pick-next-issue

Solid

Fetch and rank open GitHub issues by community engagement, present the top 3 candidates, and plan implementation for the selected issue. Use when the user asks to "pick next issue", "next issue", "which issue should I work on", "top issues", "most popular issues", "prioritize issues", or "what should I work on next".

Web & Frontend 335 stars 26 forks Updated 5 days ago MIT

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Quality Score: 89/100

Stars 20%
84
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Pick Next Issue Rank open GitHub issues by engagement and plan the selected issue. ## Step 1: Fetch and Rank Issues Run `gh issue list` to fetch open issues with engagement data: ```bash gh issue list --state open --json number,title,url,reactionGroups,comments,labels,createdAt --limit 50 ``` Calculate an engagement score for each issue: - **Reactions score**: Sum all reaction counts from `reactionGroups` (thumbs up, heart, hooray, etc.). Weight thumbs-up (`THUMBS_UP`) reactions 2x since they signal explicit demand. - **Comments score**: Count of comments on the issue. - **Engagement score**: `(weighted reactions) + comments` Sort issues by engagement score descending. ## Step 2: Present Top 3 Present the top 3 issues in a numbered list. For each issue, show: 1. **Title** with issue number and link 2. **Labels** (if any) 3. **Engagement**: reaction breakdown and comment count 4. **Created**: date 5. **First paragraph** of the issue body (truncate if long) If fewer than 3 open issues exist, present all of them. If no open issues exist, inform the user and stop. ## Step 3: User Picks an Issue Ask the user to pick one of the presented issues (or request to see more). If the user asks to **see more**, present the next 3 issues from the ranked list. ## Step 4: Read the Full Issue Fetch the complete issue details for the selected issue: ```bash gh issue view <number> --json number,title,body,url,labels,comments,reactionGroups,assignees,milestone ``` Read the fu...

Details

Author
tobihagemann
Repository
tobihagemann/turbo
Created
3 months ago
Last Updated
5 days ago
Language
Python
License
MIT

Integrates with

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