Observed arrival · 2026-11-05
TouchStone: regression tests for RL environments
TouchStone helps developers turn requirements for reinforcement-learning environments into reviewed, repeatable safety and correctness checks.
- For
- RL environment developers auditing reward and correctness behavior
- Worth noticing
- Examples include false-positive math graders and forged checkout or Harbor reward signals; production integration is explicitly unvalidated.
Field notes
The adapter runs each input against an environment and returns what it observed, while the test author reviews the expected result before approval. Approval follows the exact test content, and saved runs distinguish approved from experimental checks. The examples separate unmodified verl grader results from deliberately weak fixtures owned by the project. A passing run only means those assertions held; the site says this does not establish that the environment is safe or that the requirements are correct.
Observed signals
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