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Github

Organization
beep-effect
github

Triage and orient GitHub repository, pull request, and issue work through the connected GitHub app. Use when the user asks for general GitHub help, wants PR or issue summaries, or needs repository context before choosing a more specific GitHub workflow.

Overview

Publisherbeep-effect
Repositorybeep-effect
Skill namegithub
Stars
74
Forks
14
Bundled files
3
LicenseApache-2.0
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.

  • 3 bundled files

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

  • Open source

    Published by beep-effect on GitHub. Read the source before you install it.

Installation

Install the Github 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.
  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/beep-effect/beep-effect.git /tmp/beep-effect
mkdir -p .claude/skills
cp -r /tmp/beep-effect/plugins/github/skills/github .claude/skills/github
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Github 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 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 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

Overview

Use this skill as the umbrella entrypoint for general GitHub work in this plugin. It should decide whether the task stays in repo and PR triage or should be handed off to a more specific review, CI, or publish workflow.

This plugin is intentionally hybrid:

  • Prefer the GitHub app from this plugin for repository, issue, pull request, comment, label, reaction, and PR creation workflows.
  • Use local git and gh only when the connector does not cover the job well, especially for current-branch PR discovery, branch creation, commit and push, gh auth status, and GitHub Actions log inspection.
  • Keep connector state and local checkout context aligned. If the request is about the current branch, resolve the local repo and branch before acting.

Once the intent is clear, route to the specialist skill immediately and do not keep broad GitHub triage in scope longer than needed.

Connector-First Responsibilities

Handle these directly in this skill when the request does not need a narrower specialist workflow:

  • repository orientation once the repo, PR, issue, or local checkout is identified
  • recent PR or issue triage
  • PR metadata summaries
  • PR patch inspection
  • PR comments, labels, and reactions
  • issue lookup and summarization
  • PR creation after a branch is already pushed

Prefer the GitHub app from this plugin for those flows because it provides structured PR, issue, and review-adjacent data without depending on a local checkout. If the repository is not already identifiable from the user request or local git context, ask for the repo instead of pretending there is a repo-search flow that may not exist.

Routing Rules

  1. Resolve the operating context first:
    • If the user provides a repository, PR number, issue number, or URL, use that.
    • If the request is about "this branch" or "the current PR", resolve local git context and use gh only as needed to discover the branch PR.
    • If the repository is still ambiguous after local inspection, ask for the repo identifier.
  2. Classify the request before taking action:
    • repo or PR triage: summarize PRs, issues, patches, comments, labels, reactions, or repository state
    • review follow-up: unresolved review threads, requested changes, or inline review feedback
    • CI debugging: failing checks, Actions logs, or CI root-cause analysis
    • publish changes: create or switch branches, stage changes, commit, push, and open a draft PR
  3. Route to the specialist skill as soon as the category is clear:
    • Review comments and requested changes: ../gh-address-comments/SKILL.md
    • Failing GitHub Actions checks: ../gh-fix-ci/SKILL.md
    • Commit, push, and open PR: ../yeet/SKILL.md
  4. Keep the hybrid model consistent after routing:
    • connector first for PR and issue data
    • local git and gh only for the specific gaps the connector does not cover

Default Workflow

  1. Resolve repository and item scope.
  2. Gather structured PR or issue context through the GitHub app from this plugin.
  3. Decide whether the task stays in connector-backed triage or needs a specialist skill.
  4. Route immediately when the work becomes review follow-up, CI debugging, or publish workflow.
  5. End with a clear summary of what was inspected, what changed, and what remains.

Output Expectations

  • For triage requests, return a concise summary of the repository, PR, or issue state and the next likely action.
  • For mixed requests, tell the user which specialist path you are taking and why.
  • For connector-backed write actions, restate the exact PR, issue, label, or reaction target before applying the change.
  • Never imply that GitHub Actions logs are available through the connector alone. That remains a gh workflow.

Examples

  • "Use GitHub to summarize the open PRs in this repo and tell me what needs attention."
  • "Help with this PR."
  • "Review the latest comments on PR 482 and tell me what is actionable."
  • "Debug the failing checks on this branch."
  • "Commit these changes, push them, and open a draft PR."

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 AI skill do?

Triage and orient GitHub repository, pull request, and issue work through the connected GitHub app. Use when the user asks for general GitHub help, wants PR or issue summaries, or needs repository context before choosing a more specific GitHub workflow.

Why use Github on TypingMind?

Because you install it once and use it with any model. Github 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 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/beep-effect/beep-effect/tree/main/plugins/github/skills/github. 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?

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?

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

Is the Github AI skill free?

Yes. It is published on GitHub by beep-effect under the Apache-2.0 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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