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Setup

Organization
techwolf-ai
setup

Interactive onboarding that discovers team structure, terminology, development goals, performance and management frameworks, organizational values, and ways of working by crawling Slack, Notion, Google Drive, Gmail, and Calendar. Validates everything with the manager before persisting. Run this first before using any other skill. Also handles periodic context refreshes via /setup --refresh.

Overview

Publishertechwolf-ai
Repositoryai-first-toolkit
Skill namesetup
Stars
138
Forks
7
Bundled files
6
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • 6 bundled files

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

  • Open source

    Published by techwolf-ai on GitHub. Read the source before you install it.

Installation

Install the Setup 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/techwolf-ai/ai-first-toolkit/tree/main/plugins/people-management/skills/setup
  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/techwolf-ai/ai-first-toolkit.git /tmp/ai-first-toolkit
mkdir -p .claude/skills
cp -r /tmp/ai-first-toolkit/plugins/people-management/skills/setup .claude/skills/setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Setup 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 Setup 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 Setup 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.

Setup

Principle: "You are responsible." This skill discovers and proposes. The manager validates and decides what's accurate.

Interactive onboarding that builds the foundation every other skill relies on. Crawls connected sources, extracts context, and validates with the manager before saving.

If any MCP connector is unavailable, follow the connector unavailability protocol in references/operating-principles.md.

Prerequisites

Ensure these MCP connectors are available:

  • Slack: team channels, messages, terminology
  • Notion: performance docs, goals, team pages
  • Google Drive: 1:1 docs, meeting notes, strategy docs
  • Gmail: communication patterns
  • Google Calendar: recurring meetings, team rhythms

If any connector is missing, note it and proceed with what's available. Flag gaps at the end.

Instructions

Run phases sequentially. Each phase discovers, validates with the manager, then persists. Read references/discovery-phases.md for detailed instructions per phase.

Phase 1: Team Discovery

Identify the manager (name, role, teams), crawl sources for direct reports, validate the team list, discover internal terminology, find development goals and performance data, map ways of working, and identify customer/project context if applicable.

Persist: manager-context/manager-profile.md, manager-context/team/[name].md per report, manager-context/terminology.md, manager-context/sources.md

Phase 2: Performance & Management Frameworks

Discover how the org evaluates performance and managers. Search for existing framework docs, then walk the manager through defining their dimensions, rating scale, promotion readiness labels, review cadence, goal cadence, and management competencies. See references/performance-framework.md and references/management-framework.md for how skills use these frameworks.

Persist: manager-context/performance-framework.md, manager-context/management-framework.md

Phase 3: Organizational Values

Ask if the org has defined values. If yes, search for documentation, extract value names and behaviours, ask what signals to look for per value. If no, skip the values lens.

Persist: manager-context/values.md

Phase 4: Output Preferences

Present defaults (language, tone, file format, folder structure) and let the manager adjust.

Persist: manager-context/output-preferences.md

Phase 5: Manager's Own Context

Capture upward context: OKRs, who they report to, key deadlines.

Persist: manager-context/manager-goals.md

Phase 6: Triage Rules

Capture VIP people, hot channels, deprioritise list, privacy boundaries.

Persist: manager-context/triage-rules.md

Phase 7: Review Calendar

Capture review cycle dates, calibration sessions, promotion windows, goal cadence.

Persist: manager-context/review-calendar.md

Phase 8: Skill Preferences

Capture 1:1 style and suggest a skill rhythm (daily triage, weekly health check, etc.).

Persist: manager-context/skill-preferences.md

Phase 9: Staleness Check

Flag any discovered data older than ~2 months. Ask the manager to confirm or update.

Phase 10: Persist & Wrap Up

Save all validated context. Read references/context-templates.md for file templates. Present a summary of what was captured, flag gaps, and suggest first skills to try.

Refresh Mode

When called with --refresh:

  1. Read existing manager-context/ files
  2. Re-crawl sources for changes since last update
  3. Present only what's changed (new team members, updated goals, new terminology, stale data)
  4. Update files with confirmed changes
  5. Don't re-ask about things already validated

Important Notes

Read references/operating-principles.md for shared principles (data scope, DM flagging, connector unavailability).

  • Never assume, always validate. If something looks like a team member but you're not sure, ask.
  • Flag gaps explicitly. "I couldn't find X" is more useful than silently skipping it.
  • Stale data is worse than no data. Always check recency and flag anything older than ~2 months.

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 Setup AI skill do?

Interactive onboarding that discovers team structure, terminology, development goals, performance and management frameworks, organizational values, and ways of working by crawling Slack, Notion, Google Drive, Gmail, and Calendar. Validates everything with the manager before persisting. Run this first before using any other skill. Also handles periodic context refreshes via /setup --refresh.

Why use Setup on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/people-management/skills/setup. 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 Setup?

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 Setup?

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

Is the Setup AI skill free?

Yes. It is published on GitHub by techwolf-ai 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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