Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →mkurman/data-card-writer
Generate structured datasheets for datasets (Gebru et al. "Datasheets for Datasets" format) — purpose, composition, collection process, preprocessing, limitations, and licensing.
Passed 20 of 22 test cases with the skill, and 9 of 22 without it.
and 17 more in the full report
13 fixed7 passed either way0 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a standardized dataset card for the tabular benchmark 'KaggleHousePrices-Cleaned'. Ensure the cryptographic verification hash of the transformation script is recorded.
| Checked | Without skill | With skill |
|---|---|---|
| Includes a specific field for Cleaning script hash | Passed | Passed |
| Locates the script hash entry under the Preprocessing section | Missed | Passed |
The instructions your model reads when the skill loads.
Generates a structured datasheet following the "Datasheets for Datasets" framework (Gebru et al., 2021). Every dataset should ship with a data card that answers: who made this, what's in it, how was it collected, what are the limitations.
# [Dataset Name] — Data Card v[Version]
## Motivation
- Purpose: [What task is this for?]
- Creator: [Who created it?]
- Funding: [Who funded it?]
## Composition
- Instances: [N] examples, [M] features
- Target: [What is being predicted?]
- Protected attributes: [Gender, race, age, etc. — or "not collected"]
- Missing data: [X% missing overall, per-column breakdown]
- Class balance: [Distribution]
## Collection Process
- Source: [URL, database, API, instrument]
- Collection date: [YYYY-MM-DD to YYYY-MM-DD]
- Sampling strategy: [Random, stratified, convenience]
- Ethical review: [IRB protocol # or "not applicable"]
- Consent: [How was consent obtained?]
## Preprocessing
- Raw → cleaned pipeline: [Steps applied]
- Exclusions: [What was removed and why?]
- Transformations: [Normalization, imputation, encoding]
- Cleaning script hash: [sha256]
## Uses
- Recommended uses: [What this dataset is validated for]
- Discouraged uses: [What this should NOT be used for]
- Out-of-scope: [Inappropriate applications]
test cases passed, vs 9 / 22 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.