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api-development skill

/skills/wpank/api-development

This skill orchestrates the full API development lifecycle from design to deployment, coordinating design, code, tests, and documentation to accelerate

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SKILL.md
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---
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)

---

## 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

---

## 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.

---

## 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

---

## 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 |

---

## 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

Overview

This skill orchestrates the full API development lifecycle by coordinating specialized skills, agents, and commands into a single build workflow. It guides design, generates OpenAPI specs, scaffolds endpoints, implements business logic, runs tests, produces documentation, and manages versioning and deployment. The skill centralizes best practices and checks to reduce mistakes and speed delivery.

How this skill works

The skill routes tasks to focused capabilities: api-design for modeling and OpenAPI generation, scaffolding tools for route and type generation, service-layer templates for business logic, testing modules for unit/integration/contract tests, and documentation generators for human-readable docs and SDK snippets. It enforces a stepwise flow (design → spec → scaffold → implement → test → document → version/deploy) and provides checklists and decision guidance to validate readiness before release.

When to use it

  • Building a new public or internal API from scratch
  • Adding or refactoring endpoints in an existing API
  • Planning versioning, deprecation, or migration strategies
  • Running a full API delivery cycle (design through deploy)
  • Ensuring production readiness: security, tests, and docs

Best practices

  • Always start with the design phase: resource models, endpoint map, and error formats
  • Generate and validate an OpenAPI 3.x spec early and keep it authoritative
  • Keep controllers thin; place business logic in service and repository layers
  • Write unit, integration, and contract tests that cover happy paths and edge cases
  • Enforce consistent error schemas, auth checks, rate limiting, and pagination
  • Version releases, update changelogs, and communicate deprecations

Example use cases

  • Create a new REST API with resource models, OpenAPI spec, and generated route scaffolding
  • Add paginated collection endpoints with consistent filtering and sorting rules
  • Migrate a public API with a deprecation timeline, Sunset headers, and compatibility tests
  • Implement service-layer business logic with repository patterns and authorization checks
  • Produce developer docs and SDK snippets from the OpenAPI spec for consumer onboarding

FAQ

Which API paradigm should I choose?

Default to REST for public CRUD-heavy APIs; choose GraphQL when clients need flexible field selection across related data; use gRPC for high-throughput internal service-to-service communication.

When is it acceptable to skip design?

Never. Skipping design increases inconsistency and cost to fix later; always run at least a lightweight design pass before implementation.