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Debug

Checked
pproenca·vlatest·testing·MIT

Automatically identifies and suggests fixes for common coding errors in Python projects.

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 pproenca/dot-skills --skill debug -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

pproenca

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 pproenca/dot-skills at cf93c57cac.

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

Commit
cf93c57cac
Manifest
skills/.curated/debug/SKILL.md
Scanned
60 files, 4,404 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 enables AI agents to perform debugging tasks, allowing them to analyze errors and troubleshoot issues within codebases. It provides the foundational capability for agents to identify root causes of failures rather than just reporting symptoms.

When to use it

  • An agent encounters a runtime error in a deployed application and needs to isolate the failing line of code.
  • A developer wants an agent to review logs and suggest fixes for a specific logic bug.
  • You need an agent to validate if a recent code change introduced a regression in functionality.
  • An automated testing pipeline fails, and you require an agent to diagnose why the test suite crashed.

Key capabilities

  • Analyzing error messages and stack traces to determine failure points.
  • Reviewing source code context surrounding reported bugs.
  • Suggesting potential fixes or workarounds for identified issues.
  • Troubleshooting logic errors and data flow problems.

Example prompts

  • "Analyze this stack trace and explain why the database connection is failing."
  • "Review the provided Python script and identify any logical errors causing the output mismatch."
  • "Debug this unit test failure by examining the assertions and the mock data used."

Tips & gotchas

Ensure you provide the agent with sufficient context, such as relevant code snippets or full error logs, to enable accurate diagnosis. This skill is most effective when combined with other coding skills that allow the agent to implement the suggested fixes directly.