Tested demoQuality 97/100

aAAaqwq/AGI-Super-Team/skills/api-design-patterns/SKILL.md

api-design-patterns

Comprehensive API design patterns covering REST, GraphQL, gRPC, versioning, authentication, and modern API best practices

Source repository stars
89
Declared platforms
1
Static risk flags
1
Last source update
2026-08-26
Source checked
2026-08-28

Decision brief

What it does: where it fits

Design robust, scalable APIs using proven patterns for REST, GraphQL, and gRPC with proper versioning, authentication, and error handling.

Best for

    Not for

    • ❌ Over-fetching (REST): Returning entire objects when fields are unused ✅ Solution: Support field selection (?fields=id,name,email)
    • ❌ Under-fetching (REST): Requiring multiple requests for related data ✅ Solution: Support expansion (?expand=orders,profile) or use GraphQL
    Controlled single-run demoChecked 2026-08-20

    What changed when the Skill was used

    In this controlled same-task single run, enabling api-design-patterns changed the output from 2422 non-whitespace characters and 28 headings to 2838 characters and 19 headings. Matches among 8 signals extracted from the pinned source changed from 0 to 0. Both actual outputs are shown; this is a structural observation, not a quality score or a universal performance claim.

    Same test task

    Create a design direction and implementation handoff for a developer tool that compares two API responses. Prioritize the repeated user workflow and responsive behavior. The deliverable must specifically reflect this user intent: Comprehensive API design patterns covering REST, GraphQL, gRPC, versioning, authentication, and modern API best practices

    Without the Skill
    Screenshot of the actual model output for api-design-patterns without the Skill

    Baseline: 2422 non-whitespace characters, 28 headings, and 74 list items.

    With the Skill
    Screenshot of the actual model output for api-design-patterns with the Skill

    With Skill: 2838 non-whitespace characters, 19 headings, and 61 list items.

    ObservationWithout SkillWith Skill
    Source-signal coverage0/8: none0/8: none
    Output structure2422 chars · 28 headings · 74 list items · 0 code blocks2838 chars · 19 headings · 61 list items · 0 code blocks
    Verification and caution signals13 verification signals · 6 risk/limitation signals8 verification signals · 13 risk/limitation signals

    A prompt you can use

    Use the api-design-patterns Skill pinned at 3a4f3b9309c9 for my task. Follow its source-specific constraints around `api-design-patterns`, `design`, `patterns`, `quick`, then return the finished deliverable with explicit assumptions, verification, failure conditions, and limits. Do not treat the Skill text as a factual source or claim that a single demonstration proves universal performance.

    Method and limitationsExpand

    Test method

    • Baseline and treatment used the same task, model (gpt-5.3-codex-low), and runner; the only planned difference was whether the complete target Skill text was injected.
    • The treatment used snapshot dd50638ed6cb401697840f08199ba577d757969f; the current source commit 3a4f3b9309c9b7e1525088c2d4cca243bc241daf was verified against content hash 174b52ed0381. The baseline explicitly prohibited loading any Skill or external rule file.
    • The same deterministic script counted characters, headings, lists, code blocks, verification terms, caution terms, and source signals in both artifacts. Source signals: `api-design-patterns`, `design`, `patterns`, `quick`, `reference`, `principles`, `universal`, `standards`.
    • The visuals are local screenshots of the actual Markdown artifacts in a fixed 1200 × 800 evidence canvas, not recreated product mockups. Raw JSON artifacts and request records are retained in the research directory.

    Do not over-read this demo

    • This is one controlled demonstration per condition, not a multi-run statistical benchmark; the model is stochastic.
    • Character, structure, and keyword counts show observable differences but cannot by themselves prove correctness, originality, or business impact.
    • The task is a representative test designed for repeatability, not every real-world use of the Skill; rerun after a material source change.
    Editorial review
    SkillSignal editorial
    Runner
    Cursor Agent 2026.08.04-aaa8809
    Model
    gpt-5.3-codex-low
    Refresh due
    2026-11-18
    Reviewed commit
    3a4f3b9309c9b7e1525088c2d4cca243bc241daf
    Test snapshot
    dd50638ed6cb401697840f08199ba577d757969f

