holmesgpt: SRE Agent - CNCF Sandbox Project

by HolmesGPT · Agent Tool · ★ 3.8k

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Security audit verdict: SAFE · quality 52/100

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.

aiopschatbotchatopsdevopsdevops-toolsincidentincident-managementincident-responsejirakubernetes

Quick Facts

Stars3,806
Forks574
LanguagePython
CategoryAgent Tool
LicenseApache-2.0
Quality Score52/100
Open Issues464
Last Updated2026-11-06
Created2024-05-30
Platformsk8s, python
Est. Tokens~17k

About holmesgpt

HolmesGPT — The CNCF SRE Agent Installation | Docs | Open-source AI agent for investigating production incidents and finding root causes. Works with any stack — Kubernetes, VMs, cloud providers, databases, and SaaS platforms. We are a Cloud Native Computing Foundation sandbox project. Originally created by Robusta.Dev, with major contributions from Microsoft.

Compatible Skills

These tools work well together with holmesgpt for enhanced workflows:

  • alibabacloud-ack-mcp-server — semantic(0.17)+complementary+rare_topics+same_lang+shared_platform (56%)
  • OpenDerisk — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (55%)
  • kubefwd — semantic(0.19)+complementary+rare_topics+similar_pop+shared_platform (51%)
  • VMware-AIops — semantic(0.16)+complementary+rare_topics+same_lang+shared_platform (50%)
  • vespper — semantic(0.53)+rare_topics+similar_pop (49%)

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How this security grade is produced

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:

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