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.
npx skills add perasyudha/Nyxora --skill huggingface-hubgit clone --depth 1 https://github.com/perasyudha/NyxoraWrote 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.
[](https://agentmods.dev/skills/perasyudha/nyxora/huggingface-hub)<a href="https://agentmods.dev/skills/perasyudha/nyxora/huggingface-hub"><img src="https://agentmods.dev/badge/skills/perasyudha/nyxora/huggingface-hub/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.
<a href="https://agentmods.dev/skills/perasyudha/nyxora/huggingface-hub"><img src="https://agentmods.dev/badge/skills/perasyudha/nyxora/huggingface-hub.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.00898 |
| Opus 5 | $0.00010 | $0.00449 |
| Sonnet 5 | $0.00004 | $0.00180 |
| Haiku 4.5 | $0.00002 | $0.00090 |
Grade C, and why
huggingface-hub scanned grade C with 2 findings 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.
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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
* **Installation:** `curl -LsSf https://hf.co/cli/install.sh | bash -s` Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
* **Installation:** `curl -LsSf https://hf.co/cli/install.sh | bash -s` This is a copy
91% identical to huggingface-hub — 8 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hugging Face CLI (hf) Reference Guide
The hf command is the modern command-line interface for interacting with the Hugging Face Hub, providing tools to manage repositories, models, datasets, and Spaces.
IMPORTANT: The
hfcommand replaces the now deprecatedhuggingface-clicommand.
Quick Start
- Installation:
curl -LsSf https://hf.co/cli/install.sh | bash -s - Help: Use
hf --helpto view all available functions and real-world examples. - Authentication: Recommended via
HF_TOKENenvironment variable or the--tokenflag.
Core Commands
General Operations
hf download REPO_ID: Download files from the Hub.hf upload REPO_ID: Upload files/folders (recommended for single-commit).hf upload-large-folder REPO_ID LOCAL_PATH: Recommended for resumable uploads of large directories.hf sync: Sync files between a local directory and a bucket.hf env/hf version: View environment and version details.
Authentication (hf auth)
login/logout: Manage sessions using tokens from huggingface.co/settings/tokens.list/switch: Manage and toggle between multiple stored access tokens.whoami: Identify the currently logged-in account.
Repository Management (hf repos)
create/delete: Create or permanently remove repositories.duplicate: Clone a model, dataset, or Space to a new ID.move: Transfer a repository between namespaces.branch/tag: Manage Git-like references.delete-files: Remove specific files using patterns.
Specialized Hub Interactions
Datasets & Models
- Datasets:
hf datasets list,info, andparquet(list parquet URLs). - SQL Queries:
hf datasets sql SQL— Execute raw SQL via DuckDB against dataset parquet URLs. - Models:
hf models listandinfo. - Papers:
hf papers list— View daily papers.
Discussions & Pull Requests (hf discussions)
- Manage the lifecycle of Hub contributions:
list,create,info,comment,close,reopen, andrename. diff: View changes in a PR.merge: Finalize pull requests.
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.
- 12d ago First seen · 82 lines · 20 tokens per session scan C 60ffda7115dd
huggingface-hub is a skill published in the GitHub repository perasyudha/Nyxora (5 stars, last pushed 12d ago), licensed MIT. It adds 20 tokens to every session and 898 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). It is 91% identical to huggingface-hub, differing in 8 lines, and is treated as a copy.
Other skills, from other repositories
huggingface-hub
HuggingFace hf CLI: search/download/upload models, datasets.
huggingface-hub
HuggingFace hf CLI: search/download/upload models, datasets.
huggingface-hub
HuggingFace hf CLI: search/download/upload models, datasets.
huggingface-hub
Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.
huggingface-hub
Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.
huggingface-hub
HuggingFace hf CLI: search/download/upload models, datasets.