dataset-discovery

Find and rank datasets from HuggingFace, OpenML, GitHub, and papers.

1.0k|117|Updated Feb 26, 2026
One-click install
npx skills add https://github.com/OpenLAIR/dr-claw --skill dataset-discovery
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dataset-discovery
Source: https://github.com/OpenLAIR/dr-claw/tree/main/skills/dataset-discovery
Command: npx skills add https://github.com/OpenLAIR/dr-claw --skill dataset-discovery

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) components.

What problem does it solve?

Multi-source dataset discovery and ranking for ML tasks, saving researchers time locating relevant data.

Core Features & Use Cases

  • Cross-source search across HuggingFace, OpenML, GitHub, and papers.
  • Deduplication and relevance ranking to surface high-quality datasets.
  • Quick evaluation: preview metadata, and pull representative samples for quick inspection.

Quick Start

Find and rank datasets for a given ML task across multiple sources.

Frequently Asked Questions about dataset-discovery

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find relevant ML datasets for a research task across HuggingFace and OpenML?

To find relevant ML datasets, you can search across HuggingFace, OpenML, GitHub, and papers simultaneously. This aggregates results into a deduplicated, ranked list with metadata and source provenance tailored to your specific research needs.

Can I filter dataset search results by modality, size, and license?

Yes, you can filter dataset search results by modality, size, and license. This allows you to tailor the discovered datasets to your specific constraints and ensures the output metadata matches your project requirements.

What is the best way to deduplicate dataset search results from multiple sources?

The best way to deduplicate dataset search results is using an automated discovery tool that aggregates sources like HuggingFace and GitHub. It removes duplicates and applies relevance ranking to surface high-quality datasets.

How do I preview metadata and samples for datasets found on GitHub and papers?

You can preview metadata and pull representative samples for datasets found on GitHub and papers. This quick evaluation feature allows you to inspect the data before committing to downstream use.

Do I need the requests library to search for datasets across HuggingFace and OpenML?

Yes, you need the requests library installed in your environment. It is a required dependency for executing the scripts that query multiple sources and retrieve dataset metadata.