Starting a New Project with Squad

Try this to bootstrap a modern web app:

Set up Squad for a new React + Node.js app

Try this to initialize with deployment target:

Initialize a team for a task management app that can run in Azure Web App PaaS

Start from zero: new directory, new repo, full team in under a minute. Squad analyzes your description and assembles the right specialists.

1. Create the Repo

mkdir my-app && cd my-app
git init

2. Install Squad

npx github:bradygaster/squad

✅ .github/agents/squad.agent.md (v0.2.0)
✅ .github/workflows/ (10 workflows)
✅ .ai-team-templates/
✅ .ai-team/skills/ (starter skills)
✅ .ai-team/ceremonies.md
✅ .gitattributes (merge=union rules)

Squad is ready.

Next steps:
  1. Open Copilot:  copilot
  2. Select Squad from the /agents list
  3. Tell it what you're building

3. Open Copilot and Describe Your Project

copilot

Select Squad from the /agents list. Squad greets you:

Hey Jordan, what are you building?

Describe the project — language, stack, what it does:

> I'm building a CLI tool in Go that monitors AWS costs and sends
> Slack alerts when spending exceeds thresholds.

4. Confirm the Team

Squad proposes a team. Names come from a fictional universe:

Here's your team:

🏗️  Danny    — Lead          Scope, decisions, code review
🔧  Rusty    — Backend Dev   Go, AWS SDK, infrastructure
⚛️  Linus    — Frontend Dev  CLI interface, output formatting
🧪  Basher   — Tester        Tests, edge cases, quality
📋  Scribe   — (silent)      Memory, decisions, session logs

Look right? Say yes, add someone, or change a role.
(Or just give me a task to start!)

You can adjust the team or skip straight to work (which is implicit confirmation):

> Yes. Rusty, set up the Go module and project structure.

Squad creates .ai-team/ (roster, charters, histories, routing rules, casting state) and spawns Rusty:

🔧 Rusty — setting up Go module and project structure

Rusty is on it.

5. Give a Bigger Task — Parallel Fan-Out

Use the word “team” to trigger parallel work:

> Team, build the cost monitoring feature. We need an AWS client
> that pulls Cost Explorer data and a Slack notifier that sends
> alerts when thresholds are exceeded.

Squad decomposes the work and launches agents simultaneously:

🏗️ Danny   — reviewing requirements, defining interfaces
🔧 Rusty   — building AWS Cost Explorer client
⚛️ Linus   — building Slack notification module
🧪 Basher  — writing test cases from requirements
📋 Scribe  — logging session

All five agents work at the same time in separate context windows.

6. Check Decisions

After agents finish, see what they decided:

> Show me the decisions

### 2025-07-15: AWS Cost Explorer polling interval
**By:** Rusty
**What:** Poll every 6 hours via cron, not real-time
**Why:** Cost Explorer data updates ~3x/day, more frequent polling wastes API calls

### 2025-07-15: Slack message format
**By:** Linus
**What:** Use Block Kit for alert messages with cost breakdown table
**Why:** Rich formatting, actionable buttons for drill-down

Every agent reads these decisions before their next task. As the list grows, the team self-aligns.

7. Commit Your Team

git add .ai-team/ .ai-team-templates/ .github/ .gitattributes
git commit -m "Add Squad team"

Commit .ai-team/ — it’s your team’s brain. Anyone who clones the repo gets the full team with all their accumulated knowledge.

Tips

  • First session is the slowest. Agents have no history yet. After 2–3 sessions, they know your conventions and stop asking redundant questions.
  • Agents improve over sessions. Each agent appends what it learned to its history.md. By week 2, they know your file structure, naming patterns, and preferences.
  • Say “team” for parallel work. Naming a specific agent sends work to just that agent.
  • Directives are sticky. Say "Always use structured logging" and it’s captured permanently in decisions.md.