apply-turbo-handoffs
Audit the turbo skill lessons that /self-improve writes into this repo's .turbo/handoff/ from other projects, apply the ones the…
@tobihagemannInstall SkillDevelopment
Skill
/pick-next-issue
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\",
Claude Code
$ npx -y skills add tobihagemann/turbo --skill pick-next-issue --agent claude-code
Codex
$ npx skills add tobihagemann/turbo --skill pick-next-issue -a codex -y
Cursor
$ npx skills add tobihagemann/turbo --skill pick-next-issue -a cursor -y
Gemini CLI
$ npx skills add tobihagemann/turbo --skill pick-next-issue -a gemini-cli -y
GitHub Copilot
$ npx skills add tobihagemann/turbo --skill pick-next-issue -a github-copilot -y
OpenCode
$ npx skills add tobihagemann/turbo --skill pick-next-issue -a opencode -y
Windsurf
$ npx skills add tobihagemann/turbo --skill pick-next-issue -a windsurf -y
SKILL.md
pick-next-issue.SKILL.mdname: pick-next-issue
description: "Rank open GitHub issues by engagement, present the top 3, and plan the selected one. Use when the user asks to \"pick next issue\", \"which issue should I work on\", or \"what should I work on next\"."
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:
gh issue list --state open --json number,title,body,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:
gh issue view <number> --json number,title,body,url,labels,comments,reactionGroups,assignees,milestone
Read the full issue body and comments to understand the requirements and any discussion context.
Step 5: Run `/plan` Skill
Run the `/plan` skill with the issue body as the task description. Tell `/plan` that the plan must include a final implementation step: "Close issue #N or reference it in the PR with `Closes #N`."
Rules
- Requires `gh` CLI authenticated with access to the current repo
- If `gh` fails (not in a repo, not authenticated), inform the user and stop
- Never modify issues. This skill is read-only until the implementation is committed.
Read more
name: pick-next-issue description: "Rank open GitHub issues by engagement, present the top 3, and plan the selected one. Use when the user asks to \"pick next issue\", \"which issue should I work on\", or \"what should I work on next\"."
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:
gh issue list --state open --json number,title,body,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:
gh issue view <number> --json number,title,body,url,labels,comments,reactionGroups,assignees,milestone
Read the full issue body and comments to understand the requirements and any discussion context.
Step 5: Run `/plan` Skill
Run the `/plan` skill with the issue body as the task description. Tell `/plan` that the plan must include a final implementation step: "Close issue #N or reference it in the PR with `Closes #N`."
Rules
- Requires `gh` CLI authenticated with access to the current repo
- If `gh` fails (not in a repo, not authenticated), inform the user and stop
- Never modify issues. This skill is read-only until the implementation is committed.
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Questions about pick-next-issue.
- Which coding agents can use pick-next-issue?
- pick-next-issue installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.