gh-issue-triage
Skill2 starsChanged 5 months agoMITView on GitHub
Scans the current GitHub repo for open, unassigned issues with no linked PR, scores them against an AI-readiness rubric, and returns the top 3 picks with rationale and a ready-to-paste agent kickoff prompt for each. Use when the user mentions AI triage, AI-ready issues, picking issues for an agent, what to work on next, or wants to find issues to dispatch to an AI.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- Linearl/reasonix_skill_repotheir own version, first seen Oct 13, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- Linearl/reasonix_skill_repo★ 3same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository34 other files it gives its agents.
- AGENTS.mdAGENTS.md
- agent-guide-bootstrapSkill
- benchmarkSkill
- blazing-fast-webSkill
- create-skillSkill
- gh-issue-creatorSkill
- gh-pr-comment-assistantSkill
- gh-pr-description-updaterSkill
- gh-pr-listSkill
- git-worktreesSkill
- governance-messageSkill
- grid-reviewSkill
- grill-meSkill
- improve-promptSkill
- investigateSkill
- loop-cve-auditSkill
- loop-react-doctorSkill
- meta-ads-bulk-creatorSkill
- miguel-reviewSkill
- office-hoursSkill
- pr-dashboardSkill
- qa-manualSkill
- review-prSkill
- save-and-archiveSkill
- seo-geo-auditSkill
- share-readySkill
- teachSkill
- ui-reviewSkill
- update-branchSkill
- verification-before-completionSkill
- verify-prSkill
- whats-missingSkill
- writing-google-styleSkill
- writing-voiceSkill
The file
We split this skill into the rules it gives an agent
10 rules. About 0 are common, 8 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈8
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 21
Run from the user's cwd:
- Very specific: line 27
If that fails, tell the user the cwd is not a GitHub repo (or gh is not authenticated) and stop.
- Very specific: line 40
If the result is empty, print No AI-ready issues in OWNER/REPO and stop.
- Distinctive: line 68
If fewer than 3 issues clear the rubric, return as many as qualify.
- Distinctive: line 112
After the last pick, print a one-line summary:
- Distinctive: line 120
Do NOT invent acceptance criteria the issue does not state.
- Distinctive: line 122
Do NOT pick issues with active reviewer debate, even if otherwise clear.
- Distinctive: line 123
Do NOT pad the list to 3 when fewer issues qualify.
- Distinctive: line 124
Do NOT include the full issue body in the kickoff prompt — distill it.
- Distinctive: line 125
Do NOT recommend issues assigned to someone or already linked to a PR.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
GH Issue Triage
Find the top 3 GitHub issues in the current repo that are best suited for an AI agent to pick up, and produce a kickoff prompt for each.
This skill is read-only. Never assign, label, or comment on any issue — the output is for the user to act on.
Resolve the current repo
Run from the user's cwd:
gh repo view --json nameWithOwner -q .nameWithOwnerIf that fails, tell the user the cwd is not a GitHub repo (or gh is not
authenticated) and stop.
Fetch candidate issues
Pull open + unassigned issues that have no linked PR:
gh issue list --repo OWNER/REPO --state open --limit 50 \
--search "no:assignee -linked:pr sort:updated-desc" \
--json number,title,body,url,labels,comments,createdAt,updatedAt,authorIf the result is empty, print No AI-ready issues in OWNER/REPO and stop.
Score each issue
Apply this rubric to every issue using its body, labels, and comment metadata. Each dimension scores 0–3 for a total of 0–15.
| Dimension | 3 (great) | 0 (bad) |
| Clarity | Concrete problem statement, no ambiguity | Vague or one-line title with no body |
| Scope | Acceptance criteria stated or strongly implied | Open-ended "improve X" with no boundary |
| Self-contained | No business/product decisions or private context needed | Requires stakeholder input or hidden context |
| Size | Doable in a single AI session | "Rewrite the module" or cross-cutting refactor |
| Signal | good first issue / help wanted / ai-ready labels, low comment count, no debate | Heated thread, conflicting requirements |
Hard disqualifiers
Skip the issue (do not include in the ranking) if any of these are true:
- Body or comments call for upfront design ("needs design", "needs spec", "TBD") or flag the issue as blocked on another task or external input.
- Security-sensitive (auth, crypto, secrets handling) without clear scope.
- Comment thread shows reviewers disagreeing on the desired behavior.
- Title or labels indicate a question, discussion, or RFC — not work.
Pick the top 3
Sort by total score descending; break ties by updatedAt (most recent first).
If fewer than 3 issues clear the rubric, return as many as qualify. Never pad
the list to 3.
Output format
Render the headers, links, and bullets as plain markdown so the issue links stay clickable. Render the kickoff prompt itself inside a fenced code block so the user can copy it in one click and paste it into a fresh agent chat.
One block per pick, separated by ---:
## Top AI-ready issues in OWNER/REPO
### 1. [#NUMBER — Title](URL)
- Score: 13/15 (Clarity 3, Scope 3, Self-contained 2, Size 3, Signal 2)
- Labels: bug, good first issue
- Why it's AI-ready: <2-3 sentences distilled from the issue>
Kickoff prompt:
```
Implement issue #NUMBER in OWNER/REPO: <title>.
Context: <one-paragraph summary of the problem from the issue body>.
Acceptance criteria:
- <criterion 1>
- <criterion 2>
Out of scope: <anything explicitly deferred in the issue>.
Reference: <issue URL>
```
---
### 2. ...The kickoff prompt is the deliverable — it must be self-contained enough to paste into a fresh agent chat (Cursor, Codex, Claude Code) and start work without further questions.
After the last pick, print a one-line summary:
Scanned N open issues in OWNER/REPO, M passed the rubric, top K shown.Anti-patterns
- Do NOT invent acceptance criteria the issue does not state. If the issue is light on detail, lower the Scope score; do not fabricate.
- Do NOT pick issues with active reviewer debate, even if otherwise clear.
- Do NOT pad the list to 3 when fewer issues qualify.
- Do NOT include the full issue body in the kickoff prompt — distill it.
- Do NOT recommend issues assigned to someone or already linked to a PR; the search query should exclude them, but double-check before ranking.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

