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whox-atropos-environments

Build and test WHOX RL environments integrated with Atropos.

Updated Apr 10, 2026
Search Tags:#tooling#agent-loop#wandb#rl-environments#atropos#whox
One-click install
npx skills add https://github.com/overviewlabs/WHOX --skill whox-atropos-environments
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: whox-atropos-environments
Source: https://github.com/overviewlabs/WHOX/tree/main/optional-skills/mlops/whox-atropos-environments
Command: npx skills add https://github.com/overviewlabs/WHOX --skill whox-atropos-environments

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Build, test, and debug WHOX Agent RL environments for Atropos training. It covers the WHOXAgentBaseEnv interface, reward functions, agent loop integration, evaluation with tools, wandb logging, and the three CLI modes (serve, process, evaluate). Use this skill when creating, reviewing, or fixing RL environments in the whox-agent repo.

Core Features & Use Cases

  • Environment scaffolding: provides a structured pattern for implementing a base WHOX environment that integrates with Atropos and the WHOXAgentBaseEnv, including setup, item queuing, evaluation loops, and tool usage.
  • Agent-loop evaluation: demonstrates running a full agent loop with tool calls for end-to-end assessment rather than single-turn completions.
  • Wandb logging and metrics: includes hooks for performance tracking, custom rewards, and evaluation logging to assist reproducibility and benchmarking.
  • CLI modes: supports serve, process, and evaluate workflows to enable rapid development, offline data generation, and model benchmarking.

Quick Start

Implement a WHOXAgentBaseEnv-based environment and run the provided CLI in serve or evaluate mode to validate end-to-end RL workflows.

Frequently Asked Questions about whox-atropos-environments

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

FAQPage Schema
How do I build RL environments for Atropos agent training?▼

To build RL environments for Atropos agent training, you implement the WHOXAgentBaseEnv interface to structure setup, item queuing, evaluation loops, and tool usage for end-to-end agent loops.

What is the difference between serve, process, and evaluate CLI modes?▼

The serve, process, and evaluate CLI modes enable rapid development, offline data generation, and model benchmarking respectively, supporting distinct workflows within the Atropos RL environment lifecycle.

Do I need wandb to log metrics for WHOX RL environments?▼

You need wandb to log metrics for WHOX RL environments because the skill includes specific hooks for performance tracking, custom rewards, and evaluation logging to assist reproducibility and benchmarking.

Can I evaluate an agent loop with tool calls instead of single-turn completions?▼

You can evaluate an agent loop with tool calls by running the CLI in evaluate mode, which demonstrates a full end-to-end agent loop assessment rather than relying on single-turn completions.

What prerequisites are required to create WHOX Atropos environments?▼

Creating WHOX Atropos environments requires familiarity with the whox-agent repo, the Atropos base environment, and Python tooling such as pytest and wandb to validate end-to-end RL workflows.

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