hugging-face-tool-builder

hugging-face-tool-builder is a skill for Claude Code, Codex from eugenepyvovarov/mcpbundler-agent-skills-marketplace. It costs 67 tokens per session (1,214 once invoked), scanned A, a copy of hugging-face-tool-builder, MIT.

A guide for building reusable command-line tools that fetch, enrich, or process data through the Hugging Face API. Hugging Face is a platform that hosts machine-learning models, datasets, and applications.

In plain words
What is it for?
Creating shell, Python, or TypeScript tools to retrieve and process model or dataset information, with command help, authentication, and usage examples.
Why use it?
It turns repeated Hugging Face data tasks into scripts that can be inspected, tested, chained together, and run from a terminal.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Creating shell, Python, or TypeScript tools to retrieve and process model or dataset information, with command help, authentication, and usage examples.

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Install with agentmods
npx agentmods add skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hf-tool-builder
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 eugenepyvovarov/mcpbundler-agent-skills-marketplace --skill hf-tool-builder
Clone the repo
git clone --depth 1 https://github.com/eugenepyvovarov/mcpbundler-agent-skills-marketplace

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin hf-tool-builder/plugin install hf-tool-builder after adding the marketplace above.

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.

agentmods badge for hugging-face-tool-builder

README.md
[![agentmods](https://agentmods.dev/badge/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hf-tool-builder/github.svg)](https://agentmods.dev/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hf-tool-builder)
Your own site
<a href="https://agentmods.dev/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hf-tool-builder"><img src="https://agentmods.dev/badge/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hf-tool-builder/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.

agentmods 80×15 button for hugging-face-tool-builder

Your own site · 80×15
<a href="https://agentmods.dev/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hf-tool-builder"><img src="https://agentmods.dev/badge/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hf-tool-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,214 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.01214
Opus 5 $0.00034 $0.00607
Sonnet 5 $0.00013 $0.00243
Haiku 4.5 $0.00007 $0.00121

Measured 12d ago against content hash ad8ea7af44a9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

hugging-face-tool-builder scanned grade A with 1 finding 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 12d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (references/baseline_hf_api.py, references/baseline_hf_api.sh, references/find_models_by_paper.sh, …), 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- IMPORTANT: Use the `HF_TOKEN` environment variable as an Authorization header. For example: `curl -H "Authorization: Bearer ${HF_TOKEN}" https://huggingface.co/api/`. This provides higher rate limits and appropriate au
Origin

This is a copy

100% identical to hugging-face-tool-builder — 220 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

hf-tool-builder/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hugging Face API Tool Builder

Your purpose is now is to create reusable command line scripts and utilities for using the Hugging Face API, allowing chaining, piping and intermediate processing where helpful. You can access the API directly, as well as use the hf command line tool. Model and Dataset cards can be accessed from repositories directly.

Script Rules

Make sure to follow these rules:

  • Scripts must take a --help command line argument to describe their inputs and outputs
  • Non-destructive scripts should be tested before handing over to the User
  • Shell scripts are preferred, but use Python or TSX if complexity or user need requires it.
  • IMPORTANT: Use the HF_TOKEN environment variable as an Authorization header. For example: curl -H "Authorization: Bearer ${HF_TOKEN}" https://huggingface.co/api/. This provides higher rate limits and appropriate authorization for data access.
  • Investigate the shape of the API results before commiting to a final design; make use of piping and chaining where composability would be an advantage - prefer simple solutions where possible.
  • Share usage examples once complete.

Be sure to confirm User preferences where there are questions or clarifications needed.

Sample Scripts

Paths below are relative to this skill directory.

Reference examples:

  • references/hf_model_papers_auth.sh — uses HF_TOKEN automatically and chains trending → model metadata → model card parsing with fallbacks; it demonstrates multi-step API usage plus auth hygiene for gated/private content.
  • references/find_models_by_paper.sh — optional HF_TOKEN usage via --token, consistent authenticated search, and a retry path when arXiv-prefixed searches are too narrow; it shows resilient query strategy and clear user-facing help.
  • references/hf_model_card_frontmatter.sh — uses the hf CLI to download model cards, extracts YAML frontmatter, and emits NDJSON summaries (license, pipeline tag, tags, gated prompt flag) for easy filtering.

Read the full file on GitHub · 111 lines

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.

  1. 12d ago First seen · 111 lines · 67 tokens per session scan A ad8ea7af44a9

Subscribe to this mod's changes

hugging-face-tool-builder is a skill published in the GitHub repository eugenepyvovarov/mcpbundler-agent-skills-marketplace (12 stars, last pushed 6mo ago), licensed MIT. It adds 67 tokens to every session and 1,214 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to hugging-face-tool-builder, differing in 220 lines, and is treated as a copy.

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