icyCreater/SpreadsheetBench-2-sample

SpreadsheetBench 2 Dataset

SpreadsheetBench 2 evaluates spreadsheet agents on end-to-end business and financial workflows. The release contains 321 tasks in four categories: Debugging, Financial Model, Template, and Visualization.

Overview

Directory	Task type	Tasks	Input workbooks	Gold workbooks
Debugging	Spreadsheet debugging and error correction	100	100	10
Financial_Model	Completion of multi-sheet financial models	100	100	20
Template	Completion of spreadsheet templates	97	97	97
Visualization	Chart creation and manipulation	24	24	24
Total		321	321	151

Directory Structure

Each category contains a dataset.json manifest and a spreadsheet/ directory. Paths in the manifest are relative to the corresponding category directory.

dataset.json as the Canonical Manifest

Each category has exactly one category-level dataset.json; it contains one record per task. This file is the authoritative source for task IDs, prompts, input workbooks, gold workbooks, and evaluation metadata. File and directory names are organized for readability, but users should always resolve a task through its manifest record rather than construct paths manually.

nips2026_submit-v2/
|-- README.md
|-- Debugging/
|   |-- dataset.json
|   `-- spreadsheet/
|       |-- 01/
|       |   |-- 01_01_input.xlsx
|       |   |-- ...
|       |   `-- 01_golden.xlsx
|       `-- ...
|-- Financial_Model/
|   |-- dataset.json
|   `-- spreadsheet/
|       |-- 01/
|       |   |-- 01_01_input.xlsx
|       |   |-- ...
|       |   `-- 01_golden.xlsx
|       `-- ...
|-- Template/
|   |-- dataset.json
|   `-- spreadsheet/
|       |-- 01/
|       |   |-- 01_01_input.xlsx
|       |   `-- 01_01_golden.xlsx
|       `-- ...
`-- Visualization/
    |-- dataset.json
    `-- spreadsheet/
        |-- Task 96/
        `-- ...

Debugging, Financial_Model, and Template use the same numeric naming scheme. A numbered directory identifies a workbook group, and an input file uses the form <group>_<task>_input.xlsx. Shared references use <group>_golden.xlsx; Template references are task specific and use <group>_<task>_golden.xlsx. The numeric prefixes follow the record order in dataset.json.

Visualization is the only exception: its directories and files retain the human readable Task <id> naming scheme because each task has its own input workbook, reference workbook, and rubric set. The manifest is the authoritative index for all categories; users should resolve files through the manifest rather than infer task identity from filenames.

Prompts and Manifest Fields

All 321 tasks include a complete, non-empty prompt in the instruction field. No category omits prompts, and prompts are not distributed as separate text files. The prompt, input path, gold path, and evaluation metadata for each task are stored together in its category-level dataset.json record. Common fields are:

Field	Description
id	Task identifier within the category.
instruction	Complete prompt supplied to the spreadsheet agent.
spreadsheet_path	Relative path to the input workbook.
golden_response_path	Relative path to the completed or corrected reference workbook.
answer_position	Worksheet ranges used by the cell based evaluator.

Debugging, Financial Model, and Template records include answer_position. Visualization records include task_id, category, and criteria; criteria contains the expert designed rubric used by the VLM evaluator.

Input and Gold Mapping

Category	Mapping rule
Debugging	Each numbered directory contains ten input variants named <group>_<task>_input.xlsx and one clean gold workbook named <group>_golden.xlsx.
Financial Model	Each numbered directory contains five incomplete task variants named <group>_<task>_input.xlsx that share one completed project workbook named <group>_golden.xlsx.
Template	Each task has its own input and gold pair, named <group>_<task>_input.xlsx and <group>_<task>_golden.xlsx.
Visualization	Each task has its own input workbook, gold workbook, prompt, and rubric set. The existing Task <id> directory and file names are retained.

The exact input to gold mapping is always specified by spreadsheet_path and golden_response_path in the category manifest.

Each task record contains exactly one golden_response_path. In Debugging and Financial_Model, multiple task records intentionally point to the same gold workbook because they are controlled variants of one underlying workbook. In Template and Visualization, each task record points to its own gold workbook. Thus, there are no tasks with multiple gold paths; the apparent sharing occurs across task records and is explicitly represented by repeated golden_response_path values.

Evaluation

• Debugging, Financial Model, and Template: generated workbooks are recalculated before cached values and the annotated worksheet ranges are compared with the reference workbook.
• Visualization: each criterion in criteria receives a binary VLM judgment, and the task score is the rubric pass rate.

Loading the Dataset

import json
from pathlib import Path

category_dir = Path("Financial_Model")
with (category_dir / "dataset.json").open("r", encoding="utf-8") as f:
    tasks = json.load(f)

for task in tasks:
    input_path = category_dir / task["spreadsheet_path"]
    reference_path = category_dir / task["golden_response_path"]
    assert input_path.exists()
    assert reference_path.exists()