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api-design-principles

APIRESTGraphQLAPI designweb developmentbackendarchitecturedeveloper experience
36.8k📄 MIT🕒 2026-06-16Source ↗

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npx skills add wshobson/agents

Works across Claude Code, Cursor, Codex, Copilot & Antigravity

Effective API design creates interfaces that remain predictable as systems grow. This skill focuses on the structural patterns required to build standard RESTful endpoints and flexible GraphQL schemas. By emphasizing resource-oriented logic for REST and type-safe schema definitions for GraphQL, developers can minimize integration friction. The architectural focus centers on consistent naming conventions, appropriate HTTP status usage, and clean query patterns. It addresses the practicalities of evolving interfaces through versioning and ensures that data retrieval remains efficient via standardized pagination and filtering. By enforcing these conventions, developers provide clear contracts for consumers, allowing client-side teams to integrate services with minimal ambiguity. This approach replaces ad-hoc endpoint creation with a repeatable, predictable methodology that favors long-term maintainability over quick, opaque implementations.

When to Use This Skill

  • Standardizing endpoint naming conventions across a microservices suite
  • Transitioning from RPC-style action endpoints to resource-based REST paths
  • Writing OpenAPI or GraphQL schema definitions for new service contracts
  • Refactoring API error responses to provide structured, machine-readable details

How to Invoke This Skill

Example prompts that trigger this skill in Claude Code, Cursor, or Antigravity:

  • How should I structure my API endpoints for this service?
  • Convert these action-based routes into RESTful resources
  • Help me design a GraphQL schema for user profiles and their orders
  • What are the best practices for versioning a public REST API?
  • Define a standard pagination response model for my FastAPI backend

Pro Tips

  • 💡Always design APIs with the consumer in mind; consistent naming, clear error messages, and comprehensive documentation are paramount.
  • 💡For REST, strictly adhere to HTTP method semantics and resource-oriented architecture to leverage the web's built-in capabilities for idempotency and caching.
  • 💡When using GraphQL, prioritize a well-defined schema as your contract, and consider advanced features like subscriptions and directives for real-time and flexible data access.

What this skill does

  • Mapping domain models to resource-oriented URL structures
  • Implementing standardized HTTP status codes and error object schemas
  • Constructing type-safe GraphQL schemas for precise data fetching
  • Defining request parameter objects for predictable pagination and filtering
  • Establishing versioning strategies for backward-compatible API evolution

When not to use it

  • Internal CLI tools that do not require network-accessible interfaces
  • High-frequency binary protocols like gRPC that prioritize speed over HTTP semantic alignment
  • Rapid prototyping where contract stability is not yet a priority

Example workflow

  1. Identify core domain entities to serve as top-level resources
  2. Define CRUD routes for each entity using standard HTTP methods
  3. Implement request validation models to handle query parameters and pagination
  4. Standardize the base error response structure to maintain consistency across all endpoints
  5. Review the interface against RESTful principles for predictability
  6. Draft versioning headers or URL paths to support future updates

Prerequisites

  • Basic knowledge of HTTP protocols
  • Familiarity with serialization formats like JSON
  • Understanding of core backend data modeling

Pitfalls & limitations

  • !Overloading endpoints with too many optional query parameters
  • !Ignoring the idempotency requirements of PUT versus PATCH methods
  • !Exposing internal database models directly instead of using Data Transfer Objects (DTOs)

FAQ

Should I use REST or GraphQL for my project?
Choose REST for predictable, resource-oriented access where caching and standard HTTP semantics are priority. Use GraphQL when clients need to fetch complex, nested data structures in a single request to reduce over-fetching.
Is it okay to use verbs in my URLs?
No, resource-oriented design dictates that URLs should represent nouns. Use HTTP methods like GET or POST to describe the action taken on those nouns.
Which versioning strategy is best?
URL versioning is the most explicit and easiest to debug, while header versioning keeps URLs clean. Choose one and remain consistent throughout your entire service catalog.

How it compares

Generic prompts often generate unvalidated, inconsistent route structures; this skill enforces standardized architecture patterns that align with industry-wide developer expectations.

