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Api Testing

Community
secondsky
api-testing

HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.

Overview

Publishersecondsky
Repositoryclaude-skills
Skill nameapi-testing
Stars
219
Forks
31
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by secondsky on GitHub. Read the source before you install it.

Installation

Install the Api Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/secondsky/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/plugins/api-testing/skills/api-testing .claude/skills/api-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Testing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Api Testing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Api Testing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

API Testing

Expert knowledge for testing HTTP APIs with Supertest (TypeScript/JavaScript) and httpx/pytest (Python).

TypeScript/JavaScript (Supertest)

Installation

bash
# Using Bun
bun add -d supertest @types/supertest

# or: npm install -D supertest @types/supertest

Basic Setup

typescript
import { describe, it, expect } from 'vitest'
import request from 'supertest'
import { app } from './app'

describe('API Tests', () => {
  it('returns health status', async () => {
    const response = await request(app)
      .get('/api/health')
      .expect(200)

    expect(response.body).toEqual({ status: 'ok' })
  })

  it('creates a user', async () => {
    const response = await request(app)
      .post('/api/users')
      .send({ name: 'John Doe', email: 'john@example.com' })
      .expect(201)

    expect(response.body).toMatchObject({
      id: expect.any(Number),
      name: 'John Doe',
    })
  })

  it('validates required fields', async () => {
    await request(app)
      .post('/api/users')
      .send({ name: 'John Doe' })
      .expect(400)
  })
})

Request Methods

typescript
// GET
await request(app).get('/api/users').expect(200)

// POST with body
await request(app)
  .post('/api/users')
  .send({ name: 'John' })
  .expect(201)

// PUT
await request(app)
  .put('/api/users/1')
  .send({ name: 'Jane' })
  .expect(200)

// DELETE
await request(app).delete('/api/users/1').expect(204)

Headers and Query Parameters

typescript
// Set headers
await request(app)
  .get('/api/protected')
  .set('Authorization', 'Bearer token123')
  .expect(200)

// Query parameters
await request(app)
  .get('/api/users')
  .query({ page: 1, limit: 10 })
  .expect(200)

Authentication Testing

typescript
describe('Authentication', () => {
  let authToken: string

  beforeAll(async () => {
    const response = await request(app)
      .post('/api/auth/login')
      .send({ email: 'user@example.com', password: 'password123' })
      .expect(200)

    authToken = response.body.token
  })

  it('accesses protected endpoint', async () => {
    await request(app)
      .get('/api/protected')
      .set('Authorization', `Bearer ${authToken}`)
      .expect(200)
  })

  it('rejects without token', async () => {
    await request(app).get('/api/protected').expect(401)
  })
})

Error Handling

typescript
it('handles validation errors', async () => {
  const response = await request(app)
    .post('/api/users')
    .send({ email: 'invalid-email' })
    .expect(400)

  expect(response.body).toMatchObject({
    error: 'Validation failed',
    details: expect.any(Array),
  })
})

it('handles not found', async () => {
  await request(app).get('/api/users/999999').expect(404)
})

Python (httpx + pytest)

Installation

bash
uv add --dev httpx pytest-asyncio

Basic Setup

python
import pytest
from fastapi.testclient import TestClient
from main import app

client = TestClient(app)

def test_health_check():
    response = client.get("/api/health")
    assert response.status_code == 200
    assert response.json() == {"status": "ok"}

def test_create_user():
    response = client.post(
        "/api/users",
        json={"name": "John Doe", "email": "john@example.com"}
    )
    assert response.status_code == 201
    data = response.json()
    assert data["name"] == "John Doe"
    assert "id" in data

def test_not_found():
    response = client.get("/api/users/999")
    assert response.status_code == 404

Fixtures

python
@pytest.fixture
def auth_token(client):
    response = client.post(
        "/api/auth/login",
        json={"email": "user@example.com", "password": "password123"}
    )
    return response.json()["token"]

def test_protected_endpoint(client, auth_token):
    response = client.get(
        "/api/protected",
        headers={"Authorization": f"Bearer {auth_token}"}
    )
    assert response.status_code == 200

File Upload

python
def test_file_upload(client, tmp_path):
    test_file = tmp_path / "test.txt"
    test_file.write_text("test content")

    with open(test_file, "rb") as f:
        response = client.post(
            "/api/upload",
            files={"file": ("test.txt", f, "text/plain")}
        )

    assert response.status_code == 200

GraphQL Testing

typescript
it('queries GraphQL endpoint', async () => {
  const query = `
    query GetUser($id: ID!) {
      user(id: $id) { id name email }
    }
  `

  const response = await request(app)
    .post('/graphql')
    .send({ query, variables: { id: '1' } })
    .expect(200)

  expect(response.body.data.user).toMatchObject({
    id: '1',
    name: expect.any(String),
  })
})

Performance Testing

typescript
it('responds within acceptable time', async () => {
  const start = Date.now()
  await request(app).get('/api/users').expect(200)
  const duration = Date.now() - start
  expect(duration).toBeLessThan(100) // 100ms threshold
})

Best Practices

  • Group related endpoints in describe blocks
  • Reset database between tests
  • Validate status codes first
  • Check response structure
  • Test error message format
  • Mock external services
  • Test both happy path and error cases

See Also

  • vitest-testing - Unit testing framework
  • playwright-testing - E2E API testing
  • test-quality-analysis - Test quality patterns

Frequently asked questions

What does the Api Testing AI skill do?

HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.

Why use Api Testing on TypingMind?

Because you install it once and use it with any model. Api Testing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Api Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/secondsky/claude-skills/tree/main/plugins/api-testing/skills/api-testing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Api Testing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Api Testing?

As many as you like. As long as a model supports skills, you can use Api Testing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Api Testing AI skill free?

Yes. It is published on GitHub by secondsky under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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