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Agent skill

Hugging Face Dataset Viewer

by sickn33 in sickn33/agentic-awesome-skills

“Hugging Face Dataset Viewer”

— description from SKILL.md by sickn33
Apache-2.0Auto-check passedAI & LLM Engineering

Install Hugging Face Dataset Viewer

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill hugging-face-dataset-viewer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills hugging-face-dataset-viewer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hugging-face-dataset-viewer .claude/skills/hugging-face-dataset-viewer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hugging-face-dataset-viewer
GitHub stars
47k
Used in
1 other repo
Token cost
~1.3k tokens
SKILL.md length
461 words
Files
1
Skills in repo
1,497
Repo updated
First seen
Licence
Apache-2.0

At a glance

  • Works in 6 steps: Optionally validate dataset availability… → Resolve config + split with /splits. → Preview with /first-rows. → …
  • SKILL.md covers When to Use, Core workflow, Defaults and Dataset Viewer, plus 3 more sections
  • Calls hf, curl and npx; reaches datasets-server.huggingface.co and huggingface.co; needs HF_TOKEN

About this skill

Hugging Face Dataset Viewer is a skill in sickn33/agentic-awesome-skills (47k stars). Its SKILL.md is about 1.3k tokens, and copies of it appear in 1 other owners' repositories. Licence: Apache-2.0.

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • hf
    • curl
    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • datasets-server.huggingface.co
    • huggingface.co

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • HF_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hugging Face Dataset Viewer loads about 1.3k tokens when it runs. Until then it costs about 14 tokens; SKILL.md has 461 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~14
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit b84d35a, republished under its Apache-2.0 licence (© sickn33). 461 words, ~1,289 tokens.

Download SKILL.mdSave it as .claude/skills/hugging-face-dataset-viewer/SKILL.md (or your agent's skills folder).
name
hugging-face-dataset-viewer
description
Hugging Face Dataset Viewer
risk
critical
source
https://github.com/huggingface/skills/tree/main/skills/huggingface-datasets
source_repo
huggingface/skills
source_type
official
date_added
2026-07-01
license
Apache-2.0
license_source
https://github.com/huggingface/skills/blob/main/LICENSE

Hugging Face Dataset Viewer

When to Use

Use this skill when you need 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.

Show full SKILL.md (154 more words)Show less

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

Limitations

  • Use this skill only when the task clearly matches its upstream product or API scope.
  • Verify commands, API behavior, pricing, quotas, credentials, and deployment effects against current official documentation before making changes.
  • Do not treat generated examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

© sickn33, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/hugging-face-dataset-viewer of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit b84d35a

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Hugging Face Dataset Viewer compared with similar skills
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LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs13k8 repos~3kAutomated safety check: PassMIT
SageMaker Serving Image Selectionhuggingface/skills11k1 repos~4.6kAutomated safety check: PassApache-2.0
Hugging Face Local Model Evalshuggingface/skills11k2 repos~1.6kAutomated safety check: PassApache-2.0
Upload Post Imagehuggingface/blog3.5k—~1.1kAutomated safety check: PassNone
Esmfold2JimLiu/science-skills2284 repos~2.5kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Hugging Face Dataset Viewer

How do I install Hugging Face Dataset Viewer in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill hugging-face-dataset-viewer -a claude-code`. Or copy the skill folder (skills/hugging-face-dataset-viewer in sickn33/agentic-awesome-skills) into .claude/skills/hugging-face-dataset-viewer in your project. Claude Code loads it when a task matches its description.

How do I install Hugging Face Dataset Viewer in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill hugging-face-dataset-viewer -a codex`. Or copy the skill folder (skills/hugging-face-dataset-viewer in sickn33/agentic-awesome-skills) into .agents/skills/hugging-face-dataset-viewer in your project. Codex loads it when a task matches its description.

Can I use Hugging Face Dataset Viewer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill hugging-face-dataset-viewer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hugging-face-dataset-viewer, .gemini/skills/hugging-face-dataset-viewer, .github/skills/hugging-face-dataset-viewer and .opencode/skills/hugging-face-dataset-viewer in your project.

What does Hugging Face Dataset Viewer need to run?

Going by SKILL.md and its folder, Hugging Face Dataset Viewer needs the command-line tools its instructions call (hf, curl and npx) and credentials named HF_TOKEN.

Does Hugging Face Dataset Viewer access the network?

SKILL.md names 2 domains. In commands or code: datasets-server.huggingface.co and huggingface.co; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Hugging Face Dataset Viewer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hugging Face Dataset Viewer use?

Hugging Face Dataset Viewer is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hugging Face Dataset Viewer use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hugging Face Dataset Viewer?

Skills that share tags, products or a category with Hugging Face Dataset Viewer: LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), SageMaker Serving Image Selection (huggingface/skills, 11k stars), Hugging Face Local Model Evals (huggingface/skills, 11k stars) and Upload Post Image (huggingface/blog, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hugging Face Dataset Viewer?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.