GitHub Issue Analysis & Label Inference

About

This skill empowers Claude to perform intelligent, AI-driven analysis of GitHub issues by automatically inferring appropriate labels from the comprehensive Miyabi 57-label system. It streamlines the issue lifecycle—from creation to backlog management—by evaluating technical keywords, urgency, and project hierarchy. It ensures consistent categorization across 11 categories, including Priority, Severity, and Agent assignment, allowing teams to maintain a highly organized, autonomous development workflow with minimal manual intervention.

Key Features

• Priority and Severity detection based on security, impact, and SLA requirements
• Automatic inference across 11 categories and 57 specialized labels
• 7 GitHub stars
• Automated escalation recommendations for critical security or performance bugs
• Intelligent hierarchy mapping (root, parent, child, leaf) for task decomposition
• Contextual analysis of titles, descriptions, comments, and linked issues

Use Cases

• Managing and prioritizing project backlogs based on technical complexity
• Ensuring consistent metadata across large-scale open-source repositories
• Automating the triage process for newly created GitHub issues