hermes-atropos-environments

What problem does it solve?

This Skill streamlines the creation, testing, and debugging of Reinforcement Learning (RL) environments specifically designed for the Atropos training framework within the hermes-agent repository.

Core Features & Use Cases

• Environment Development: Provides a structured guide and base classes for implementing custom RL environments that integrate with Atropos.
• Agent Loop Orchestration: Details how to handle multi-turn agent interactions, tool resolution, and reward calculation within the environment.
• Testing & Debugging: Offers clear instructions and CLI modes (serve, process, evaluate) for verifying environment logic, scoring mechanisms, and agent performance.
• Use Case: A machine learning engineer needs to create a new RL environment to train an agent to perform complex code generation tasks. They will use this Skill to define the environment's reward function, integrate it with the agent's tool-calling capabilities, and test its performance against a set of evaluation criteria.

Quick Start

Use the hermes-atropos-environments skill to evaluate your custom RL environment using the 'evaluate' CLI command, ensuring you specify the correct inference setup.