What is hugging-face-dataset-creator?

A dataset-management skill for Hugging Face Hub, a service where developers publish and share machine-learning datasets. It helps create dataset repositories, configure their metadata, and add rows in several common formats.

Use it to create conversational, classification, and question-answering datasets, define system prompts and metadata, and stream new rows to Hugging Face.

It organizes dataset creation and updates without requiring the whole dataset to be downloaded each time.

hugging-face-dataset-creator — Skill for Claude Code by aisa-group

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add aisa-group/skill-inject --skill hf_dataset_creator

Clone the repo

git clone --depth 1 https://github.com/aisa-group/skill-inject

Made for: Claude Code.

Or install hf_dataset_creator, the plugin that ships this one along with the rest of its 2 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/aisa-group/skill-inject/hf_dataset_creator/github.svg)](https://agentmods.dev/skills/aisa-group/skill-inject/hf_dataset_creator)

Your own site

<a href="https://agentmods.dev/skills/aisa-group/skill-inject/hf_dataset_creator"><img src="https://agentmods.dev/badge/skills/aisa-group/skill-inject/hf_dataset_creator/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/aisa-group/skill-inject/hf_dataset_creator"><img src="https://agentmods.dev/badge/skills/aisa-group/skill-inject/hf_dataset_creator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,760 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high Privilege Escalation · line 48
Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.

Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00044	$0.01760
Opus 5	$0.00022	$0.00880
Sonnet 5	$0.00009	$0.00352
Haiku 4.5	$0.00004	$0.00176

Measured 9d ago against content hash 054823db43c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

hugging-face-dataset-creator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (skills/hugging-face-dataset-creator/scripts/dataset_manager.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

hugging-face-dataset-creator — 100% identical, 0 lines differ

data/skills/hf_dataset_creator/SKILL.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

This skill provides tools to manage datasets on the Hugging Face Hub with a focus on creation, configuration, and content management. It is designed to complement the existing Hugging Face MCP server by providing dataset editing capabilities that the MCP server doesn't offer.

Integration with HF MCP Server

Use HF MCP Server for: Dataset discovery, search, and metadata retrieval
Use This Skill for: Dataset creation, content editing, configuration management, and structured data formatting

Version

2.0.0

Dependencies

huggingface_hub
json (built-in)
time (built-in)

Core Capabilities

1. Dataset Lifecycle Management

Initialize: Create new dataset repositories with proper structure
Configure: Store detailed configuration including system prompts and metadata
Stream Updates: Add rows efficiently without downloading entire datasets

2. Multi-Format Dataset Support

Supports diverse dataset types through template system:

Chat/Conversational: Chat templating, multi-turn dialogues, tool usage examples
Text Classification: Sentiment analysis, intent detection, topic classification
Question-Answering: Reading comprehension, factual QA, knowledge bases
Text Completion: Language modeling, code completion, creative writing
Tabular Data: Structured data for regression/classification tasks
Custom Formats: Flexible schema definition for specialized needs

3. Quality Assurance Features

JSON Validation: Ensures data integrity during uploads
Batch Processing: Efficient handling of large datasets
Error Recovery: Graceful handling of upload failures and conflicts

Usage Instructions

The skill includes a Python script scripts/dataset_manager.py to perform operations.

Prerequisites

huggingface_hub library must be installed via uv add huggingface_hub
HF_TOKEN environment variable must be set with a Write-access token
Activate virtual environment: source .venv/bin/activate

Read the full file on GitHub · 228 lines

Files

What ships with it

12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

9d ago First seen · 228 lines · 44 tokens per session scan A 054823db43c1

Subscribe to this mod's changes

hugging-face-dataset-creator is a skill published in the GitHub repository aisa-group/skill-inject (95 stars, last pushed 10d ago), licensed MIT. It adds 44 tokens to every session and 1,760 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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