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Api Documenter

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zhaono1
api-documenter

API documentation specialist for OpenAPI/Swagger specifications. Use when documenting REST or GraphQL APIs.

Overview

Publisherzhaono1
Repositoryagent-playbook
Skill nameapi-documenter
Stars
79
Forks
12
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by zhaono1 on GitHub. Read the source before you install it.

Installation

Install the Api Documenter 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/zhaono1/agent-playbook.git /tmp/agent-playbook
mkdir -p .claude/skills
cp -r /tmp/agent-playbook/skills/api-documenter .claude/skills/api-documenter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Documenter 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 Documenter 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 Documenter 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 Documenter

Specialist in creating comprehensive API documentation using OpenAPI/Swagger specifications.

When This Skill Activates

Activates when you:

  • Ask to document an API
  • Create OpenAPI/Swagger specs
  • Need API reference documentation
  • Mention "API docs"

OpenAPI Specification Structure

yaml
openapi: 3.0.3
info:
  title: API Title
  version: 1.0.0
  description: API description
servers:
  - url: https://example.com/api/v1
paths:
  /users:
    get:
      summary: List users
      operationId: listUsers
      tags:
        - users
      parameters: []
      responses:
        '200':
          description: Successful response
          content:
            application/json:
              schema:
                type: array
                items:
                  $ref: '#/components/schemas/User'
components:
  schemas:
    User:
      type: object
      properties:
        id:
          type: string
        name:
          type: string

Endpoint Documentation

For each endpoint, document:

Required Fields

  • summary: Brief description
  • operationId: Unique identifier
  • description: Detailed explanation
  • tags: For grouping
  • responses: All possible responses

Recommended Fields

  • parameters: All parameters with details
  • requestBody: For POST/PUT/PATCH
  • security: Authentication requirements
  • deprecated: If applicable

Example

yaml
/users/{id}:
  get:
    summary: Get a user by ID
    operationId: getUserById
    description: Retrieves a single user by their unique identifier
    tags:
      - users
    parameters:
      - name: id
        in: path
        required: true
        schema:
          type: string
        description: The user ID
    responses:
      '200':
        description: User found
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/User'
      '404':
        description: User not found
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/Error'

Schema Documentation

Best Practices

  1. Use references for shared schemas
  2. Add descriptions to all properties
  3. Specify format for strings (email, uuid, date-time)
  4. Add examples for complex schemas
  5. Mark required fields

Example

yaml
components:
  schemas:
    User:
      type: object
      required:
        - id
        - email
      properties:
        id:
          type: string
          format: uuid
          description: Unique user identifier
          example: "550e8400-e29b-41d4-a716-446655440000"
        email:
          type: string
          format: email
          description: User's email address
          example: "user@example.com"
        createdAt:
          type: string
          format: date-time
          description: Account creation timestamp

Authentication Documentation

Document auth requirements:

yaml
security:
  - bearerAuth: []

components:
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT
      description: Use your JWT token from /auth/login

Error Responses

Standard error format:

yaml
components:
  schemas:
    Error:
      type: object
      properties:
        error:
          type: string
          description: Error message
        code:
          type: string
          description: Application-specific error code
        details:
          type: object
          description: Additional error details

Common HTTP status codes:

  • 200: Success
  • 201: Created
  • 204: No Content
  • 400: Bad Request
  • 401: Unauthorized
  • 403: Forbidden
  • 404: Not Found
  • 409: Conflict
  • 422: Unprocessable Entity
  • 500: Internal Server Error

Scripts

Generate OpenAPI spec from code:

bash
python3 scripts/generate_openapi.py --name <resource-name> --output openapi.yaml

Validate OpenAPI spec:

bash
python3 scripts/validate_openapi.py --input openapi.yaml

References

  • references/openapi-template.yaml - OpenAPI template
  • references/examples/ - API documentation examples
  • OpenAPI Specification

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 Documenter AI skill do?

API documentation specialist for OpenAPI/Swagger specifications. Use when documenting REST or GraphQL APIs.

Why use Api Documenter on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaono1/agent-playbook/tree/main/skills/api-documenter. 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 Documenter?

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 Documenter?

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

Is the Api Documenter AI skill free?

Yes. It is published on GitHub by zhaono1 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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