.claude/skills/code-documenter/SKILL.md
Generates, formats, and validates technical documentation — including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user guides. Use when adding docstrings to functions or classes, creating API documentation, building documentation sites, or writing tutorials and user guides. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, getting started guides.
npx skillsauth add shalevamin/The-_Ultimate_agents code-documenterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.
Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.
python -m doctest file.py for doctest blocks; pytest --doctest-modules for module-wide checkstsc --noEmit to confirm typed examples compilenpx @redocly/cli lint openapi.yamldef fetch_user(user_id: int, active_only: bool = True) -> dict:
"""Fetch a single user record by ID.
Args:
user_id: Unique identifier for the user.
active_only: When True, raise an error for inactive users.
Returns:
A dict containing user fields (id, name, email, created_at).
Raises:
ValueError: If user_id is not a positive integer.
UserNotFoundError: If no matching user exists.
"""
def compute_similarity(vec_a: np.ndarray, vec_b: np.ndarray) -> float:
"""Compute cosine similarity between two vectors.
Parameters
----------
vec_a : np.ndarray
First input vector, shape (n,).
vec_b : np.ndarray
Second input vector, shape (n,).
Returns
-------
float
Cosine similarity in the range [-1, 1].
Raises
------
ValueError
If vectors have different lengths.
"""
/**
* Fetches a paginated list of products from the catalog.
*
* @param {string} categoryId - The category to filter by.
* @param {number} [page=1] - Page number (1-indexed).
* @param {number} [limit=20] - Maximum items per page.
* @returns {Promise<ProductPage>} Resolves to a page of product records.
* @throws {NotFoundError} If the category does not exist.
*
* @example
* const page = await fetchProducts('electronics', 2, 10);
* console.log(page.items);
*/
async function fetchProducts(
categoryId: string,
page = 1,
limit = 20
): Promise<ProductPage> { ... }
Load detailed guidance based on context:
| Topic | Reference | Load When |
|-------|-----------|-----------|
| Python Docstrings | references/python-docstrings.md | Google, NumPy, Sphinx styles |
| TypeScript JSDoc | references/typescript-jsdoc.md | JSDoc patterns, TypeScript |
| FastAPI/Django API | references/api-docs-fastapi-django.md | Python API documentation |
| NestJS/Express API | references/api-docs-nestjs-express.md | Node.js API documentation |
| Coverage Reports | references/coverage-reports.md | Generating documentation reports |
| Documentation Systems | references/documentation-systems.md | Doc sites, static generators, search, testing |
| Interactive API Docs | references/interactive-api-docs.md | OpenAPI 3.1, portals, GraphQL, WebSocket, gRPC, SDKs |
| User Guides & Tutorials | references/user-guides-tutorials.md | Getting started, tutorials, troubleshooting, FAQs |
Depending on the task, provide:
Google/NumPy/Sphinx docstrings, JSDoc, OpenAPI 3.0/3.1, AsyncAPI, gRPC/protobuf, FastAPI, Django, NestJS, Express, GraphQL, Docusaurus, MkDocs, VitePress, Swagger UI, Redoc, Stoplight
development
Use when building cross-platform applications with Flutter 3+ and Dart. Invoke for widget development, Riverpod/Bloc state management, GoRouter navigation, platform-specific implementations, performance optimization.
testing
Use when fine-tuning LLMs, training custom models, or adapting foundation models for specific tasks. Invoke for configuring LoRA/QLoRA adapters, preparing JSONL training datasets, setting hyperparameters for fine-tuning runs, adapter training, transfer learning, finetuning with Hugging Face PEFT, OpenAI fine-tuning, instruction tuning, RLHF, DPO, or quantizing and deploying fine-tuned models. Trigger terms include: LoRA, QLoRA, PEFT, finetuning, fine-tuning, adapter tuning, LLM training, model training, custom model.
tools
Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
tools
Translate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Trigger when the user provides Figma URLs or node IDs, or asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection.