api-development

name	api-development
model	reasoning
description	Meta-skill that orchestrates the full API development lifecycle — from design through documentation — by coordinating specialized skills, agents, and commands into a seamless build workflow.

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	api-design	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. 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