Artificial — AI skill for Claude Code
Open source multi-agent harness for orchestrating AI workers.
How to install Artificial
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open AndreBaltazar8/artificial and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Artificial does
Open source multi-agent harness for orchestrating AI workers. Supports Claude Code, OpenAI Codex, Cursor Agent, and local models.
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README
Artificial
An open source AI agent harness for orchestrating multiple AI workers from a single dashboard. Built in Go.
Artificial lets you spawn, manage, and coordinate AI agents (Claude Code, OpenAI Codex, ACP-compatible models, local LLMs) as a team. Agents get personas, skills, communication channels, and a shared task board. You manage them from a real-time web dashboard or the REST API.
What it does
- Multi-agent orchestration — run multiple AI agents in parallel, each with their own role and persona
- Real-time dashboard — chat with agents, manage tasks on a kanban board, monitor activity
- Channel-based communication — agents can message each other and receive notifications mid-task
- Multiple backends — supports Claude Code, OpenAI Codex, ACP (Agent Communication Protocol), and local models via OpenAI-compatible APIs
- MCP integration — each worker exposes tools to its agent via Model Context Protocol
- Session persistence — stop and resume agent sessions without losing context
Architecture
┌───────────────────────────────────────────────────┐
│ svc-artificial │
│ Dashboard · REST API · WebSocket Hub │
│ SQLite DB │
└─────────┬──────────────┬─────────────┬────────────┘
│ WebSocket │ WebSocket │ WebSocket
┌─────┴──────┐ ┌────┴──────┐ ┌───┴────────┐
│ cmd-worker │ │ cmd-worker│ │ cmd-worker │
│ (Codex) │ │ (Claude) │ │ (ACP) │
│ ┌──────┐ │ │ ┌──────┐ │ │ ┌────────┐ │
│ │ GPT │ │ │ │Claude│ │ │ │Cursor/ │ │
│ │ 5.4 │ │ │ │Opus │ │ │ │opencode│ │
│ └──────┘ │ │ └──────┘ │ │ └────────┘ │
└────────────┘ └───────────┘ └────────────┘
Quick start
# Build both binaries
make build
# Start the central service (dashboard at http://localhost:4000)
make run-artificial
# In another terminal, start a worker (or spawn from the Dashboard)
make r
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