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Github Triage

Community
Teaonly
github-triage

Triage GitHub issues through a label-based state machine. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.

Overview

PublisherTeaonly
RepositorySKILL.mk
Skill namegithub-triage
Stars
103
Forks
4
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Teaonly on GitHub. Read the source before you install it.

Installation

Install the Github Triage AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Teaonly/SKILL.mk/tree/main/examples/github-triage
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Teaonly/SKILL.mk.git /tmp/SKILL.mk
mkdir -p .claude/skills
cp -r /tmp/SKILL.mk/examples/github-triage .claude/skills/github-triage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Github Triage in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Github Triage on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Github Triage is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GitHub Issue Triage

Triage issues in the current repo using a label-based state machine. Infer the repo from git remote. Use gh for all GitHub operations.

AI Disclaimer

Every comment or issue posted to GitHub during triage must include the following disclaimer at the top of the comment body, before any other content:

> *This was generated by AI during triage.*

Reference docs

Labels

LabelTypeDescription
bugCategorySomething is broken
enhancementCategoryNew feature or improvement
needs-triageStateMaintainer needs to evaluate this issue
needs-infoStateWaiting on reporter for more information
ready-for-agentStateFully specified, ready for AFK agent
ready-for-humanStateRequires human implementation
wontfixStateWill not be actioned

Every issue should have exactly one state label and one category label. If an issue has conflicting state labels (e.g. both needs-triage and ready-for-agent), flag the conflict and ask the maintainer which state is correct before doing anything else. Provide a recommendation.

State Machine

Current StateCan transition toWho triggers itWhat happens
unlabeledneeds-triageSkill (on first look)Issue needs maintainer evaluation. Skill applies label after presenting recommendation.
unlabeledready-for-agentMaintainer (via skill)Issue is already well-specified and agent-suitable. Skill writes agent brief comment, applies label.
unlabeledready-for-humanMaintainer (via skill)Issue requires human implementation. Skill writes a brief comment summarizing the task, applies label.
unlabeledwontfixMaintainer (via skill)Issue is spam, duplicate, or out of scope. Skill closes with comment (and writes .out-of-scope/ for enhancements).
needs-triageneeds-infoMaintainer (via skill)Issue is underspecified. Skill posts triage notes capturing progress so far + questions for reporter.
needs-triageready-for-agentMaintainer (via skill)Grilling session complete, agent-suitable. Skill writes agent brief comment, applies label.
needs-triageready-for-humanMaintainer (via skill)Grilling session complete, needs human. Skill writes a brief comment summarizing the task, applies label.
needs-triagewontfixMaintainer (via skill)Maintainer decides not to action. Skill closes with comment (and writes .out-of-scope/ for enhancements).
needs-infoneeds-triageSkill (detects reply)Reporter has replied. Skill surfaces to maintainer for re-evaluation.

An issue can only move along these transitions. The maintainer can override any state directly (see Quick State Override below), but the skill should flag if the transition is unusual.

Invocation

The maintainer invokes /github-triage then describes what they want in natural language. The skill interprets the request and takes the appropriate action.

Example requests:

  • "Show me anything that needs my attention"
  • "Let's look at #42"
  • "Move #42 to ready-for-agent"
  • "What's ready for agents to pick up?"
  • "Are there any unlabeled issues?"

Workflow: Show What Needs Attention

When the maintainer asks for an overview, query GitHub and present a summary grouped into three buckets:

  1. Unlabeled issues — new, no labels at all. These have never been triaged.
  2. needs-triage issues — maintainer needs to evaluate or continue evaluating.
  3. needs-info issues with new activity — the reporter has commented since the last triage notes comment. Check comment timestamps to determine this.

Display counts per group. Within each group, show issues oldest first (longest-waiting gets attention first). For each issue, show: number, title, age, and a one-line summary of the issue body.

Let the maintainer pick which issue to dive into.

