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hermes-atropos-environments

Create and modify RL environments for Atropos training in the hermes-agent ecosystem.

Updated May 11, 2026
Search Tags:#reinforcement-learning#rl#atropos#hermes-agent#environment-building
One-click install
npx skills add https://github.com/richardnguyen0715/keep-it-real --skill hermes-atropos-environments-richardnguyen0715
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hermes-atropos-environments
Source: https://github.com/richardnguyen0715/keep-it-real/tree/main/refer-projects/hermes-agent/optional-skills/mlops/hermes-atropos-environments
Command: npx skills add https://github.com/richardnguyen0715/keep-it-real --skill hermes-atropos-environments-richardnguyen0715

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, vllm, atropos, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill assists in the creation, review, and correction of reinforcement learning (RL) environments in the hermes-agent repository, specifically tailored for Atropos training.

Core Features & Use Cases

  • Environment Building: Facilitates the setup and configuration of RL environments for Atropos.
  • Integration: Offers tools for integrating agent loops and reward functions.
  • CLI Modes: Provides CLI commands for serving, processing, and evaluating environments.

Quick Start

Run the Skill with the 'serve' mode to set up a full training loop for Atropos.

Frequently Asked Questions about hermes-atropos-environments

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a reinforcement learning environment for Atropos training?▼

Yes, this Skill requires a Python environment with the Atropos, OpenAI, and VLLM packages installed, along with access to Atropos API or VLLM endpoints to function properly.

How do I test and debug an RL environment setup for the hermes-agent ecosystem?▼

You can test and debug RL environments for the hermes-agent ecosystem using the provided CLI commands for processing and evaluating environments to ensure proper setup and reward function integration.

Does this environment building Skill work with OpenAI and VLLM endpoints?▼

Yes, this Skill works with both OpenAI and VLLM endpoints, requiring access to Atropos API or VLLM endpoints to properly set up and execute reinforcement learning training loops.

Can I integrate custom reward functions into an Atropos environment?▼

Yes, this Skill facilitates the integration of custom reward functions and agent loops into Atropos environments, ensuring proper configuration for reinforcement learning training.

What CLI modes are available for processing and evaluating Atropos environments?▼

The Skill provides CLI commands for serving, processing, and evaluating environments, allowing you to set up a full training loop for Atropos and debug the environment setup.

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