by Human-Agent-Society · Codex Skill · ★ 722
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Robust, lightweight infrastructure for multi-agent self-evolution, built for autoresearch. English | 中文 Installation · Supported Agents · How It Works · Examples · Docs · Paper 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 [2026-06-13] Legacy grader
| Stars | 722 |
| Forks | 94 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 36.25/100 |
| Open Issues | 10 |
| Last Updated | 2026-06-12 |
| Created | 2026-03-16 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~13k |
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CORAL is CORAL is a robust, lightweight infrastructure for multi-agent autonomous self-evolution, built for autoresearch. Works with Claude Code, Codex, Cursor, OpenCode, Kiro, and more.. It is categorized as a Codex Skill with 722 GitHub stars.
CORAL is primarily written in Python. It covers topics such as agent-framework, agentic-ai, alpha-evolve.
You can find installation instructions and usage details in the CORAL GitHub repository at github.com/Human-Agent-Society/CORAL. The project has 722 stars and 94 forks, indicating an active community.
CORAL is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to CORAL on Agent Skills Hub include SWE-AF, bernstein, evo. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.