Systematic Debugging
CheckedSystematically identifies and resolves software bugs using guided analysis and automated 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 guyhoozdis/superpowers --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
guyhoozdis
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 guyhoozdis/superpowers at 0b35ec30ec.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 0b35ec30ec
- Scanned
- 11 files, 1,223 lines
About this skill
What it does
This skill allows AI agents to systematically debug code, identifying and isolating issues through a structured process. It can analyze error messages, trace execution paths, and suggest potential fixes based on identified patterns. The agent will provide detailed explanations of its debugging steps and reasoning.
When to use it
- When an AI agent is producing incorrect or unexpected results in a software program.
- To troubleshoot complex errors that are difficult to diagnose manually.
- For automated regression testing, ensuring code changes haven't introduced new bugs.
- When needing assistance understanding the root cause of a specific error message.
Key capabilities
- Error Message Analysis
- Execution Path Tracing
- Pattern Recognition for Bug Identification
- Suggestion of Potential Fixes
- Detailed Explanation of Debugging Steps
Example prompts
- "Debug this Python code and explain the issue: [code snippet]"
- "I'm getting a 'TypeError: unsupported operand type(s) for +:' error. Can you help me debug it?"
- "Trace the execution path of this function to find out why it’s returning an incorrect value."
Tips & gotchas
The agent requires access to the relevant code base and any associated logs or documentation to effectively perform debugging. Providing clear context about the expected behavior is crucial for accurate analysis.