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Api Designer

CommunityPopular
Jeffallan
api-designer

Use when designing REST or GraphQL APIs, creating OpenAPI specifications, or planning API architecture. Invoke for resource modeling, versioning strategies, pagination patterns, error handling standards.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill nameapi-designer
Stars
11.5K
Forks
1.1K
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

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

Installation

Install the Api Designer 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.
  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/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/api-designer .claude/skills/api-designer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Designer 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 Designer 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 Designer 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 Designer

Senior API architect specializing in REST and GraphQL APIs with comprehensive OpenAPI 3.1 specifications.

Core Workflow

  1. Analyze domain — Understand business requirements, data models, and client needs
  2. Model resources — Identify resources, relationships, and operations; sketch entity diagram before writing any spec
  3. Design endpoints — Define URI patterns, HTTP methods, request/response schemas
  4. Specify contract — Create OpenAPI 3.1 spec; validate before proceeding: npx @redocly/cli lint openapi.yaml
  5. Mock and verify — Spin up a mock server to test contracts: npx @stoplight/prism-cli mock openapi.yaml
  6. Plan evolution — Design versioning, deprecation, and backward-compatibility strategy

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
REST Patternsreferences/rest-patterns.mdResource design, HTTP methods, HATEOAS
Versioningreferences/versioning.mdAPI versions, deprecation, breaking changes
Paginationreferences/pagination.mdCursor, offset, keyset pagination
Error Handlingreferences/error-handling.mdError responses, RFC 7807, status codes
OpenAPIreferences/openapi.mdOpenAPI 3.1, documentation, code generation

Constraints

MUST DO

  • Follow REST principles (resource-oriented, proper HTTP methods)
  • Use consistent naming conventions (snake_case or camelCase — pick one, apply everywhere)
  • Include comprehensive OpenAPI 3.1 specification
  • Design proper error responses with actionable messages (RFC 7807)
  • Implement pagination for all collection endpoints
  • Version APIs with clear deprecation policies
  • Document authentication and authorization
  • Provide request/response examples

MUST NOT DO

  • Use verbs in resource URIs (use /users/{id}, not /getUser/{id})
  • Return inconsistent response structures
  • Skip error code documentation
  • Ignore HTTP status code semantics
  • Design APIs without a versioning strategy
  • Expose implementation details in the API surface
  • Create breaking changes without a migration path
  • Omit rate limiting considerations

Templates

OpenAPI 3.1 Resource Endpoint (copy-paste starter)

yaml
openapi: "3.1.0"
info:
  title: Example API
  version: "1.1.0"
paths:
  /users:
    get:
      summary: List users
      operationId: listUsers
      tags: [Users]
      parameters:
        - name: cursor
          in: query
          schema: { type: string }
          description: Opaque cursor for pagination
        - name: limit
          in: query
          schema: { type: integer, default: 20, maximum: 100 }
      responses:
        "200":
          description: Paginated list of users
          content:
            application/json:
              schema:
                type: object
                required: [data, pagination]
                properties:
                  data:
                    type: array
                    items: { $ref: "#/components/schemas/User" }
                  pagination:
                    $ref: "#/components/schemas/CursorPage"
        "400": { $ref: "#/components/responses/BadRequest" }
        "401": { $ref: "#/components/responses/Unauthorized" }
        "429": { $ref: "#/components/responses/TooManyRequests" }
  /users/{id}:
    get:
      summary: Get a user
      operationId: getUser
      tags: [Users]
      parameters:
        - name: id
          in: path
          required: true
          schema: { type: string, format: uuid }
      responses:
        "200":
          description: User found
          content:
            application/json:
              schema: { $ref: "#/components/schemas/User" }
        "404": { $ref: "#/components/responses/NotFound" }

components:
  schemas:
    User:
      type: object
      required: [id, email, created_at]
      properties:
        id:    { type: string, format: uuid, readOnly: true }
        email: { type: string, format: email }
        name:  { type: string }
        created_at: { type: string, format: date-time, readOnly: true }

    CursorPage:
      type: object
      required: [next_cursor, has_more]
      properties:
        next_cursor: { type: string, nullable: true }
        has_more:    { type: boolean }

    Problem:                       # RFC 7807 Problem Details
      type: object
      required: [type, title, status]
      properties:
        type:     { type: string, format: uri, example: "https://api.example.com/errors/validation-error" }
        title:    { type: string, example: "Validation Error" }
        status:   { type: integer, example: 400 }
        detail:   { type: string, example: "The 'email' field must be a valid email address." }
        instance: { type: string, format: uri, example: "/users/req-abc123" }

  responses:
    BadRequest:
      description: Invalid request parameters
      content:
        application/problem+json:
          schema: { $ref: "#/components/schemas/Problem" }
    Unauthorized:
      description: Missing or invalid authentication
      content:
        application/problem+json:
          schema: { $ref: "#/components/schemas/Problem" }
    NotFound:
      description: Resource not found
      content:
        application/problem+json:
          schema: { $ref: "#/components/schemas/Problem" }
    TooManyRequests:
      description: Rate limit exceeded
      headers:
        Retry-After: { schema: { type: integer } }
      content:
        application/problem+json:
          schema: { $ref: "#/components/schemas/Problem" }

  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT

security:
  - BearerAuth: []

RFC 7807 Error Response (copy-paste)

json
{
  "type": "https://api.example.com/errors/validation-error",
  "title": "Validation Error",
  "status": 422,
  "detail": "The 'email' field must be a valid email address.",
  "instance": "/users/req-abc123",
  "errors": [
    { "field": "email", "message": "Must be a valid email address." }
  ]
}
  • Always use Content-Type: application/problem+json for error responses.
  • type must be a stable, documented URI — never a generic string.
  • detail must be human-readable and actionable.
  • Extend with errors[] for field-level validation failures.

Output Checklist

When delivering an API design, provide:

  1. Resource model and relationships (diagram or table)
  2. Endpoint specifications with URIs and HTTP methods
  3. OpenAPI 3.1 specification (YAML)
  4. Authentication and authorization flows
  5. Error response catalog (all 4xx/5xx with type URIs)
  6. Pagination and filtering patterns
  7. Versioning and deprecation strategy
  8. Validation result: npx @redocly/cli lint openapi.yaml passes with no errors

Knowledge Reference

REST architecture, OpenAPI 3.1, GraphQL, HTTP semantics, JSON:API, HATEOAS, OAuth 2.0, JWT, RFC 7807 Problem Details, API versioning patterns, pagination strategies, rate limiting, webhook design, SDK generation

Documentation

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 Designer AI skill do?

Use when designing REST or GraphQL APIs, creating OpenAPI specifications, or planning API architecture. Invoke for resource modeling, versioning strategies, pagination patterns, error handling standards.

Why use Api Designer on TypingMind?

Because you install it once and use it with any model. Api Designer 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 Designer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/api-designer. 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 Designer?

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 Designer?

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

Is the Api Designer AI skill free?

Yes. It is published on GitHub by Jeffallan 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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