rl-env-from-description

Turns a user's plain-English description of an RL training environment into runnable code across the four target frameworks — OpenEnv, OpenReward (ORS), Verifiers, and NeMo Gym. Use whenever someone describes an environment they want to build ("I want to train an agent that does X", "make an env where the model has to Y"), asks to scaffold a new env, asks to port an existing env to one of these frameworks, or asks how to design tools/rewards/state for a new env. Use even when the user does not explicitly say "RL environment" — descriptions like "agent that browses the web", "tool-calling agent for SQL", or "game-playing agent" all qualify. Drives the full flow — clarifying interview, env-name selection, shared-domain extraction, per-framework implementation, and rollout-based smoke tests.