Jeffallan/claude-skills

code-documenter

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.

83Collecting
See how to use itView GitHub source
npx skills add https://github.com/Jeffallan/claude-skills --skill "skills/code-documenter"
Automated source guide

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Reorganized from the pinned upstream SKILL.md

Turn code-documenter's source instructions into a guide you can follow

According to the pinned SKILL.md from Jeffallan/claude-skills: Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.

npx skills add https://github.com/Jeffallan/claude-skills --skill "skills/code-documenter"
Check the pinned source

Best fit

  • Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.
  • 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.

Bring this context

  • A concrete task that matches the documented purpose of code-documenter.
  • The files, examples, or context the task depends on.
  • Your constraints, target environment, and definition of done.

Expected outputs

  • Code Documentation: Documented files + coverage report
  • API Docs: OpenAPI specs + portal configuration
  • Doc Sites: Site configuration + content structure + build instructions

Key source sections

Read code-documenter through these 5 source sections

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

01

Core Workflow

1. Discover - Ask for format preference and exclusions 2. Detect - Identify language and framework 3. Analyze - Find undocumented code 4. Document - Apply consistent format 5. Validate - Test all code examples compile/run: - Python: python -m doctest file.py for doctest blocks;…

SKILL.md · Core Workflow
Discover - Ask for format preference and exclusionsDetect - Identify language and frameworkAnalyze - Find undocumented code
02

When to Use This Skill

Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.

SKILL.md · When to Use This Skill
Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.
03

Quick-Reference Examples

Review the “Quick-Reference Examples” section in the pinned source before continuing.

SKILL.md · Quick-Reference Examples
Review and apply the “Quick-Reference Examples” source section.
04

Google-style Docstring (Python)

Review the “Google-style Docstring (Python)” section in the pinned source before continuing.

SKILL.md · Google-style Docstring (Python)
Review and apply the “Google-style Docstring (Python)” source section.
05

NumPy-style Docstring (Python)

Review the “NumPy-style Docstring (Python)” section in the pinned source before continuing.

SKILL.md · NumPy-style Docstring (Python)
Review and apply the “NumPy-style Docstring (Python)” source section.

SkillSignal prompt templates

Provide the task, context, and acceptance criteria

These prompts were written by SkillSignal from the source structure; they are not upstream text.

Task-start prompt

Confirm source fit, inputs, and outputs before acting.

Use code-documenter to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.

Source-guided execution

Make the Agent explicitly follow the key extracted sections.

Apply the pinned code-documenter source to [task]. Pay particular attention to these source sections: “Core Workflow”, “When to Use This Skill”, “Quick-Reference Examples”, “Google-style Docstring (Python)”, “NumPy-style Docstring (Python)”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].

Result-review prompt

Check omissions, permissions, and source drift before delivery.

Review the current code-documenter result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.

Output checklist

Verify each item before delivery

The task matches the purpose documented in the SKILL.md.

The source section “Core Workflow” has been checked.

The source section “When to Use This Skill” has been checked.

The source section “Quick-Reference Examples” has been checked.

The source section “Google-style Docstring (Python)” has been checked.

Inputs, constraints, and acceptance criteria are explicit.

Unverified facts, compatibility, and outcome claims are clearly marked.

Any file, command, network, or data action has been reviewed.

Choose a different workflow

When another Skill is the better fit

fastapi-expert

Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python.

A separate implementation from Jeffallan/claude-skills; compare its source, maintenance signals, and permission requirements.

Open source detail

genomic-intelligence

Predict regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene sy

A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.

Open source detail

build-with-exa

Build applications and agents with Exa's API Platform: search, contents, answer, context, Agent API, monitors, websets, OpenAI-compatible endpoints, and exa-py / exa-js. Use when choosing Exa endpoints, writing Exa API calls, integrating semantic web search or research into products, or debugging Exa request shapes. Load references/ on demand for endpoint details.

A separate implementation from MoizIbnYousaf/marketing-cli; compare its source, maintenance signals, and permission requirements.