Source & trust

37k stars📄 MIT🕒 Updated 2026-06-16
📄 Full skill instructions — original source: wshobson/agents
# 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 resources
- PUT: Replace entire resource (idempotent)
- PATCH: Partial resource updates
- DELETE: 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 HTTPException(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
detail={
"error": "ValidationError",
"message": "Request validation failed",
"details": {"errors": [e.dict() for e in errors]}
}
)

# Example usage
@app.get("/api/users/{user_id}")
async def get_user(user_id: str):
user = await fetch_user(user_id)
if not user:
raise_not_found("User", user_id)
return user


### Pattern 4: HATEOAS (Hypermedia as the Engine of Application State)

class UserResponse(BaseModel):
id: str
name: str
email: str
_links: dict

@classmethod
def from_user(cls, user: User, base_url: str):
return cls(
id=user.id,
name=user.name,
email=user.email,
_links={
"self": {"href": f"{base_url}/api/users/{user.id}"},
"orders": {"href": f"{base_url}/api/users/{user.id}/orders"},
"update": {
"href": f"{base_url}/api/users/{user.id}",
"method": "PATCH"
},
"delete": {
"href": f"{base_url}/api/users/{user.id}",
"method": "DELETE"
}
}
)


## GraphQL Design Patterns

### Pattern 1: Schema Design

# schema.graphql

# Clear type definitions
type User {
id: ID!
email: String!
name: String!
createdAt: DateTime!

# Relationships
orders(first: Int = 20, after: String, status: OrderStatus): OrderConnection!

profile: UserProfile
}

type Order {
id: ID!
status: OrderStatus!
total: Money!
items: [OrderItem!]!
createdAt: DateTime!

# Back-reference
user: User!
}

# Pagination pattern (Relay-style)
type OrderConnection {
edges: [OrderEdge!]!
pageInfo: PageInfo!
totalCount: Int!
}

type OrderEdge {
node: Order!
cursor: String!
}

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

# Enums for type safety
enum OrderStatus {
PENDING
CONFIRMED
SHIPPED
DELIVERED
CANCELLED
}

# Custom scalars
scalar DateTime
scalar Money

# Query root
type Query {
user(id: ID!): User
users(first: Int = 20, after: String, search: String): UserConnection!

order(id: ID!): Order
}

# Mutation root
type Mutation {
createUser(input: CreateUserInput!): CreateUserPayload!
updateUser(input: UpdateUserInput!): UpdateUserPayload!
deleteUser(id: ID!): DeleteUserPayload!

createOrder(input: CreateOrderInput!): CreateOrderPayload!
}

# Input types for mutations
input CreateUserInput {
email: String!
name: String!
password: String!
}

# Payload types for mutations
type CreateUserPayload {
user: User
errors: [Error!]
}

type Error {
field: String
message: String!
}


### Pattern 2: Resolver Design

from typing import Optional, List
from ariadne import QueryType, MutationType, ObjectType
from dataclasses import dataclass

query = QueryType()
mutation = MutationType()
user_type = ObjectType("User")

@query.field("user")
async def resolve_user(obj, info, id: str) -> Optional[dict]:
"""Resolve single user by ID."""
return await fetch_user_by_id(id)

@query.field("users")
async def resolve_users(
obj,
info,
first: int = 20,
after: Optional[str] = None,
search: Optional[str] = None
) -> dict:
"""Resolve paginated user list."""
# Decode cursor
offset = decode_cursor(after) if after else 0

# Fetch users
users = await fetch_users(
limit=first + 1, # Fetch one extra to check hasNextPage
offset=offset,
search=search
)

# Pagination
has_next = len(users) > first
if has_next:
users = users[:first]

edges = [
{
"node": user,
"cursor": encode_cursor(offset + i)
}
for i, user in enumerate(users)
]

return {
"edges": edges,
"pageInfo": {
"hasNextPage": has_next,
"hasPreviousPage": offset > 0,
"startCursor": edges[0]["cursor"] if edges else None,
"endCursor": edges[-1]["cursor"] if edges else None
},
"totalCount": await count_users(search=search)
}

@user_type.field("orders")
async def resolve_user_orders(user: dict, info, first: int = 20) -> dict:
"""Resolve user's orders (N+1 prevention with DataLoader)."""
# Use DataLoader to batch requests
loader = info.context["loaders"]["orders_by_user"]
orders = await loader.load(user["id"])

return paginate_orders(orders, first)

@mutation.field("createUser")
async def resolve_create_user(obj, info, input: dict) -> dict:
"""Create new user."""
try:
# Validate input
validate_user_input(input)

