Init Mode logo

Init Mode

CommunityPopular
bradygaster
init-mode

Team initialization flow (Phase 1 proposal + Phase 2 creation)

Overview

Publisherbradygaster
Repositorysquad
Skill nameinit-mode
Stars
3.3K
Forks
506
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 bradygaster on GitHub. Read the source before you install it.

Installation

Install the Init Mode 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/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/init-mode
  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/bradygaster/squad.git /tmp/squad
mkdir -p .claude/skills
cp -r /tmp/squad/packages/squad-cli/templates/skills/init-mode .claude/skills/init-mode
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Init Mode 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 Init Mode 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 Init Mode 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.

Context

Init Mode activates when .squad/team.md does not exist, or exists but has zero roster entries under ## Members. The coordinator proposes a team (Phase 1), waits for user confirmation, then creates the team structure (Phase 2).

Patterns

Phase 1: Propose the Team

No team exists yet. Propose one — but DO NOT create any files until the user confirms.

  1. Identify the user. Run git config user.name to learn who you're working with. Use their name in conversation (e.g., "Hey {user}, what are you building?"). Store their name (NOT email) in team.md under Project Context. Never read or store git config user.email — email addresses are PII and must not be written to committed files.
  2. Ask: "What are you building? (language, stack, what it does)"
  3. Cast the team. Before proposing names, run the Casting & Persistent Naming algorithm (see that section):
    • Determine team size (typically 4–5 + Scribe).
    • Default to descriptive names (Lead, Frontend, Backend, Tester, etc.) unless the user requests a themed universe.
    • If the user requests a specific universe (built-in or custom), allocate character names from that universe. For custom universes not in the allowlist, use your knowledge of the source material and apply spoiler-safety rules.
    • If the user asks for themed names without specifying a universe, auto-select from built-in universes using the scoring algorithm (size_fit + shape_fit + resonance_fit + LRU).
    • Scribe is always "Scribe" — exempt from casting.
    • Ralph is always "Ralph" — exempt from casting.
  4. Propose the team with their cast names. Example (names will vary per cast):
🏗️  Lead         — Lead          Scope, decisions, code review
⚛️  Frontend     — Frontend Dev  React, UI, components
🔧  Backend      — Backend Dev   APIs, database, services
🧪  Tester       — Tester        Tests, quality, edge cases
📋  Scribe       — (silent)      Memory, decisions, session logs
🔄  Ralph        — (monitor)     Work queue, backlog, keep-alive
  1. Use the ask_user tool to confirm the roster. Provide choices so the user sees a selectable menu:
    • question: "Look right?"
    • choices: ["Yes, cast this team", "Add someone", "Change a role"]

⚠️ STOP. Your response ENDS here. Do NOT proceed to Phase 2. Do NOT create any files or directories. Wait for the user's reply.

Phase 2: Create the Team

Trigger: The user replied to Phase 1 with confirmation ("yes", "looks good", or similar affirmative), OR the user's reply to Phase 1 is a task (treat as implicit "yes").

If the user said "add someone" or "change a role," go back to Phase 1 step 3 and re-propose. Do NOT enter Phase 2 until the user confirms.

  1. Create the .squad/ directory structure (see .squad/templates/ for format guides or use the standard structure: team.md, routing.md, ceremonies.md, decisions.md, decisions/inbox/, casting/, agents/, orchestration-log/, skills/, log/).

Casting state initialization: Copy .squad/templates/casting-policy.json to .squad/casting/policy.json (or create from defaults). Create registry.json (entries: persistent_name, universe, created_at, legacy_named: false, status: "active") and history.json (first assignment snapshot with unique assignment_id).

Seeding: Each agent's history.md starts with the project description, tech stack, and the user's name so they have day-1 context. Agent folder names are the cast name in lowercase (e.g., .squad/agents/ripley/). The Scribe's charter includes maintaining decisions.md and cross-agent context sharing.

Team.md structure: team.md MUST contain a section titled exactly ## Members (not "## Team Roster" or other variations) containing the roster table. This header is hard-coded in GitHub workflows (squad-heartbeat.yml, squad-issue-assign.yml, squad-triage.yml, sync-squad-labels.yml) for label automation. If the header is missing or titled differently, label routing breaks.

Merge driver for append-only files: Create or update .gitattributes at the repo root to enable conflict-free merging of .squad/ state across branches:

.squad/decisions.md merge=union
.squad/agents/*/history.md merge=union
.squad/log/** merge=union
.squad/orchestration-log/** merge=union

The union merge driver keeps all lines from both sides, which is correct for append-only files. This makes worktree-local strategy work seamlessly when branches merge — decisions, memories, and logs from all branches combine automatically.

  1. Say: "✅ Team cast. Try: '{FirstCastName}, set up the project structure'"

  2. Post-setup input sources (optional — ask after team is created, not during casting):

    • PRD/spec: "Do you have a PRD or spec document? (file path, paste it, or skip)" → If provided, follow PRD Mode flow
    • GitHub issues: "Is there a GitHub repo with issues I should pull from? (owner/repo, or skip)" → If provided, follow GitHub Issues Mode flow
    • Human members: "Are any humans joining the team? (names and roles, or just AI for now)" → If provided, add per Human Team Members section
    • Copilot agent: "Want to include @copilot? It can pick up issues autonomously. (yes/no)" → If yes, follow Copilot Coding Agent Member section and ask about auto-assignment
    • These are additive. Don't block — if the user skips or gives a task instead, proceed immediately.

Examples

Example flow:

  1. Coordinator detects no team.md → Init Mode
  2. Runs git config user.name → "{user}"
  3. Asks: "Hey {user}, what are you building?"
  4. User: "TypeScript CLI tool with GitHub API integration"
  5. Coordinator uses descriptive naming by default
  6. Proposes: Lead (Lead), Frontend (Frontend Dev), Backend (Backend Dev), Tester (Tester), Scribe, Ralph
  7. Uses ask_user with choices → user selects "Yes, cast this team"
  8. Coordinator creates .squad/ structure, initializes casting state, seeds agents
  9. Says: "✅ Team cast. Try: 'Lead, set up the project structure'"

Anti-Patterns

  • ❌ Creating files before user confirms Phase 1
  • ❌ Mixing agents from different universes in the same cast
  • ❌ Skipping the ask_user tool and assuming confirmation
  • ❌ Proceeding to Phase 2 when user said "add someone" or "change a role"
  • ❌ Using ## Team Roster instead of ## Members as the header (breaks GitHub workflows)
  • ❌ Forgetting to initialize .squad/casting/ state files
  • ❌ Reading or storing git config user.email (PII violation)
  • ❌ Rejecting a user's universe choice because it is not in the built-in allowlist
  • ❌ Auto-selecting a themed universe when the user didn't ask for one (use descriptive names by default)

Frequently asked questions

What does the Init Mode AI skill do?

Team initialization flow (Phase 1 proposal + Phase 2 creation)

Why use Init Mode on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bradygaster/squad/tree/dev/packages/squad-cli/templates/skills/init-mode. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Init Mode?

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 Init Mode?

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

Is the Init Mode AI skill free?

Yes. It is published on GitHub by bradygaster 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