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Agent Skill · 研究检索

api-test-generator(API 测试生成器)

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

api-test-generator 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 68,166。

总安装 235周安装 10GitHub Stars 195下载 82核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:api-test-generator(API 测试生成器)
来源仓库:https://github.com/microck/ordinary-claude-skills
仓库路径:skills/api-test-generator
安装命令:
npx skills add https://github.com/microck/ordinary-claude-skills --skill api-test-generator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/microck/ordinary-claude-skills --skill api-test-generator

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助 API 设计、接口文档和请求响应结构梳理。适合生成 OpenAPI 草稿、检查字段命名和错误码。使用时需确认真实业务语义和鉴权方式。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。应避免凭空补字段,优先从现有代码中提取事实。

api-test-generator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/api-test-generator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/microck/ordinary-claude-skills --skill api-tes…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

api-test-generator 怎么安装?

在终端执行 npx skills add https://github.com/microck/ordinary-claude-skills --skill api-test-generato…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

api-test-generator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

api-test-generator 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

api-test-generator 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

api-test-generator 用的人多吗?

公开数据是累计安装 235 次,近一周安装 10 次,下载 82 次,GitHub 195 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

api-test-generator 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
api-test-generator

API 测试生成器 · 本页

235195接触敏感数据MIT未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

MikoPBX API Test Generating

Generate comprehensive Python pytest tests for MikoPBX REST API endpoints with full parameter coverage, schema validation, and edge case testing.

What This Skill Does

Analyzes DataStructure.php files and generates complete pytest test suites including:

  • ✅ CRUD operation tests (Create, Read, Update, Delete)
  • ✅ Positive and negative test cases
  • ✅ Parameter validation tests
  • ✅ Edge cases and boundary conditions
  • ✅ Schema validation tests
  • ✅ Proper fixtures and authentication
  • ✅ Detailed assertions with error messages

When to Use This Skill

Use this skill when you need to:

  • Create pytest tests for new REST API endpoints
  • Add comprehensive test coverage for existing endpoints
  • Generate tests covering all parameter combinations
  • Add schema validation tests for API responses
  • Create edge case and negative tests
  • Ensure API compliance with OpenAPI specification

Quick Start

Basic Usage

When the user requests test generation:

  1. Identify the endpoint

- API path (e.g., /pbxcore/api/v3/extensions) - HTTP methods (GET, POST, PUT, DELETE, PATCH) - Resource name (e.g., Extensions)

  1. Locate DataStructure.php find /Users/nb/PhpstormProjects/mikopbx/Core/src/PBXCoreREST/Lib -name "DataStructure.php" | grep -i "{resource}"
  2. Analyze parameter definitions Extract from DataStructure.php:

- Required vs optional parameters - Data types and validation rules - Default values - Enum values - Pattern constraints (regex) - Min/max values

  1. Generate test file Use the complete template from test-template.py
  2. Customize for endpoint

- Replace {ResourceName} placeholders - Fill in actual payload structures - Add specific field validations - Include enum and pattern validations

Test Structure

File Organization

tests/api/
├── test_{resource}_api.py        # Main test file
└── conftest.py                   # Shared fixtures

Test Class Structure

Each test file should have these test classes:

class TestCreate{ResourceName}:
    """Test POST endpoint for creating resources"""
    - test_create_with_valid_data()
    - test_create_missing_required_field()
    - test_create_with_invalid_type()

class TestGet{ResourceName}:
    """Test GET endpoint for retrieving resources"""
    - test_get_all()
    - test_get_by_id()
    - test_get_nonexistent()

class TestUpdate{ResourceName}:
    """Test PUT/PATCH endpoints for updating resources"""
    - test_update_with_valid_data()
    - test_patch_partial_update()

class TestDelete{ResourceName}:
    """Test DELETE endpoint for removing resources"""
    - test_delete_existing()
    - test_delete_nonexistent()

class TestSchemaValidation{ResourceName}:
    """Test response schema validation"""
    - test_response_matches_openapi_schema()

class TestEdgeCases{ResourceName}:
    """Test edge cases and boundary conditions"""
    - test_special_characters_in_fields()
    - test_empty_string_values()
    - test_boundary_values()

