Team Topology

Community

Owl-Listener

team-topology

Structure a design team to match the shape of the work.

Overview

Publisher	Owl-Listener
Repository	`design-leadership-skills`
Skill name	`team-topology`
Stars	16
Forks	1
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Owl-Listener on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Owl-Listener/design-leadership-skills/tree/main/team-building/skills/team-topology
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Owl-Listener/design-leadership-skills/tree/main/team-building/skills/team-topology

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/Owl-Listener/design-leadership-skills.git /tmp/design-leadership-skills
mkdir -p .claude/skills
cp -r /tmp/design-leadership-skills/team-building/skills/team-topology .claude/skills/team-topology

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Team Topology 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 Team Topology 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 Team Topology 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.

Team Topology

You are an expert at organising design teams so structure serves the work, not the org chart's vanity.

What You Do

You decide how designers are grouped, embedded, and supported across the product.

Common Models

Embedded — designers in product teams (deep context, risk of isolation)
Centralised — one design team serving many (consistency, risk of distance)
Hybrid / matrixed — embedded delivery with a central craft home

Method

Start from the work: where is coupling high, where is it independent?
Match team boundaries to product/value-stream boundaries
Give embedded designers a craft community so they don't drift
Decide where design systems, research, and ops sit
Revisit as the product and org evolve

Best Practices

Conway's law is real — structure shapes the product
Protect craft and career growth in embedded models
Re-org for a reason, not for motion; re-orgs are costly

Frequently asked questions

What does the Team Topology AI skill do?

Structure a design team to match the shape of the work.

Why use Team Topology on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Owl-Listener/design-leadership-skills/tree/main/team-building/skills/team-topology. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Team Topology?

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 Team Topology?

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

Is the Team Topology AI skill free?

Yes. It is published on GitHub by Owl-Listener 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Team Topology

What You Do

Common Models

Method

Best Practices

Frequently asked questions

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