Skill

Build Hugging Face API CLI Scripts

A skill for building reusable, pipeable CLI scripts around the Hugging Face API and hf CLI tool.

Works with huggingface

79
Spark score
out of 100
Updated yesterday
Source checked Sep 22, 2026
Version 18.1.0

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Why it matters

Automate repetitive Hugging Face Hub tasks by generating reusable command-line scripts. This asset enables chaining, piping, and intermediate processing for efficient API interaction.

Outcomes

What it gets done

01

Create shell scripts for Hugging Face API and `hf` CLI.

02

Develop utilities for data extraction and processing from Hugging Face.

03

Implement authenticated API access using `HF_TOKEN`.

04

Generate composable scripts for model and dataset metadata retrieval.

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-hugging-face-tool-builder | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Hugging Face API Tool Builder

This skill builds reusable, pipeable command-line scripts for the Hugging Face API and the hf CLI tool. It documents the main API endpoints, the full OpenAPI spec, HF_TOKEN authentication, and the hf CLI's command set. Sample scripts show chaining, stdin-to-NDJSON streaming, and querying model metadata, licenses, and gated status. Use it when automating repeated Hugging Face Hub tasks with composable scripts. Skip it for one-off, non-repeated API calls.

What it does

This skill turns an agent into a builder of reusable command-line scripts and utilities around the Hugging Face API and the hf CLI tool, favoring composable, pipeable interfaces over one-off API calls. It documents the main high-level API endpoints (/api/datasets, /api/models, /api/spaces, /api/collections, /api/daily_papers, /api/notifications, /api/settings, /api/whoami-v2, /api/trending, /oauth/userinfo), the full OpenAPI spec at https://huggingface.co/.well-known/openapi.json (160 endpoints, too large to read directly, so it's queried with jq instead), and the hf CLI's own command set (auth, cache, download, endpoints, env, jobs, repo, repo-files, upload, upload-large-folder, version), noting that hf has replaced the deprecated huggingface_hub CLI.

When to use - and when NOT to

Use it when you need reusable CLI scripts around the Hugging Face API or the hf tool, want shell-friendly utilities that support chaining and piping, or are automating repeated Hub tasks and need a composable interface instead of ad hoc API calls.

Inputs and outputs

Every script must accept --help describing its inputs and outputs, and non-destructive scripts should be tested before being handed to the user; shell is preferred unless complexity calls for Python or TSX, and authentication goes through the HF_TOKEN environment variable as an Authorization header, for example curl -H "Authorization: Bearer ${HF_TOKEN}" https://huggingface.co/api/. Example scripts shown include hf_model_papers_auth.sh (chains trending, model metadata, and model card parsing with fallbacks, using HF_TOKEN automatically), find_models_by_paper.sh (authenticated search with a retry path when arXiv-prefixed searches are too narrow), hf_model_card_frontmatter.sh (uses the hf CLI to download model cards and emit NDJSON of license, pipeline tag, tags, and gated-prompt flag), three ultra-simple baseline scripts in bash, Python, and TSX, and hf_enrich_models.sh, which reads model IDs from stdin and streams one JSON object per line. A composability example chains them:

baseline_hf_api.sh 25 | jq -r '.[].id' | hf_enrich_models.sh | jq -s 'sort_by(.downloads) | reverse | .[:10]'

Integrations

Talks to the Hugging Face Hub API directly, documented via its OpenAPI schema, and to the hf CLI for repo, download, upload, and Inference Endpoint management; jq is used throughout for querying both the OpenAPI spec and API responses. A related example pipes model IDs through hf_model_card_frontmatter.sh to summarize license and gated-prompt status: printf '%s\n' openai/gpt-oss-120b meta-llama/Meta-Llama-3.1-8B | hf_model_card_frontmatter.sh | jq -s 'map({id, license, has_extra_gated_prompt})'.

Who it's for

Developers automating Hugging Face Hub workflows, such as querying model or dataset metadata, checking licenses and gated status, or managing repos and uploads, who want a library of small, composable, well-documented scripts rather than writing one-off curl calls each time.

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