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Api Docs Generator

Organization
pnp
api-docs-generator

Generate structured API reference documentation from source code, OpenAPI specs, or route definitions. Trigger phrases include "generate API docs", "document this API", "create API reference", "write endpoint docs", "scaffold API docs".

Overview

Publisherpnp
Repositorycopilot-prompts
Skill nameapi-docs-generator
Stars
894
Forks
307
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 pnp on GitHub. Read the source before you install it.

Installation

Install the Api Docs Generator 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/pnp/copilot-prompts/tree/main/samples/skills/api-docs-generator
  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/pnp/copilot-prompts.git /tmp/copilot-prompts
mkdir -p .claude/skills
cp -r /tmp/copilot-prompts/samples/skills/api-docs-generator .claude/skills/api-docs-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Docs Generator 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 Docs Generator 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 Docs Generator 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 Documentation Generator

Generate clean, structured Markdown API reference docs from source code, OpenAPI/Swagger specs, or route definitions.

Gather Context

Before writing anything, determine:

  1. Source — Controller, route file, OpenAPI spec (JSON/YAML), or a set of files?
  2. API name — e.g., "User Management API". Infer from class/file name if not stated.
  3. Base URL — e.g., https://api.example.com/v1. Default to https://api.example.com if unknown.
  4. Auth method — Bearer token (default), API key, OAuth 2.0, or none.
  5. Output format:
    • single-file (default) — one Markdown file with all endpoints
    • per-endpoint — one file per endpoint ({method}-{path-slug}.md) plus a README.md index
  6. Language/framework — Auto-detect from file extensions, imports, and decorators.

If context is missing: In conversational mode, ask. In agent/inline mode, use sensible defaults and note your assumptions at the top of the output.

Analyzing the Source

From Source Code

Read the file(s) and extract:

  • Every endpoint: HTTP method + route path
  • Route params, query params, request body schemas
  • Response types, status codes, and return models
  • Auth requirements (per-endpoint if they vary)
  • Doc comments, decorators, or annotations (/// <summary>, @ApiOperation, @app.get(...), JSDoc @param/@returns, etc.)

Framework detection hints:

SignalFramework
[ApiController], [HttpGet]ASP.NET Core
@app.get(), @router.post()FastAPI
router.get(), app.use()Express.js
@GetMapping, @RestControllerSpring Boot
@Controller, @Get()NestJS
resources :usersRails

From OpenAPI/Swagger Specs

Parse the spec and map directly:

  • paths → endpoints
  • parameters → params table
  • requestBody → request body section
  • responses → response table + examples
  • components/schemas → inline the referenced models
  • securityDefinitions / securitySchemes → auth section
  • info.title, info.version, servers[0].url → header metadata

Prefer descriptions from the spec. Only infer descriptions when the spec omits them.

Handling Incomplete Source

If the source references models, DTOs, or types defined in other files:

  • Document what's visible. Use the type name as-is (e.g., UserDto) and note that the full schema is defined elsewhere.
  • If the user provides multiple files, cross-reference them to build complete schemas.
  • Never fabricate fields for a model you can't see.

Documentation Template

markdown
# {API Name} — API Reference

> Base URL: `{base-url}`
> Authentication: {auth-method}
> Version: {version}

## Table of Contents

- [Authentication](#authentication)
- [{Resource Group}](#{resource-group-slug})
  - [{METHOD} {path}](#{endpoint-anchor})

## Authentication

{How to authenticate: header format, token acquisition, expiration/refresh if known.}

**Header format:**

```
Authorization: Bearer {token}
```

---

## {Resource Group}

### {METHOD} `{path}`

{One-line description from doc comments or inferred from the code.}

**Parameters**

| Name | In | Type | Required | Description |
|------|----|------|----------|-------------|
| `id` | path | integer | ✅ | Resource ID |
| `limit` | query | integer | ❌ | Max results (default: 20) |

**Request Body** *(POST/PUT/PATCH only)*

```json
{
  "email": "string — the user's email address",
  "displayName": "string — display name"
}
```

**Responses**

| Status | Description |
|--------|-------------|
| `200 OK` | Returns the resource |
| `404 Not Found` | Resource not found |

```json
{
  "id": 42,
  "email": "jane@example.com",
  "displayName": "Jane Smith",
  "createdAt": "2026-01-15T10:30:00Z"
}
```

**Example**

```bash
curl -X GET "{base-url}/{path}" \
  -H "Authorization: Bearer eyJhbG..."
```

For per-endpoint format: one file per endpoint named {method}-{path-slug}.md (e.g., get-users-id.md), each using the endpoint section above, plus a README.md that links to all of them grouped by resource.

