Supporting material availability

This catalog copy contains the inline guidance below, but does not include the following supporting paths. They are external prerequisites, not bundled files:

• <support-root>/references/hf_model_papers_auth.sh
• <support-root>/references/find_models_by_paper.sh
• <support-root>/references/hf_model_card_frontmatter.sh
• <support-root>/references/baseline_hf_api.sh
• <support-root>/references/baseline_hf_api.py
• <support-root>/references/baseline_hf_api.tsx
• <support-root>/references/hf_enrich_models.sh

Ask for the original supporting material or an existing installation before using a step that depends on these paths; this catalog does not identify a verified download source for them. Resolve each path relative to that installation, inspect its contents, and verify any applicable license and execution prerequisites. Do not run a command or claim a referenced procedure was followed until its required file exists. Do not fabricate the missing scripts or treat an unrelated file with the same name as equivalent. Independent steps fully documented here can proceed within the user’s authorized scope; report any dependent step as unavailable.

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.

When to Use

• You need reusable CLI scripts around the Hugging Face API or hf command line tool.
• You want shell-friendly utilities that support chaining, piping, and intermediate processing.
• You are automating repeated Hub tasks and need a composable interface instead of ad hoc API calls.

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.

Baseline examples (ultra-simple, minimal logic, raw JSON output with HF_TOKEN header):

• references/baseline_hf_api.sh — bash
• references/baseline_hf_api.py — python
• references/baseline_hf_api.tsx — typescript executable

Composable utility (stdin → NDJSON):

• references/hf_enrich_models.sh — reads model IDs from stdin, fetches metadata per ID, emits one JSON object per line for streaming pipelines.

Composability through piping (shell-friendly JSON output):

• <support-root>/references/baseline_hf_api.sh 25 | jq -r '.[].id' | references/hf_enrich_models.sh | jq -s 'sort_by(.downloads) | reverse | .[:10]'
• <support-root>/references/baseline_hf_api.sh 50 | jq '[.[] | {id, downloads}] | sort_by(.downloads) | reverse | .[:10]'
• printf '%s\n' openai/gpt-oss-120b meta-llama/Meta-Llama-3.1-8B | references/hf_model_card_frontmatter.sh | jq -s 'map({id, license, has_extra_gated_prompt})'

High Level Endpoints

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