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Greenfield Bootstrap

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cubetribe
greenfield-bootstrap

Bootstrap repo-local governance before CC_GodMode workflows run in an empty, newly initialized, or undocumented workspace. Use proactively when a project has no CLAUDE.md, no README, or no clear structure yet.

Overview

Publishercubetribe
RepositoryClaudeCode_GodMode-On
Skill namegreenfield-bootstrap
Stars
54
Forks
10
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by cubetribe on GitHub. Read the source before you install it.

Installation

Install the Greenfield Bootstrap 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/cubetribe/ClaudeCode_GodMode-On/tree/main/skills/greenfield-bootstrap
  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/cubetribe/ClaudeCode_GodMode-On.git /tmp/ClaudeCode_GodMode-On
mkdir -p .claude/skills
cp -r /tmp/ClaudeCode_GodMode-On/skills/greenfield-bootstrap .claude/skills/greenfield-bootstrap
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Greenfield Bootstrap 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 Greenfield Bootstrap 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 Greenfield Bootstrap 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.

Greenfield Bootstrap

Use this skill before the normal workflows pipeline when the current workspace is empty, newly initialized, or missing the local governance needed for safe multi-step implementation. It establishes just enough structure that @architect and @builder have firm ground to stand on.

Required outcome

  • a minimal, truthful repo-local constitution before feature work starts
  • structure that is tied to the actual project, not an invented one
  • small enough that it can realistically stay maintained

Default route

  1. Inspect the workspace and confirm what already exists (files, language, package manager, VCS state). Do not assume.
  2. Create the smallest governance surface needed:
    • a project CLAUDE.md (copy ~/.claude/templates/CLAUDE-ORCHESTRATOR.md and trim to the project) so the Orchestrator and agents have rules
    • a basic README.md with purpose + how to run, if none exists
    • a VERSION file (start at 0.1.0) as the single source of truth for the project version (written only by release sprints, ADR-004)
    • validation and release notes for the touched scope (how tests run, how releases are cut — even if "none yet")
  3. Make structure explicit — where source, config, tests, and docs belong.
  4. Hand off — once the constitution exists, continue under the normal workflows pipeline. The architecture gate for the first real feature is the same one Core Rule 3 sets for everything else: an inline 3–5 bullet brief for small/medium work, @architect only for new modules, breaking changes, cross-domain designs, or genuine uncertainty. An empty repo is not, by itself, a reason for a stricter gate than usual.

Core rules

  • Do not invent architecture the project has not chosen yet — record decisions as they are made via @architect, not preemptively.
  • Prefer durable markdown guidance over chat-only agreements.
  • Keep initial rules short enough to stay maintained.
  • Still honor CC_GodMode core rules: plan-first (ADR-004), never push without permission, delegate via the Task tool.

Hand-off targets

After bootstrapUse
First real featureworkflows → Feature workflow (Core Rule 3 architecture gate → @builder → gates)
Security-sensitive scaffoldingroute gates through @security
Throwaway spike insteadprototype-mode skill

Do not use when

  • the workspace already has clear local governance (CLAUDE.md + structure)
  • the task is only a one-off answer with no lasting repo changes

CC_GodMode — © 2025–2026 Dennis Westermann (dennis-westermann.de). Proprietary — not open source. Free for private, non-commercial use; redistribution or re-hosting outside GitHub is prohibited; attribution required. Official source: github.com/cubetribe/ClaudeCode_GodMode-On. See LICENSE.

Frequently asked questions

What does the Greenfield Bootstrap AI skill do?

Bootstrap repo-local governance before CC_GodMode workflows run in an empty, newly initialized, or undocumented workspace. Use proactively when a project has no CLAUDE.md, no README, or no clear structure yet.

Why use Greenfield Bootstrap on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cubetribe/ClaudeCode_GodMode-On/tree/main/skills/greenfield-bootstrap. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Greenfield Bootstrap?

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 Greenfield Bootstrap?

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

Is the Greenfield Bootstrap AI skill free?

It is published on GitHub by cubetribe. Check the repository for licensing terms. 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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