AI Engineering Hub is a learning and project repository covering large language models, retrieval-augmented generation, AI agents, and related applications. Beginners, practitioners, and researchers use its tutorials and projects to learn AI engineering and build working systems. The catalogue entries are examples of the skills, plugins, and agent resources included with it.
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 patchy631/ai-engineering-hub --skill hugging-face-cligit clone --depth 1 https://github.com/patchy631/ai-engineering-hubWrote 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/patchy631/ai-engineering-hub/hugging-face-cli)<a href="https://agentmods.dev/skills/patchy631/ai-engineering-hub/hugging-face-cli"><img src="https://agentmods.dev/badge/skills/patchy631/ai-engineering-hub/hugging-face-cli/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/patchy631/ai-engineering-hub/hugging-face-cli"><img src="https://agentmods.dev/badge/skills/patchy631/ai-engineering-hub/hugging-face-cli.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- 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 Tool Misuse · line 92 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 173 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00068 | $0.01809 |
| Opus 5.5 | $0.00027 | $0.00724 |
| Sonnet 5.5 | $0.00014 | $0.00362 |
| Haiku 4.5 | $0.00007 | $0.00181 |
Grade A, and why
hugging-face-cli scanned grade A with 0 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
5 near-identical copies found in the catalogue:
- hugging-face-cli — 100% identical, 372 lines differ
- hugging-face-cli — 100% identical, 372 lines differ
- hugging-face-cli — 91% identical, 382 lines differ
- hugging-face-cli — 88% identical, 384 lines differ
- hugging-face-cli — 86% identical, 390 lines differ
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hugging Face CLI
The hf CLI provides direct terminal access to the Hugging Face Hub for downloading, uploading, and managing repositories, cache, and compute resources.
Quick Command Reference
| Task | Command |
|---|---|
| Login | hf auth login |
| Download model | hf download <repo_id> |
| Download to folder | hf download <repo_id> --local-dir ./path |
| Upload folder | hf upload <repo_id> . . |
| Create repo | hf repo create <name> |
| Create tag | hf repo tag create <repo_id> <tag> |
| Delete files | hf repo-files delete <repo_id> <files> |
| List cache | hf cache ls |
| Remove from cache | hf cache rm <repo_or_revision> |
| List models | hf models ls |
| Get model info | hf models info <model_id> |
| List datasets | hf datasets ls |
| Get dataset info | hf datasets info <dataset_id> |
| List spaces | hf spaces ls |
| Get space info | hf spaces info <space_id> |
| List endpoints | hf endpoints ls |
| Run GPU job | hf jobs run --flavor a10g-small <image> <cmd> |
| Environment info | hf env |
Core Commands
Authentication
hf auth login # Interactive login
hf auth login --token $HF_TOKEN # Non-interactive
hf auth whoami # Check current user
hf auth list # List stored tokens
hf auth switch # Switch between tokens
hf auth logout # Log out
Download
hf download <repo_id> # Full repo to cache
hf download <repo_id> file.safetensors # Specific file
hf download <repo_id> --local-dir ./models # To local directory
hf download <repo_id> --include "*.safetensors" # Filter by pattern
hf download <repo_id> --repo-type dataset # Dataset
hf download <repo_id> --revision v1.0 # Specific version
Upload
hf upload <repo_id> . . # Current dir to root
hf upload <repo_id> ./models /weights # Folder to path
hf upload <repo_id> model.safetensors # Single file
hf upload <repo_id> . . --repo-type dataset # Dataset
hf upload <repo_id> . . --create-pr # Create PR
hf upload <repo_id> . . --commit-message="msg" # Custom message
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 187 lines · 68 tokens per session scan A 0ee5649dc4db
hugging-face-cli is a skill published in the GitHub repository patchy631/ai-engineering-hub (38,357 stars, last pushed 6d ago), licensed MIT. It adds 68 tokens to every session and 1,809 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
mcp-builder
DEPRECATED: This skill has been replaced by mcp-app-builder. Check if mcp-app-builder is available in the skills folder. If not, install it: npx skills install mcp-use/mcp-use --skill mcp-app-builder Use mcp-app-builder instead of this skill. Build Model Context Protocol (MCP) servers with mcp-use framework. Use when…
thinking-out-loud
A contract for what the agent does when a long, messy, stream-of-consciousness ramble arrives (usually voice dictation): act on nothing until the echo brief is approved. The echo audits the entire transfer, mission, locked decisions and constraints, open questions, flips and parked tangents, with the model's…
advisor-orchestrator-worker
Use when a task is too large for one model pass, needs parallel research or generation across many subtasks (like researching a dozen competitors at once), or the user asks to orchestrate multiple models, split work across a model team, run an advisor-worker loop, have a stronger model review the plan while cheap…
first-reader
Beta readers for any draft, run by simulating how a real reader experiences it, moment by moment. A skim gate, a no-lookahead timed read producing an attention transcript with quit points, a recall test of what a reader remembers the next day, and a trust ledger of the implied author. Use when the user asks for a beta…
project-graveyard
Scans the developer's machine for dead side projects, autopsies each one from its git history (died at the payments wall, killed by a newer project, finished but never shipped), surfaces their personal death patterns, and picks the corpse most worth resurrecting — then helps ship it. Use when the user mentions…
mcp-apps-builder
MANDATORY for ALL MCP server work - mcp-use framework best practices and patterns. READ THIS FIRST before any MCP server work, including: Creating new MCP servers Modifying existing MCP servers (adding/updating tools, resources, prompts, widgets) Debugging MCP server issues or errors Reviewing MCP server code for…