huggingface-datasets
This skill executes read-only queries against Hugging Face's Dataset Viewer API to explore, search, filter, and extract data from hosted datasets.
Identity proven by GitHub's verified organisation badge (huggingface)
- Agents
- Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode, claude.ai and API
- License
- Apache-2.0 (permissive)
- Pin
- c3ff942pinned Oct 9, 2026
- Context cost
- about 1,100 tokenswhen the skill loads
- GitHub stars
- 11,150on huggingface/skills
- Scripts
- None found
What it does
“Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.”
Generated summary from the skill's own text
This skill executes read-only queries against Hugging Face's Dataset Viewer API to explore, search, filter, and extract data from hosted datasets. It supports paginated row retrieval, text search, predicate-based filtering, parquet shard discovery, and metadata retrieval without requiring local dataset files.
When to use it
- Exploring and sampling rows from Hugging Face hosted datasets
- Searching or filtering dataset content by text or predicates
- Retrieving parquet URLs for bulk data download
- Getting dataset statistics, sizes, or column metadata
When not to
- Creating or modifying datasets, which requires separate upload workflows
- Working with local datasets not hosted on Hugging Face
- Executing complex SQL queries against datasets
Install
These commands install from the publisher's repository and need no account.
skills CLI
npx skills add huggingface/skills --skill huggingface-datasetsInstalls from the repository's default branch, which may have changed since the commit we checked.
GitHub CLI 2.90 or later
gh skill install huggingface/skills huggingface-datasets@c3ff942be3e07116b475253f0a8fc4f54682c1a8Installs the commit we checked (c3ff942).
Copy by hand
Download the folder at c3ff942 and put it in .claude/skills/huggingface-datasets for Claude Code and in .agents/skills/huggingface-datasets for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.
Claude Code plugin
/plugin install huggingface-skills@claude-plugins-officialThe publisher's plugin in Claude's official marketplace. It may hold more than this skill, and we have not pinned it.
Copy for your agent
A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.
Prompt
Install the agent skill "huggingface-datasets" by Hugging Face. Source, pinned to commit c3ff942be3e07116b475253f0a8fc4f54682c1a8: https://github.com/huggingface/skills/tree/c3ff942be3e07116b475253f0a8fc4f54682c1a8/skills/huggingface-datasets 1. Download that folder at exactly this commit. Do not use the default branch. 2. Copy every file unchanged, keeping the folder structure, into .claude/skills/huggingface-datasets/ for Claude Code and .agents/skills/huggingface-datasets/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist. 3. Do not edit the files, and do not run any script in the folder unless I ask you to. 4. When you are done, list the files you copied and where you put them. Listing and checks: https://www.agentnative.dev/skills/hugging-face/huggingface-datasets
SKILL.md at the pin
--- name: huggingface-datasets description: Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics. --- # Hugging Face Dataset Viewer Use this skill to execute read-only Dataset Viewer API calls for dataset exploration and extraction. ## Core workflow 1. Optionally validate dataset availability with `/is-valid`. 2. Resolve `config` + `split` with `/splits`. 3. Preview with `/first-rows`. 4. Paginate content with `/rows` using `offset` and `length` (max 100). 5. Use `/search` for text matching and `/filter` for row predicates. 6. Retrieve parquet links via `/parquet` and totals/metadata via `/size` and `/statistics`. ## Defaults - Base URL: `https://datasets-server.huggingface.co` - Default API method: `GET` - Query params should be URL-encoded. - `offset` is 0-based. - `length` max is usually `100` for row-like endpoints. - Gated/private datasets require `Authorization: Bearer <HF_TOKEN>`. ## Dataset Viewer - `Validate dataset`: `/is-valid?dataset=<namespace/repo>` - `List subsets and splits`: `/splits?dataset=<namespace/repo>` - `Preview first rows`: `/first-rows?dataset=<namespace/repo>&config=<config>&split=<split>` - `Paginate rows`: `/rows?dataset=<namespace/repo>&config=<config>&split=<split>&offset=<int>&length=<int>` - `Search text`: `/search?dataset=<namespace/repo>&config=<config>&split=<split>&query=<text>&offset=<int>&length=<int>` - `Filter with predicates`: `/filter?dataset=<namespace/repo>&config=<config>&split=<split>&where=<predicate>&orderby=<sort>&offset=<int>&length=<int>` - `List parquet shards`: `/parquet?dataset=<namespace/repo>` - `Get size totals`: `/size?dataset=<namespace/repo>` - `Get column statistics`: `/statistics?dataset=<namespace/repo>&config=<config>&split=<split>` - `Get Croissant metadata (if available)`: `/croissant?dataset=<namespace/repo>` Pagination pattern: ```bash curl "https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=0&length=100" curl "https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=100&length=100" ``` When pagination is partial, use response fields such as `num_rows_total`, `num_rows_per_page`, and `partial` to drive continuation logic. Search/filter notes: - `/search` matches string columns (full-text style behavior is internal to the API). - `/filter` requires predicate syntax in `where` and optional sort in `orderby`. - Keep filtering and searches read-only and side-effect free. For CLI-based parquet URL discovery or SQL, use the `hf-cli` skill with `hf datasets parquet` and `hf datasets sql`. ## Creating and Uploading Datasets Use one of these flows depending on dependency constraints. Zero local dependencies (Hub UI): - Create dataset repo in browser: `https://huggingface.co/new-dataset` - Upload parquet files in the repo "Files and versions" page. - Verify shards appear in Dataset Viewer: ```bash curl -s "https://datasets-server.huggingface.co/parquet?dataset=<namespace>/<repo>" ``` Low dependency CLI flow (`npx @huggingface/hub` / `hfjs`): - Set auth token: ```bash export HF_TOKEN=<your_hf_token> ``` - Upload parquet folder to a dataset repo (auto-creates repo if missing): ```bash npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data ``` - Upload as private repo on creation: ```bash npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data --private ``` After upload, call `/parquet` to discover `<config>/<split>/<shard>` values for querying with `@~parquet`. ## Agent Traces The Hub supports raw agent session traces from Claude Code, Codex, and Pi Agent. Upload them to Hugging Face Datasets as original JSONL files and the Hub can auto-detect the trace format, tag the dataset as `Traces`, and enable the trace viewer for browsing sessions, turns, tool calls, and model responses. Common local session directories: - Claude Code: `~/.claude/projects` - Codex: `~/.codex/sessions` - Pi: `~/.pi/agent/sessions` Default to private dataset repos because traces can contain prompts, file paths, tool outputs, secrets, or PII. Preserve the raw `.jsonl` files and nest them by project/cwd instead of uploading every session at the dataset root. ```bash hf repos create <namespace>/<repo> --type dataset --private --exist-ok hf upload <namespace>/<repo> ~/.codex/sessions codex/<project-or-cwd> --type dataset ```
From huggingface/skills at c3ff942, shown as plain text under its license: Apache-2.0 (permissive). The license text is in LICENSE.
View SKILL.md on GitHub at c3ff942Files
- SKILL.md4.7 KB · eeca50adf211
1 file, 4.7 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.
Skill folder on GitHub at c3ff942Also in
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