scartissue

Analyze code branches against historical bug data to flag risky changes.

Updated Apr 23, 2026

Search Tags:#code review #code analysis #checklist #risk assessment #bug detection

Ready to run

npx skills add https://github.com/goderecho/scartissue --skill scartissue

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scartissue
Source: https://github.com/goderecho/scartissue/tree/main
Command: npx skills add https://github.com/goderecho/scartissue --skill scartissue

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill detects risky code changes based on historical bug data and surfaces relevant checklists to help engineers avoid common pitfalls.

Core Features & Use Cases

Bug Detection: Analyzes code changes and flags risky files and co-change gaps.
Checklist Surfaces: Provides checklists for high-risk areas based on historical bugs.
Use Case: When working on a feature branch, use the scartissue skill to identify potentially risky code changes and access relevant checklists.

Quick Start

Activate the scartissue skill in your Claude Code session to scan the current branch for risky code changes.

Frequently Asked Questions about scartissue

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I detect risky code changes before merging a feature branch?▼

You can detect risky code changes by running static code analysis on your feature branch to cross-reference commits with a historical database of known bugs. This flags risky files, identifies co-change gaps, and surfaces relevant checklists to prevent common pitfalls.

What is static code analysis using historical bug data for risk assessment?▼

Static code analysis for risk assessment evaluates code changes against a database of historical bugs to identify potential risks. It flags risky files and missing co-changes, then surfaces checklists for high-risk areas to improve code review safety.

Do I need git to perform code analysis and check for risky commits?▼

Yes, you need git to analyze branches and extract code commit data for cross-referencing with the historical bug database. A pre-built skill is also required to process the commits and perform the risk assessment during code review workflows.

How do I get a code review checklist for high-risk files and co-change gaps?▼

You get a code review checklist by analyzing your feature branch for risky code changes based on historical bug data. The analysis identifies high-risk areas and missing co-changes, automatically surf relevant checklists to help you avoid known issues.

Can I use this static code analysis with my existing development workflow?▼

Yes, this static code analysis integrates into code review and development workflows. Activate it during feature branch development to scan for risky code changes and access relevant checklists without disrupting your existing process.

What are the limitations of bug detection based on historical code data?▼

Bug detection based on historical data is limited by the scope and quality of the pre-built bug database. It cannot detect novel bugs absent from historical records and requires a populated database of known issues to accurately flag risky files and co-change gaps.