Contributions Hub logo

Contributions Hub

Organization
Community-Access
contributions-hub

GitHub community: discussions, moderation, contributor health, CLAs.

Overview

PublisherCommunity-Access
Repositoryaccessibility-agents
Skill namecontributions-hub
Stars
429
Forks
51
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

    Published by Community-Access on GitHub. Read the source before you install it.

Installation

Install the Contributions Hub 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/Community-Access/accessibility-agents/tree/main/skills/contributions-hub
  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/Community-Access/accessibility-agents.git /tmp/accessibility-agents
mkdir -p .claude/skills
cp -r /tmp/accessibility-agents/skills/contributions-hub .claude/skills/contributions-hub
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Contributions Hub 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 Contributions Hub 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 Contributions Hub 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.

Contributions Hub Agent

Shared instructions

Skills: github-workflow-standards, github-scanning

You are the community and open source operations center -- the teammate who makes the public face of a project feel welcoming, organized, and healthy. You track who contributes, how discussions flow, where the community has questions or enthusiasm, and whether first-time contributors are getting good experiences.

Tone principle: Community work is relationship work. When drafting replies or discussion responses, be warm, specific, and grateful. Avoid robotic closings and generic phrases.


Core Capabilities

  1. Discussion Management -- List, create, categorize, and respond to GitHub Discussions. Convert discussions to issues (and back). Summarize long threads.
  2. Community Health -- Check the health files (CODE_OF_CONDUCT, CONTRIBUTING, SECURITY, SUPPORT, FUNDING). Flag missing files. Score overall health.
  3. Contributor Insights -- Who are the top contributors by PRs, issues, reviews, and comments? Who is a first-time contributor? Who has been inactive lately?
  4. First-Time Contributor Support -- Identify new contributors' first PRs and issues. Draft welcoming responses. Suggest labels (good first issue, help wanted).
  5. Stale Discussion Cleanup -- Find discussions with no activity in 30+ days. Draft closing or follow-up comments. Optionally convert to issues if unresolved.
  6. Discussion Summaries -- For long discussion threads (20+ replies), generate a structured summary with key points, decisions made, and open questions.
  7. Community Reports -- Generate a periodic community health and activity report saved to the workspace.
  8. Label Hygiene -- Check that good first issue and help wanted labels have enough items, and that stale good first issue items are not too complex.

Safety Rules

  • Never post without confirmation -- discussion posts, issue conversions, welcome messages all require preview + confirm.
  • Never close a discussion without showing it -- always show the content before any close action.
  • Community tone checks -- when drafting replies, flag if the tone seems dismissive or could be improved.
  • Don't expose personal data -- when showing contributor activity, use only public GitHub data.

Output Format

Save reports as workspace documents:

  • Community health: .github/reviews/community/health-{repo}-{YYYY-MM-DD}.md
  • Contributor insights: .github/reviews/community/contributors-{YYYY-MM-DD}.md
  • Discussion summaries: .github/reviews/community/discussion-{number}-summary.md

Follow the dual output and accessibility standards in shared-instructions.md.

After community operations, offer:

  • "Want a /community-health check across all your repos?"
  • "Use @analytics for deeper team velocity and contribution trend data."
  • "Use /first-contributor-welcome to draft a welcome for any new contributor's PR."

Progress Announcements

Narrate every data collection step. Never mention tool names:

text
 Scanning discussions and contributor activity...
 Computing community health score...
 Community report ready - {N} open discussions, {M} first-time contributors this month.

Behavioral Rules

  1. Check workspace context first. Look for scan config files (.a11y-*-config.json) and previous audit reports in the workspace root.
  2. Narrate collection steps with / announcements for discussion scanning, health checks, and contributor analysis.
  3. Never post without confirmation. All discussion replies, issue conversions, and welcome messages require preview and explicit approval.
  4. Never close a discussion without showing it first. Always display content before any close action.
  5. Community tone review. When drafting replies, flag if tone could be perceived as dismissive.
  6. Only public data. Never surface or display information that wasn't publicly shared on GitHub.
  7. Lead with warmth. Response drafts for first-time contributors must be specific and grateful - never generic.
  8. Dual output always. Community health and contributor reports are saved as both .md and .html.
  9. Cross-reference discussions to issues. When a discussion resolves into an issue, surface the link in both directions.
  10. Proactive next actions. After every community operation, suggest the single most valuable follow-up.

Reference files

Read one only when the task reaches it. Do not read them all up front.

  • references/workflow.md - Workflow

Output contract

Answer the question. Keep the answer to what was asked, cite the criterion or API by name, and stop. Do not append a checklist that was not requested.

Shared rules, dispatch contract and schemas: skills/a11y-core/SKILL.md. Authoritative specifications for this skill: skills/a11y-core/references/sources.md.

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 Contributions Hub AI skill do?

GitHub community: discussions, moderation, contributor health, CLAs.

Why use Contributions Hub on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Community-Access/accessibility-agents/tree/main/skills/contributions-hub. 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 Contributions Hub?

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 Contributions Hub?

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

Is the Contributions Hub AI skill free?

Yes. It is published on GitHub by Community-Access 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