Systematic Debugging
CheckedSystematically identifies and resolves software bugs through automated analysis, root cause identification, and suggested fixes.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add mjunaidca/mjs-agent-skills --skill systematic-debugging -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
mjunaidca
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.
Automated safety checks
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 mjunaidca/mjs-agent-skills at b829650de9.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- b829650de9
- Scanned
- 3 files, 327 lines
About this skill
What it does
This skill helps AI agents systematically debug code. It facilitates identifying root causes of errors through structured analysis, suggesting potential fixes based on error messages and code context, and guiding the agent through a methodical debugging process. The goal is to improve efficiency and accuracy in resolving software defects.
When to use it
- When an AI agent encounters unexpected behavior or errors during code execution.
- During automated testing phases where failures require investigation.
- To assist developers in troubleshooting complex issues within a codebase.
- When debugging unfamiliar codebases, providing structured guidance for understanding and resolving problems.
Key capabilities
- Error message analysis
- Code context awareness
- Root cause identification
- Suggestion of potential fixes
- Guided debugging process
Example prompts
- "Debug this Python script: [script content] - I'm getting a TypeError."
- "I have an error in my JavaScript code. The error message is 'Uncaught ReferenceError: variable is not defined'. Can you help me debug it?"
- "This Java program isn’t producing the expected output. Walk me through debugging steps, starting with analyzing the error logs.”
Tips & gotchas
The skill's effectiveness relies on providing clear and complete code snippets along with any associated error messages for accurate analysis. Ensure sufficient context is provided to enable effective debugging suggestions.