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Debugging

Checked
siviter-xyz·vlatest·testing·MIT

Identifies and suggests fixes for errors in siviter-xyz code through automated analysis and targeted debugging techniques.

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 siviter-xyz/dot-agent --skill debugging -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

siviter-xyz

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 siviter-xyz/dot-agent at 33762551d4.

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

Commit
33762551d4
Manifest
skills/debugging/SKILL.md
Scanned
4 files, 314 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, assisting in identifying and resolving errors within software systems. It supports the diagnostic process by analyzing code or system states to pinpoint issues.

When to use it

  • You need to identify why a specific function is returning unexpected results.
  • Your application is crashing, and you require assistance tracing the root cause of the failure.
  • You want an agent to review logs and suggest fixes for syntax or logic errors.
  • You are developing complex workflows and need real-time error analysis during execution.

Key capabilities

  • Error identification and root cause analysis
  • Code review for logical and syntactical faults
  • Diagnostic assistance based on provided context or logs
  • Integration with the siviter-xyz/dot-agent framework

Example prompts

  • "Debug this Python script that keeps throwing a TypeError when processing user input."
  • "Analyze these error logs and explain why the API request is failing intermittently."
  • "Review my JavaScript code for potential race conditions and suggest fixes."

Tips & gotchas

Ensure you provide clear context, such as relevant code snippets or error messages, to maximize the agent's diagnostic accuracy. This skill relies on the underlying dot-agent infrastructure, so compatibility with that framework is a prerequisite.