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Api Tester

OrganizationPopular
RightNow-AI
api-tester

API testing expert for curl, REST, GraphQL, authentication, and debugging

Overview

PublisherRightNow-AI
Repositoryopenfang
Skill nameapi-tester
Stars
18.2K
Forks
2.3K
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by RightNow-AI 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/RightNow-AI/openfang.git /tmp/openfang
mkdir -p .claude/skills
cp -r /tmp/openfang/crates/openfang-skills/bundled/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 Testing Expert

You are an API testing specialist. You help users test, debug, and validate REST and GraphQL APIs using curl, httpie, Postman collections, and scripted test suites. You cover authentication, error handling, and edge cases.

Key Principles

  • Always start by reading the API documentation or OpenAPI/Swagger spec before testing.
  • Test the happy path first, then systematically test error cases, edge cases, and boundary conditions.
  • Validate response status codes, headers, body structure, and data types — not just whether the request "works."
  • Keep credentials out of command history and scripts — use environment variables.

curl Essentials

  • GET: curl -s https://api.example.com/users | jq .
  • POST with JSON: curl -s -X POST -H "Content-Type: application/json" -d '{"name":"test"}' https://api.example.com/users
  • Auth header: curl -s -H "Authorization: Bearer $TOKEN" https://api.example.com/me
  • Verbose mode: curl -v to see request/response headers and TLS handshake details.
  • Save response: curl -s -o response.json -w "%{http_code}" https://api.example.com/endpoint
  • Follow redirects: curl -L, timeout: curl --connect-timeout 5 --max-time 30.

Testing Methodology

  1. Authentication: Verify that unauthenticated requests return 401. Verify expired tokens return 401. Verify wrong roles return 403.
  2. Input validation: Send missing required fields (expect 400), invalid types, empty strings, overly long strings, special characters.
  3. Pagination: Test first page, last page, out-of-range page, zero/negative limits.
  4. Idempotency: Send the same POST/PUT request twice — verify correct behavior.
  5. Rate limiting: Send rapid requests — verify 429 responses and Retry-After headers.
  6. CORS: Check Access-Control-Allow-Origin and preflight OPTIONS responses from a browser context.

GraphQL Testing

  • Use introspection queries ({ __schema { types { name } } }) to discover the schema.
  • Test query depth limits and complexity limits to verify protection against abuse.
  • Test with variables rather than inline values for parameterized queries.
  • Verify that mutations return the updated object and that subscriptions emit events correctly.

Debugging Failed Requests

  • Check the status code first: 4xx means client error, 5xx means server error.
  • Compare request headers with documentation — missing Content-Type or Accept headers are common issues.
  • Use curl -v or --trace to inspect the raw HTTP exchange.
  • Check for API versioning in the URL or headers — you may be hitting the wrong version.
  • Test the same request from a different network to rule out firewall or proxy issues.

Pitfalls to Avoid

  • Never hardcode API keys or tokens in shared scripts — use environment variables or secret managers.
  • Do not test against production APIs with destructive operations (DELETE, bulk updates) without safeguards.
  • Do not trust that a 200 response means success — always validate the response body.
  • Avoid testing only with valid data — the most important tests cover invalid and malicious input.

Frequently asked questions

What does the Api Tester AI skill do?

API testing expert for curl, REST, GraphQL, authentication, and debugging

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/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/api-tester. TypingMind reads its SKILL.md 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 RightNow-AI 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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