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeDeclaredSource recordInstall path and trigger
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/aAAaqwq/AGI-Super-Team --skill "skills/api-design-patterns"
    Safe inspection promptEditorial

    Inspect the Agent Skill "api-design-patterns" from https://github.com/aAAaqwq/AGI-Super-Team/blob/bfcfb64081f94e5869ff420aaaed63b6da716bc6/skills/api-design-patterns/SKILL.md at commit bfcfb64081f94e5869ff420aaaed63b6da716bc6. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Version Deprecation Process

      Include deprecation warnings:

      Include deprecation warnings:See references/versioning-strategies.md for detailed migration patterns
    2. 02

      Signature Verification

      Review the “Signature Verification” section in the pinned source before continuing.

      Review and apply the “Signature Verification” source section.
    3. 03

      Quick Reference

      API Style Selection: - REST: Resource-based CRUD, simple clients, HTTP-native caching - GraphQL: Client-driven queries, complex data graphs, real-time subscriptions - gRPC: High-performance RPC, microservices, strong typing, streaming

      REST: Resource-based CRUD, simple clients, HTTP-native cachingGraphQL: Client-driven queries, complex data graphs, real-time subscriptionsgRPC: High-performance RPC, microservices, strong typing, streaming
    4. 04

      Core Principles

      Apply these principles across all API styles:

      Follow established conventions for your API styleUse predictable naming patterns (snakecase or camelCase, pick one)Maintain consistent error response formats
    5. 05

      Universal API Design Standards

      Apply these principles across all API styles:

      Follow established conventions for your API styleUse predictable naming patterns (snakecase or camelCase, pick one)Maintain consistent error response formats

    Permission review

    Static risk signals and limitations

    Network access

    medium · line 169

    The documentation includes network, browsing, or remote request actions.

    "documentation_url": "https://api.example.com/docs/errors/validation"

    Network access

    medium · line 378

    The documentation includes network, browsing, or remote request actions.

    "migration_guide": "https://docs.api.com/v1-to-v2",

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score97/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars89SourceRepository attention, not individual Skill quality
    Compatibility1 platformsSourceDeclared in the catalog source record
    Usage guidetested outcome pageTestedGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    aAAaqwq/AGI-Super-Team
    Skill path
    skills/api-design-patterns/SKILL.md
    Commit
    bfcfb64081f94e5869ff420aaaed63b6da716bc6
    License
    MIT
    Collected
    2026-08-28
    Default branch
    main
    View the original SKILL.md

    API Design Patterns

    Design robust, scalable APIs using proven patterns for REST, GraphQL, and gRPC with proper versioning, authentication, and error handling.

    Quick Reference

    API Style Selection:

    • REST: Resource-based CRUD, simple clients, HTTP-native caching
    • GraphQL: Client-driven queries, complex data graphs, real-time subscriptions
    • gRPC: High-performance RPC, microservices, strong typing, streaming

    Critical Patterns:

    • Versioning: URI (/v1/users), header (Accept: application/vnd.api+json;version=1), content negotiation
    • Pagination: Offset (simple), cursor (stable), keyset (performant)
    • Auth: OAuth2 (delegated), JWT (stateless), API keys (service-to-service)
    • Rate limiting: Token bucket, fixed window, sliding window
    • Idempotency: Idempotency keys, conditional requests, safe retry

    See references/ for deep dives: rest-patterns.md, graphql-patterns.md, grpc-patterns.md, versioning-strategies.md, authentication.md

    Core Principles

    Universal API Design Standards

    Apply these principles across all API styles:

    1. Consistency Over Cleverness

    • Follow established conventions for your API style
    • Use predictable naming patterns (snake_case or camelCase, pick one)
    • Maintain consistent error response formats
    • Version breaking changes, never surprise clients

    2. Design for Evolution

    • Plan for versioning from day one
    • Use optional fields with sensible defaults
    • Deprecate gracefully with sunset dates
    • Document breaking vs non-breaking changes

    3. Security by Default

    • Require authentication unless explicitly public
    • Use HTTPS/TLS for all production endpoints
    • Implement rate limiting and throttling
    • Validate and sanitize all inputs
    • Return minimal error details to clients

