lueurxax

Chainworks Forge — Development skill for Claude Code

Development community

Local macOS control plane for agent-driven engineering workflows with YAML runs, artifacts, and approval gates.

How to install Chainworks Forge

This entry records only its repository, not the path inside it, so there is no exact command to give. Open lueurxax/chainworks-forge and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Chainworks Forge does

Local macOS control plane for agent-driven engineering workflows with YAML runs, artifacts, and approval gates.

Alternatives in Development

  • Zeron — A native control plane for Claude Code, Codex, Cursor, Devin and other coding agents 1.4k ★
  • OpenSquirrel — For people who get distracted by agents 1.3k ★
  • Agentcontrolplane — ACP is the Agent Control Plane - a distributed agent scheduler optimized for simplicity, clarity, and control 463 ★

README

Chainworks Forge

Chainworks Forge brand hero

Chainworks Forge is a macOS SwiftUI control plane for agent-driven engineering workflows.

It is built around one idea: the primary object is not a chat thread. It is a **Run**. A run takes one idea, compiles a frozen workflow snapshot, routes work through specialized agents, pauses at explicit approval gates, stores durable artifacts, and leaves behind a truthful report of what happened.

Why This Project Exists

Chainworks Forge did not start as a generic AI chat app. It started from a practical frustration: too much engineering work was still happening through repetitive manual steps.

The first version of the idea was much closer to "a workflow orchestrator on top of `goosed`." After experimenting with Goose and seeing how interesting multi-agent coordination could become when different agents had different roles, parameters, and responsibilities, the project expanded from a thin wrapper into a real operator-facing workflow system.

The turning point was simple: once the workflows became useful, too many important actions still depended on manual coordination. That pushed the project toward a stricter model:

  • workflows instead of ad hoc prompt chains
  • explicit agent roles instead of one general-purpose assistant
  • durable artifacts and reports instead of ephemeral chat history
  • approval gates instead of invisible autonomous continuation
  • runtime abstraction instead of hard-coding one backend forever

That is why the runtime story changed as well. The project originally leaned on Goose and `goosed` as the practical execution substrate. Today, the product is moving away from Goose as the canonical transport model and toward a set of ACP-backed runtimes such as Codex, Claude Code, and Gemini. Goose still matters as legacy and compatibility infrastructure, but it is no longer the long-term center of the