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Oh-My-Hermes (OMH)
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Oh-My-Hermes (OMH)

Curated harness and skills pack for Hermes Agent — install once to get optimized configurations, productivity skills, and agent power-ups out of the box.

hermesharnessskills-packconfigurationproductivity
Verified 8 days ago

Skill details

For
Hermes Agent
Author
rlaope
Install
git clone https://github.com/rlaope/oh-my-hermes && follow README
Dependencies
  • Hermes Agent
  • Python 3.11+

Oh-My-Hermes (OMH)

What it is

Oh-My-Hermes (OMH) is a curated harness and skills collection for Hermes Agent. Think of it as "oh-my-zsh for Hermes" — install it once and get a set of optimized configurations, productivity-enhancing skills, and agent power-ups that maximize what Hermes can do out of the box.

Who it targets

  • New Hermes users who want a strong starting configuration without manual tuning
  • Multi-agent operators looking for a shared baseline across team members
  • Power users who want a community-maintained skills pack they can extend

What it does

  • Pre-configured harness. Optimized Hermes settings for common workflows (coding, research, writing, ops).
  • Curated skill bundle. A selection of community skills pre-wired and ready to use.
  • One-command install. Clone and run the setup script — no manual skill-by-skill installation.
  • Python-based. Easy to inspect, modify, and contribute back.
  • Active community. 61+ stars on GitHub with regular updates as of July 2026.

How to install

  1. Clone the repository: git clone https://github.com/rlaope/oh-my-hermes
  2. Follow the README for installation instructions.
  3. Restart Hermes to pick up the new configuration and skills.
  4. Review which skills are enabled and adjust for your use case.

Why it matters

Hermes Agent is powerful but comes with a blank slate. OMH gives you a opinionated starting point — the equivalent of a senior engineer's dotfiles — so you skip the configuration phase and start producing immediately. It is especially valuable for teams standardizing on a shared Hermes setup.

Limitations

  • Opinionated — may conflict with existing custom configurations.
  • Skills pack may include capabilities you do not need (review before deploying).
  • Community-maintained — verify skill quality before using in production.
  • Python dependency management can be tricky across different environments.