    4. Developer Experience First

    • Provide comprehensive documentation (OpenAPI, GraphQL schema)
    • Return meaningful error messages with actionable guidance
    • Use standard HTTP status codes correctly
    • Include request IDs for debugging
    • Offer SDKs and code generators

    API Style Decision Tree

    When to Choose REST

    Use REST when:

    • Building CRUD-focused resource APIs
    • Clients need HTTP caching (ETags, Cache-Control)
    • Wide platform compatibility required (browsers, mobile, IoT)
    • Simple, stateless client-server model fits
    • Team familiar with HTTP/REST conventions

    Avoid REST when:

    • Complex data fetching with nested relationships (N+1 queries)
    • Real-time updates are primary use case
    • Need strong typing and code generation
    • High-performance RPC between microservices

    Example Use Cases: Public APIs, mobile backends, traditional web services

    When to Choose GraphQL

    Use GraphQL when:

    • Clients need flexible, client-driven queries
    • Complex data graphs with nested relationships
    • Multiple client types with different data needs
    • Real-time subscriptions required
    • Strong typing and schema validation needed

    Avoid GraphQL when:

    • Simple CRUD operations dominate
    • HTTP caching is critical (GraphQL uses POST)
    • File uploads are primary feature (requires extensions)
    • Team lacks GraphQL expertise
    • Performance optimization is complex (N+1 problem)

    Example Use Cases: Client-facing APIs, dashboards, mobile apps with varied UIs

    When to Choose gRPC

    Use gRPC when:

    • Microservice-to-microservice communication
    • High performance and low latency critical
    • Bidirectional streaming needed
    • Strong typing with Protocol Buffers
    • Polyglot environments (language interop)

    Avoid gRPC when:

    • Browser clients (limited support, needs grpc-web)
    • HTTP/JSON required for compatibility
    • Human-readable payloads preferred
    • Simple request/response patterns

    Example Use Cases: Internal microservices, streaming data, service mesh

    REST API Patterns

    Resource Naming

    Good: Plural nouns, hierarchical

    GET    /users              # List users
    GET    /users/123          # Get user
    POST   /users              # Create user
    PUT    /users/123          # Update user (full)
    PATCH  /users/123          # Update user (partial)
    DELETE /users/123          # Delete user
    GET    /users/123/orders   # User's orders (sub-resource)
    

    Bad: Verbs, mixed conventions

    GET    /getUsers           # Don't use verbs
    POST   /user/create        # Don't use verbs
    GET    /Users/123          # Don't capitalize
    GET    /user/123           # Don't mix singular/plural
    

    HTTP Status Codes

    Success Codes:

    • 200 OK: Successful GET, PUT, PATCH, DELETE with body
    • 201 Created: Successful POST, return Location header
    • 202 Accepted: Async operation started
    • 204 No Content: Successful DELETE, no body

    Client Error Codes:

    • 400 Bad Request: Invalid input, validation error
    • 401 Unauthorized: Missing or invalid authentication
    • 403 Forbidden: Authenticated but insufficient permissions
    • 404 Not Found: Resource doesn't exist
    • 409 Conflict: State conflict (duplicate, version mismatch)
    • 422 Unprocessable Entity: Semantic validation error
    • 429 Too Many Requests: Rate limit exceeded

    Server Error Codes:

    • 500 Internal Server Error: Unexpected error
    • 502 Bad Gateway: Upstream service error
    • 503 Service Unavailable: Temporary outage
    • 504 Gateway Timeout: Upstream timeout

    Error Response Format

    Consistent error structure

    {
      "error": {
        "code": "VALIDATION_ERROR",
        "message": "Invalid request parameters",
        "details": [
          {
            "field": "email",
            "message": "Invalid email format",
            "code": "INVALID_FORMAT"
          }
        ],
        "request_id": "req_abc123",
        "documentation_url": "https://api.example.com/docs/errors/validation"
      }
    }
    

    Pagination Patterns

    Offset Pagination (simple, familiar):

    GET /users?limit=20&offset=40
    

    ✅ Use for: Small datasets, admin interfaces ❌ Avoid for: Large datasets (skips become expensive), real-time data

    Cursor Pagination (stable, efficient):

    GET /users?limit=20&cursor=eyJpZCI6MTIzfQ
    Response: { "data": [...], "next_cursor": "eyJpZCI6MTQzfQ" }
    

