Skip to content
TrustedSkillsbeta
Back to all skills

Pythonista Debugging

Checked
gigaverse-app·vlatest·backend·MIT

Quickly identify and fix Python code errors within your Gigaverse backend applications using automated debugging insights.

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 gigaverse-app/skillet --skill pythonista-debugging --full-depth -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

gigaverse-app

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 gigaverse-app/skillet at 6c7e8f8928.

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

Commit
6c7e8f8928
Manifest
pythonista/skills/pythonista-debugging/SKILL.md
Scanned
2 files, 326 lines
Copies in repo
2 — 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 debug Python code. It can identify and explain errors, suggest fixes based on common debugging patterns, and provide insights into potential issues within a given Python script or snippet. The agent can analyze stack traces and pinpoint the source of problems, aiding in efficient code troubleshooting.

When to use it

  • Troubleshooting failing scripts: Use when an AI agent is generating or executing Python code that produces errors.
  • Understanding error messages: When presented with a complex Python traceback, leverage this skill to get a clear explanation of the problem.
  • Improving code quality: Employ it to proactively identify potential bugs and inefficiencies in existing Python codebases.
  • Learning from mistakes: When an AI agent makes errors while coding, use this skill to understand why the error occurred and how to avoid it in the future.

Key capabilities

  • Error identification
  • Stack trace analysis
  • Code explanation
  • Fix suggestions
  • Debugging pattern recognition

Example prompts

  • "Explain this Python traceback: [paste stack trace here]"
  • "I'm getting a TypeError in my code. Can you help me debug it? Here’s the relevant snippet: [paste code snippet here]"
  • “What could be causing this error in my script?”

Tips & gotchas

  • The skill is most effective when provided with complete and accurate Python code or traceback information. Incomplete snippets may lead to less precise debugging suggestions.