| --- |
| license: bsd-3-clause |
| pretty_name: Eval-rules desk (OpenEnv) |
| tags: |
| - openenv |
| - reinforcement-learning |
| - agents |
| - tool-use |
| configs: |
| - config_name: tasks |
| data_files: |
| - split: train |
| path: data/tasks.jsonl |
| --- |
| |
| # Eval-rules desk (Workbench v9.1) |
|
|
| An OpenEnv environment for [OpenEnv Arena](https://openenvarena-arena.hf.space/). It trains the **survival habits** that, in our local proxy of the hidden test, decided whether an episode ever reached an answer: |
| - one clean JSON object per turn |
| - small observations |
| - short scripts |
| - write the output early, then submit |
|
|
| The tasks are served under the hidden test's published rules. |
|
|
| - **Source:** https://github.com/moarshy/workbench (`server/evalrules_environment.py`) |
| - **Image:** `ghcr.io/moarshy/workbench@sha256:1ac8bdb927b007bed9bb8db1c4979ee115c6d23f5bd7435ca3d31915406830a1` |
| - **Design, calibration and pre-registration:** https://github.com/moarshy/openenv-arena-notes/blob/main/versions/v9-eval-rules-desk.md |
| - **Day-0 proxy:** 23 public SkillsBench tasks, untrained Qwen3.8-27B. 0/91 episodes reached submit; 48 died on invalid replies and 35 on the budget. https://github.com/moarshy/openenv-arena-notes/blob/main/research/2026-10-18-day0-proxy-eval.md |
|
|
| ## Interface |
| Field for field the organizers' PostTrain adapter: `{type: run_bash | submit | finalize, command, answer}`. |
| - Output is cut to the first 8,192 characters. |
| - The workspace is `/root`. |
| - The first observation is the instruction only. |
| - Budgets: 8,192 completion tokens (counting observations), 16,384 context, 128 tool calls. |
|
|
| ## Tasks (9, v9.1) |
| loans-lite/easy/medium (finance), expenses-lite/medium (office), downtime-medium and reflow-hard (industrial), pyrepo-bug1 and repair-medium (software). |
| - Data arrives as real **.xlsx** workbooks and **.pdf** documents where a SkillsBench task would use them. |
| - v9.1 swaps the three tasks that showed no reward spread in v9 training (loans-hard, expenses-easy, pyrepo-implement) for smaller lite levels of the finance and office tasks. |
|
|
| ## Reward |
| ``` |
| task_score = share of checks passed, 0 if a protected check fails (schema, inputs unchanged, regressions) |
| reward = 0.85*task_score + 0.15*(submitted, if task_score >= 0.5) + 0.02*valid actions (max 5) - 0.05*repeated turns (max 0.2) |
| ``` |
| The reward is clipped to [0, 1]. |
|
|
| ## Licences |
| Vendored libraries keep their own licences: toolz and boltons are BSD-3-Clause, tabulate and inflection are MIT. |
|
|
