api-tester
Test and document API endpoints - validate responses, check status, generate examples
Best use case
api-tester is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Test and document API endpoints - validate responses, check status, generate examples
Teams using api-tester should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/orthogonal-api-tester/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How api-tester Compares
| Feature / Agent | api-tester | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Test and document API endpoints - validate responses, check status, generate examples
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# API Tester - Test Any API Endpoint
Test API endpoints, validate responses, and generate documentation examples.
## Workflow
### Step 1: Test GET Endpoints
Make GET requests to test endpoints:
```bash
orth api run linkup /fetch --body '{"url": "https://api.example.com/health"}'
```
### Step 2: Test POST Endpoints
Test POST requests by fetching API docs:
```bash
orth api run scrapegraph /v1/smartscraper --body '{
"website_url": "https://api.example.com/docs",
"user_prompt": "Extract all API endpoints, methods, parameters, and example responses"
}'
```
### Step 3: Get API Documentation
Fetch and parse API docs:
```bash
orth api run scrapegraph /v1/markdownify --body '{"website_url": "https://api.example.com/docs"}'
```
### Step 4: Validate Response Schema
Check response structure:
```bash
orth api run riveter /v1/run --body '{
"url": "https://api.example.com/endpoint",
"schema": {
"id": "string",
"name": "string",
"created_at": "string"
}
}'
```
## Example Usage
```bash
# Extract API spec from docs
orth api run scrapegraph /v1/smartscraper --body '{
"website_url": "https://stripe.com/docs/api",
"user_prompt": "Extract API authentication methods and example curl commands"
}'
# Fetch API page
orth api run linkup /fetch --body '{"url": "https://api.openai.com/v1/models"}'
```
## Tips
- Test both happy paths and error cases
- Verify response schemas match documentation
- Check rate limits and authentication
- Document any discrepancies found
## Discover More
List all endpoints, or add a path for parameter details:
```bash
orth api show linkup
orth api show riveter
orth api show scrapegraph
```
Example: `orth api show olostep /v1/scrapes` for endpoint parameters.Related Skills
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