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Google Docstring Assistant

Checked
dmitriiweb·vlatest·writing·MIT

This AI assists in generating comprehensive Google Docstrings for Python code, improving readability and maintainability.

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 dmitriiweb/extract-emails --skill google-docstring-assistant -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

dmitriiweb

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 dmitriiweb/extract-emails at 1f2bb4008e.

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

Commit
1f2bb4008e
Manifest
.codex/skills/google-docstring-assistant/SKILL.md
Scanned
2 files, 102 lines
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 extracts email addresses from provided text. It can identify and isolate multiple email addresses within a larger block of text, such as documents or web pages. The extracted emails are returned in a clean, formatted list for easy use.

When to use it

  • You need to quickly extract contact information from a scanned document.
  • You want to compile a list of email addresses mentioned on a webpage without manual copying.
  • A customer support ticket contains multiple email mentions that you need to process.
  • You're analyzing text data and require a list of all email addresses present.

Key capabilities

  • Email address extraction
  • Multiple email identification
  • Formatted output (list)

Example prompts

  • "Extract all email addresses from this document: [paste document content]"
  • "Find the emails in this text: [paste text]"
  • "Can you give me a list of email addresses mentioned here? [paste text]"

Tips & gotchas

The skill relies on pattern recognition; complex or obfuscated email formats might not be accurately identified. Ensure the input text is reasonably clean for optimal results.