    ✅ Use for: Infinite scroll, real-time feeds, large datasets ❌ Avoid for: Random access, page numbers

    Keyset Pagination (performant):

    GET /users?limit=20&after_id=123
    

    ✅ Use for: Ordered data, database index friendly ❌ Avoid for: Complex sorting, multiple sort keys

    See references/rest-patterns.md for filtering, sorting, field selection, HATEOAS

    GraphQL Patterns

    Schema Design

    Good: Clear types, nullable by default

    type User {
      id: ID!                    # Non-null ID
      email: String!             # Required field
      name: String               # Optional (nullable by default)
      createdAt: DateTime!
      orders: [Order!]!          # Non-null array of non-null orders
    }
    
    type Query {
      user(id: ID!): User
      users(first: Int, after: String): UserConnection!
    }
    
    type Mutation {
      createUser(input: CreateUserInput!): CreateUserPayload!
    }
    
    input CreateUserInput {
      email: String!
      name: String
    }
    
    type CreateUserPayload {
      user: User
      userEdge: UserEdge
      errors: [UserError!]
    }
    

    Resolver Patterns

    Avoid N+1 Queries with DataLoader:

    import DataLoader from 'dataloader';
    
    const userLoader = new DataLoader(async (userIds: string[]) => {
      const users = await db.users.findMany({ where: { id: { in: userIds } } });
      return userIds.map(id => users.find(u => u.id === id));
    });
    
    // Resolver batches queries automatically
    const resolvers = {
      Order: {
        user: (order) => userLoader.load(order.userId)
      }
    };
    

    Query Complexity Analysis

    Prevent expensive queries:

    import { createComplexityLimitRule } from 'graphql-validation-complexity';
    
    const server = new ApolloServer({
      schema,
      validationRules: [
        createComplexityLimitRule(1000, {
          onCost: (cost) => console.log('Query cost:', cost),
        }),
      ],
    });
    

    See references/graphql-patterns.md for subscriptions, relay cursor connections, error handling

    gRPC Patterns

    Service Definition

    syntax = "proto3";
    
    package users.v1;
    
    service UserService {
      rpc GetUser (GetUserRequest) returns (User) {}
      rpc ListUsers (ListUsersRequest) returns (ListUsersResponse) {}
      rpc CreateUser (CreateUserRequest) returns (User) {}
      rpc StreamUsers (StreamUsersRequest) returns (stream User) {}
      rpc BidiChat (stream ChatMessage) returns (stream ChatMessage) {}
    }
    
    message User {
      string id = 1;
      string email = 2;
      string name = 3;
      google.protobuf.Timestamp created_at = 4;
    }
    
    message GetUserRequest {
      string id = 1;
    }
    
    message ListUsersRequest {
      int32 page_size = 1;
      string page_token = 2;
    }
    
    message ListUsersResponse {
      repeated User users = 1;
      string next_page_token = 2;
    }
    

    Error Handling

    import (
        "google.golang.org/grpc/codes"
        "google.golang.org/grpc/status"
    )
    
    func (s *server) GetUser(ctx context.Context, req *pb.GetUserRequest) (*pb.User, error) {
        if req.Id == "" {
            return nil, status.Error(codes.InvalidArgument, "user ID is required")
        }
    
        user, err := s.db.GetUser(ctx, req.Id)
        if err != nil {
            if errors.Is(err, sql.ErrNoRows) {
                return nil, status.Error(codes.NotFound, "user not found")
            }
            return nil, status.Error(codes.Internal, "database error")
        }
    
        return user, nil
    }
    

    See references/grpc-patterns.md for streaming, interceptors, metadata, health checks

    Versioning Strategies

    URI Versioning (Simple, Explicit)

    Most common, easy to understand

    GET /v1/users/123
    GET /v2/users/123
    

    Pros: Clear, easy to route, browser-friendly Cons: Couples version to URL, duplicates routes

    Header Versioning (Clean URLs)

    GET /users/123
    Accept: application/vnd.myapi.v2+json
    

    Pros: Clean URLs, version separate from resource Cons: Less visible, harder to test manually

    Content Negotiation (Granular)

