chenhg5

chenhg5 / agencycli

Public

Lightweight CLI to build self-managing AI agent teams. Define roles, skills & projects in Markdown+YAML — agents run autonomously on a heartbeat schedule, talk to each other via inbox, and delegate tasks. Works with Claude Code, Codex, Gemini, Cursor & more.

19
0
100% credibility
Found Mar 22, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

AgencyCLI is a command-line tool for setting up and running teams of autonomous AI coding agents that self-organize, execute tasks, communicate via inboxes, and operate on schedules without servers.

How It Works

1
🔍 Discover AI helpers

You hear about a simple way to build a team of smart AI assistants that work together on your projects without constant babysitting.

2
📦 Get the tool

Download and set up the easy command-line helper with one quick install—no complicated setup needed.

3
🏢 Create your agency

Make a new workspace for your AI team, like setting up a virtual office where everyone knows their place.

4
👥 Build teams and roles

Define teams like engineering or marketing, and roles like developer or writer, so each AI knows exactly what to do.

5
📁 Start a project

Set up a new project folder with ready-made blueprints that automatically hire the right AI helpers.

6
🤖 Launch the team

Turn on the heartbeat scheduler, and your AI agents wake up, grab tasks, chat with each other, and get to work.

7
📨 Check in anytime

Peek at the inbox for updates or approvals, reply if needed, and let the team handle the rest.

Autonomous success

Your projects move forward on their own while you sleep, with AIs planning, coding, reviewing, and coordinating perfectly.

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Star Growth

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AI-Generated Review

What is agencycli?

Agencycli is a Go CLI for assembling self-managing AI agent teams without servers or SDK lock-in. Define teams, roles, projects, and skills in Markdown+YAML; agents wake on heartbeat schedules, process task queues, message via inboxes, and delegate autonomously using tools like Claude Code, Codex, Gemini CLI, or Cursor. Docker sandboxes keep runs isolated, with templates for packaging setups.

Why is it gaining traction?

It sidesteps Python frameworks like CrewAI by treating agents as your existing CLI tools—no custom loops or prompt assembly. Heartbeat autonomy, inter-agent inboxes, and cron jobs deliver hands-off coordination, while context grids auto-merge role+project prompts on sync. Lightweight like github lightweight charts python libs, it mixes models freely and runs anywhere.

Who should use this?

Dev teams building AI-driven repos, PMs delegating code reviews or QA via agents, or solo devs wanting scheduled workflows for PR scans and task handoffs. Perfect for agencyclients juggling Claude/Cursor pipelines without agencyclick login hassles or heavy setups.

Verdict

Worth a spin for lightweight AI teams—promising at 19 stars but 1.0% credibility signals early days with basic tests. Strong docs and no-server design outweigh maturity gaps; fork or contribute if it clicks.

(198 words)

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