Automates GitHub issue triage by analyzing content and inferring labels using the Miyabi 57-label system.
This skill provides an AI-driven framework for triaging and organizing GitHub issues within the Miyabi development ecosystem. By scanning titles, descriptions, and comments, it automatically applies a sophisticated 11-category labeling system to manage issue lifecycles, assign agents, set priorities, and assess severity. It is particularly useful for maintainers who need to standardize backlog management, ensure consistent metadata across their repository, and automate the escalation of critical bugs or security vulnerabilities.
Key Features
01Context-aware priority and severity assessment for bug reporting
02Automatic inference across 57 distinct labels and 11 specialized categories
03Security-first detection for XSS, SQL injection, and CVE keywords
04Hierarchy mapping to identify parent-child relationships between issues
057 GitHub stars
06Structured output in both JSON and human-readable formats with reasoning
Use Cases
01Automating security escalation workflows based on keyword detection in issue descriptions
02Auditing an existing backlog to standardize labels across hundreds of legacy tasks
03Triaging newly created GitHub issues to ensure they have correct metadata and priority
