TrendWhat rose on GitHub, every day at 07:30 KST · 한국어

GitHub · as of November 8, 2026 · View on GitHub →

rlaope/oh-my-hermes

AI coding agent orchestrator

+246 stars in 7 days

Run goal-based parallel execution and automatic model assignment for Hermes Agent users

If you want to split complex coding tasks into multiple steps and process them simultaneously but find it burdensome to manually select the right model for each step, this tool coordinates in between. It is an operational layer that sits on top of Hermes Agent, automatically selecting the appropriate model and technology for each task and executing them in parallel while you continue conversing with Hermes. It includes a structure that verifies actual execution evidence to ensure planned tasks are not reported as completed without proof.

Goal-based graph execution and model chains

When a user inputs a goal, it is converted into a graph composed of small nodes, and the prepared nodes are executed in parallel. Each node is assigned a suitable model chain and inference effort based on task categories such as ultrabrain, deep, or quick. If a provider rejects a specific model, it moves to the next model without silently lowering performance. Nodes running simultaneously are restricted to using different file areas to prevent conflicts.

Execution evidence-based status reporting

Before reporting that a task is complete, it verifies whether actual tests, reviews, or CI gates have passed. Status is displayed with both the stage and reliability, such as Plan · not run, Code · reported done, or Test · verified. It does not consider a task verified solely because the executor said it was done, and failed nodes undergo a recovery process before report generation. It does not read or modify the existing memory of Hermes Agent, using only OMH's own memory system.

Installation methods and requirements

On macOS and Linux, you can install by receiving the installation script with the curl command, executing it, and then entering omh setup. Windows uses the irm command in PowerShell 5.1 or higher. It can also be installed via Homebrew, Bun, or npm; when using Bun or npm, Node 18 or higher and Python 3.11 or higher must be in the PATH.

Decision criteria for Hermes Agent users

It is suitable for developers who already use Hermes Agent and need parallel execution and model optimization rather than sequential processing by a single agent. The feature that automatically selects a model suitable for each step is particularly useful for large-scale refactoring, security reviews, or changes spanning multiple files. Enabling LSP (Language Server Protocol) allows you to use definition, reference, and rename features based on code structure rather than text search. It is released under the MIT license and operates independently while maintaining compatibility with Hermes Agent.

Written by AI from this repository's README on October 29, 2026. For the facts, the original on GitHub is the reference.

By the numbers

GitHub trending history
2 days between Jun 19, when Trend began recording, and Nov 8, 2026 · first on Sep 14 · best daily rank #8 (Sep 14)

Read from GitHub, as of November 8, 2026.

Language
Python
Topics
agent · ai · ai-agent · ai-tools · claude-code · codex · hermes-agent · hermes-skill
Stars
5,242
Stars gained in 7 days
+246
Contributors
42
Forks
417
Latest release
v4.0.6 · November 5, 2026
Commits
7,450
Last commit
November 8, 2026
Open issues
10
Open pull requests
0

Related repositories

View on GitHub → · Homepage

README badge

trend.ondo.sh · GitHub daily trending #8 · September 14, 2026

The badge above shows the highest this repository has ranked on GitHub's daily trending since June 19, 2026, and the day it did. Paste the Markdown below into your README. The badge opens this page, and it updates by itself when the repository climbs higher.

[![trend.ondo.sh](https://trend.ondo.sh/github/r/rlaope--oh-my-hermes/badge.en.svg)](https://trend.ondo.sh/github/r/rlaope--oh-my-hermes/en.html)