API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.

API Patterns API design decisions tied to the consumers and deployment constraints. Learn to THINK, not copy fixed patterns. 🎯 Selective Reading Rule Read ONLY files relevant to the request! Check the content map, find what you need. 📑 Content Map File Description When to Read api style.md REST vs GraphQL vs tRPC decision tree Choosing API type rest.md Resource naming, HTTP methods, status codes Designing REST API response.md Envelope pattern, error format, pagination Response structure graphql.md Schema design, when to use, security Considering GraphQL trpc.md TypeScript monorepo, type safety TS fullstack projects versioning.md URI/Header/Query versioning API evolution planning auth.md JWT, OAuth, Passkey, API Keys Auth pattern selection rate limiting.md Token bucket, sliding window API protection documentation.md OpenAPI/Swagger best practices Documentation security testing.md OWASP API Top 10, auth/authz testing Security audits 🔗 Related Skills Need Skill API implementation @[skills/backend architect] Data structure @[skills/database design] Security details @[skills/api security best practices] ✅ Decision Checklist Before designing an API: [ ] Asked user about API consumers? [ ] Chosen API style for THIS context? (REST/GraphQL/tRPC) [ ] Defined consistent response format? [ ] Planned versioning strategy? [ ] Considered authentication needs? [ ] Planned rate limiting? [ ] Documentation approach defined? ❌ Anti Patterns DON'T: Default to REST for everything Use verbs in REST endpoints (/getUsers) Return inconsistent response formats Expose internal errors to clients Skip rate limiting DO: Choose API style based on context Ask about client requirements Document thoroughly Use appropriate status codes Script Script Purpose Command scripts/api validator.py Local heuristic source scan (not schema validation) python3 skills/api patterns/scripts/api validator.py <project path When to Use Use when defining a new endpoint contract, selecting REST/GraphQL/tRPC for known consumers, or changing pagination, errors, authentication or compatibility behavior. For a bug inside an existing contract, preserve that contract unless the task authorizes a change. Inputs and procedure Record consumers and deployed versions, expected payload size, access rules, compatibility obligations and one concrete operation. Read the relevant files in the map, compare the realistic choices, then specify request/response examples and rejection cases. Types shared at build time do not ensure that independently deployed clients remain compatible. Worked example Input: a public order list changes while clients page through it. Choose a bounded page size and cursor over a stable (created at, id) order. Define the next cursor format, authorization filter and behavior for a removed record or invalid cursor. Test two equal timestamps and an insertion between pages. Expected: no duplicate IDs within the promised snapshot semantics; document whether newly inserted rows can appear. Limitations The Python helper scans at most 15 matching files using regular expressions and shallow JSON/YAML checks. Its output is a triage hint, not OpenAPI validation, an authorization audit or deployment approval. GraphQL query shape, tRPC inference and HTTP method names do not enforce resource authorization or backwards compatibility. Rate limiting cannot alone prevent all resource exhaustion; size, concurrency, time and provider cost bounds depend on the operation. Perform security checks only against authorized local/test targets with isolated accounts and a defined scope.

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