---
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: mcp_config
    dtype: string
  - name: id
    dtype: string
  - name: metadata
    dtype: string
  - name: setup_tool
    dtype: string
  - name: evaluate_tool
    dtype: string
  - name: system_prompt
    dtype: string
  - name: agent_config
    dtype: string
  splits:
  - name: train
    num_bytes: 130705
    num_examples: 50
  download_size: 45847
  dataset_size: 130705
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

## Task Categories

### 1. Data Preparation and Hygiene (29 tasks)
- De-duplication, type normalization, time parsing, joins/FX conversions, pivot tables

### 2. Derivations & Extraction (16 tasks)
- Correlations, z-scores, grouping logic, compliance filters (e.g., 1099)

### 3. Modeling & Forecasts (5 tasks)
- Revenue/breakeven projections, amortization schedules, depreciation calculations, scenario tables

## Example Task

```
For the ticker that has the greatest correlation between volume and next day price change % 
find the day with the greatest volume and the next days price change %

- put the ticker in ANSWER A1
- put the volume in ANSWER B1
- put the next day price change in ANSWER C1

NOTE:
- use CORREL to determine correlation for each ticker group
- be sure to first sort the date by ticker z to a and then date ascending before calculating nextdaypricechange %
```

## System prompt

```
All solutions should be put in the sheet called ‘ANSWER’.
In the answer sheet, all dates should use the American standard format MM/DD/YYYY with no leading zero.
All numbers should use the format and decimal place precision given in the input sheets (e.g., with or without a thousands separator should depend on the inputs), unless specified otherwise.				
```

## Quick Start

### Prerequisites
1. HUD API key: https://www.hud.so/project/api-keys
2. Anthropic API key: https://console.anthropic.com/settings/keys

### Installation & Run
```bash
# Install HUD SDK
uv tool install hud-python

# Configure API keys
hud set HUD_API_KEY=... ANTHROPIC_API_KEY=...

# Run evaluation with Claude
hud eval hud-evals/SheetBench-50 claude

# View full dataset
hud get hud-evals/SheetBench-50
```

## Key Features
- **Production-grade**: Tasks validated by finance professionals from PwC, Cisco, Charles Schwab, Fannie Mae
- **Blind validation**: Each task has single reproducible solution with expert consensus
- **Full telemetry**: Records actions, reasoning traces, and screenshots
- **Tool dexterity**: Tests real spreadsheet operations (pivots, formatting, formulas)


## Results
- View example scorecard: https://www.hud.so/leaderboards/hud-evals/SheetBench-50?scorecard=19c2f4b7-ea8a-4c2b-866f-20ae57976d13
- Replay trajectories: https://www.hud.so/jobs/7c06c24e-22c7-4c9a-a667-1de4bb05b080

## Contact
For enterprise evaluations or custom benchmarks: founders@hud.so