    GET /users/123
    Accept: application/vnd.myapi.user.v2+json
    

    Pros: Resource-level versioning, backward compatible Cons: Complex, harder to implement

    Version Deprecation Process

    {
      "version": "1.0",
      "deprecated": true,
      "sunset_date": "2025-12-31",
      "migration_guide": "https://docs.api.com/v1-to-v2",
      "replacement_version": "2.0"
    }
    

    Include deprecation warnings:

    HTTP/1.1 200 OK
    Deprecation: true
    Sunset: Sat, 31 Dec 2025 23:59:59 GMT
    Link: <https://docs.api.com/v1-to-v2>; rel="deprecation"
    

    See references/versioning-strategies.md for detailed migration patterns

    Authentication & Authorization

    OAuth 2.0 (Delegated Access)

    Use for: Third-party access, user consent, token refresh

    Authorization Code Flow (most secure for web/mobile):

    1. Client redirects to /authorize
    2. User authenticates, grants permissions
    3. Auth server redirects to callback with code
    4. Client exchanges code for access token
    5. Client uses access token for API requests
    
    # Request token
    POST /oauth/token
    Content-Type: application/x-www-form-urlencoded
    
    grant_type=authorization_code
    &code=AUTH_CODE
    &redirect_uri=https://client.com/callback
    &client_id=CLIENT_ID
    &client_secret=CLIENT_SECRET
    
    # Response
    {
      "access_token": "eyJhbGc...",
      "token_type": "Bearer",
      "expires_in": 3600,
      "refresh_token": "tGzv3JOkF0XG5Qx2TlKWIA",
      "scope": "read write"
    }
    
    # Use token
    GET /v1/users/me
    Authorization: Bearer eyJhbGc...
    

    JWT (Stateless Auth)

    Use for: Microservices, stateless API auth, short-lived tokens

    Good: Minimal claims, short expiry

    {
      "sub": "user_123",
      "iat": 1516239022,
      "exp": 1516242622,
      "scope": "read:users write:orders"
    }
    

    Validation:

    import jwt from 'jsonwebtoken';
    
    const token = req.headers.authorization?.split(' ')[1];
    const payload = jwt.verify(token, process.env.JWT_SECRET);
    req.userId = payload.sub;
    

    API Keys (Service-to-Service)

    Use for: Server-to-server, CLI tools, webhooks

    GET /v1/users
    X-API-Key: sk_live_abc123...
    
    # Or query parameter (less secure)
    GET /v1/users?api_key=sk_live_abc123
    

    Key Practices:

    • Prefix keys with environment (sk_live_, sk_test_)
    • Hash keys before storage (bcrypt, scrypt)
    • Allow key rotation without downtime
    • Support multiple keys per user
    • Rate limit per key

    See references/authentication.md for API key rotation, scopes, RBAC

    Rate Limiting

    Token Bucket (Burst-Friendly)

    Bucket: 100 tokens, refill 10/second
    Request costs 1 token
    Allows bursts up to bucket size
    

    Headers:

    HTTP/1.1 200 OK
    X-RateLimit-Limit: 100
    X-RateLimit-Remaining: 73
    X-RateLimit-Reset: 1640995200
    

    429 Response:

    HTTP/1.1 429 Too Many Requests
    Retry-After: 60
    X-RateLimit-Limit: 100
    X-RateLimit-Remaining: 0
    X-RateLimit-Reset: 1640995200
    
    {
      "error": {
        "code": "RATE_LIMIT_EXCEEDED",
        "message": "Rate limit exceeded. Try again in 60 seconds.",
        "limit": 100,
        "reset_at": "2025-01-01T00:00:00Z"
      }
    }
    

    Sliding Window (Fair Distribution)

    Counts requests in rolling time window. More accurate than fixed window.

