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Api Design

Community
MartinOlivero
api-design

This skill should be used when designing or building an API — endpoints, routes, request/response shapes, error formats, pagination, versioning, or deciding REST vs GraphQL. Trigger phrases include "design the API", "build an endpoint", "REST or GraphQL", "how should I structure my routes", "API error format", "paginate results", "version my API", "validate env vars", "idempotency", "what should this endpoint return". It applies proven REST conventions and a clear REST-vs-GraphQL decision, with env-config validation.

Overview

PublisherMartinOlivero
Repositorysaas-builder
Skill nameapi-design
Stars
4
Forks
2
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by MartinOlivero on GitHub. Read the source before you install it.

Installation

Install the Api Design AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/MartinOlivero/saas-builder/tree/main/skills/api-design
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/MartinOlivero/saas-builder.git /tmp/saas-builder
mkdir -p .claude/skills
cp -r /tmp/saas-builder/skills/api-design .claude/skills/api-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Design in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Api Design on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Api Design is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

API Design

This skill turns "I need an endpoint" into an API that is consistent, predictable, and safe to evolve. It encodes the conventions that the best public APIs (Stripe, Microsoft, GitHub) share.

Analogy: an API is the menu of a restaurant. A good menu is consistent — every dish described the same way, prices where you expect, no surprises. A messy menu makes every order a negotiation.

Discovery (max 3 questions, only if unknown)

  1. Who consumes this — your own React SPA only, or also mobile / partners / the public?
  2. Is it mostly simple CRUD, or deeply nested reads across many relations?
  3. Is it public-facing (needs versioning + stability) or internal?

Step 1 — REST vs GraphQL (decide first)

Default to REST. Reach for GraphQL only when: clients need flexible, deeply nested reads across many relations; you have multiple divergent clients (web + mobile + partners); or you're composing several backend services. For a single React SPA on one Postgres DB, REST (or tRPC for end-to-end TS types) is simpler and cacheable.

If you do choose GraphQL:

  • Solve N+1 from day one with DataLoader (batch + cache per request).
  • Design the schema around the domain graph, not DB tables.
  • Paginate every list field (Relay-style edges/node/pageInfo); enforce depth/complexity limits.
  • Mutations return the mutated object so clients update cache without a refetch.

Step 2 — REST conventions (the defaults)

  • Resources are plural nouns: /invoices, /invoices/{id}/lines. Verbs are HTTP methods, not paths. Non-CRUD actions: /invoices/{id}:send.
  • Version from day one: URI versioning /v1/..., even with only a v1.
  • Cursor-based pagination by default (opaque cursor + has_more), not offset — stays consistent on insert, avoids slow OFFSET scans. Default page 25, max 100.
  • One consistent error envelope with the correct HTTP status:
    json
    { "error": { "type": "validation_error", "code": "invalid_email", "message": "…", "param": "email" } }
    Never return 200 on failure.
  • Status codes: 201 + Location on create, 204 on delete, 409 conflict, 422 validation, 429 + Retry-After rate limit.
  • Idempotency: require an Idempotency-Key header on unsafe POSTs (payments, signups). Store key→response for 24h; replay returns the original — no double-charge on retry. GET/PUT/DELETE are idempotent by spec.
  • Consistency: ISO-8601 UTC timestamps, one field-casing convention (snake_case or camelCase) across the whole API.
  • Filtering over endpoint sprawl: ?status=open&fields=id,total instead of a new endpoint per view.

Step 3 — Validate env config at the boundary

Every API needs config, and a missing var should fail loudly at boot, not silently in prod:

  • Validate all env vars at startup with a zod schema (or t3-env on Vite/Next). Fail fast on a missing/malformed var.
  • Separate server secrets from client config: on Vite, only VITE_-prefixed vars reach the browser — never put a secret there.
  • Commit .env.example (names + dummy values); never commit real .env*. (Secrets handling lives in the secure-coding skill.)

Handoff

API shape decided here feeds the data-modeling skill (the schema behind it), the auth skill (who can call each endpoint), and secure-coding (validation + rate limits on each handler).

Step 4 — Failure semantics (decide them per endpoint)

  • Check every { error }. Many SDKs return errors instead of throwing; an unchecked one is a silent failure.
  • Three outcomes, not two: succeeded, refused, unknown. "Could not read" is not "not found"; a timeout is not "nothing changed".
  • A retry must be safe. "The response was lost" is not "it was not saved" — check what exists before inserting again.
  • Send only the fields the user changed, so a form cannot overwrite what moved in the meantime.
  • One server-side writer for rewards, credits, balances and payment states.
  • Chunk id lists and paginate reads; auto-generated APIs cap rows and URLs have a length limit.

Field notes

references/field-notes.md holds 11 API failures from production apps. The three that cost the most:

  1. Failures invisible for days because an SDK's returned error was never read.
  2. A duplicated order that took four rounds to fix.
  3. Editing one field of a record silently reset another.

Output

Deliver: the REST-vs-GraphQL call with reason, the route list with methods + status codes, the error envelope, the pagination scheme, and a zod env schema for the service.

Reference

microsoft/api-guidelines (~23k⭐), Stripe API design + idempotency docs, donnemartin/system-design-primer (~352k⭐), graphql/dataloader (~13k⭐), t3-oss/t3-env (~4k⭐), colinhacks/zod (~43k⭐).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Api Design AI skill do?

This skill should be used when designing or building an API — endpoints, routes, request/response shapes, error formats, pagination, versioning, or deciding REST vs GraphQL. Trigger phrases include "design the API", "build an endpoint", "REST or GraphQL", "how should I structure my routes", "API error format", "paginate results", "version my API", "validate env vars", "idempotency", "what should this endpoint return". It applies proven REST conventions and a clear REST-vs-GraphQL decision, with env-config validation.

Why use Api Design on TypingMind?

Because you install it once and use it with any model. Api Design is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Api Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MartinOlivero/saas-builder/tree/main/skills/api-design. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Api Design?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Api Design?

As many as you like. As long as a model supports skills, you can use Api Design with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Api Design AI skill free?

Yes. It is published on GitHub by MartinOlivero under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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