Open source · Declared runtime for agent swarms

Agents are unpredictable. Your swarm shouldn’t be.

Let agents reason freely inside a declared runtime: isolated workers, explicit message paths, deterministic objects, live events, API control, and supervised recovery.

Or hand it to your agent:
Read https://genswarms.com/skill.md and set up a production-ready swarm.
MIT-licensedModel-agnosticREST + WebSocket API
Other agent frameworks

Loose agents and hidden behavior.

You wire agents together with prompts, callbacks, and glue code. Message flow becomes implicit. State is scattered. When agents drift, hang, or fail, the system is hard to see and harder to control.

GenSwarms

Declared swarms, operable at runtime.

Define the agents, objects, backends, and message paths. GenSwarms runs them as isolated workers, streams every event, and keeps the swarm recoverable through supervision and API control.

A declared system around stochastic agents

Task · API · CLI work enters Swarm Manager dispatch · supervise Message graph declared edges isolated workers + objects Events · logs result · live crashed worker → supervisor restarts it

Under the hood, GenSwarms uses Elixir/OTP supervision. But the core idea is simpler: agents can behave unpredictably, while the swarm remains declared, observable, and recoverable.

01

Declare the swarm

A swarm is not just a set of agents. It is a declared system of roles, boundaries, and message paths.

The agent can be flexible. The system does not have to be implicit.

02

Keep the swarm structured while agents run

01

Isolate every agent

Every agent runs as its own worker with its own role, tools, backend, and sandbox. Stochastic behavior stays contained.

02

Recover without losing the swarm

Agents crash, tools hang, models drift, loops go off-path. Failed workers restart without bringing down the rest of the graph.

03

Watch behavior as it happens

Stream task flow, agent messages, crashes, restarts, state changes, and outputs in real time. Debug the swarm while it is alive.

04

Control the system through an API

Start swarms, send tasks, inspect state, scale workers, and stream events over REST and WebSocket.

03

The runtime surface for declared swarms

01
Pluggable backends

Local, Docker, SSH, Bwrap, and Mock.

02
Explicit message paths

Directed edges define who talks to whom.

03
Markdown skills

Plain markdown files become agent roles.

04
Supervised recovery

Failed workers restart without killing the swarm.

05
REST API and WebSocket

Programmatic control plus live event streaming.

06
Live scaling

Grow or shrink worker groups while inspecting state live.

04

Powered by a tiny agent

Each worker uses SubZeroClaw, a minimal open-source agent written in C. GenSwarms wraps that agent with the system layer a swarm needs: isolation, routing, supervision, state, observability, and API control.

~380
lines of C
54KB
binary
~2MB
RAM at runtime
SubZeroClaw on GitHub

Run a swarm in minutes.

Clone it. Declare the graph. Start the swarm.