman
./newman-run.sh

Test Coverage:

• User CRUD operations (Create, Read, Update, Delete)
• Authentication and authorization testing
• Error handling and boundary conditions
• Response time validation
• Data format validation

See: examples/postman-rest-api/README.md

2. REST Assured (Java)

Coming soon - Java-based REST API testing with REST Assured framework.

Location: examples/rest-assured-java/

3. SuperTest (Node.js)

Coming soon - Node.js API testing with SuperTest framework.

Location: examples/supertest-nodejs/

Best Practices

API Test Design Principles

1. Test Pyramid

   • Unit tests: Test individual API endpoints
   • Integration tests: Test interactions between multiple endpoints
   • End-to-end tests: Test complete business workflows

2. Test Data Management

   • Use environment variables for different environment configurations
   • Use dynamic variables to avoid hardcoding
   • Clean up data after tests

3. Assertion Strategy

   • Verify status codes
   • Verify response structure (Schema Validation)
   • Verify response data
   • Verify response time

4. Error Handling

   • Test various error scenarios (4xx, 5xx)
   • Verify error message format
   • Test boundary conditions

Tool Selection Guide

Tool	Use Case	Advantages
Postman/Newman	REST API testing	Easy to use, visual, CI/CD integration
REST Assured	Java projects	Strong typing, BDD style
Pytest + Requests	Python projects	Flexible, rich ecosystem
SuperTest	Node.js projects	Good integration with Express
GraphQL Playground	GraphQL API	Designed specifically for GraphQL

Common Pitfalls

• ❌ Testing only happy paths → ✅ Cover validation, error handling, auth failures, and edge cases
• ❌ Weak contract checks → ✅ Assert status, schema, business fields, and backward compatibility
• ❌ Not isolating test data → ✅ Use deterministic seed data and clear teardown rules
• ❌ Ignoring environment parity → ✅ Validate base URL, auth config, and dependency versions per environment

Troubleshooting

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

Reference Files

• prompts/api-testing_EN.md — API testing Standard-version prompt
• output-formats.md — Markdown / Excel / CSV / JSON request instructions
• examples/postman-rest-api/ — Complete Postman + Newman example
• quick-start.md — 5-minute quick start guide

Related skills: automation-testing-en, performance-testing-en, security-testing-en, functional-testing-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