agentleFS
mergisimergisi/awesome-hermes-agent/skills/github-issue-triage/SKILL.md

github-issue-triage

Skill2 starsChanged 7 months agoMITView on GitHub

Triage GitHub issues: label by type/priority, ask for repro on bugs, close obvious duplicates with a link to the canonical thread.

7 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 7 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Default trigger is the GitHub issues.opened webhook.

    line 34

“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

GitHub Issue Triage

Triage incoming GitHub issues so a solo maintainer's inbox doesn't explode. This skill labels new issues, asks for reproduction steps when they're missing, and closes duplicates with a link to the canonical thread.

What this skill does

For every new issue in a repository:

  1. Read the issue body — title, description, any code blocks, version mentioned, OS/runtime mentioned.
  2. Classify by type — apply one of: bug, feature-request, docs, question, support, spam. Use the existing labels on the repo if they exist; don't invent new label names.
  3. Estimate priority — if the issue mentions data loss, security, crashes, or production blockage → priority-high. If it mentions a minor visual glitch or a "nice to have" → priority-low. Default → priority-medium.
  4. Check for duplicates — search the last 90 days of closed and open issues for similar titles or error messages. If a duplicate exists, post a comment linking the canonical thread and close the new issue (only if confidence is high).
  5. Ask for repro — for any bug label without clear reproduction steps (steps, expected, actual, version), post a comment asking for them in plain language.
  6. Spam detection — if the issue is single-line marketing, has no relevance to the repo, or is from a brand-new account with a generic title → spam label and close.

What this skill does NOT do

  • It does not auto-merge or auto-fix issues.
  • It does not assign issues to specific maintainers.
  • It does not reply with code suggestions — only labels, classification, repro requests, and dup-closes.
  • It does not auto-close stale issues. Use a separate stale-bot for that.

How to invoke

Default trigger is the GitHub issues.opened webhook. Configure via hermes webhook list. For manual run on a single issue:

/github-issue-triage owner/repo#42

Configuration

In your agent config or skill metadata:

github:
  default_repo: "owner/repo"
  labels:
    bug: "bug"
    feature: "enhancement"
    docs: "documentation"
    spam: "spam"
  dup_search_days: 90
  spam_threshold: 0.85
  ask_repro_template: |
    Thanks for opening this. To reproduce on our end, can you share:
    - The version of {project} you're on
    - Steps to reproduce (1, 2, 3...)
    - What you expected vs what actually happened
    - Your OS / runtime if relevant

Models

This skill is mostly classification + pattern matching:

  • Recommended: Claude Haiku 4.5 or GPT-5.5 mini class. Cheap, fast, accurate enough for triage.
  • Avoid: Opus-class models — overkill for the workload, you'll burn budget.
  • Edge cases: for ambiguous issues (the LLM's confidence is below threshold), the skill is configured to NOT auto-act and instead flag for human review.

Pairing

This skill works best with the triager personality. Together they handle ~80% of incoming issues without the maintainer touching a keyboard.

For full PR review (not just issues), see the pr-first-review skill.

Failure modes to watch

  • Wrongly labeled issues: the skill defers to existing human labels and won't re-label. If you see consistent miscategorization, tune the SKILL.md classification keys for your repo's terminology.
  • Spam false positives: the spam detector is conservative (default threshold 0.85). If legitimate issues get spam-closed, raise the threshold to 0.92 and revisit weekly.
  • Repro request loops: the skill only asks for repro once. If the user doesn't reply within 14 days, a stale-bot should handle it — this skill won't pester.

Want a coordinated crew (issue triage + PR review + changelog + docs)?

The full GitHub Maintainer team ships as a 4-agent bundle. See crewclaw.com/use-cases/github-maintainer-team.

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.