ef285b5c97
* fix: stabilize validation and tests on Windows * test: add Windows smoke coverage for skill activation * refactor: make setup_web script CommonJS * fix: repair aegisops-ai frontmatter * docs: add when-to-use guidance to core skills * docs: add when-to-use guidance to Apify skills * docs: add when-to-use guidance to Google and Expo skills * docs: add when-to-use guidance to Makepad skills * docs: add when-to-use guidance to git workflow skills * docs: add when-to-use guidance to fp-ts skills * docs: add when-to-use guidance to Three.js skills * docs: add when-to-use guidance to n8n skills * docs: add when-to-use guidance to health analysis skills * docs: add when-to-use guidance to writing and review skills * meta: sync generated catalog metadata * docs: add when-to-use guidance to Robius skills * docs: add when-to-use guidance to review and workflow skills * docs: add when-to-use guidance to science and data skills * docs: add when-to-use guidance to tooling and automation skills * docs: add when-to-use guidance to remaining skills * fix: gate bundle helper execution in Windows activation * chore: drop generated artifacts from contributor PR * docs(maintenance): Record PR 457 sweep Document the open issue triage, PR supersedence decision, local verification, and source-only cleanup that prepared PR #457 for re-running CI. --------- Co-authored-by: sickn33 <sickn33@users.noreply.github.com>
5.5 KiB
name, description, risk, source
| name | description | risk | source |
|---|---|---|---|
| hugging-face-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. | unknown | community |
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
hfcommand 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
--helpcommand 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_TOKENenvironment 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— usesHF_TOKENautomatically 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— optionalHF_TOKENusage 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 thehfCLI 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— bashreferences/baseline_hf_api.py— pythonreferences/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):
references/baseline_hf_api.sh 25 | jq -r '.[].id' | references/hf_enrich_models.sh | jq -s 'sort_by(.downloads) | reverse | .[:10]'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
The following are the main API endpoints available at https://huggingface.co
/api/datasets
/api/models
/api/spaces
/api/collections
/api/daily_papers
/api/notifications
/api/settings
/api/whoami-v2
/api/trending
/oauth/userinfo
Accessing the API
The API is documented with the OpenAPI standard at https://huggingface.co/.well-known/openapi.json.
IMPORTANT: DO NOT ATTEMPT to read https://huggingface.co/.well-known/openapi.json directly as it is too large to process.
IMPORTANT Use jq to query and extract relevant parts. For example,
Command to Get All 160 Endpoints
curl -s "https://huggingface.co/.well-known/openapi.json" | jq '.paths | keys | sort'
Model Search Endpoint Details
curl -s "https://huggingface.co/.well-known/openapi.json" | jq '.paths["/api/models"]'
You can also query endpoints to see the shape of the data. When doing so constrain results to low numbers to make them easy to process, yet representative.
Using the HF command line tool
The hf command line tool gives you further access to Hugging Face repository content and infrastructure.
❯ hf --help
Usage: hf [OPTIONS] COMMAND [ARGS]...
Hugging Face Hub CLI
Options:
--help Show this message and exit.
Commands:
auth Manage authentication (login, logout, etc.).
cache Manage local cache directory.
download Download files from the Hub.
endpoints Manage Hugging Face Inference Endpoints.
env Print information about the environment.
jobs Run and manage Jobs on the Hub.
repo Manage repos on the Hub.
repo-files Manage files in a repo on the Hub.
upload Upload a file or a folder to the Hub.
upload-large-folder Upload a large folder to the Hub.
version Print information about the hf version.
The hf CLI command has replaced the now deprecated huggingface_hub CLI command.