Dataset Discovery

OrganizationPopular

OpenLAIR

dataset-discovery

Multi-source ML dataset discovery. Search HuggingFace Hub, OpenML, GitHub, and paper cross-references for datasets relevant to a research task. Use when asked to "find datasets for", "search ML datasets", "what datasets exist for", or "discover training data for".

Overview

Publisher	OpenLAIR
Repository	`dr-claw`
Skill name	`dataset-discovery`
Stars	1.2K
Forks	136
Bundled files	2
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by OpenLAIR on GitHub. Read the source before you install it.

Installation

Install the Dataset Discovery AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/OpenLAIR/dr-claw/tree/main/skills/dataset-discovery
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git /tmp/dr-claw
mkdir -p .claude/skills
cp -r /tmp/dr-claw/skills/dataset-discovery .claude/skills/dataset-discovery

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dataset Discovery in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dataset Discovery on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dataset Discovery is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

bash
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:

bash
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:

bash
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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

scripts/search_ml_datasets.py25 KB
tests/prompts.txt1 KB

Frequently asked questions

What does the Dataset Discovery AI skill do?

Why use Dataset Discovery on TypingMind?

Because you install it once and use it with any model. Dataset Discovery is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dataset Discovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenLAIR/dr-claw/tree/main/skills/dataset-discovery. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dataset Discovery?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dataset Discovery?

As many as you like. As long as a model supports skills, you can use Dataset Discovery with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dataset Discovery AI skill free?

It is published on GitHub by OpenLAIR. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Dataset Discovery Skill

Overview

Agent Workflow

Phase 1: SCOPE

Phase 2: SEARCH

Phase 3: PRESENT

Phase 4: DETAIL

Phase 5: PULL

Workspace Layout

Dependencies

Bundled files

Frequently asked questions

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