api-documenter▌
charon-fan/agent-playbook · updated Apr 8, 2026
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Specialist in creating comprehensive API documentation using OpenAPI/Swagger specifications.
API Documenter
Specialist in creating comprehensive API documentation using OpenAPI/Swagger specifications.
When This Skill Activates
Activates when you:
- Ask to document an API
- Create OpenAPI/Swagger specs
- Need API reference documentation
- Mention "API docs"
OpenAPI Specification Structure
openapi: 3.0.3
info:
title: API Title
version: 1.0.0
description: API description
servers:
- url: https://example.com/api/v1
paths:
/users:
get:
summary: List users
operationId: listUsers
tags:
- users
parameters: []
responses:
'200':
description: Successful response
content:
application/json:
schema:
type: array
items:
$ref: '#/components/schemas/User'
components:
schemas:
User:
type: object
properties:
id:
type: string
name:
type: string
Endpoint Documentation
For each endpoint, document:
Required Fields
- summary: Brief description
- operationId: Unique identifier
- description: Detailed explanation
- tags: For grouping
- responses: All possible responses
Recommended Fields
- parameters: All parameters with details
- requestBody: For POST/PUT/PATCH
- security: Authentication requirements
- deprecated: If applicable
Example
/users/{id}:
get:
summary: Get a user by ID
operationId: getUserById
description: Retrieves a single user by their unique identifier
tags:
- users
parameters:
- name: id
in: path
required: true
schema:
type: string
description: The user ID
responses:
'200':
description: User found
content:
application/json:
schema:
$ref: '#/components/schemas/User'
'404':
description: User not found
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
Schema Documentation
Best Practices
- Use references for shared schemas
- Add descriptions to all properties
- Specify format for strings (email, uuid, date-time)
- Add examples for complex schemas
- Mark required fields
Example
components:
schemas:
User:
type: object
required:
- id
- email
properties:
id:
type: string
format: uuid
description: Unique user identifier
example: "550e8400-e29b-41d4-a716-446655440000"
email:
type: string
format: email
description: User's email address
example: "[email protected]"
createdAt:
type: string
format: date-time
description: Account creation timestamp
Authentication Documentation
Document auth requirements:
security:
- bearerAuth: []
components:
securitySchemes:
bearerAuth:
type: http
scheme: bearer
bearerFormat: JWT
description: Use your JWT token from /auth/login
Error Responses
Standard error format:
components:
schemas:
Error:
type: object
properties:
error:
type: string
description: Error message
code:
type: string
description: Application-specific error code
details:
type: object
description: Additional error details
Common HTTP status codes:
- 200: Success
- 201: Created
- 204: No Content
- 400: Bad Request
- 401: Unauthorized
- 403: Forbidden
- 404: Not Found
- 409: Conflict
- 422: Unprocessable Entity
- 500: Internal Server Error
Scripts
Generate OpenAPI spec from code:
python scripts/generate_openapi.py
Validate OpenAPI spec:
python scripts/validate_openapi.py openapi.yaml
References
references/openapi-template.yaml- OpenAPI templatereferences/examples/- API documentation examples- OpenAPI Specification
How to use api-documenter on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add api-documenter
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches api-documenter from GitHub repository charon-fan/agent-playbook and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate api-documenter. Access the skill through slash commands (e.g., /api-documenter) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★71 reviews- ★★★★★Arya Agarwal· Dec 20, 2024
Keeps context tight: api-documenter is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Dhruvi Jain· Dec 16, 2024
api-documenter has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Nia Park· Dec 16, 2024
I recommend api-documenter for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Min Martinez· Dec 12, 2024
api-documenter is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Hana Garcia· Dec 8, 2024
api-documenter fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Hana Okafor· Dec 4, 2024
Solid pick for teams standardizing on skills: api-documenter is focused, and the summary matches what you get after install.
- ★★★★★Alexander Ndlovu· Dec 4, 2024
api-documenter has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ren Haddad· Dec 4, 2024
api-documenter reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ishan Garcia· Nov 23, 2024
api-documenter has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Arjun Farah· Nov 23, 2024
Solid pick for teams standardizing on skills: api-documenter is focused, and the summary matches what you get after install.
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