by Human-Agent-Society · Codex Skill · ★ 961
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 961 |
| Forks | 121 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 67/100 |
| Open Issues | 19 |
| Last Updated | 2026-09-08 |
| Created | 2026-03-16 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~15k |
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.
These tools work well together with CORAL for enhanced workflows:
Looking for a CORAL alternative? If you're comparing CORAL with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Autonomous software engineering fleet of AI agents for production-grade PRs on AgentField: plan, code, test, a
A curated list of autonomous improvement loops, research agents, and autoresearch-style systems inspired by Ka
List of agent orchestrators
Web, Desktop & Mobile client and orchestrator for Codex, Claude Code, OpenCode, Pi, Cursor, Grok, Antigravity,
TAKT Agent Koordination Topology - Define how AI agents coordinate, where humans intervene, and what gets reco
Fully Autonomous AI Research System with Self-Evolution, built natively on Claude Code
Explore other popular codex skill tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: