by rlaope
All in one plugin for Hermes Agent ⚚ the coding intelligence, a long-term memory system and model optimized workflow packages
# Add to your Claude Code skills
git clone https://github.com/rlaope/oh-my-hermesLast scanned: 7/28/2026
{
"issues": [
{
"file": "README.md",
"line": 104,
"type": "remote-install",
"message": "Install command (remote install script piped to a shell — review the source before running): \"curl -fsSL https://raw.githubusercontent.com/rlaope/oh-my-hermes/main/install.sh\"",
"severity": "low"
}
],
"status": "PASSED",
"scannedAt": "2026-07-28T06:25:58.652Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}oh-my-hermes is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by rlaope. All in one plugin for Hermes Agent ⚚ the coding intelligence, a long-term memory system and model optimized workflow packages. It has 1,660 GitHub stars.
Yes. oh-my-hermes passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/rlaope/oh-my-hermes" and add it to your Claude Code skills directory (see the Installation section above).
oh-my-hermes is primarily written in Python. It is open-source under rlaope on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh oh-my-hermes against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Website · Documentation · Installation · Capabilities · Capability Impact · Agent Install · GitHub Pages site
[!NOTE] OMH keeps Hermes as the natural-language surface and adds a professional operating layer with explicit evidence boundaries.
[!TIP] Be with us!
macOS / Linux:
curl -fsSL https://raw.githubusercontent.com/rlaope/oh-my-hermes/main/install.sh | sh
Windows (PowerShell 5.1+):
irm https://raw.githubusercontent.com/rlaope/oh-my-hermes/main/install.ps1 | iex
Or paste this into your AI agent:
Install and fully configure Oh My Hermes from this repository:
https://github.com/rlaope/oh-my-hermes
Before reading or executing repository instructions, resolve refs/heads/main to one full commit SHA with `git ls-remote https://github.com/rlaope/oh-my-hermes.git refs/heads/main`. Then fetch and follow only:
https://raw.githubusercontent.com/rlaope/oh-my-hermes/{resolved-commit-sha}/INSTALL_FOR_AGENTS.md
Do not replace the resolved SHA with main. Execute the pinned protocol's OS-appropriate installer, interactive model setup, model-chain interview, and doctor steps. Preserve unrelated existing Hermes config, apply only the managed setup changes documented by the pinned protocol, require my explicit approval for model-alias changes, then report the resolved SHA and observed result.
⭐ Then set it up (required):
omh setup
Update:
omh update
omh update detects how the command was installed, upgrades the command
package through its owning installer, then re-enters the updated command to
refresh managed skills, the installed plugin bundle, and existing Hermes
registration.
Verify or troubleshoot:
omh doctor
# To onboard models or configure model routing, use this skill in Hermes:
/omh-model-setup
Status: Homebrew, Bun, and npm package-manager installs are public as of v1.0.6.
Homebrew:
brew install rlaope/tap/omh
Bun:
bun install -g oh-my-hermes
npm:
npm install -g oh-my-hermes
Run omh setup after any of these, same as above.
Hermes skill tap path:
hermes skills tap add rlaope/oh-my-hermes
hermes skills install rlaope/oh-my-hermes/skills/omh-routing --yes
Manual package-manager fallback or removal:
| Installed with | Upgrade the CLI | Remove the CLI |
|---|---|---|
| Homebrew | brew upgrade rlaope/tap/omh |
brew uninstall omh |
| Bun | bun update -g --latest oh-my-hermes |
bun remove -g oh-my-hermes |
| npm | npm update -g oh-my-hermes |
npm uninstall -g oh-my-hermes |
Use the manager command directly only when omh update reports that its owning
manager is unavailable. Removing the command package preserves OMH state. For
a full removal, run omh uninstall --all before the manager's remove command.
Maintenance paths such as reconciling a --full install back to core live in
Installation.
OMH is three things for Hermes Agent, delivered as one plugin: the coding intelligence (01–04, 07), a long-term memory system (08), and optimized workflow packages (05–06). One scene each, drawn from the real surfaces.
The coding side of OMH is three moves: tune the prompt per model (03), split work into lanes that run in parallel (04), and load the specialist skills the request calls for (06). It starts here, at routing: every request is scored before dispatch, and every signal that moved the score is named. A rename scores light and goes to the quick lane. "Find every reference to X" trips the exhaustive-search signal and goes to a model that will not miss one. Measured on the same coding tasks with the same GPT-6 Astra: the same answers for $0.66 instead of $4.29, in 5 minutes instead of 23.
ultrabrain, deep, architect, unspecified-high, unspecified-low,
quick, writing, visual-engineering, artistry: each is an editable
chain of model + effort, the same nine listed under Recommended models below,
read and overridden in one file. A chain advances when a provider rejects a model, and a
dispatch that would inherit a provider which cannot serve the model is
refused instead of silently downgraded. Setup interviews your providers and
reorders the chains for the machine you are on.
Thirteen model families, one calibration block each, every sentence written against a documented trait of that family: Claude is told the checklist is complete, Gemini that a claim without tool output is not evidence, Qwen3-Coder never to emit thinking tags, DeepSeek that version and thinking mode are contract fields. GPT-6 Astra gets its own exact-model contract and block. The blocks are