Debugging Checklist
CheckedSystematically identifies common code errors using a comprehensive debugging checklist to improve software quality.
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 proflead/codex-skills-library --skill debugging-checklist -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
proflead
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 proflead/codex-skills-library at a05260c883.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- a05260c883
- Scanned
- 1 file, 27 lines
About this skill
What it does
This skill provides a structured debugging checklist to systematically identify and resolve issues in code. It guides the AI agent through common error sources, ensuring a thorough investigation process. The checklist covers areas like input validation, boundary conditions, and resource management, leading to more robust solutions.
When to use it
- When an AI agent is generating incorrect or unexpected results from code.
- During automated testing phases to ensure comprehensive bug detection.
- To help troubleshoot complex errors where the root cause isn't immediately apparent.
- After receiving feedback indicating a program has failed in a specific scenario.
Key capabilities
- Provides a step-by-step debugging process.
- Covers common error categories (input validation, boundary conditions).
- Helps identify resource leaks and inefficient code.
- Offers guidance on isolating the source of errors.
Example prompts
- "Run the debugging checklist on this Python script: [script content]"
- "I'm getting a 'TypeError' in my JavaScript code; can you use the debugging checklist to help me find the problem?"
- "Apply the debugging checklist to analyze why this function is returning incorrect values."
Tips & gotchas
The skill assumes basic familiarity with programming concepts and error types. It’s most effective when used on relatively small, self-contained code snippets for focused analysis.