Issue Analysis with Label Inference

What problem does it solve?

This Skill automates the analysis and labeling of GitHub Issues, inferring appropriate labels from Miyabi's 57-label system across 11 categories. It eliminates manual triage, ensures consistent labeling, and accelerates issue processing and backlog management.

Core Features & Use Cases

• AI-Driven Label Inference: Automatically suggests TYPE, PRIORITY, SEVERITY, SPECIAL, COMMUNITY, and HIERARCHY labels based on issue content.
• 57-Label System Integration: Leverages a comprehensive labeling framework to ensure granular and consistent issue classification.
• Analysis Workflow: Guides through reading issue content, extracting keywords, applying inference rules, and generating a structured label set.
• Use Case: A new bug report comes in. Use this Skill to analyze the issue title and description. It will automatically infer that it's a type:bug, priority:P0-Critical, severity:Sev.1-Critical, and security issue, and recommend immediate escalation, saving critical triage time.

Quick Start

Analyze GitHub Issue #270, titled "XSS vulnerability in comment form", and infer the appropriate labels and escalation recommendations.