How do I install the Triaging Module Requests skill?

Run npx skillmds@latest add multiqc/triaging-module-requests in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Triaging Module Requests safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Triaging Module Requests?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Triaging Module Requests free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Triaging Module Requests?

multiqc (@multiqc) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Triaging Module Requests by multiqc

Name: Triaging Module Requests
Author: multiqc

Triaging Module Requests

Triage MultiQC `module: new` GitHub issues: calculate 0-100 priority scores, apply priority labels, post analysis comments with score breakdowns, and give contributors actionable feedback to improve their request. Use when a new `module: new` issue is opened, when a user comments `@claude analyze-module` on a request, during weekly bulk triage, or when manually re-evaluating a module request.

multiqc 8a4343b 5 files · 32.7 KB Updated Sep 17, 2026

File contents

Triage MultiQC Module Requests

Invoked by .github/workflows/module-requests.yml on new module: new issues, on @claude analyze-module comments, and on a weekly schedule (Mondays 9 AM UTC). Also runs on manual workflow dispatch.

Workflow

Pick a mode from context:
- analyze-single — one issue (new issue or on-demand request)
- triage-all — every open module: new issue (weekly batch)
- dry-run — calculate and print, but make no GitHub changes
Fetch issue data with gh issue view / gh issue list. See github-actions.md for the exact commands.
Fetch tool metrics via scripts/fetch-tool-metrics.js (GitHub stars, PyPI/Conda downloads, last commit date).
Calculate the priority score using the rubric in scoring-criteria.md.
Apply the priority label (see Priority bands below). Remove any existing priority labels first; see github-actions.md.
Post the analysis comment using analysis-templates.md. Always show the score breakdown, what's good, and concrete improvements (with +X points tags where they apply).

Priority bands

Score	Band	Label
≥70	🔴 High	`module: prio-high`
40–69	🟡 Medium	`module: prio-medium`
20–39	🟢 Low	`module: prio-low`
<20	⚪ Hold	`module: prio-hold`

The five score categories (full rubric in scoring-criteria.md):

Tool Popularity (25) — GitHub stars + maintenance bonus
Package Downloads (15) — PyPI / Conda / Bioconda monthly
Community Engagement (35) — reactions, comments, duplicates
Request Quality (20) — completed fields + example files
Technical Feasibility (15) — output format, metric clarity, parsing

Feedback principles

Be specific (point to exact fields), be encouraging (acknowledge strengths first), be consistent (apply the rubric uniformly), be transparent (show the calculation). Cache API results when batch-processing to stay under rate limits.

---name: triaging-module-requestsdescription: Triage MultiQC `module: new` GitHub issues: calculate 0-100 priority scores, apply priority labels, post analysis comments with score breakdowns, and give contributors actionable feedback to improve their request. Use when a new `module: new` issue is opened, when a user comments `@claude analyze-module` on a request, during weekly bulk triage, or when manually re-evaluating a module request.---# Triage MultiQC Module RequestsInvoked by `.github/workflows/module-requests.yml` on new `module: new`issues, on `@claude analyze-module` comments, and on a weekly schedule(Mondays 9 AM UTC). Also runs on manual workflow dispatch.## Workflow1. **Pick a mode** from context: - `analyze-single` — one issue (new issue or on-demand request) - `triage-all` — every open `module: new` issue (weekly batch) - `dry-run` — calculate and print, but make no GitHub changes2. **Fetch issue data** with `gh issue view` / `gh issue list`. See [github-actions.md](github-actions.md) for the exact commands.3. **Fetch tool metrics** via `scripts/fetch-tool-metrics.js` (GitHub stars, PyPI/Conda downloads, last commit date).4. **Calculate the priority score** using the rubric in [scoring-criteria.md](scoring-criteria.md).5. **Apply the priority label** (see Priority bands below). Remove any existing priority labels first; see [github-actions.md](github-actions.md).6. **Post the analysis comment** using [analysis-templates.md](analysis-templates.md). Always show the score breakdown, what's good, and concrete improvements (with `+X points` tags where they apply).## Priority bands| Score | Band | Label || ----- | --------- | --------------------- || ≥70 | 🔴 High | `module: prio-high` || 40–69 | 🟡 Medium | `module: prio-medium` || 20–39 | 🟢 Low | `module: prio-low` || <20 | ⚪ Hold | `module: prio-hold` |The five score categories (full rubric in [scoring-criteria.md](scoring-criteria.md)):- Tool Popularity (25) — GitHub stars + maintenance bonus- Package Downloads (15) — PyPI / Conda / Bioconda monthly- Community Engagement (35) — reactions, comments, duplicates- Request Quality (20) — completed fields + example files- Technical Feasibility (15) — output format, metric clarity, parsing## Feedback principlesBe specific (point to exact fields), be encouraging (acknowledge strengthsfirst), be consistent (apply the rubric uniformly), be transparent (showthe calculation). Cache API results when batch-processing to stay underrate limits.

Frequently asked questions