    Per-User vs Per-IP

    • Per-User: Authenticated requests, fair quotas
    • Per-IP: Unauthenticated requests, prevent abuse
    • Combined: Both limits, take stricter

    Idempotency

    Idempotent Methods (HTTP Spec)

    Naturally Idempotent: GET, PUT, DELETE, HEAD, OPTIONS Not Idempotent: POST, PATCH

    Idempotency Keys

    Make POST requests idempotent:

    POST /v1/payments
    Idempotency-Key: uuid-or-client-generated-key
    Content-Type: application/json
    
    {
      "amount": 1000,
      "currency": "USD",
      "customer": "cust_123"
    }
    

    Server behavior:

    1. First request: Process and store result with key
    2. Duplicate request (same key): Return stored result (200 or 201)
    3. Different request (same key): Return 409 Conflict

    Implementation:

    const idempotencyKey = req.headers['idempotency-key'];
    if (idempotencyKey) {
      const cached = await redis.get(`idempotency:${idempotencyKey}`);
      if (cached) {
        return res.status(cached.status).json(cached.body);
      }
    }
    
    const result = await processPayment(req.body);
    await redis.setex(`idempotency:${idempotencyKey}`, 86400, {
      status: 201,
      body: result
    });
    

    Conditional Requests

    Use ETags for safe updates:

    # Get resource with ETag
    GET /v1/users/123
    Response: ETag: "abc123"
    
    # Update only if unchanged
    PUT /v1/users/123
    If-Match: "abc123"
    
    # 412 Precondition Failed if ETag changed
    

    Caching Strategies

    HTTP Caching Headers

    # Public, cacheable for 1 hour
    Cache-Control: public, max-age=3600
    
    # Private (user-specific), revalidate
    Cache-Control: private, must-revalidate, max-age=0
    
    # No caching
    Cache-Control: no-store, no-cache, must-revalidate
    

    ETag Validation

    # Server returns ETag
    GET /v1/users/123
    Response:
      ETag: "33a64df551425fcc55e4d42a148795d9f25f89d4"
      Cache-Control: max-age=3600
    
    # Client conditional request
    GET /v1/users/123
    If-None-Match: "33a64df551425fcc55e4d42a148795d9f25f89d4"
    
    # 304 Not Modified if unchanged (saves bandwidth)
    HTTP/1.1 304 Not Modified
    

    Last-Modified

    GET /v1/users/123
    Response:
      Last-Modified: Wed, 21 Oct 2025 07:28:00 GMT
    
    # Conditional request
    GET /v1/users/123
    If-Modified-Since: Wed, 21 Oct 2025 07:28:00 GMT
    
    # 304 Not Modified if not modified
    

    Webhooks

    Event Delivery

    POST https://client.com/webhooks/payments
    Content-Type: application/json
    X-Webhook-Signature: sha256=abc123...
    X-Webhook-Id: evt_abc123
    X-Webhook-Timestamp: 1640995200
    
    {
      "id": "evt_abc123",
      "type": "payment.succeeded",
      "created": 1640995200,
      "data": {
        "object": {
          "id": "pay_123",
          "amount": 1000,
          "status": "succeeded"
        }
      }
    }
    

    Signature Verification

    import crypto from 'crypto';
    
    function verifyWebhookSignature(
      payload: string,
      signature: string,
      secret: string
    ): boolean {
      const expectedSignature = crypto
        .createHmac('sha256', secret)
        .update(payload)
        .digest('hex');
      return crypto.timingSafeEqual(
        Buffer.from(signature),
        Buffer.from(`sha256=${expectedSignature}`)
      );
    }
    

    Retry Strategy

    • Exponential backoff: 1s, 2s, 4s, 8s, 16s, 32s, 64s
    • Timeout: 5-30 seconds per attempt
    • Max attempts: 3-7 attempts
    • Dead letter queue: Store failed events
    • Manual retry: UI for re-sending failed events

    API Documentation

    OpenAPI/Swagger (REST)

    openapi: 3.0.0
    info:
      title: User API
      version: 1.0.0
    paths:
      /users/{id}:
        get:
          summary: Get user by ID
          parameters:
            - name: id
              in: path
              required: true
              schema:
                type: string
          responses:
            '200':
              description: Successful response
              content:
                application/json:
                  schema:
                    $ref: '#/components/schemas/User'
            '404':
              description: User not found
    components:
      schemas:
        User:
          type: object
          required: [id, email]
          properties:
            id:
              type: string
            email:
              type: string
              format: email
            name:
              type: string
    

    GraphQL Schema (Self-Documenting)

    GraphQL introspection provides automatic documentation. Use descriptions:

    """
    Represents a user account in the system.
    Created via the createUser mutation.
    """
    type User {
      """Unique identifier for the user"""
      id: ID!
    
