Spin up a self-managing AI agent team in minutes.
One CLI. No server. Agents that plan, execute, and talk to each other — while you sleep.
中文文档 | Quick Start | Install | Commands | Workspace Layout
agencycli is a lightweight CLI for building and operating teams of AI agents. You define the org chart once — teams, roles, projects, skills — and agents assemble their own context, pick up tasks, and run autonomously on a heartbeat schedule.
The killer feature: agents can hire, message, and coordinate with each other. Your PM agent can create a task for the dev agent, the dev agent can ask a human for confirmation before merging, and the QA agent wakes up every 30 minutes to scan for open PRs — all without you lifting a finger.
Context composes from two axes — role (horizontal) and project (vertical). Every agent gets agency → team → role → project context merged automatically at hire time. Change a role prompt once; every agent with that role gets it on the next sync.
Agents wake up on a schedule, drain their task queue, then — when the queue is empty — execute a wakeup routine (wakeup.md) to proactively find new work. Time windows, active days, cron schedules — all configurable. Startup jitter prevents thundering herd when the scheduler restarts.
Every participant (agent or human) has an inbox. Messages are non-blocking and async — unread messages are auto-injected at the top of every wakeup prompt. confirm-request creates a blocking gate: the task pauses until you decide.
Bundle your whole agency setup — teams, roles, skills, agent playbooks, project blueprints — into a single .tar.gz. Share it. Apply it to a new project in one command.
Agents run inside isolated Docker containers. No accidental host damage, no credential leaks, no runaway processes. The workspace and agencycli binary are mounted read-write; credentials are mounted read-only.
Skills are a SKILL.md (YAML frontmatter + Markdown prompt) plus optional scripts, deployed into every agent that has the skill bound. Define once, attach to a role, propagate automatically on sync.
The easiest way — send this to Claude Code or any AI coding agent, and it will handle the entire installation and configuration for you:
Follow https://raw.githubusercontent.com/chenhg5/agencycli/refs/heads/main/INSTALL.md to install and configure agencycli.
npm install -g @agencycli/agencycli # npm, no Go required
go install github.com/chenhg5/agencycli/cmd/agencycli@latest # Go
# From source
git clone https://github.com/chenhg5/agencycli && cd agencycli && make install# 1. Create a workspace (generates .gitignore + agency-prompt.md)
agencycli create agency --name "MyAgency"
cd MyAgency
# 2. Apply a project blueprint — hires all agents + configures heartbeats + installs playbooks
agencycli create project --name "my-service" --blueprint default
agencycli project apply --project my-service
# 3. Start the scheduler — agents wake up and run autonomously
agencycli scheduler start
# 4. Check in
agencycli inbox list # task confirmations waiting for your decision
agencycli inbox messages # async messages from agents
agencycli task list --project my-service --agent pmagencycli is a runtime layer, not an SDK. Agents are whatever CLI tool you already use:
| Agent runtime | --model |
|---|---|
| Claude Code | claudecode |
| OpenAI Codex | codex |
| Gemini CLI | gemini |
| Cursor | cursor |
| Qoder | qoder |
| OpenCode | opencode |
| iFlow | iflow |
| Any CLI tool | generic-cli |
Mix models freely — your PM can run on Claude, your dev agents on Codex, your writer on Gemini. Each gets its context in the exact format its runtime expects.
agencycli
├── overview # dashboard: agents, teams, skills, inbox
├── create agency / team / role / project # scaffold your org
├── hire / fire / sync # manage agents
├── task add / list / done / confirm-request# task queue (7-state lifecycle)
├── inbox send / messages / reply / fwd # async messaging
├── scheduler start / stop / status # heartbeat scheduler
├── cron add / list / delete # scheduled tasks
├── template pack / info # share your setup
└── --dir <path> # work on any agency from anywhere
→ Full command reference
→ Workspace layout
→ Docker sandbox
Those are frameworks — you write Python to wire agents together. agencycli is infrastructure — you write Markdown and YAML. Agents are whatever CLI tool you already use. No SDK, no lock-in, no server to run.
| agencycli | Framework-based | |
|---|---|---|
| Agent runtime | Your existing CLI tool | Framework's agent loop |
| Config format | Markdown + YAML | Python code |
| Multi-model | Any CLI, mix freely | Usually one SDK |
| Context management | Layered, auto-merged | Manual prompt assembly |
| Server required | No | Often yes |
MIT