API Development

Orchestrate the full API development lifecycle by coordinating design, implementation, testing, and documentation into a single workflow.

When to Use This Skill

• - Building a new API from scratch
• Adding endpoints to an existing API
• Redesigning or refactoring an API
• Planning API versioning and migration
• Running a complete API development cycle (design → build → test → document → deploy)

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Orchestration Flow

Follow these steps in order. Each step routes to the appropriate skill or tool.

1. Design the API

Load the api-design skill to establish resource models, URL structure, HTTP method semantics, error formats, and pagination strategy.

Deliverables: Resource list, endpoint map, request/response schemas, error format

2. Generate OpenAPI Spec

Produce a machine-readable OpenAPI 3.x specification from the design. Use the OpenAPI template in api-design/assets/openapi-template.yaml as a starting point.

Deliverables: openapi.yaml with all endpoints, schemas, auth schemes, and examples

3. Scaffold Endpoints

Generate route files, request/response types, and validation schemas for each endpoint. Group routes by resource.

Deliverables: Route files, type definitions, validation schemas per resource

4. Implement Business Logic

Write service-layer logic with input validation, authorization checks, database queries, and proper error propagation. Keep controllers thin — business logic lives in the service layer.

Deliverables: Service modules, repository layer, middleware (auth, rate limiting, CORS)

5. Test

Write tests at three levels:

• - Unit tests — service logic, validation, error handling
• Integration tests — endpoint behavior with real DB
• Contract tests — response shapes match OpenAPI spec

Deliverables: Test suite with coverage for happy paths, error cases, edge cases, and auth

6. Document

Generate human-readable API documentation with usage examples and SDK snippets. Ensure every endpoint has description, parameters, request/response examples, and error codes.

Deliverables: API docs, changelog, authentication guide

7. Version and Deploy

Apply a versioning strategy, tag the release, update changelogs, and deploy through the pipeline. Follow the api-versioning skill for deprecation and migration guidance.

Deliverables: Version tag, changelog entry, deployment confirmation

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API Design Decision Table

Choose the right paradigm for your use case.

Criteria	REST	GraphQL	gRPC
Best for	CRUD-heavy public APIs	Complex relational data, client-driven queries	Internal microservices, high-throughput
Data fetching

Fixed response shape per endpoint | Client specifies exact fields | Strongly typed protobuf messages |
| Over/under-fetching | Common problem | Solved by design | Minimal — schema is explicit |
| Caching | Native HTTP caching (ETags, Cache-Control) | Requires custom caching | No built-in HTTP caching |
| Real-time | Polling or WebSockets | Subscriptions (built-in) | Bidirectional streaming |
| Tooling | Mature — OpenAPI, Postman, curl | Growing — Apollo, Relay, GraphiQL | Mature — protoc, grpcurl, Buf |
| Learning curve | Low | Medium | Medium-High |
| Versioning | URL or header versioning | Schema evolution with @deprecated | Package versioning in .proto |

Rule of thumb: Default to REST for public APIs. Use GraphQL when clients need flexible queries across related data. Use gRPC for internal service-to-service communication.

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API Checklist

Run through this checklist before marking any API work as complete.

Authentication & Authorization

• - [ ] Authentication mechanism chosen (JWT, OAuth2, API key)
• [ ] Authorization rules enforced at every endpoint
• [ ] Tokens validated and scoped correctly
• [ ] Secrets stored securely (never in code or logs)

Rate Limiting

• - [ ] Rate limits configured per endpoint or consumer tier
• [ ] RateLimit-* headers included in responses
• [ ] 429 Too Many Requests returned with Retry-After header
• [ ] Rate limit strategy documented for consumers

Pagination

• - [ ] All collection endpoints paginated
• [ ] Pagination style chosen (cursor-based or offset-based)
• [ ] page_size bounded with a sensible maximum
• [ ] Total count or hasNextPage indicator included

Filtering & Sorting

• - [ ] Filter parameters validated and sanitized
• [ ] Sort fields allow-listed (no arbitrary column sorting)
• [ ] Default sort order defined and documented

Error Handling

• - [ ] Consistent error response schema across all endpoints
• [ ] Correct HTTP status codes (4xx for client, 5xx for server)
• [ ] Validation errors return field-level detail
• [ ] Internal errors never leak stack traces or sensitive data

Versioning

• - [ ] Versioning strategy selected and applied uniformly
• [ ] Breaking vs non-breaking change policy documented
• [ ] Deprecation timeline communicated via Sunset header

CORS

• - [ ] Allowed origins configured (no wildcard * in production with credentials)
• [ ] Allowed methods and headers explicitly listed
• [ ] Preflight (OPTIONS) requests handled correctly

Documentation

• - [ ] OpenAPI / Swagger spec generated and up to date
• [ ] Every endpoint has description, parameters, and example responses
• [ ] Authentication requirements documented
• [ ] Error codes and meanings listed
• [ ] Changelog maintained for each version

Security

• - [ ] Input validation on all fields
• [ ] SQL injection prevention
• [ ] HTTPS enforced
• [ ] Sensitive data never in URLs or logs
• [ ] CORS configured correctly

Monitoring

• - [ ] Structured logging with request IDs
• [ ] Error tracking configured (Sentry, Datadog, etc.)
• [ ] Performance metrics collected (latency, error rate)
• [ ] Health check endpoint available (/health)
• [ ] Alerts configured for error rate spikes

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Skill Routing Table

Need	Skill	Purpose
API design principles	INLINECODE15	Resource modeling, HTTP semantics, pagination, error formats
Versioning strategy

api-versioning | Version lifecycle, deprecation, migration patterns | | Authentication | auth-patterns | JWT, OAuth2, sessions, RBAC, MFA | | Error handling | error-handling | Error types, retry patterns, circuit breakers, HTTP errors | | Rate limiting | rate-limiting | Algorithms, HTTP headers, tiered limits, distributed limiting | | Caching | caching | Cache strategies, HTTP caching, invalidation, Redis patterns | | Database migrations | database-migrations | Schema evolution, zero-downtime patterns, rollback strategies |

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NEVER Do

1. 1. NEVER skip the design phase — jumping straight to code produces inconsistent APIs that are expensive to fix
2. NEVER expose database schema directly — API resources are not database tables; design around consumer use cases
3. NEVER ship without authentication — every production endpoint must have an auth strategy
4. NEVER return inconsistent error formats — every error response must follow the same schema
5. NEVER break a published API without a versioning plan — breaking changes require a new version, migration guide, and deprecation timeline
6. NEVER deploy without tests and documentation — untested APIs ship bugs, undocumented APIs frustrate developers