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 rlaope · Codex Skill · ★ 2.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is oh-my-hermes safe to install? View the security audit →
Hermes Desktop, with oh-my-hermes.Pick a workflow; Hermes clarifies before it builds. Hermes CLI, with oh-my-hermes.The same workflows, in your terminal. Hermes messenger app, with oh-my-hermes.Ask in a thread; the run reports back there. omh setup, one command.Installs the workflows and connects them to Hermes. oh-my-hermes English | 한국어 | 日本語 | 中文 <p align="cente
| Stars | 2,811 |
| Forks | 207 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 67.164718643052/100 |
| Open Issues | 35 |
| Last Updated | 2026-09-20 |
| Created | 2026-06-03 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~16k |
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oh-my-hermes is All in one plugin for Hermes Agent ⚚ the coding intelligence, a long-term memory system and model optimized workflow packages. It is categorized as a Codex Skill with 2.8k GitHub stars.
oh-my-hermes is primarily written in Python. It covers topics such as agent, ai, ai-agent.
You can find installation instructions and usage details in the oh-my-hermes GitHub repository at github.com/rlaope/oh-my-hermes. The project has 2.8k stars and 207 forks, indicating an active community.
oh-my-hermes is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to oh-my-hermes on Agent Skills Hub include cursor-talk-to-figma-mcp, openpencil, autocontext. 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: