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Setup

Organization
MadAppGang
setup

Initialize Conductor with product.md, tech-stack.md, and workflow.md

Overview

PublisherMadAppGang
Repositoryclaude-code
Skill namesetup
Stars
281
Forks
26
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by MadAppGang 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.
  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/MadAppGang/claude-code.git /tmp/claude-code
mkdir -p .claude/skills
cp -r /tmp/claude-code/plugins/conductor/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.

plugin: conductor updated: 2026-01-20

<resume_capability>
  Check for conductor/setup_state.json FIRST.
  If exists with status != "complete":
  1. Load saved answers
  2. Resume from last incomplete section
  3. Show user what was already collected
</resume_capability>

<question_protocol>
  - Ask questions SEQUENTIALLY (one at a time)
  - Maximum 5 questions per section
  - Always include "Type your own answer" option
  - Use AskUserQuestion with appropriate question types
  - Save state after EACH answer (for resume)
</question_protocol>

<validation_first>
  Before any operation:
  1. Check if conductor/ already exists
  2. If complete setup exists, ask: "Re-initialize or abort?"
  3. Respect .gitignore patterns
</validation_first>

</critical_constraints>

<core_principles> Never ask multiple questions at once. Wait for answer before asking next question.

<principle name="State Persistence" priority="critical">
  Save progress after each answer.
  Enable resume from any interruption point.
</principle>

<principle name="Context Quality" priority="high">
  Gather enough context to be useful.
  Don't overwhelm with excessive questions.
</principle>

</core_principles>

<phase number="2" name="Project Type Detection">
  <step>Check for existing code files (src/, package.json, etc.)</step>
  <step>Ask user: Greenfield (new) or Brownfield (existing)?</step>
  <step>For Brownfield: Scan existing code for context</step>
</phase>

<phase number="3" name="Product Context">
  <step>Ask: What is this project about? (1-2 sentences)</step>
  <step>Ask: Who is the target audience?</step>
  <step>Ask: What are the 3 main goals?</step>
  <step>Ask: Any constraints or requirements?</step>
  <step>Generate product.md from answers</step>
</phase>

<phase number="4" name="Technical Context">
  <step>Ask: Primary programming language(s)?</step>
  <step>Ask: Key frameworks/libraries?</step>
  <step>Ask: Database/storage preferences?</step>
  <step>Ask: Deployment target?</step>
  <step>Generate tech-stack.md from answers</step>
</phase>

<phase number="5" name="Guidelines">
  <step>Ask: Any specific coding conventions?</step>
  <step>Ask: Testing requirements?</step>
  <step>Generate product-guidelines.md</step>
  <step>Generate code_styleguides/general.md (always)</step>
  <step>Generate language-specific styleguides based on tech stack:
    - TypeScript/JavaScript → typescript.md, javascript.md
    - Web projects → html-css.md
    - Python → python.md
    - Go → go.md
  </step>
</phase>

<phase number="6" name="Finalization">
  <step>Copy workflow.md template</step>
  <step>Create empty tracks.md</step>
  <step>Mark setup_state.json as complete</step>
  <step>Present summary to user</step>
</phase>
**Brownfield (Existing Project):**
- Scan existing files for context
- Infer tech stack from package.json, requirements.txt, etc.
- Focus on documenting current state

</greenfield_vs_brownfield>

<question_types> Additive (Multi-Select): - "Which frameworks are you using?" [React, Vue, Angular, Other] - User can select multiple

**Exclusive (Single-Select):**
- "Primary language?" [TypeScript, Python, Go, Other]
- User picks one

**Open-Ended:**
- "Describe your project in 1-2 sentences"
- Free text response

</question_types>

<state_file_schema>

json
{
  "status": "in_progress" | "complete",
  "startedAt": "ISO-8601",
  "lastUpdated": "ISO-8601",
  "projectType": "greenfield" | "brownfield",
  "currentSection": "product" | "tech" | "guidelines",
  "answers": {
    "product": {
      "description": "...",
      "audience": "...",
      "goals": ["...", "...", "..."]
    },
    "tech": {
      "languages": ["TypeScript"],
      "frameworks": ["React", "Node.js"]
    }
  }
}

</state_file_schema>

<completion_template>

Conductor Setup Complete

Project: {project_name} Type: {Greenfield/Brownfield}

Created Artifacts:

  • conductor/product.md - Project vision and goals
  • conductor/product-guidelines.md - Standards and conventions
  • conductor/tech-stack.md - Technical preferences
  • conductor/workflow.md - Development workflow (comprehensive)
  • conductor/tracks.md - Track index (empty)
  • conductor/code_styleguides/general.md - General coding principles
  • conductor/code_styleguides/{language}.md - Language-specific guides

Next Steps:

  1. Review generated artifacts and adjust as needed
  2. Use conductor:new-track to plan your first feature
  3. Use conductor:implement to execute the plan

Your project is now ready for Context-Driven Development! </completion_template>

Frequently asked questions

What does the Setup AI skill do?

Initialize Conductor with product.md, tech-stack.md, and workflow.md

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/MadAppGang/claude-code/tree/main/plugins/conductor/skills/setup. TypingMind reads its SKILL.md 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 MadAppGang 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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