---
license: apache-2.0
pretty_name: Science Desk
tags:
  - openenv
  - reinforcement-learning
  - agents
  - tool-use
  - terminal-bench
  - science
task_categories:
  - text-generation
---

# Science Desk

An OpenEnv environment for the [OpenEnv Arena](https://openenvarena-arena.hf.space): natural-science data tasks in
the style of public SkillsBench v1.1 science tasks, served through the same `tbench2_env` interface the arena uses for
its own tasks. Each episode is a workspace under `/app` with a short instruction. The agent runs commands
(`exec`), writes files (`write_file`) and sends `evaluate`; a hidden verifier checks the one output file the task
names and returns 1 or 0.

Image: `ghcr.io/syndicate604/science-desk` (linux/amd64). Source: `source/` in this repo. Forked from
[dnakhla/terminal-desk](https://huggingface.co/datasets/dnakhla/terminal-desk) v2 (Apache-2.0); see `NOTICE`.

## Interface

Terminal Desk v2's copy of OpenEnv's upstream `tbench2_env` contract: `exec`, `write_file`, `evaluate`, `close`;
the instruction repeated in every observation; output not cut; per-task budgets of 4096 completion tokens (model
tokens plus every observation after the first), 8192 context tokens and 32 tool calls. The image has numpy, scipy,
pandas and astropy.

## Tasks

10 families x 3 levels = 30 task ids (`<family>-L<level>`); each id is one fixed problem, so a GRPO group compares
answers to the same question. `<family>-L<level>-i<k>` names further fixed instances. Eight families are modelled
on SkillsBench science tasks with generated data: `sci_units` (lab-unit-harmonization), `sci_protein`
(protein-expression-analysis), `sci_flood` (flood-risk-analysis), `sci_trend` (lake-warming-attribution),
`sci_quake` (earthquake-plate-calculation), `sci_period` (exoplanet-detection-period), `sci_picking`
(seismic-phase-picking), `sci_vitals` (radar-vital-signs). `sci_kinetics` and `sci_stoich` come from Terminal Desk.
`tasks.jsonl` lists every id with its fixed instruction, output file and screen numbers.

Every task is checked by tests: the reference answer scores 1, missing or corrupted output scores 0, and an
independent solver that reads only the files and the instruction scores 1 on four instances per level.

## Submission (v5)

`selected_tasks.txt`, 12 tasks with both successes and failures in a screen of Qwen3.8-27B (thinking off) via
OpenRouter, DeepInfra bf16 pinned, 6 episodes each, under the budgets above with observation tokens counted by the
Qwen tokenizer on arrival:

| Task | Solved / 6 |
|---|---:|
| sci_picking-L1 / L3 | 3 / 1 |
| sci_units-L2 / L3 | 3 / 3 |
| sci_quake-L3 | 2 |
| sci_trend-L3 | 4 |
| sci_flood-L2, sci_protein-L3, sci_stoich-L3 | 5 each |
| sci_period-L1 / L2 / L3 (with astropy) | 3 / 3 / 2 |

Failures include malformed action replies, stopping before writing the output, budget exhaustion and wrong
results. A malformed final reply ends the episode through `evaluate`, so a correct file already written still
scores 1.

Limitations: six episodes per task is noisy, and earlier screens underestimated the arena-trained model, so these
numbers are not predictions of arena solve rates. Twelve ids are twelve fixed problems: this is an
interface-and-workflow experiment, not broad science coverage.

## Build and test

See `source/README.md`.