Open source detail

FAQ

What does code-documenter do?

Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.

How do I start using code-documenter?

The catalog detected this source-specific install command: npx skills add https://github.com/Jeffallan/claude-skills --skill "skills/code-documenter". Inspect the command and pinned source before running it.

Which Agent platforms does it declare?

No dedicated Agent platform is declared in the pinned source record.

Repository stars
10,762
Repository forks
984
Quality
83/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

83/100
Documentation28/30
Specificity23/25
Maintenance17/20
Trust signals15/25

Compare before choosing

Related Agent Skills and source variants

These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.

fastapi-expert by jeffallan

Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python.

genomic-intelligence by k-dense-ai

Predict regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene sy

build-with-exa by MoizIbnYousaf

Build applications and agents with Exa's API Platform: search, contents, answer, context, Agent API, monitors, websets, OpenAI-compatible endpoints, and exa-py / exa-js. Use when choosing Exa endpoints, writing Exa API calls, integrating semantic web search or research into products, or debugging Exa request shapes. Load references/ on demand for endpoint details.

astropy by k-dense-ai

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

mcp-builder by anthropics

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 2 min

Code Documenter

Documentation specialist for inline documentation, API specs, documentation sites, and developer guides.

When to Use This Skill

Applies to any task involving code documentation, API specs, or developer-facing guides. See the reference table below for specific sub-topics.

Core Workflow

  1. Discover - Ask for format preference and exclusions
  2. Detect - Identify language and framework
  3. Analyze - Find undocumented code
  4. Document - Apply consistent format
  5. Validate - Test all code examples compile/run:
    • Python: python -m doctest file.py for doctest blocks; pytest --doctest-modules for module-wide checks
    • TypeScript/JavaScript: tsc --noEmit to confirm typed examples compile
    • OpenAPI: validate spec with npx @redocly/cli lint openapi.yaml
    • If validation fails: fix examples and re-validate before proceeding to the Report step
  6. Report - Generate coverage summary

Quick-Reference Examples

Google-style Docstring (Python)

def 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.
    """

NumPy-style Docstring (Python)

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.
    """

JSDoc (TypeScript)

/**
 * 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> { ... }

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Python Docstringsreferences/python-docstrings.mdGoogle, NumPy, Sphinx styles
TypeScript JSDocreferences/typescript-jsdoc.mdJSDoc patterns, TypeScript
FastAPI/Django APIreferences/api-docs-fastapi-django.mdPython API documentation
NestJS/Express APIreferences/api-docs-nestjs-express.mdNode.js API documentation
Coverage Reportsreferences/coverage-reports.mdGenerating documentation reports
Documentation Systemsreferences/documentation-systems.mdDoc sites, static generators, search, testing
Interactive API Docsreferences/interactive-api-docs.mdOpenAPI 3.1, portals, GraphQL, WebSocket, gRPC, SDKs
User Guides & Tutorialsreferences/user-guides-tutorials.mdGetting started, tutorials, troubleshooting, FAQs

Constraints

MUST DO

  • Ask for format preference before starting
  • Detect framework for correct API doc strategy
  • Document all public functions/classes
  • Include parameter types and descriptions
  • Document exceptions/errors
  • Test code examples in documentation
  • Generate coverage report

MUST NOT DO

  • Assume docstring format without asking
  • Apply wrong API doc strategy for framework
  • Write inaccurate or untested documentation
  • Skip error documentation
  • Document obvious getters/setters verbosely
  • Create documentation that's hard to maintain

Output Formats

Depending on the task, provide:

  1. Code Documentation: Documented files + coverage report
  2. API Docs: OpenAPI specs + portal configuration
  3. Doc Sites: Site configuration + content structure + build instructions
  4. Guides/Tutorials: Structured markdown with examples + diagrams

Knowledge Reference

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

Documentation

Skill path
skills/code-documenter/SKILL.md
Commit SHA
e8be415bc94d
Repository license
MIT
Data collected