Standard Fixtures

@pytest.fixture
def auth_token():
    """Get authentication token"""
    response = requests.post(
        f"{BASE_URL}/pbxcore/api/v3/auth/login",
        json={"login": "admin", "password": "123456789MikoPBX#1"},
        verify=False
    )
    return response.json()["data"]["access_token"]

@pytest.fixture
def headers(auth_token):
    """Standard headers with authentication"""
    return {
        "Authorization": f"Bearer {auth_token}",
        "Content-Type": "application/json"
    }

Common Test Patterns

1. Create with Valid Data

def test_create_with_valid_data(self, headers):
    """Test creating a resource with all valid required parameters"""
    payload = {
        # Based on DataStructure.php
    }

    response = requests.post(
        f"{BASE_URL}{API_PATH}",
        json=payload,
        headers=headers,
        verify=False
    )

    assert response.status_code == 200, f"Expected 200, got {response.status_code}: {response.text}"
    data = response.json()
    assert "data" in data
    assert "id" in data["data"]

    # Validate returned values match input
    for key, value in payload.items():
        assert data["data"][key] == value

2. Validation Tests

def test_create_missing_required_field(self, headers):
    """Test validation when required field is missing"""
    payload = {
        # Missing required field
    }

    response = requests.post(
        f"{BASE_URL}{API_PATH}",
        json=payload,
        headers=headers,
        verify=False
    )

    assert response.status_code == 400
    assert "messages" in response.json()

3. Edge Cases

def test_special_characters_in_fields(self, headers):
    """Test handling of special characters"""
    special_chars = "Test <script>alert('xss')</script> & \"quotes\""
    payload = {
        "string_field": special_chars,
    }

    response = requests.post(...)
    assert response.status_code == 200
    assert response.json()["data"]["string_field"] == special_chars

DataStructure Analysis

When analyzing DataStructure.php, extract these key elements:

Parameter Structure

public static function getParameterDefinitions(): array
{
    return [
        'request' => [
            'POST' => [
                'parameter_name' => [
                    'type' => 'string',              // Extract type
                    'description' => 'Description',  // Extract description
                    'example' => 'value',            // Use for test data
                    'required' => true,              // Required vs optional
                    'default' => 'default_value',    // Default value
                    'enum' => ['val1', 'val2'],      // Valid enum values
                    'pattern' => '^[a-z]+$',         // Regex pattern
                    'minLength' => 1,                // Min length
                    'maxLength' => 100,              // Max length
                ],
            ],
        ],
    ];
}

Use This Data To

  1. Generate valid payloads - Use example and default values
  2. Test required fields - Create tests omitting each required field
  3. Test data types - Create tests with wrong types
  4. Test enums - Create tests for each enum value and invalid values
  5. Test patterns - Create tests for valid/invalid patterns
  6. Test boundaries - Create tests for min/max values

Test Documentation Template

Add to the top of each test file:

"""
Tests for {ResourceName} API endpoint

API Endpoint: /pbxcore/api/v3/{resource-path}
DataStructure: src/PBXCoreREST/Lib/{ResourceName}/DataStructure.php

Test Coverage:
- CRUD operations (Create, Read, Update, Delete)
- Required vs optional parameters
- Data type validations
- Enum value validations
- Pattern validations (regex)
- Boundary conditions (min/max values)
- Special characters and edge cases
- Schema validation (when SCHEMA_VALIDATION_STRICT=1)

Requirements:
- pytest
- requests
- Docker container running with MikoPBX

Run tests:
    pytest tests/api/test_{resource_name}.py -v

Run with schema validation:
    # Ensure SCHEMA_VALIDATION_STRICT=1 is set in container
    pytest tests/api/test_{resource_name}.py -v
"""

Output Format

Always generate:

  1. ✅ Complete pytest file - Runnable without modifications
  2. ✅ Documentation block - Clear description at the top
  3. ✅ All test classes - CRUD, schema validation, edge cases
  4. ✅ Proper fixtures - Authentication and headers
  5. ✅ Clear assertions - With descriptive error messages
  6. ✅ Comments - Explaining complex validations

