Debugging
CheckedAutomates debugging Python code by identifying errors, suggesting fixes, and generating test cases based on mrgoonie's expertise.
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 mrgoonie/claudekit-skills --skill 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
mrgoonie
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 mrgoonie/claudekit-skills at 80113d86bc.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 80113d86bc
- Scanned
- 11 files, 1,154 lines
About this skill
The debugging skill empowers AI agents to autonomously identify, analyze, and resolve errors within codebases. It leverages advanced reasoning to interpret stack traces, logs, and runtime behaviors to pinpoint root causes without manual intervention.
When to use it
- Runtime failures: When an application crashes or throws unexpected exceptions during execution.
- Logic errors: To trace incorrect output that stems from flawed algorithmic logic rather than syntax issues.
- Integration issues: When debugging communication breakdowns between microservices, APIs, or external dependencies.
- Performance bottlenecks: To identify and fix code segments causing latency or resource exhaustion.
Key capabilities
- Automated error log analysis for root cause identification.
- Stack trace interpretation to map execution flow failures.
- Context-aware debugging across multiple programming languages.
- Suggestion of targeted fixes based on detected anomalies.
Example prompts
- "Analyze this stack trace and explain the sequence of events leading to the NullPointerException."
- "Review the provided logs for the payment service and identify why transactions are timing out."
- "Debug this Python script that is returning incorrect calculations despite passing syntax checks."
Tips & gotchas
Ensure you provide full context, including relevant code snippets and complete error messages, as limited input reduces diagnostic accuracy. This skill requires access to runtime logs or a live environment to effectively trace execution paths.