      """Email address, must be unique"""
      email: String!
    
      """Optional display name"""
      name: String
    }
    

    API Documentation Best Practices

    1. Interactive examples: Provide working code samples
    2. Authentication guide: Step-by-step auth setup
    3. Error catalog: Document all error codes with examples
    4. Rate limits: Clearly state limits and headers
    5. Changelog: Track breaking and non-breaking changes
    6. Migration guides: Version upgrade instructions
    7. SDKs: Provide client libraries for popular languages

    Anti-Patterns

    Over-fetching (REST): Returning entire objects when fields are unused ✅ Solution: Support field selection (?fields=id,name,email)

    Under-fetching (REST): Requiring multiple requests for related data ✅ Solution: Support expansion (?expand=orders,profile) or use GraphQL

    Chatty APIs: Too many round-trips for common operations ✅ Solution: Batch endpoints, compound documents, or GraphQL

    Ignoring HTTP semantics: Using GET for mutations, wrong status codes ✅ Solution: Follow HTTP spec, use correct methods and status codes

    Exposing internal structure: URLs/schemas mirror database ✅ Solution: Design resource-oriented APIs independent of storage

    Missing versioning: Breaking changes without version increments ✅ Solution: Version from day one, never break existing versions

    Poor error messages: Generic "An error occurred" ✅ Solution: Specific, actionable error messages with codes

    No rate limiting: APIs vulnerable to abuse ✅ Solution: Implement rate limiting from the start

    Testing Strategies

    Contract Testing

    // Pact contract test
    import { PactV3 } from '@pact-foundation/pact';
    
    const provider = new PactV3({
      consumer: 'FrontendApp',
      provider: 'UserAPI'
    });
    
    it('gets a user by ID', () => {
      provider
        .given('user 123 exists')
        .uponReceiving('a request for user 123')
        .withRequest({
          method: 'GET',
          path: '/users/123'
        })
        .willRespondWith({
          status: 200,
          body: { id: '123', email: '[email protected]' }
        });
    });
    

    Load Testing

    // k6 load test
    import http from 'k6/http';
    import { check } from 'k6';
    
    export const options = {
      stages: [
        { duration: '30s', target: 20 },
        { duration: '1m', target: 20 },
        { duration: '10s', target: 0 }
      ],
      thresholds: {
        http_req_duration: ['p(95)<500'], // 95% under 500ms
        http_req_failed: ['rate<0.01']    // <1% errors
      }
    };
    
    export default function () {
      const res = http.get('https://api.example.com/users');
      check(res, {
        'status is 200': (r) => r.status === 200,
        'response time < 500ms': (r) => r.timings.duration < 500
      });
    }
    

    Related Skills

    • graphql: Deep GraphQL schema design, resolvers, Apollo Server
    • typescript: Type-safe API clients and servers
    • nodejs-backend: Express/Fastify REST API implementation
    • django: Django REST Framework patterns
    • fastapi: FastAPI Python REST/GraphQL APIs
    • flask: Flask-RESTful patterns

    References

    • rest-patterns.md: Deep REST coverage (HATEOAS, filtering, field selection)
    • graphql-patterns.md: GraphQL subscriptions, relay cursor connections, federation
    • grpc-patterns.md: Streaming patterns, interceptors, service mesh integration
    • versioning-strategies.md: Detailed versioning approaches and migration patterns
    • authentication.md: OAuth flows, JWT best practices, API key rotation, RBAC

    Additional Resources

    Frequently asked questions

    What to verify before installation and use

    What does the api-design-patterns source document cover?

    Design robust, scalable APIs using proven patterns for REST, GraphQL, and gRPC with proper versioning, authentication, and error handling.

    How do I install api-design-patterns?

    The source record exposes this install command: npx skills add https://github.com/aAAaqwq/AGI-Super-Team --skill "skills/api-design-patterns". Inspect the command and pinned source before running it.

    Which Agent platforms does the source record declare?

    The pinned source record declares support for: claude code.

    Which permission-related actions were detected?

    Static rules flagged network in the source; the page lists the matching lines and excerpts.

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