CLI for managing AI agent squads. Status, memory, goals, feedback, and dashboard for your autonomous agents.
51
stars
312
commits
TypeScript
primary language
Aug 14, 2026
updated
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 doctorchecks both and tells you exactly what's missing.
.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
| 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 |
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.
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.
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.
303 commits
9 commits
TypeScript
99.2%
CLI for managing AI agent squads. Status, memory, goals, feedback, and dashboard for your autonomous agents.
51
stars
312
commits
TypeScript
primary language
Aug 14, 2026
updated
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 doctorchecks both and tells you exactly what's missing.
.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
| 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 |
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.
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.
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.
303 commits
9 commits
TypeScript
99.2%