Triage MultiQC Module Requests

What problem does it solve?

Manual triage of MultiQC module requests is time-consuming, inconsistent, and can delay the integration of valuable new features. This Skill automates the entire process, ensuring that development efforts are focused on the most impactful and well-prepared requests. It removes the burden of subjective evaluation and provides a clear, data-driven prioritization system, allowing maintainers to rest while AI handles the initial assessment.

Core Features & Use Cases

• Automated Priority Scoring: Calculates a comprehensive priority score (0-100) for each module request based on tool popularity (GitHub stars, downloads), community engagement (reactions, comments), request quality (completeness, example files), and technical feasibility. This saves maintainers significant time in evaluation.
• GitHub Workflow Integration: Seamlessly integrates with GitHub to automatically add priority labels (High, Medium, Low, Hold), post detailed analysis comments, and update project boards, keeping maintainers and contributors informed without manual effort.
• Actionable Feedback for Contributors: Provides specific, constructive feedback and clear next steps to requesters, empowering them to improve their submissions and increase their request's priority, reducing complexity for both sides.
• Use Case: A new module request is submitted for a popular bioinformatics tool. This Skill automatically analyzes the request, assigns a "High Priority" label, and posts a comment detailing the score breakdown and confirming it's ready for development, all without human intervention.

Quick Start

To analyze a specific module request, comment @claude analyze-module on the GitHub issue. For a weekly batch analysis, trigger the triage-all mode via workflow dispatch.