AgentSkillsCN

Triage MultiQC Module Requests

处理MultiQC模块请求

SKILL.md

Triage MultiQC Module Requests

Description

Analyze and prioritize MultiQC module requests through automated triage. Calculate priority scores, assign labels, update project boards, and provide actionable feedback to contributors.

Use this skill when:

  • •A new module request issue is opened (labeled module: new)
  • •User comments @claude analyze-module on a module request
  • •Weekly bulk triage is scheduled
  • •Manual analysis is requested via workflow dispatch

Operation Modes

analyze-single

Analyze one specific module request issue. Requires issue number.

When to use: New issues, on-demand analysis requests

triage-all

Analyze all open module requests labeled module: new.

When to use: Weekly batch processing, cleanup operations

dry-run

Perform analysis without making any GitHub changes (no labels, comments, or board updates).

When to use: Testing, validation, debugging

Quick Start

  1. •Determine the mode from the workflow context or user request
  2. •Fetch issue data using GitHub CLI (gh issue view or gh issue list)
  3. •Calculate priority score using scoring-criteria.md
  4. •Perform GitHub actions following github-actions.md
  5. •Post analysis using templates from analysis-templates.md

Priority Score Overview

Score is 0-100 based on five weighted categories:

  • •Tool Popularity (25 pts): GitHub metrics
  • •Package Downloads (15 pts): PyPI/Conda/Bioconda downloads
  • •Community Engagement (35 pts): Reactions, comments, duplicates
  • •Request Quality (20 pts): Completeness, example files
  • •Technical Feasibility (15 pts): Output parseability, metrics clarity

Priority Bands:

  • •🔴 High (≥70): priority: high label
  • •🟡 Medium (40-69): priority: medium label
  • •🟢 Low (20-39): priority: low label
  • •⚪ Hold (<20): needs-triage label only

See scoring-criteria.md for detailed rubric.

Workflow Integration

This skill is invoked by .github/workflows/module-requests.yml which:

  • •Triggers on new issues with module: new label
  • •Responds to @claude analyze-module comments
  • •Runs weekly bulk triage (Mondays at 9 AM UTC)
  • •Supports manual workflow dispatch

GitHub Operations

Key operations (see github-actions.md for details):

  • •Fetch issue metadata and body content
  • •Extract tool information (name, URL, description)
  • •Add/update priority labels
  • •Post analysis comments
  • •Update project board positions (if configured)

Tool Metrics Collection

Use scripts/fetch-tool-metrics.js for reliable API calls:

  • •GitHub stars, forks, last commit date
  • •PyPI download statistics
  • •Bioconda package data
  • •Repository activity metrics

Analysis Output

Generate clear, actionable feedback using templates from analysis-templates.md:

  • •Current priority score with breakdown
  • •Specific improvement recommendations
  • •Comparison to similar requests
  • •Next steps for increasing priority

Error Handling

  • •Missing tool URL: Assign low score, request homepage in feedback
  • •Private/deleted repository: Note in analysis, use partial scoring
  • •API rate limits: Implement exponential backoff, cache results
  • •Invalid issue format: Log warning, assign to "Needs Analysis" column

Best Practices

  1. •Be specific: Point to exact fields that need improvement
  2. •Be encouraging: Frame feedback positively, emphasize what's good
  3. •Be consistent: Apply scoring rubric uniformly across all requests
  4. •Be transparent: Show score calculations in analysis comments
  5. •Respect rate limits: Cache API results, batch operations

Files in This Skill

  • •SKILL.md (this file): High-level overview and workflow
  • •scoring-criteria.md: Detailed scoring rubric with examples
  • •github-actions.md: GitHub API operations and CLI commands
  • •analysis-templates.md: Comment templates and feedback patterns
  • •scripts/fetch-tool-metrics.js: Tool metrics collection script

Related Documentation