generate-verifiers-env

generate-verifiers-env is a Model training & evaluation skill for AI agents, published by adithya-s-k in the RL_Envs_101 repository on GitHub. Skillspace rates generate-verifiers-env C (70/100) and it passed the safety scan; the rating is based on static analysis only.

Builds a Verifiers (PrimeIntellect) variant of an RL environment. Use whenever someone asks to scaffold a Verifiers env, port to Verifiers, build an in-process toolkit, set up a `vf.ToolEnv` with a Rubric, or wire up a TRL `GRPOTrainer` rollout. Verifiers is the right framework when the user wants in-process tools (no HTTP server), structured tool calling driven by plain Python functions, composable reward rubrics with multiple grader functions, fast iteration with no Docker, or the cleanest path from prototype to TRL training. Output is a runnable `<env_dir>/verifiers/` folder with `env.py` (toolkit + standalone tool functions + `create_verifiers_env`), `rollout.py`, and `pyproject.toml`. Use for prompts like "make a verifiers env for X", "wrap my game in verifiers", or "set up a vf.ToolEnv".

Grade

C

Quality

70 / 100

Safety

Passed

GitHub stars

154

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