Running Tests

Basic Execution

# Run all API tests
pytest tests/api/ -v

# Run specific endpoint tests
pytest tests/api/test_extensions_api.py -v

# Run specific test class
pytest tests/api/test_extensions_api.py::TestCreateExtensions -v

# Run specific test
pytest tests/api/test_extensions_api.py::TestCreateExtensions::test_create_with_valid_data -v

With Schema Validation

# Enable schema validation in container
docker exec mikopbx_container sh -c 'export SCHEMA_VALIDATION_STRICT=1'

# Run tests
pytest tests/api/test_extensions_api.py -v

Test Markers

# Run only CRUD tests
pytest tests/api/ -m crud -v

# Skip slow tests
pytest tests/api/ -m "not slow" -v

# Run smoke tests
pytest tests/api/ -m smoke -v

Important Notes

MikoPBX-Specific Considerations

  • Authentication: All tests need Bearer token from /auth/login
  • HTTPS: Use verify=False for self-signed certificates
  • Base URL: Default is https://mikopbx-php83.localhost:8445
  • Schema validation: Only active when SCHEMA_VALIDATION_STRICT=1 in container
  • Container restart: Changes to PHP code require container restart
  • Test isolation: Each test should be independent and idempotent

Best Practices

  1. ✅ Analyze DataStructure first - Don't guess parameter structures
  2. ✅ Include schema validation tests - Only work with SCHEMA_VALIDATION_STRICT=1
  3. ✅ Test success and failure cases - Negative tests are critical
  4. ✅ Use fixtures for auth - Avoid code duplication
  5. ✅ Clean up after tests - Delete created resources in teardown
  6. ✅ Document expected behavior - Each test should state what it validates
  7. ✅ Use descriptive test names - Clear indication of what's being tested
  8. ✅ One assertion per test - Or group related assertions

Additional Resources

Templates

Complete test templates for copy-paste usage:

Reference Documentation

Quick Reference

Test a new endpoint in 5 steps:

  1. Find DataStructure.php
  2. Copy test-template.py
  3. Replace {ResourceName} and {resource-path}
  4. Fill in payloads based on DataStructure
  5. Run pytest tests/api/test_{resource}_api.py -v

Need specific patterns?

Example Invocation

User: "Generate pytest tests for the Extensions API endpoint"

Your response should:

  1. Find /src/PBXCoreREST/Lib/Extensions/DataStructure.php
  2. Read and analyze parameter definitions
  3. Use test-template.py as base
  4. Generate comprehensive test file with:

- Valid test data from DataStructure - All CRUD operations - Edge cases for special characters, boundaries - Schema validation tests

  1. Save to tests/api/test_extensions_api.py
  2. Provide run instructions

Troubleshooting

Common Issues

Issue: Test fails with "Unauthorized" Solution: Check that auth_token fixture is working and token is valid

Issue: Schema validation tests don't run Solution: Ensure SCHEMA_VALIDATION_STRICT=1 is set in container

Issue: Tests are flaky Solution: Ensure test isolation - each test should create its own resources

Issue: Container not accessible Solution: Check container is running: docker ps | grep mikopbx

Issue: SSL certificate errors Solution: Ensure verify=False is set in requests

Debug Commands

# Check container is running
docker ps | grep mikopbx

# Check environment variable
docker exec mikopbx_container env | grep SCHEMA_VALIDATION_STRICT

# View API logs
docker exec mikopbx_container tail -f /storage/usbdisk1/mikopbx/log/php/error.log

# Test API manually
curl -k https://mikopbx-php83.localhost:8445/pbxcore/api/v3/system/ping

平台分布

Claude Code

27.11%
按下载量换算22

Codex

22.8%
按下载量换算19

Antigravity

16.4%
按下载量换算13

windsurf

11.28%
按下载量换算9

Gemini CLI

7.19%
按下载量换算6

OpenCode

3.25%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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