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API design and implementation across REST, GraphQL, gRPC, and tRPC patterns.
Passed 23 of 23 test cases with the skill, and 22 of 23 without it.
1 fixed22 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
We have an internal admin endpoint displaying a fixed list of 300 static department code records where business admins must jump directly to page 4. Which pagination strategy is appropriate for this small static dataset?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends offset-based pagination. | Missed | Passed |
The instructions your model reads when the skill loads.
Design and implement APIs using the optimal pattern and framework for the use case. Choose between REST, GraphQL, gRPC, and tRPC based on API consumers, performance requirements, and type safety needs.
Use when:
WHO CONSUMES YOUR API?
├─ PUBLIC/THIRD-PARTY DEVELOPERS → REST with OpenAPI
│ ├─ Python → FastAPI (auto-docs, 40k req/s)
│ ├─ TypeScript → Hono (edge-first, 50k req/s, 14KB)
│ ├─ Rust → Axum (140k req/s, <1ms latency)
│ └─ Go → Gin (100k+ req/s, mature ecosystem)
│
├─ FRONTEND TEAM (same org)
│ ├─ TypeScript full-stack? → tRPC (E2E type safety)
│ └─ Complex data needs? → GraphQL
│ ├─ Python → Strawberry
│ ├─ Rust → async-graphql
│ ├─ Go → gqlgen
│ └─ TypeScript → Pothos
│
├─ SERVICE-TO-SERVICE (microservices)
│ └─ High performance → gRPC
│ ├─ Rust → Tonic
│ ├─ Go → Connect-Go (browser-friendly)
│ └─ Python → grpcio
test cases passed, vs 22 / 23 without
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