Systematic Debugging
CheckedSystematically identifies and resolves software bugs using Chris Wiles' proven debugging methodology and automated analysis.
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 chriswiles/claude-code-showcase --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
chriswiles
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 chriswiles/claude-code-showcase at a95518f0cb.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- a95518f0cb
- Scanned
- 1 file, 141 lines
About this skill
What it does
This skill, systematic-debugging, helps AI agents systematically identify and resolve bugs in code. It breaks down the debugging process into smaller, manageable steps, focusing on isolating the root cause of errors. The agent can generate test cases to reproduce issues, analyze stack traces for clues, and suggest potential fixes based on error patterns.
When to use it
- Debugging complex errors: When faced with a bug that's difficult to pinpoint through standard debugging techniques.
- Reproducing intermittent issues: To create targeted tests that consistently trigger the problematic behavior.
- Analyzing unfamiliar codebases: To understand and debug code you are not familiar with, by systematically isolating potential problem areas.
- Improving code quality: As a proactive measure to identify and address potential bugs before they impact users.
Key capabilities
- Test case generation for bug reproduction
- Stack trace analysis
- Error pattern identification
- Suggestion of potential fixes
Example prompts
- "Debug this Python function: [code snippet]. It's returning incorrect results."
- "I’m seeing a 'TypeError' in my JavaScript code. Can you help me systematically debug it?"
- “Generate test cases to reproduce the bug described here: [bug report].”
Tips & gotchas
The skill is most effective when provided with clear error messages or detailed descriptions of the problematic behavior. It may require additional context about the codebase for optimal results.