Debug — Root Cause Debugging Workflow

Trust Score 71/100

A structured root-cause debugging workflow: investigate, understand, reason, and fix — with commands and templates for code search, GitHub issue lookup, log ana

triggers:debugroot causeinvestigaterg searchgh issuesgenerate fixlog analysis

GitHub SKILL.md

What it does

Debug codifies a disciplined root-cause analysis workflow for software issues. It guides an investigator through evidence collection (code search, logs, GH issues), systematic reasoning (first principles, differential diagnosis), and fix generation (specific code changes and verification steps). The skill provides command templates for rg, gh, git, log analysis, and prompts for AI assistants to synthesise findings.

When to use it

Use Debug when faced with reproducible bugs, flaky tests, performance regressions, or errors with unclear origins. It's especially valuable in complex codebases where multi-source evidence (code, history, issues, logs) must be combined to find THE root cause rather than surface symptoms.

What's included

Scripts: none bundled (has_scripts=false) but many terminal command templates are provided for investigation and synthesis.
References: recommended CLI tools (Gemini/GH) and an output markdown template for presenting root cause, confidence, fix, verification, and prevention.
Instructions: phased workflows (Full Debug, Quick Debug, Debug with Context) and a strict Root Cause Protocol that prevents band-aid fixes.

Compatible agents

Designed for agents and engineers that can run shell commands, query GitHub, and call large-model assistants for reasoning. Works well with developer-assistant agents (Gemini/GPT-style) and CLI-integrated automation.

Audit Summary

A structured root-cause debugging workflow skill that enforces Investigate→Understand→Reason→Fix protocol. Contains no scripts — purely a reference document of bash commands using rg, gh, and gemini CLI. The root cause protocol and forbidden shortcuts table are valuable, but the skill is essentially a long cheat sheet of shell one-liners with heavy reliance on the Gemini CLI for reasoning steps.

Watch Out

Requires Gemini CLI (pip install google-generativeai) and GEMINI_API_KEY for core reasoning functionality
Shell interpolation in gemini commands (e.g. $(cat file)) poses injection risk if filenames are untrusted
No actual automation — agent must manually execute each bash command

Notes

Pure documentation skill with no scripts. Monolithic single-file structure with no scripts/ or references/ directories. Heavy coupling to Gemini CLI — most reasoning steps are gemini invocations rather than agent-native reasoning. The 'Forbidden Shortcuts' table is a genuinely useful pattern worth highlighting.

Information

Repository: claude
Stars: 24
Installs: 0

Trust Score

Overall71

Security88

Code Quality62

Architecture40

Usefulness72

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