Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Miaoge-Ge/coding-agent-skills --skill api-design-expertgit clone --depth 1 https://github.com/Miaoge-Ge/coding-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/miaoge-ge/coding-agent-skills/api-design-expert)<a href="https://agentmods.dev/skills/miaoge-ge/coding-agent-skills/api-design-expert"><img src="https://agentmods.dev/badge/skills/miaoge-ge/coding-agent-skills/api-design-expert.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00088 | $0.01070 |
| Opus 5 | $0.00044 | $0.00535 |
| Sonnet 5 | $0.00018 | $0.00214 |
| Haiku 4.5 | $0.00009 | $0.00107 |
Grade A, and why
api-design-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API Design Expert
Design for the consumer and for change. Consistency beats cleverness: predictable naming, one error shape, accurate status codes, additive evolution. The contract is the product.
When to Use
- Designing or reviewing a REST/GraphQL API.
- Resource modeling, naming, versioning, pagination, filtering.
- Error formats, status codes, idempotency, rate limiting.
- Writing an OpenAPI/GraphQL SDL contract.
When NOT to Use
- Implementing the server framework →
nodejs-backend-expert/ language skill. - DB schema/query design →
sql-expert. - Overall system topology/scaling →
software-architect.
Core Principles
1. Resource modeling (REST)
- Nouns, plural collections, hierarchy for relationships:
GET /orders/{id}/items. No verbs in paths (/getOrder❌). - Methods carry semantics: GET safe & cacheable, POST create/non-idempotent, PUT full idempotent replace, PATCH partial, DELETE idempotent.
- Accurate status codes:
200/201/204;400(malformed) vs422(valid syntax, semantic error) vs409(conflict);401(unauthenticated) vs403(unauthorized);404;429(rate limit). Never200with an error body.
2. One consistent contract
- Single error envelope everywhere:
{ "error": { "code", "message", "details" } }with a stable machine-readablecode. - Consistent field naming/casing across all endpoints. Use ISO-8601 UTC timestamps, explicit currency/units, and string IDs. Document everything in OpenAPI/SDL — contract first.
3. Evolve without breaking
- Version at the edge (
/v1, or media-type/header). Change additively; never repurpose, retype, or silently drop a field. Deprecate with headers + sunset dates. - Make writes idempotent: support an
Idempotency-Keyfor POST so retries don't double-charge. Document side effects.
4. Collections & resilience
- Paginate large collections — prefer cursor/keyset over offset for large or changing data. Provide filtering/sorting/field-selection explicitly and consistently.
- Publish rate limits (headers), auth scheme, and idempotency semantics. Validate every input; return precise field-level errors.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 77 lines · 88 tokens per session scan A d00ffd05508e
api-design-expert is a skill published in the GitHub repository Miaoge-Ge/coding-agent-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 88 tokens to every session and 1,070 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
springboot-patterns
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.
django-patterns
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.
api-design
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.
backend-patterns
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
cqrs-implementation
Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.
workflow-orchestration-patterns
Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.