Overview
OpenRigor is a clean-room, open-source implementation of a persistent AI-agent workspace. It is a chat-first product that can plan work, run tools in an isolated workspace, stream progress, survive disconnects, and return inspectable files. The repository is an implementation workspace created from the ClawsGO public-product research snapshot, and it does not copy ClawsGO code, branding, screenshots, text, or protected visual assets. The goal is behavioral and architectural equivalence where the behavior is publicly observable.
The current status includes a completed research baseline and a working local alpha with real Codex app-server execution, streamed answers, reasoning, tools, and files, SSE replay, stop/interrupt, and same-thread follow-up turns. The interface is an original desktop-first operator console with preview-before-send examples, Light/Dark/System themes, Codex-style Sol/Terra/Luna and low through max controls, a separate Ultra multi-agent mode, knowledge and skill selectors, structured reasoning and tool output, and a browser-side recent-task list. Scope is one local user and one configured workspace. Recent conversations can restore their complete in-memory run chain, but runs and events are still process-memory only; attachments, approvals, queued follow-ups, and restart-safe server history are not implemented yet.
Pricing
Free
Detailed plans have not been confirmed in our catalog. Check the official website for current limits and billing terms.
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Use Cases
- Developers use OpenRigor to run a local Codex alpha with real Codex app-server execution.
- Developers use OpenRigor to preview and edit a task draft before it becomes a run.
- Developers use OpenRigor to choose model and routing controls.
- Developers use OpenRigor to inspect execution by following run status and expanding tool steps.
- Developers use OpenRigor to run a deterministic UI/API demo without Codex.
Features
Maintain persistent AI agent workspaces
Keep agent runs durable
Run tools in sandboxes
Replay SSE event streams
Deliver generated artifacts
Reviews
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