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Debug

Checked
nth5693·vlatest·testing·MIT

Identifies and suggests fixes for code errors based on detailed logs and error messages, improving test reliability.

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 nth5693/gemini-kit --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

nth5693

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 nth5693/gemini-kit at f3db206869.

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

Commit
f3db206869
Manifest
skills/debug/SKILL.md
Scanned
3 files, 90 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

The debug skill provides a mechanism to inspect and understand the internal state of an AI agent. It allows for detailed logging of actions, thoughts, and observations, facilitating troubleshooting and performance analysis. This is particularly useful in complex workflows or when unexpected behavior occurs.

When to use it

  • Troubleshooting errors: When an agent fails to complete a task successfully, use this skill to examine its reasoning process.
  • Analyzing decision-making: Understand why the agent chose a particular course of action by reviewing its internal thought processes.
  • Optimizing performance: Identify bottlenecks or inefficiencies in the agent's workflow through detailed logging.
  • Validating logic: Confirm that the agent is following the intended logic and reasoning steps.

Key capabilities

  • Detailed Logging
  • Action Inspection
  • Thought Process Analysis
  • Observation Review

Example prompts

  • "Enable debug mode and run this task."
  • "Show me the last 10 actions taken by the agent."
  • "Log all thoughts related to planning a route."

Tips & gotchas

The skill's output can be verbose. Use it selectively, especially in production environments, as excessive logging can impact performance and increase costs.