Api Tester logo

Api Tester

Organization
TerminalSkills
api-tester

Test REST and GraphQL API endpoints with structured assertions and reporting. Use when a user asks to test an API, hit an endpoint, check if an API works, validate a response, debug an API call, test authentication flows, or verify API contracts. Supports GET, POST, PUT, PATCH, DELETE with headers, body, auth, and response validation.

Overview

PublisherTerminalSkills
Repositoryskills
Skill nameapi-tester
Stars
155
Forks
21
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Api Tester 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/TerminalSkills/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/api-tester .claude/skills/api-tester
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Tester 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 Tester 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 Tester 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 Tester

Overview

Test API endpoints by sending HTTP requests, validating responses, and reporting results. Supports REST and GraphQL APIs with authentication, custom headers, request bodies, and structured assertions on status codes, headers, and response payloads.

Instructions

When a user asks you to test or debug an API endpoint, follow these steps:

Step 1: Gather endpoint details

Determine from the user or codebase:

  • URL: The full endpoint URL
  • Method: GET, POST, PUT, PATCH, DELETE
  • Headers: Content-Type, Authorization, custom headers
  • Body: JSON payload, form data, or query parameters
  • Auth: Bearer token, API key, basic auth
  • Expected response: Status code, response shape, specific values

Step 2: Send the request

Using curl (preferred for quick tests):

bash
# GET request
curl -s -w "\nHTTP Status: %{http_code}\nTime: %{time_total}s\n" \
  -H "Authorization: Bearer $TOKEN" \
  "https://api.example.com/users?page=1"

# POST request with JSON
curl -s -w "\nHTTP Status: %{http_code}\nTime: %{time_total}s\n" \
  -X POST \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOKEN" \
  -d '{"name": "Jane", "email": "jane@example.com"}' \
  "https://api.example.com/users"

Using Python (for complex flows):

python
import requests
import json
import time

def test_endpoint(method, url, headers=None, body=None, expected_status=200):
    start = time.time()
    response = requests.request(method, url, headers=headers, json=body, timeout=30)
    elapsed = time.time() - start

    result = {
        "status": response.status_code,
        "time_ms": round(elapsed * 1000),
        "headers": dict(response.headers),
        "body": response.json() if response.headers.get("content-type", "").startswith("application/json") else response.text,
    }

    passed = response.status_code == expected_status
    print(f"{'PASS' if passed else 'FAIL'} | {method} {url} | {response.status_code} | {result['time_ms']}ms")
    return result, passed

Step 3: Validate the response

Check these in order:

  1. Status code matches expected (200, 201, 204, 400, 401, 404, etc.)
  2. Response time is acceptable (flag if > 2 seconds)
  3. Content-Type header matches expected format
  4. Response body structure matches expected schema
  5. Specific values match assertions
python
def validate_response(result, assertions):
    failures = []
    body = result["body"]

    for field, expected in assertions.items():
        actual = body
        for key in field.split("."):
            if isinstance(actual, dict):
                actual = actual.get(key)
            elif isinstance(actual, list) and key.isdigit():
                actual = actual[int(key)]
            else:
                actual = None
                break

        if actual != expected:
            failures.append(f"  {field}: expected {expected!r}, got {actual!r}")

    return failures

Step 4: Report results

Format as a clear test report:

API Test Results
================
Endpoint: POST /api/users
Status:   201 Created (expected 201) -- PASS
Time:     142ms
Body:     Valid JSON, 3 fields

Assertions:
  [PASS] body.id is present
  [PASS] body.name == "Jane"
  [PASS] body.email == "jane@example.com"
  [FAIL] body.role expected "admin", got "user"

Result: 3/4 assertions passed

Examples

Example 1: Test a CRUD flow

User request: "Test the users API -- create, read, update, delete"

Output:

API Test Suite: Users CRUD
==========================

1. POST /api/users
   Status: 201 Created -- PASS
   Time:   156ms
   Body:   {"id": 42, "name": "Test User", "email": "test@example.com"}

2. GET /api/users/42
   Status: 200 OK -- PASS
   Time:   38ms
   Body:   {"id": 42, "name": "Test User", "email": "test@example.com"}

3. PUT /api/users/42
   Status: 200 OK -- PASS
   Time:   89ms
   Body:   {"id": 42, "name": "Updated Name", "email": "test@example.com"}

4. DELETE /api/users/42
   Status: 204 No Content -- PASS
   Time:   45ms

5. GET /api/users/42 (verify deletion)
   Status: 404 Not Found -- PASS
   Time:   22ms

Result: 5/5 PASSED

Example 2: Debug a failing request

User request: "I'm getting a 401 on POST /api/orders, can you figure out why?"

Output:

Debugging POST /api/orders
===========================

Test 1: No auth header
  Status: 401 -- Missing Authorization header (expected)

Test 2: With Bearer token
  Status: 401 -- Response: {"error": "Token expired"}
  Note: Token exp claim is 2024-01-15T00:00:00Z (expired)

Test 3: With refreshed token
  Status: 201 Created -- PASS

Root cause: Your Bearer token has expired.
Fix: Refresh the token using POST /api/auth/refresh

Guidelines

  • Never send requests to production APIs unless the user explicitly confirms. Ask first.
  • Mask sensitive values (tokens, passwords, API keys) in output. Show only the last 4 characters.
  • For sequences of dependent requests (create then read), use the response from the first request to build the second.
  • Include response time in reports. Flag responses over 2 seconds as slow.
  • When testing auth flows, test both the happy path and common failure modes (expired token, wrong credentials, missing permissions).
  • For GraphQL, use POST with the query in the JSON body and validate the data field separately from errors.
  • If an endpoint returns pagination, test the first page and mention the total count.
  • Always set a timeout (30 seconds) to avoid hanging on unresponsive endpoints.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Api Tester AI skill do?

Test REST and GraphQL API endpoints with structured assertions and reporting. Use when a user asks to test an API, hit an endpoint, check if an API works, validate a response, debug an API call, test authentication flows, or verify API contracts. Supports GET, POST, PUT, PATCH, DELETE with headers, body, auth, and response validation.

Why use Api Tester on TypingMind?

Because you install it once and use it with any model. Api Tester 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 Tester in TypingMind?

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

Which AI models can use Api Tester?

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 Tester?

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

Is the Api Tester AI skill free?

Yes. It is published on GitHub by TerminalSkills under the Apache-2.0 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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