No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by sympozium-ai · Codex Skill · ★ 644
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sympozium safe to install? View the security audit →
Agents don't need better prompts. They need shared situational awareness. Sympozium is a coordination layer for multi-agent AI systems on Kubernetes — selective permeability, structured handoffs, and shared memory. Every agent is a Pod. Every policy is a CRD. Every execution is a Job. From the creator of k8sgpt and llmfit This project is under active development. API's will change, things will break. Be brave. Full documentation: deploy.sympozium.ai/docs The problem this solves: The Sticky-Note Problem — why message-passing between a
| Stars | 644 |
| Forks | 78 |
| Language | Go |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65.1347170815579/100 |
| Open Issues | 45 |
| Last Updated | 2026-09-11 |
| Created | 2026-02-23 |
| Platforms | go, k8s |
| Est. Tokens | ~4262k |
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sympozium is Run a fleet of AI agents on Kubernetes. Administer your cluster agentically. It is categorized as a Codex Skill with 644 GitHub stars.
sympozium is primarily written in Go. It covers topics such as agentic, agentic-ai, kubeclaw.
You can find installation instructions and usage details in the sympozium GitHub repository at github.com/sympozium-ai/sympozium. The project has 644 stars and 78 forks, indicating an active community.
sympozium is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to sympozium on Agent Skills Hub include sympozium, awesome_ai_agents, AgenticRAG-Survey. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: