Dataset Discovery Skill

Overview

Search multiple ML dataset sources (HuggingFace Hub, OpenML, GitHub, Semantic Scholar) and return a ranked, deduplicated list of relevant datasets.

Agent Workflow

Phase 1: SCOPE

Clarify the user's needs before searching:

• Research task: What problem or domain? (e.g., "sentiment analysis", "medical image segmentation")
• Modality: image / text / tabular / audio / any
• Size preference: small (< 10K rows), medium (10K–1M), large (> 1M), any
• License preference: permissive (MIT/Apache/CC-BY), any, or specific

Phase 2: SEARCH

Run the search script with the user's query:

python3 scripts/search_ml_datasets.py search --query "<query>" --sources huggingface,openml,github,papers --max 30

Options:

• --sources: Comma-separated list from huggingface, openml, github, papers. Default: all four.
• --max: Maximum results to return after dedup + ranking. Default: 30.
• --modality: Filter by modality (image, text, tabular, audio).
• --workspace: Output directory. Default: ./datasets/discovery/

Optionally also call HF MCP tool hub_repo_search with repo_types: ["dataset"] for semantic search to supplement results.

Phase 3: PRESENT

Show results as a markdown table:

Name	Source	Downloads	Size	License	Tags	URL

Sort by relevance score (highest first).

Phase 4: DETAIL

When the user wants more info on a specific dataset:

python3 scripts/search_ml_datasets.py detail --dataset-id "huggingface:stanfordnlp/imdb" --workspace ./datasets/discovery/

Writes metadata.json and README.md to {workspace}/datasets/{source}_{slug}/.

Phase 5: PULL

When the user wants to preview data:

python3 scripts/search_ml_datasets.py pull --dataset-id "huggingface:stanfordnlp/imdb" --sample-rows 20 --workspace ./datasets/discovery/

Writes sample.jsonl to {workspace}/datasets/{source}_{slug}/.

For full dataset download, confirm with the user first, then use huggingface-cli download or equivalent.

Workspace Layout

{workspace}/                         # default: ./datasets/discovery/
  search-{YYYY-MM-DD}.json           # search results log
  datasets/
    {source}_{slug}/
      metadata.json                  # detailed metadata
      README.md                      # human-readable summary
      sample.jsonl                   # sample rows

Dependencies

• Python 3.8+
• requests (stdlib-adjacent, universally available)
• gh CLI (for GitHub source only)
• No other packages required