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hermes-atropos-environments

Build and validate Hermes Agent Atropos RL environments with reward functions and CLI modes.

Updated Mar 24, 2026
Search Tags:#tool-calling#agent-loop#reinforcement-learning#rl-environments#atropos#hermes-agent#wandb-logging
One-click install
npx skills add https://github.com/1thirteeng3/greenmoire --skill hermes-atropos-environments-1thirteeng3
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hermes-atropos-environments
Source: https://github.com/1thirteeng3/greenmoire/tree/main/integrations/hermes-agent/skills/mlops/training/hermes-atropos-environments
Command: npx skills add https://github.com/1thirteeng3/greenmoire --skill hermes-atropos-environments-1thirteeng3

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Build, test, and debug Hermes Agent RL environments for Atropos training. Covers the HermesAgentBaseEnv interface, reward functions, agent loop integration, evaluation with tools, wandb logging, and the three CLI modes (serve/process/evaluate). Use when creating, reviewing, or fixing RL environments in the hermes-agent repo.

Core Features & Use Cases

  • Manage and implement Atropos-compatible Hermes environments with multi-turn tool-enabled loops
  • Provide reward computation via reward functions, evaluator integration, and wandb logging
  • Support the three CLI modes (serve, process, evaluate) for end-to-end development and testing

Quick Start

Create, test, and debug Hermes Atropos RL environments and run full tool-enabled evaluations.

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 Atropos RL environments with multi-turn tool-enabled agent loops?▼

To build Atropos RL environments, implement the HermesAgentBaseEnv interface by defining setup, get_next_item, format_prompt, compute_reward, evaluate, and wandb_log methods to enable multi-turn tool-enabled agent loop training.

What is needed to integrate reward functions and wandb logging in Hermes Agent training?▼

Integrating reward functions and wandb logging requires implementing the compute_reward and wandb_log methods within your HermesAgentBaseEnv subclass to capture and track evaluation metrics during reinforcement learning training.

How do I evaluate Atropos environments using HermesAgentLoop and ToolContext?▼

Evaluating Atropos environments involves running the agent loop with HermesAgentLoop and ToolContext, executing robust tool handling, and extracting results from AgentResult.messages to verify sandbox performance.

Can I use the Atropos CLI serve, process, and evaluate modes for end-to-end RL environment testing?▼

Yes, you can use the three Atropos CLI modes to serve, process, and evaluate environments for end-to-end development and testing of Hermes Agent reinforcement learning training scenarios.

How to debug a Hermes Agent RL environment that is not computing rewards correctly?▼

Debugging reward computation involves reviewing the compute_reward method implementation in your HermesAgentBaseEnv subclass and validating evaluator integration and result extraction from AgentResult.messages.

Does this Hermes Atropos environment framework require specific dependencies for tool calling?▼

No specific external dependencies are required to start building, as the framework relies on internal HermesAgentLoop and ToolContext components to manage tool calling and agent loop integration.

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