api-design-principles▌
wshobson/agents · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
REST and GraphQL API design principles for building scalable, developer-friendly APIs.
- ›Covers resource-oriented REST patterns including HTTP method semantics, URL design, pagination, filtering, and error handling with consistent status codes
- ›Includes GraphQL schema-first development with type definitions, resolver patterns, Relay-style pagination, and DataLoader implementation for N+1 prevention
- ›Provides versioning strategies (URL, header, query parameter) and HATEOAS patterns for hy
API Design Principles
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers and stand the test of time.
When to Use This Skill
- Designing new REST or GraphQL APIs
- Refactoring existing APIs for better usability
- Establishing API design standards for your team
- Reviewing API specifications before implementation
- Migrating between API paradigms (REST to GraphQL, etc.)
- Creating developer-friendly API documentation
- Optimizing APIs for specific use cases (mobile, third-party integrations)
Core Concepts
1. RESTful Design Principles
Resource-Oriented Architecture
- Resources are nouns (users, orders, products), not verbs
- Use HTTP methods for actions (GET, POST, PUT, PATCH, DELETE)
- URLs represent resource hierarchies
- Consistent naming conventions
HTTP Methods Semantics:
GET: Retrieve resources (idempotent, safe)POST: Create new resourcesPUT: Replace entire resource (idempotent)PATCH: Partial resource updatesDELETE: Remove resources (idempotent)
2. GraphQL Design Principles
Schema-First Development
- Types define your domain model
- Queries for reading data
- Mutations for modifying data
- Subscriptions for real-time updates
Query Structure:
- Clients request exactly what they need
- Single endpoint, multiple operations
- Strongly typed schema
- Introspection built-in
3. API Versioning Strategies
URL Versioning:
/api/v1/users
/api/v2/users
Header Versioning:
Accept: application/vnd.api+json; version=1
Query Parameter Versioning:
/api/users?version=1
REST API Design Patterns
Pattern 1: Resource Collection Design
# Good: Resource-oriented endpoints
GET /api/users # List users (with pagination)
POST /api/users # Create user
GET /api/users/{id} # Get specific user
PUT /api/users/{id} # Replace user
PATCH /api/users/{id} # Update user fields
DELETE /api/users/{id} # Delete user
# Nested resources
GET /api/users/{id}/orders # Get user's orders
POST /api/users/{id}/orders # Create order for user
# Bad: Action-oriented endpoints (avoid)
POST /api/createUser
POST /api/getUserById
POST /api/deleteUser
Pattern 2: Pagination and Filtering
from typing import List, Optional
from pydantic import BaseModel, Field
class PaginationParams(BaseModel):
page: int = Field(1, ge=1, description="Page number")
page_size: int = Field(20, ge=1, le=100, description="Items per page")
class FilterParams(BaseModel):
status: Optional[str] = None
created_after: Optional[str] = None
search: Optional[str] = None
class PaginatedResponse(BaseModel):
items: List[dict]
total: int
page: int
page_size: int
pages: int
@property
def has_next(self) -> bool:
return self.page < self.pages
@property
def has_prev(self) -> bool:
return self.page > 1
# FastAPI endpoint example
from fastapi import FastAPI, Query, Depends
app = FastAPI()
@app.get("/api/users", response_model=PaginatedResponse)
async def list_users(
page: int = Query(1, ge=1),
page_size: int = Query(20, ge=1, le=100),
status: Optional[str] = Query(None),
search: Optional[str] = Query(None)
):
# Apply filters
query = build_query(status=status, search=search)
# Count total
total = await count_users(query)
# Fetch page
offset = (page - 1) * page_size
users = await fetch_users(query, limit=page_size, offset=offset)
return PaginatedResponse(
items=users,
total=total,
page=page,
page_size=page_size,
pages=(total + page_size - 1) // page_size
)
Pattern 3: Error Handling and Status Codes
from fastapi import HTTPException, status
from pydantic import BaseModel
class ErrorResponse(BaseModel):
error: str
message: str
details: Optional[dict] = None
timestamp: str
path: str
class ValidationErrorDetail(BaseModel):
field: str
message: str
value: Any
# Consistent error responses
STATUS_CODES = {
"success": 200,
"created": 201,
"no_content": 204,
"bad_request": 400,
"unauthorized": 401,
"forbidden": 403,
"not_found": 404,
"conflict": 409,
"unprocessable": 422,
"internal_error": 500
}
def raise_not_found(resource: str, id: str):
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail={
"error": "NotFound",
"message": f"{resource} not found",
"details": {"id": id}
}
)
def raise_validation_error(errors: List[ValidationErrorDetail]):
raise HTTPExceptionHow to use api-design-principles 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-design-principles
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches api-design-principles from GitHub repository wshobson/agents 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-design-principles. Access the skill through slash commands (e.g., /api-design-principles) 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★★★★★65 reviews- ★★★★★Mia Thomas· Dec 20, 2024
api-design-principles reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Shikha Mishra· Dec 16, 2024
Solid pick for teams standardizing on skills: api-design-principles is focused, and the summary matches what you get after install.
- ★★★★★Benjamin Shah· Dec 16, 2024
api-design-principles reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Yusuf Singh· Dec 4, 2024
Registry listing for api-design-principles matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Zara Ghosh· Nov 23, 2024
Useful defaults in api-design-principles — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Benjamin Verma· Nov 11, 2024
I recommend api-design-principles for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yash Thakker· Nov 7, 2024
We added api-design-principles from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Anaya Reddy· Nov 7, 2024
I recommend api-design-principles for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Dhruvi Jain· Oct 26, 2024
api-design-principles fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Kofi Sharma· Oct 26, 2024
Useful defaults in api-design-principles — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
showing 1-10 of 65