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hugging-face-tool-builder

Build reusable CLI tools to fetch and process Hugging Face API data.

1|Updated Jan 22, 2026
Search Tags:#automation#workflow#API#scripting#data enrichment#huggingface#CLI tooling
One-click install
npx skills add https://github.com/sitammeur/ml-agent-skills --skill hugging-face-tool-builder-sitammeur
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hugging-face-tool-builder
Source: https://github.com/sitammeur/ml-agent-skills/tree/main/skills/hugging-face-tool-builder
Command: npx skills add https://github.com/sitammeur/ml-agent-skills --skill hugging-face-tool-builder-sitammeur

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps developers rapidly create reusable command line tools to fetch, enrich, and process data from the Hugging Face API, reducing manual work and enabling repeatable workflows.

Core Features & Use Cases

  • Composable API tooling: Build small scripts that chain HF API calls (e.g., fetch model metadata, enrich with additional info, and format results).
  • Referenceable examples: Leverage a catalog of baseline and reference scripts to accelerate integration with hf CLI and curl, with support for authentication via HF_TOKEN.
  • Use Case: Create end-to-end workflows that fetch data, enrich it, and output structured results for dashboards or pipelines.

Quick Start

Use a simple example: fetch models from the HF API and then enrich metadata using the reference scripts. HF_TOKEN=your_token bash references/baseline_hf_api.sh 5 | jq -r '.[].id' | xargs -I{} bash references/hf_enrich_models.sh {}

Frequently Asked Questions about hugging-face-tool-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build reusable command line tools to fetch and enrich Hugging Face data?▼

To build reusable command line tools for Hugging Face data, you use reference scripts that chain API calls to fetch model metadata and enrich it. This approach automates repeatable workflows across models, datasets, and model cards.

Can I use the hf CLI and curl to automate Hugging Face API workflows?▼

Yes, you can automate Hugging Face API workflows using a scripting environment with curl or the hf CLI. The skill provides baseline reference scripts to compose CLI utilities and chain API calls for data processing.

Do I need an HF_TOKEN to authenticate API calls when processing Hugging Face models?▼

You need an optional HF_TOKEN to authenticate API calls when processing Hugging Face models. Including this token in your scripting environment allows the CLI utilities to securely fetch and enrich data from the API.

What is the best way to chain Hugging Face API calls for data enrichment in Bash or Python?▼

The best way to chain Hugging Face API calls for data enrichment is by composing small scripts in Bash, Python, or TSX. This creates portable tooling that fetches data, enriches metadata, and outputs structured results.

Does this tool support formatting Hugging Face API responses for dashboards or pipelines?▼

Yes, the tool supports formatting Hugging Face API responses for dashboards or pipelines. You can create end-to-end workflows that fetch data, enrich it, and output structured results suitable for downstream applications.

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