python-docstring-generator

A Python documentation skill that adds or completes docstrings for functions, methods, classes, and utility code. Docstrings are text inside Python code that explains how it should be used, following common PEP 257 conventions.

In plain words
What is it for?
Use it when creating or refactoring Python code, documenting async functions, preparing for review, or keeping Google, NumPy, or Sphinx-style docstrings consistent.
Why use it?
It fills gaps in code documentation, including missing parameter, type, and return-value explanations, making code easier to understand and review.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/darellchua2/opencode-config-template/python-docstring-generator
Any agent
npx skills add darellchua2/opencode-config-template --skill python-docstring-generator
Clone the repo
git clone --depth 1 https://github.com/darellchua2/opencode-config-template

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,374 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00033 $0.04374
Opus 5 $0.00016 $0.02187
Sonnet 5 $0.00007 $0.00875
Haiku 4.5 $0.00003 $0.00437

Measured 2d ago against content hash 62fbe3fc2813, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-docstring-generator scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = await fetch(f"/api/users/{user_id}")
opencode_app/.opencode/skills/_archived/python-docstring-generator/SKILL.md · 852 lines

How it starts

The opening of the file, as written. The whole thing — 852 lines — stays where its author put it; the contents beside it link to each section on GitHub.

What this skill does

  • Adds docstrings to all Python functions and methods
  • Ensures all functions with parameters have proper parameter documentation with type information
  • Documents return values with Returns: sections
  • Handles async functions, classes, and utility functions
  • Maintains existing docstring style conventions in codebase (Google, NumPy, or Sphinx)
  • Follows PEP 257 standards for Python code documentation
  • Integrates with Python's type hints for better IDE support

When to use

Use this when:

  • Implementing new functions, classes, or utility modules in Python projects
  • Refactoring code and adding missing documentation
  • Preparing for code review and ensuring proper docstring standards
  • Functions lack docstrings or have incomplete parameter documentation
  • You need to enforce docstring presence as part of quality checks

Common signals:

  • Python functions without docstrings
  • Functions with parameters but missing parameter documentation
  • Return values not documented
  • Async functions without proper return type documentation
  • Python code lacking type-aware documentation

Python Docstring Standard Formats

Google Style (Recommended for most projects)

Basic Function
def calculate_sum(a: int, b: int) -> int:
    """Calculate the sum of two numbers.

    Args:
        a: The first number to add.
        b: The second number to add.

    Returns:
        The sum of a and b.
    """
    return a + b
Async Function
async def fetch_user(user_id: str) -> User:
    """Fetch user data from API.

    Args:
        user_id: The unique identifier of user.

    Returns:
        The user data object.

    Raises:
        APIError: When the API request fails.
    """
    response = await fetch(f"/api/users/{user_id}")
    if not response.ok:
        raise APIError('Failed to fetch user')
    return response.json()
Class Method
class UserProfile:
    """User profile display component.

    This class manages user profile data and display logic.

    Attributes:
        user_id: The user's unique identifier.
        on_edit: Callback when edit button is clicked.
    """

    def __init__(self, user_id: str, on_edit: Callable):
        """Initialize user profile.

        Args:
            user_id: The user's unique identifier.
            on_edit: Callback when edit button is clicked.
        """
        self.user_id = user_id
        self.on_edit = on_edit

Read the full file on GitHub · 852 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 852 lines · 33 tokens per session scan A 62fbe3fc2813

Subscribe to this mod's changes

python-docstring-generator is a skill published in the GitHub repository darellchua2/opencode-config-template (6 stars, last pushed 2d ago), licensed Apache-2.0. It adds 33 tokens to every session and 4,374 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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