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Python Comments

Checked
acaprino·vlatest·backend·MIT

Generate clear, concise Python code comments explaining logic and purpose within a given function or block.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add acaprino/daodan --skill python-comments -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

acaprino

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned acaprino/alfio-claude-plugins at 10363691a2.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
10363691a2
Manifest
exports/pi/plugins/python-development/skills/python-comments/SKILL.md
Scanned
15 files, 3,978 lines
Copies in repo
3 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill allows AI agents to add comments to Python code. It can insert single-line or multi-line comments, and explain existing code through commenting. The agent can also remove existing comments from a codebase.

When to use it

  • Code Documentation: Automatically generate documentation for a Python script by adding descriptive comments.
  • Code Explanation: Have the AI agent explain complex sections of code by inserting clarifying comments.
  • Clean Up Codebases: Remove unnecessary or outdated comments from a project to improve readability.
  • Learning and Debugging: Add temporary comments to understand the flow of execution during debugging.

Key capabilities

  • Adds single-line comments
  • Adds multi-line comments
  • Explains code through commenting
  • Removes existing comments

Example prompts

  • "Add a comment explaining what this function does."
  • "Remove all the comments from this file."
  • "Insert a multi-line comment describing the purpose of this class."

Tips & gotchas

This skill requires access to Python code as input. The quality of explanations depends on the clarity and structure of the original code.