Common API Patterns to Document

When you encounter these in the source, document them:

  • Pagination — query params like page, limit, offset, cursor. Note defaults and max values if visible.
  • Filtering/sorting — query params like sort, filter, q, status. Document allowed values.
  • Rate limiting — if headers like X-RateLimit-* or decorators like @Throttle() are present, add a "Rate Limiting" section.
  • Versioning — if the API uses path versioning (/v1/, /v2/) or header versioning, note it in the header.
  • Bulk operations — endpoints accepting arrays or batch payloads.

Rules

Do:

  • Extract only what exists in the source — never invent endpoints, params, or fields
  • Use exact route paths, param names, and types from the code
  • Preserve existing descriptions from doc comments, annotations, or spec descriptions
  • Include a curl example for every endpoint
  • Use realistic fake data in examples (jane@example.com, 42, "acme-corp" — not "string" or "value")
  • Document both success and error responses
  • Use standard HTTP status descriptions (200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, etc.)
  • Flag ambiguity with a note (e.g., "Response schema inferred from return type; actual response may differ")

Don't:

  • Invent endpoints or params that aren't in the source
  • Use placeholder junk like "string", "value", or "example" in response bodies
  • Skip error responses — include at least 400 and 404 where applicable
  • Assume auth requirements if the code doesn't specify them — note the uncertainty instead

Example

Input — ASP.NET Core controller:

csharp
[ApiController]
[Route("api/[controller]")]
public class UsersController : ControllerBase
{
    /// <summary>Gets a user by their ID.</summary>
    [HttpGet("{id}")]
    public async Task<ActionResult<UserDto>> GetUser(int id) { }

    /// <summary>Creates a new user.</summary>
    [HttpPost]
    public async Task<ActionResult<UserDto>> CreateUser([FromBody] CreateUserRequest request) { }
}

Output:

markdown
# Users API — API Reference

> Base URL: `https://api.example.com`
> Authentication: Bearer token

## Users

### GET `/api/users/{id}`

Gets a user by their ID.

**Parameters**

| Name | In | Type | Required | Description |
|------|----|------|----------|-------------|
| `id` | path | integer | ✅ | The user's unique ID |

**Responses**

| Status | Description |
|--------|-------------|
| `200 OK` | Returns the user |
| `404 Not Found` | User not found |

```json
{
  "id": 42,
  "email": "jane@example.com",
  "displayName": "Jane Smith",
  "createdAt": "2026-01-15T10:30:00Z"
}
```

**Example**

```bash
curl -X GET "https://api.example.com/api/users/42" \
  -H "Authorization: Bearer eyJhbG..."
```

---

### POST `/api/users`

Creates a new user.

**Request Body**

```json
{
  "email": "string — the user's email address",
  "displayName": "string — the user's display name",
  "role": "string — user role (admin, member, viewer)"
}
```

**Responses**

| Status | Description |
|--------|-------------|
| `201 Created` | User created successfully |
| `400 Bad Request` | Invalid request body |
| `409 Conflict` | Email already exists |

```json
{
  "id": 43,
  "email": "john@example.com",
  "displayName": "John Doe",
  "createdAt": "2026-02-18T14:00:00Z"
}
```

**Example**

```bash
curl -X POST "https://api.example.com/api/users" \
  -H "Authorization: Bearer eyJhbG..." \
  -H "Content-Type: application/json" \
  -d '{"email": "john@example.com", "displayName": "John Doe", "role": "member"}'
```

Pre-Delivery Checklist

  • Every endpoint in the source is documented — none missing, none invented
  • All params have correct name, location (path/query/header/body), type, and required status
  • Every endpoint has a curl example with realistic data
  • Response examples use plausible fake data, not placeholders
  • Endpoints are grouped by resource and sorted GET → POST → PUT → PATCH → DELETE
  • Auth section matches what the code actually specifies
  • Ambiguities are flagged, not silently assumed
  • TOC anchors resolve correctly

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 Docs Generator AI skill do?

Generate structured API reference documentation from source code, OpenAPI specs, or route definitions. Trigger phrases include "generate API docs", "document this API", "create API reference", "write endpoint docs", "scaffold API docs".

Why use Api Docs Generator on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pnp/copilot-prompts/tree/main/samples/skills/api-docs-generator. 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 Docs Generator?

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 Docs Generator?

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

Is the Api Docs Generator AI skill free?

Yes. It is published on GitHub by pnp 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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