CORAL

CORAL: Open-Source Autoresearch Powered by Autonomous Coding Agents

Robust, lightweight infrastructure for multi-agent self-evolution, built for autoresearch.

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CORAL is infrastructure for autonomous AI agent organizations that run experiments, share knowledge, and continuously improve solutions. Give it a codebase and a grader, and CORAL handles the rest: isolated workspaces, safe evaluation, persistent shared state, and multi-agent collaboration. Natively integrated with Claude Code, OpenCode, Codex, Cursor Agent, and Kiro.

🔥 News

- [2026-07-08] CORAL has been accepted to COLM 2026! 🎉
- [2026-06-24] The Docker session now isolates the agent from the grader: each agent runs as an unprivileged user (manager and grader stay root), so agents can no longer read .coral/private/ (grader venv, answer keys) — not even via Bash. On the host this stays opt-in via agents.isolate_user.
- [2026-06-13] Legacy eval/grader.py grader auto-discovery is deprecated and removed — wire graders via grader.entrypoint pointing at a packaged grader. See the custom grader guide.
- [2026-06-06] CORAL v0.6.0 adds multi-island runs: partition agents into isolated islands with scoped attempts, notes, skills, heartbeat state, and migration between islands for broader exploration.
- [2026-04-24] Rubric judges — two reusable LLM-judge grader packages for open-ended tasks (reports, memos, legal analysis). See the Rubric Judges guide.
- [2026-04-03] Our paper, "CORAL: Towards Autonomous Multi-Agent Evolution for Open-Ended Discovery," is now out! Check it out on Arxiv.
- [2026-03-18] CORAL is released! Check out our blog post.

Installation

Installs the latest coral release globally via uv tool install.…