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Debug Buttercup

Checked
lv416e·vlatest·testing

Automates repetitive test case execution and failure analysis using detailed log correlation and root cause suggestions.

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 lv416e/dotfiles --skill debug-buttercup -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

lv416e

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 lv416e/dotfiles at d182953f5e.

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

Commit
d182953f5e
Manifest
dot_claude/skills/debug-buttercup/SKILL.md
Scanned
3 files, 510 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 lv416e-debug-buttercup skill provides debugging capabilities for AI agents. It allows users to inspect the agent's internal state and execution flow, aiding in identifying and resolving issues during development or runtime. This skill is designed to enhance transparency and control over AI agent behavior.

When to use it

  • Troubleshooting unexpected behavior: If an agent isn’t performing as expected, use this skill to examine its decision-making process.
  • Understanding complex logic: When debugging intricate workflows or chains of reasoning within the agent.
  • Validating state transitions: To verify that internal variables and data structures are being updated correctly during execution.
  • Debugging integrations: When issues arise when integrating with external tools or APIs.

Key capabilities

  • Inspects agent's internal state
  • Provides visibility into the execution flow
  • Aids in identifying root causes of errors
  • Enhances transparency and control over AI agent behavior

Example prompts

  • "Show me the current values of all variables."
  • "Trace the steps taken to reach this decision."
  • "What was the state of the system before the last action?"

Tips & gotchas

This skill requires a level of familiarity with the AI agent's internal workings. The output can be verbose and may require careful interpretation to diagnose problems effectively.