Systematic Debugging

Name: Systematic Debugging
Author: obra

Checked

obra·vlatest·testing·MIT

obra's systematic-debugging analyzes code execution traces to identify root causes of errors and suggest targeted fixes.

Repository skills.sh

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Run this in your project

terminal

$ npx skills add obra/superpowers --skill systematic-debugging -a claude-code

Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

obra

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.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned 5 Oct 2026

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 obra/superpowers at 8ca22dba9a.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: 8ca22dba9a
Manifest: skills/systematic-debugging/SKILL.md
Scanned: 11 files, 1,214 lines

This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.

What each check looks for →

About this skill

What it does

The systematic-debugging skill enables AI agents to methodically identify and resolve errors in code. It supports structured approaches such as isolating variables, reproducing bugs, analyzing logs, and testing hypotheses in a controlled manner.

When to use it

When encountering intermittent or hard-to-reproduce bugs in complex systems
When debugging legacy code with limited documentation
When troubleshooting performance issues that require root cause analysis

Key capabilities

Step-by-step error isolation
Log file parsing and pattern recognition
Hypothesis-driven testing scenarios
Integration with version control for tracking changes

Example prompts

"Debug this Python script by isolating the source of the runtime error."
"Analyze these logs to identify the root cause of the system crash."
"Test this function systematically under different input conditions."

Tips & gotchas

Ensure log files are accessible and formatted consistently for accurate analysis.
Systematic debugging may require additional computational resources for large-scale testing scenarios.