api-designer

charon-fan/agent-playbook · updated Apr 8, 2026

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$npx skills add https://github.com/charon-fan/agent-playbook --skill api-designer
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summary

Expert in designing REST and GraphQL APIs that are robust, scalable, and maintainable.

skill.md

API Designer

Expert in designing REST and GraphQL APIs that are robust, scalable, and maintainable.

When This Skill Activates

Activates when you:

  • Design a new API
  • Review API design
  • Improve existing API
  • Create API specifications

REST API Design Principles

1. Resource-Oriented Design

Good:

GET    /users          # List users
POST   /users          # Create user
GET    /users/{id}     # Get specific user
PATCH  /users/{id}     # Update user
DELETE /users/{id}     # Delete user

Avoid:

POST   /getUsers       # Should be GET
POST   /users/create  # Redundant
GET    /users/get/{id} # Redundant

2. HTTP Methods

Method Safe Idempotent Purpose
GET Read resource
POST Create resource
PUT Replace resource
PATCH Update resource
DELETE Delete resource

3. Status Codes

Code Meaning Usage
200 OK Successful GET, PATCH, DELETE
201 Created Successful POST
204 No Content Successful DELETE with no body
400 Bad Request Invalid input
401 Unauthorized Missing or invalid auth
403 Forbidden Authenticated but not authorized
404 Not Found Resource doesn't exist
409 Conflict Resource already exists
422 Unprocessable Valid syntax but semantic errors
429 Too Many Requests Rate limit exceeded
500 Internal Server Error Server error

4. Naming Conventions

  • URLs: kebab-case (/user-preferences)
  • JSON: camelCase ({"userId": "123"})
  • Query params: snake_case or camelCase (?page_size=10)

5. Pagination

GET /users?page=1&page_size=20

Response:
{
  "data": [...],
  "pagination": {
    "page": 1,
    "page_size": 20,
    "total": 100,
    "total_pages": 5
  }
}

6. Filtering and Sorting

GET /users?status=active&sort=-created_at,name

# -created_at = descending
# name = ascending

GraphQL API Design

Schema Design

type Query {
  user(id: ID!): User
  users(limit: Int, offset: Int): UserConnection!
}

type Mutation {
  createUser(input: CreateUserInput!): CreateUserPayload!
  updateUser(id: ID!, input: UpdateUserInput!): UpdateUserPayload!
}

type User {
  id: ID!
  email: String!
  profile: Profile
  posts(first: Int, after: String): PostConnection!
}

type UserConnection {
  edges: [UserEdge!]!
  pageInfo: PageInfo!
}

type UserEdge {
  node: User!
  cursor: String!
}

type PageInfo {
  hasNextPage: Boolean!
  hasPreviousPage: Boolean!
  startCursor: String
  endCursor: String
}

Best Practices

  • Nullability: Default to non-null, nullable only when appropriate
  • Connections: Use cursor-based pagination for lists
  • Payloads: Use mutation payloads for consistent error handling
  • Descriptions: Document all types and fields

API Versioning

Approaches

URL Versioning (Recommended):

/api/v1/users
/api/v2/users

Header Versioning:

GET /users
Accept: application/vnd.myapi.v2+json

Versioning Guidelines

  • Start with v1
  • Maintain backwards compatibility when possible
  • Deprecate old versions with notice
  • Document breaking changes

Authentication & Authorization

Authentication Methods

  1. JWT Bearer Token
Authorization: Bearer <token>
  1. API Key
X-API-Key: <key>
  1. OAuth 2.0
Authorization: Bearer <access_token>

Authorization

  • Use roles/permissions
  • Document required permissions per endpoint
  • Return 403 for authorization failures

Rate Limiting

HTTP/1.1 200 OK
X-RateLimit-Limit: 1000
X-RateLimit-Remaining: 999
X-RateLimit-Reset: 1631234567

Recommended limits:

  • Public APIs: 100-1000 requests/hour
  • Authenticated APIs: 1000-10000 requests/hour
  • Webhooks: 10-100 requests/minute

Documentation Requirements

  • All endpoints documented
  • Request/response examples
  • Authentication requirements
  • Error response formats
  • Rate limits
  • SDK examples (if available)

Scripts

Generate API scaffold:

python scripts/generate_api.py <resource-name>

Validate API design:

python scripts/validate_api.py openapi.yaml

References

how to use api-designer

How to use api-designer on Cursor

AI-first code editor with Composer

1

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-designer
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/charon-fan/agent-playbook --skill api-designer

The skills CLI fetches api-designer from GitHub repository charon-fan/agent-playbook and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/api-designer

Reload or restart Cursor to activate api-designer. Access the skill through slash commands (e.g., /api-designer) 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

GET_STARTED →

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. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.761 reviews
  • Aanya Zhang· Dec 28, 2024

    api-designer has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Min Thomas· Dec 28, 2024

    api-designer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ganesh Mohane· Dec 24, 2024

    We added api-designer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ren Bansal· Dec 24, 2024

    We added api-designer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Sofia Shah· Dec 20, 2024

    api-designer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ren Anderson· Dec 16, 2024

    Useful defaults in api-designer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Noor Harris· Dec 4, 2024

    Useful defaults in api-designer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Sofia Sharma· Nov 23, 2024

    Registry listing for api-designer matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kwame Garcia· Nov 19, 2024

    Solid pick for teams standardizing on skills: api-designer is focused, and the summary matches what you get after install.

  • Noor Singh· Nov 19, 2024

    I recommend api-designer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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