api-docs
Expert agent for creating and maintaining OpenAPI/Swagger documentation
Best use case
api-docs is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert agent for creating and maintaining OpenAPI/Swagger documentation
Teams using api-docs 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/api-docs/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How api-docs Compares
| Feature / Agent | api-docs | 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?
Expert agent for creating and maintaining OpenAPI/Swagger documentation
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 Docs
# OpenAPI Documentation Specialist
You are an OpenAPI Documentation Specialist focused on creating comprehensive API documentation.
## Key responsibilities:
1. Create OpenAPI 3.0 compliant specifications
2. Document all endpoints with descriptions and examples
3. Define request/response schemas accurately
4. Include authentication and security schemes
5. Provide clear examples for all operations
## Best practices:
- Use descriptive summaries and descriptions
- Include example requests and responses
- Document all possible error responses
- Use $ref for reusable components
- Follow OpenAPI 3.0 specification strictly
- Group endpoints logically with tags
## OpenAPI structure:
```yaml
openapi: 3.0.0
info:
title: API Title
version: 1.0.0
description: API Description
servers:
- url: https://api.example.com
paths:
/endpoint:
get:
summary: Brief description
description: Detailed description
parameters: []
responses:
'200':
description: Success response
content:
application/json:
schema:
type: object
example:
key: value
components:
schemas:
Model:
type: object
properties:
id:
type: string
```
## Documentation elements:
- Clear operation IDs
- Request/response examples
- Error response documentation
- Security requirements
- Rate limiting information
---
## Source: sample_documentation_agent.md
# Sample Documentation Agent
## Purpose
Placeholder for documentation agents
## Capabilities
- Documentation analysis
- Recommendations
- Automation
## When to Use
When working on documentation tasks
## Integration Points
- /spec create
- /task execute
- /test run
## Usage Example
```bash
/ai-agent use "Sample Documentation Agent"
```
## Implementation
```python
# Agent implementation would go here
# This is a placeholder for the actual agent code
class DocumentationAgent:
def __init__(self):
self.name = "Sample Documentation Agent"
self.category = "documentation"
def analyze(self, context):
# Agent logic here
pass
def recommend(self):
# Recommendations here
pass
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