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Debug Investigator

Checked
mathews-tom·vlatest·testing·MIT

Pinpoints root causes of test failures by analyzing logs, code, and execution traces with detailed explanations.

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 mathews-tom/armory --skill debug-investigator -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

mathews-tom

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 mathews-tom/praxis-skills at ca902da10b.

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

Commit
ca902da10b
Manifest
skills/debug-investigator/SKILL.md
Scanned
7 files, 1,339 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-investigator skill helps users systematically diagnose and resolve issues within AI agent workflows. It can analyze error messages, trace execution paths, and identify potential root causes of failures. This allows for faster debugging cycles and improved overall system reliability.

When to use it

  • Troubleshooting unexpected behavior: When an AI agent produces incorrect or undesirable results.
  • Analyzing error logs: To understand the context surrounding errors and pinpoint their origin.
  • Debugging complex workflows: When multiple steps are involved, and isolating the problem area is difficult.
  • Improving system stability: Proactively identify and address potential failure points in agent processes.

Key capabilities

  • Error message analysis
  • Execution path tracing
  • Root cause identification
  • Workflow debugging

Example prompts

  • "Analyze this error message: 'TypeError: Cannot read property 'name' of undefined'"
  • "Trace the execution flow for order processing when a payment fails."
  • "Investigate why my agent is consistently generating incorrect summaries."

Tips & gotchas

The skill's effectiveness relies on having access to detailed logs and error information from the AI agent’s environment. Ensure sufficient logging is enabled before using debug-investigator.