# Create user
user = await create_user(
email=input["email"],
name=input["name"],
password=hash_password(input["password"])
)

return {
"user": user,
"errors": []
}
except ValidationError as e:
return {
"user": None,
"errors": [{"field": e.field, "message": e.message}]
}


### Pattern 3: DataLoader (N+1 Problem Prevention)

from aiodataloader import DataLoader
from typing import List, Optional

class UserLoader(DataLoader):
"""Batch load users by ID."""

async def batch_load_fn(self, user_ids: List[str]) -> List[Optional[dict]]:
"""Load multiple users in single query."""
users = await fetch_users_by_ids(user_ids)

# Map results back to input order
user_map = {user["id"]: user for user in users}
return [user_map.get(user_id) for user_id in user_ids]

class OrdersByUserLoader(DataLoader):
"""Batch load orders by user ID."""

async def batch_load_fn(self, user_ids: List[str]) -> List[List[dict]]:
"""Load orders for multiple users in single query."""
orders = await fetch_orders_by_user_ids(user_ids)

# Group orders by user_id
orders_by_user = {}
for order in orders:
user_id = order["user_id"]
if user_id not in orders_by_user:
orders_by_user[user_id] = []
orders_by_user[user_id].append(order)

# Return in input order
return [orders_by_user.get(user_id, []) for user_id in user_ids]

# Context setup
def create_context():
return {
"loaders": {
"user": UserLoader(),
"orders_by_user": OrdersByUserLoader()
}
}


## Best Practices

### REST APIs

1. **Consistent Naming**: Use plural nouns for collections (/users, not /user)
2. **Stateless**: Each request contains all necessary information
3. **Use HTTP Status Codes Correctly**: 2xx success, 4xx client errors, 5xx server errors
4. **Version Your API**: Plan for breaking changes from day one
5. **Pagination**: Always paginate large collections
6. **Rate Limiting**: Protect your API with rate limits
7. **Documentation**: Use OpenAPI/Swagger for interactive docs

### GraphQL APIs

1. **Schema First**: Design schema before writing resolvers
2. **Avoid N+1**: Use DataLoaders for efficient data fetching
3. **Input Validation**: Validate at schema and resolver levels
4. **Error Handling**: Return structured errors in mutation payloads
5. **Pagination**: Use cursor-based pagination (Relay spec)
6. **Deprecation**: Use @deprecated directive for gradual migration
7. **Monitoring**: Track query complexity and execution time

## Common Pitfalls

- **Over-fetching/Under-fetching (REST)**: Fixed in GraphQL but requires DataLoaders
- **Breaking Changes**: Version APIs or use deprecation strategies
- **Inconsistent Error Formats**: Standardize error responses
- **Missing Rate Limits**: APIs without limits are vulnerable to abuse
- **Poor Documentation**: Undocumented APIs frustrate developers
- **Ignoring HTTP Semantics**: POST for idempotent operations breaks expectations
- **Tight Coupling**: API structure shouldn't mirror database schema

## Resources

- **references/rest-best-practices.md**: Comprehensive REST API design guide
- **references/graphql-schema-design.md**: GraphQL schema patterns and anti-patterns
- **references/api-versioning-strategies.md**: Versioning approaches and migration paths
- **assets/rest-api-template.py**: FastAPI REST API template
- **assets/graphql-schema-template.graphql**: Complete GraphQL schema example
- **assets/api-design-checklist.md**: Pre-implementation review checklist
- **scripts/openapi-generator.py**: Generate OpenAPI specs from code

How to Use This Skill Unit

Option A: Project-Specific (Recommended)

  1. Click "Download" above
  2. In your project, create the directory: .agent/skills/api-design-principles/
  3. Save the file as SKILL.md
  4. The agent will automatically discover the skill based on its description.

Option B: Global Installation (All Agents)

Save the file to these locations to make it available across all projects:

  • Claude Code: ~/.claude/skills/wshobson/agents/api-design-principles/SKILL.md
  • Cursor: ~/.cursor/skills/wshobson/agents/api-design-principles/SKILL.md
  • Antigravity: ~/.gemini/antigravity/skills/wshobson/agents/api-design-principles/SKILL.md

🚀 Install with CLI:
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For Cursor or Windsurf, individual skills are best used in the "Rules for AI" section. This specific unit helps the agent avoid architecture & design patterns issues, leading to cleaner, more efficient code.

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Source & attribution

This skill is categorized under Architecture & Design Patterns and is published by W. Shobson, maintained in wshobson/agents.

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