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Debugging With Opensrc

Checked
blogic-cz·vlatest·testing

Identifies and suggests fixes for code errors using open-source debugging tools and community knowledge.

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 blogic-cz/blogic-marketplace --skill debugging-with-opensrc -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

blogic-cz

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 blogic-cz/blogic-marketplace at aaa7762eb5.

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

Commit
aaa7762eb5
Manifest
template-ts/skills/debugging-with-opensrc/SKILL.md
Scanned
2 files, 154 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 allows AI agents to debug open source code. It can analyze error messages, identify potential causes of bugs, and suggest fixes based on the codebase. The agent leverages its understanding of programming concepts and common debugging techniques to pinpoint issues within open-source projects.

When to use it

  • When encountering errors while running an open-source project locally.
  • To understand and resolve bug reports filed by other users for a project you contribute to.
  • For investigating crashes or unexpected behavior in open-source software.
  • When needing assistance understanding complex codebases and identifying the root cause of issues.

Key capabilities

  • Error message analysis
  • Root cause identification
  • Fix suggestion
  • Codebase understanding

Example prompts

  • "Analyze this error message: 'TypeError: Cannot read property 'name' of undefined' in this React component."
  • "I’m seeing a crash when running this Python script. Can you help me debug it?"
  • “What could be causing this NullPointerException in this Java library?”

Tips & gotchas

The skill is most effective with well-documented open source projects and clear error messages. Providing the relevant code snippet alongside the problem description will significantly improve debugging accuracy.