Systematic Debugging
CheckedSystematically identifies and isolates software bugs using automated analysis and targeted test case generation.
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 grnfromdark/autodevskill --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
grnfromdark
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 grnfromdark/autodevskill at 79c05a2134.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 79c05a2134
- Scanned
- 11 files, 1,218 lines
About this skill
What it does
This skill, "Systematic Debugging," assists AI agents in identifying and resolving software bugs through a structured process. It helps pinpoint root causes by analyzing error messages, stack traces, and code execution paths. The agent can then suggest or implement fixes based on this analysis, improving the reliability of applications.
When to use it
- When an application is exhibiting unexpected behavior or errors.
- During automated testing where failures need detailed investigation.
- To assist developers in understanding complex error scenarios and accelerating debugging workflows.
- For analyzing crash reports and identifying recurring issues in production environments.
Key capabilities
- Error message analysis
- Stack trace interpretation
- Code execution path tracing
- Root cause identification
- Fix suggestion/implementation
Example prompts
- "Analyze this error message: 'TypeError: Cannot read property 'name' of undefined'"
- "Explain the stack trace from this crash report."
- "Trace the code execution leading up to this error."
- "Suggest a fix for this bug based on the provided information."
Tips & gotchas
The skill's effectiveness depends on providing clear and complete error data, including relevant code snippets or logs. It is intended as an aid to developers, not a replacement for thorough testing practices.