Agents Squads

Your AI ops teams.

Autonomous AI agents for engineering, marketing, finance, and operations. You make the decisions. They do the work.

A squad is a team of AI agents — different models, different roles — working toward a shared goal with persistent memory. A lead briefs the team, workers execute, a verifier checks the output, and feedback from each cycle is injected into the next. Everything is a markdown file in a git repo: no database, no server, no DSL.

npm install -g squads-cli
mkdir my-workforce && cd my-workforce
git init                       # squads runs on git — it's the state and audit trail
squads init                    # scaffolds .agents/ with starter squads
squads run demo hello-world    # verify your setup end to end
squads run research/analyst    # your first real agent

Claude Code must be installed and logged in (claude /login) before the first run — squads doctor checks both and tells you exactly what's missing.

How it works

.agents/
├── BUSINESS_BRIEF.md      # Your business context — every agent reads it
├── config/SYSTEM.md       # Immutable rules shared by all agents
├── squads/                # Identity: SQUAD.md + one .md file per agent
│   ├── intelligence/
│   ├── research/
│   ├── product/
│   └── company/           # Evaluates outputs, closes the feedback loop
└── memory/                # State: strategy, goals, learnings, feedback

Before every run, an agent loads a context cascade — company strategy, squad goals, feedback from the last cycle, active work across the team — tuned by role so scanners stay lightweight and leads get the full picture. Agents that know what's been done don't duplicate work; agents that see their own feedback stop producing noise.

Squads shells out to native AI CLIs (claude, gemini, aider, …), so mixed-model teams work out of the box: a cheap model scans, a deep reasoning model builds, a mid-tier model verifies.

squads run research                             # squad conversation (plan → work → review → verify)
squads run intelligence --task "Scan X"         # directed, bounded run
squads inbox                                    # everything waiting on YOUR decision — approve / reject / defer

Documentation

| | | |---|---| | Philosophy | Why squads, why CLI-first, skills + tools | | Architecture | Context cascade, roles, phases, the feedback loop | | Configuration | Starter squads, building your own, secrets | | Running Agents | Execution modes, local limits, scaling | | Commands | Reference for humans and for agents | | Providers | Claude, Gemini, DeepSeek, and per-agent routing |

Requirements

Node.js >= 20, Git, and Claude Code (default provider — others optional). squads doctor checks your machine.

Everything runs locally: your machine, your API keys, your data. No login, no cloud, no telemetry surprises.

Development

git clone https://github.com/agents-squads/squads-cli.git
cd squads-cli
npm install
npm run build && npm link
npm test

TypeScript (strict mode), Commander.js, Vitest, tsup.

Contributing

Contributions welcome — open an issue first to discuss changes. See CONTRIBUTING.md for guidelines, and GitHub Discussions for questions and ideas. We'd love to see what you build — share your squads and skills.

License

MIT