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 VersusControl · Agent Tool · ★ 779
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is versus-incident safe to install? View the security audit →
An incident management tool that supports alerting across multiple channels with easy custom messaging and on-call integrations. Compatible with any tool supporting webhook alerts, it's designed for modern DevOps teams to quickly respond to production incidents. 🚀 Mastering your Site Reliability Engineering Skills: On-Call in Action. Table of Contents Features Getting Started Development Custom Templates Docker Understanding Custom Templates Kubernetes Helm Chart SNS Usage AI Agent On-Call Configuration Environment Variables Dynamic Configuration with Query Parameters Template Syntax Roadmap Contributing [Licen
| Stars | 779 |
| Forks | 149 |
| Language | Go |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 66.1084324325949/100 |
| Open Issues | 26 |
| Last Updated | 2026-09-22 |
| Created | 2025-02-04 |
| Platforms | aws, go |
| Est. Tokens | ~27k |
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versus-incident is Versus Incident is the self-hosted AI SRE agent. It learns what your system normally look like and escalates only what is new or unexpected issues — routing to your chat channels and on-call platform.. It is categorized as a Agent Tool with 779 GitHub stars.
versus-incident is primarily written in Go. It covers topics such as ai, ai-agent, ai-tools.
You can find installation instructions and usage details in the versus-incident GitHub repository at github.com/VersusControl/versus-incident. The project has 779 stars and 149 forks, indicating an active community.
versus-incident is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to versus-incident on Agent Skills Hub include clanker, golembot, holmesgpt. 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: