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Automate Team

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ScriptedAlchemy
automate-team

Discover a repository's active core contributors and create or refresh a team mode from their engineering activity. Use for automate team or capture this repository's maintainer conventions.

Overview

PublisherScriptedAlchemy
Repositorypstack-codex
Skill nameautomate-team
Stars
77
Forks
7
Bundled files
2
LicenseMIT
Links
Skill sourceRepository
  • 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 ScriptedAlchemy on GitHub. Read the source before you install it.

Installation

Install the Automate Team 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/ScriptedAlchemy/pstack-codex/tree/main/plugins/pstack/skills/automate-team
  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/ScriptedAlchemy/pstack-codex.git /tmp/pstack-codex
mkdir -p .claude/skills
cp -r /tmp/pstack-codex/plugins/pstack/skills/automate-team .claude/skills/automate-team
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Automate Team 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 Automate Team 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 Automate Team 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.

Before following this workflow, read the Codex runtime contract.

Automate team

Discover a repository's active core contributors and build a mode from their observed engineering conventions. Use automate-maintainer for mining, attribution, group synthesis, authoring, and evaluation; read it before collecting training evidence.

Establish scope

Accept a repository URL or owner/repo, otherwise resolve the checkout's Git remote. Ask which repository only when remotes make the intended scope unclear. Verify visibility and default branch through an authenticated GitHub connector or gh. Default to the last 12 months; several repositories need separate ownership and visibility records. Linked projects supply context without expanding the crawl.

Discover the roster

Read roster discovery. Compare declared ownership with substantive authorship, reviews, design discussions, triage, and release activity. Exclude bots and distinguish active owners from inactive declared maintainers and uncertain candidates. Counts alone do not establish a core role.

Report the inferred roster with ownership evidence and proceed with well-supported accounts. Honor supplied inclusions and exclusions. Ask only when identity, an uncertain inclusion, scope, or crawl size changes the work. Do not silently reduce “all core contributors” to the busiest few. Process large rosters in batches, and record every included person and any unfinished coverage.

Mine, draft, and validate

Pass the roster, repository, window, ownership evidence, destination, and omissions to automate-maintainer. Reserve held-out evaluation cases before reading their conversations. Collect each person's record separately; delegate only when allowed, with bounded scope and output ownership.

Default to one <repo>-team-mode with individual evidence in references. Create separately invocable individual modes when requested. Preserve an existing team mode's name, category, and invocation policy.

State shared conventions, supported ownership, and disagreements. Repository requirements can apply across the team without proving each contributor's preference. Do not claim unanimity from missing evidence or resolve conflicts by activity counts.

Validate through skill-creator and automate-maintainer's evaluation procedure. Report roster and source coverage, unsupported areas, and validation limits. Land within existing authorization; creating a mode does not launch a team, authorize communication as its members, or schedule crawling.

Refresh

Compare roster and ownership with the previous evidence cutoff. Reassess departed or inactive contributors, new owners, changed conventions, and counterexamples. Preserve supported rules; remove contradicted claims. Record membership changes and the new cutoff so the next refresh can continue without repeating the crawl.

Use automate-maintainer for a supplied person or group, and automate-me for the user's conversation history.

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 Automate Team AI skill do?

Discover a repository's active core contributors and create or refresh a team mode from their engineering activity. Use for automate team or capture this repository's maintainer conventions.

Why use Automate Team on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ScriptedAlchemy/pstack-codex/tree/main/plugins/pstack/skills/automate-team. 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 Automate Team?

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 Automate Team?

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

Is the Automate Team AI skill free?

Yes. It is published on GitHub by ScriptedAlchemy 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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