Workflow: Triage a Specific Issue

Step 1: Gather context

Before presenting anything to the maintainer:

  • Read the full issue: body, all comments, all labels, who reported it, when
  • If there are prior triage notes comments (from previous sessions), parse them to understand what has already been established
  • Explore the codebase to build context — understand the domain, relevant interfaces, and existing behavior related to the issue
  • Read .out-of-scope/*.md files and check if this issue matches or is similar to a previously rejected concept

Step 2: Present a recommendation

Tell the maintainer:

  • Category recommendation: bug or enhancement, with reasoning
  • State recommendation: where this issue should go, with reasoning
  • If it matches a prior out-of-scope rejection, surface that: "This is similar to .out-of-scope/concept-name.md — we rejected this before because X. Do you still feel the same way?"
  • A brief summary of what you found in the codebase that's relevant

Then wait for the maintainer's direction. They may:

  • Agree and ask you to apply labels → do it
  • Want to flesh it out → start a /domain-model session
  • Override with a different state → apply their choice
  • Want to discuss → have a conversation

Step 3: Bug reproduction (bugs only)

If the issue is categorized as a bug, attempt to reproduce it before starting a /domain-model session. This will vary by codebase, but do your best:

  • Read the reporter's reproduction steps (if provided)
  • Explore the codebase to understand the relevant code paths
  • Try to reproduce the bug: run tests, execute commands, or trace the logic to confirm the reported behavior
  • If reproduction succeeds, report what you found to the maintainer — include the specific behavior you observed and where in the code it originates
  • If reproduction fails, report that too — the bug may be environment-specific, already fixed, or the report may be inaccurate
  • If the report lacks enough detail to attempt reproduction, note that — this is a strong signal the issue should move to needs-info

The reproduction attempt informs the /domain-model session and the agent brief. A confirmed reproduction with a known code path makes for a much stronger brief.

Step 4: /domain-model session (if needed)

If the issue needs to be fleshed out before it's ready for an agent, interview the maintainer to build a complete specification. Use the /domain-model skill.

Step 5: Apply the outcome

Depending on the outcome:

  • ready-for-agent — post an agent brief comment (see AGENT-BRIEF.md)
  • ready-for-human — post a comment summarizing the task, what was established during triage, and why it needs human implementation. Use the same structure as an agent brief but note the reason it can't be delegated to an agent (e.g. requires judgment calls, external system access, design decisions, or manual testing).
  • needs-info — post triage notes with progress so far and questions for the reporter (see Needs Info Output below)
  • wontfix (bug) — post a polite comment explaining why, then close the issue
  • wontfix (enhancement) — write to .out-of-scope/, post a comment linking to it, then close the issue (see OUT-OF-SCOPE.md)
  • needs-triage — apply the label. Optionally leave a comment if there's partial progress to capture.

Workflow: Quick State Override

When the maintainer explicitly tells you to move an issue to a specific state (e.g. "move #42 to ready-for-agent"), trust their judgment and apply the label directly.

Still show a confirmation of what you're about to do: which labels will be added/removed, and whether you'll post a comment or close the issue. But skip the /domain-model session entirely.

If moving to ready-for-agent without a /domain-model session, ask the maintainer if they want to write a brief agent brief comment or skip it.

Needs Info Output

When moving an issue to needs-info, post a comment that captures the interview progress and tells the reporter what's needed:

markdown
## Triage Notes

**What we've established so far:**

- point 1
- point 2

**What we still need from you (@reporter):**

- question 1
- question 2

Include everything resolved during the /domain-model session in "established so far" — this work should not be lost. The questions for the reporter should be specific and actionable, not vague ("please provide more info").

Resuming Previous Sessions

When triaging an issue that already has triage notes from a previous session:

  1. Read all comments to find prior triage notes
  2. Parse what was already established
  3. Check if the reporter has answered any outstanding questions
  4. Present the maintainer with an updated picture: "Here's where we left off, and here's what the reporter has said since"
  5. Continue the /domain-model session from where it stopped — do not re-ask resolved questions

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Github Triage AI skill do?

Triage GitHub issues through a label-based state machine. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.

Why use Github Triage on TypingMind?

Because you install it once and use it with any model. Github Triage is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Github Triage in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Teaonly/SKILL.mk/tree/main/examples/github-triage. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Github Triage?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Github Triage?

As many as you like. As long as a model supports skills, you can use Github Triage with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Github Triage AI skill free?

Yes. It is published on GitHub by Teaonly under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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