Hermes Agent is an AI assistant that learns from its use by creating and improving skills, retaining knowledge, searching past conversations, and adapting to its users. It is for people who want to run an agent through a terminal or messaging platforms while connecting it to different AI models and scheduled tasks.
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 NousResearch/hermes-agent --skill huggingface-hubgit clone --depth 1 https://github.com/NousResearch/hermes-agentWrote 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/nousresearch/hermes-agent/huggingface-hub)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/huggingface-hub"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/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/nousresearch/hermes-agent/huggingface-hub"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/huggingface-hub.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Supply Chain · line 18 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Privilege Escalation · line 35 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00911 |
| Opus 5 | $0.00010 | $0.00456 |
| Sonnet 5 | $0.00004 | $0.00182 |
| Haiku 4.5 | $0.00002 | $0.00091 |
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 6d 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` Copies of this mod
8 near-identical copies found in the catalogue:
- huggingface-hub — 100% identical, 0 lines differ
- huggingface-hub — 100% identical, 0 lines differ
- huggingface-hub — 100% identical, 0 lines differ
- huggingface-hub — 91% identical, 8 lines differ
- huggingface-hub — 91% identical, 8 lines differ
- huggingface-hub — 91% identical, 9 lines differ
- huggingface-hub — 91% identical, 9 lines differ
- huggingface-hub — 91% identical, 8 lines differ
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; also handles resumable uploads of large directories).hf upload-large-folder REPO_ID LOCAL_PATH: [Deprecated] — usehf uploadinstead.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 ls— View daily papers.
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.
- 6d ago First seen · 82 lines · 20 tokens per session scan C 68ee2e5ae17e
huggingface-hub is a skill published in the GitHub repository NousResearch/hermes-agent (243,598 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 911 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). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
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.
huggingface-hub
HuggingFace hf CLI: search/download/upload models, datasets.
huggingface-hub
HuggingFace hf CLI: search/download/upload models, datasets.