Skills hugging-face-jobs

📦

hugging-face-jobs

Name: hugging-face-jobs
Author: sickn33

Content revision r2 High Risk 🌐 Network access📁 Filesystem access🔑 Env variables⚙️ External commands⚡ Contains scripts

Run Managed Hugging Face Jobs

Large machine learning workloads need costly hardware and reliable persistence. This skill prepares Hugging Face Jobs with suitable compute, secrets, schedules, and Hub storage.

Supports: Claude Codex Code(CC)

⚠️ 38 Poor

Stop for confirmation before installing.

Review the plan and obtain explicit user consent before changing files.

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "hugging-face-jobs" from https://skillstore.io/skills/sickn33-hugging-face-jobs.md and its manifest at https://skillstore.io/api/skills/sickn33-hugging-face-jobs/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/sickn33-hugging-face-jobs.md Signed manifest GET /api/skills/sickn33-hugging-face-jobs/manifest Signed lockfile GET /api/skills/sickn33-hugging-face-jobs/lockfile

Test it

Using "hugging-face-jobs". Prepare a small sentiment-analysis test on managed CPU.

Expected outcome:

Hardware: cpu-basic
Timeout: 20 minutes
Persistence: Save the result to the named Hub dataset
Status: Awaiting approval before submission

Using "hugging-face-jobs". Run batch inference on a private dataset with an eight-billion-parameter model.

Expected outcome:

Hardware: Start with one A10G GPU and validate a small sample
Authentication: Use a read token for input and write access only for the output repository
Safety: Pin the model, script, dependencies, and container image

Using "hugging-face-jobs". Create a daily dataset statistics job.

Expected outcome:

Schedule: Daily at the approved UTC time
Output: Versioned statistics in the selected Hub repository
Control: Confirm estimated monthly cost before schedule creation

Security Audit

High Risk

v5 • 7/24/2026 Open versioned report

Most static findings are detector noise from Markdown, documentation URLs, safe environment access, and ordinary API examples. Confirmed risks involve exposed tokens and mutable remote code; semantic review also found unpinned images and missing approval gates for paid jobs.

Files scanned

4,871

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (3)

High

SKILL.md:315-321 scripts/cot-self-instruct.py:41-45

Unpinned Container Images Receive Credentials

Examples run mutable latest or implicit-latest container images. One command passes HF_TOKEN into that image, allowing a compromised future image to capture the credential.

The image references are visibly unpinned, and the script example places HF_TOKEN in the same container invocation.

Medium

SKILL.md:41-45 SKILL.md:617-640 SKILL.md:724-748

Paid Job Submission Has No Confirmation Gate

The skill directs the agent to submit paid jobs before reporting cost details and also supports recurring schedules. It does not require final user approval before creating either workload.

The directive explicitly submits first and reports details afterward, while the documented examples show nonzero costs and recurring jobs.

Medium

scripts/cot-self-instruct.py:547-551 scripts/generate-responses.py:527-530 scripts/finepdfs-stats.py:345-348

Secrets Accepted Through Command-Line Arguments

All bundled scripts accept Hugging Face tokens as command-line values. Tokens supplied this way can remain in shell history or appear in process listings.

Each parser explicitly defines an hf-token option, a well-known credential exposure channel when users supply the value on a command line.

Capability review items (13)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

High

references/troubleshooting.md:190

Hardcoded URL

hf_jobs("uv", {"script": "https://huggingface.co/user/repo/resolve/main/script.py"})

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/cot-self-instruct.py:44

Shell command substitution

-e HF_TOKEN=$(python3 -c "from huggingface_hub import get_token; print(get_token())") \\

The example expands the local HF token into a command-line environment argument. The token can be exposed through process listings, shell tracing, or copied command output.

High

scripts/cot-self-instruct.py:707

Shell command substitution

-e HF_TOKEN=$(python3 -c "from huggingface_hub import get_token; print(get_token())") \\

The example expands the local HF token into a command-line environment argument. The token can be exposed through process listings, shell tracing, or copied command output.

High

scripts/cot-self-instruct.py:45

Hardcoded URL

https://huggingface.co/datasets/uv-scripts/synthetic-data/raw/main/cot-self-instruct.py \\

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/cot-self-instruct.py:431

Hardcoded URL

uv run https://huggingface.co/datasets/uv-scripts/synthetic-data/raw/main/cot-self-instruct.py \\

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/cot-self-instruct.py:708

Hardcoded URL

https://huggingface.co/datasets/uv-scripts/synthetic-data/raw/main/cot-self-instruct.py \\

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/finepdfs-stats.py:34

Hardcoded URL

https://huggingface.co/datasets/uv-scripts/dataset-stats/raw/main/finepdfs-stats.py \\

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/finepdfs-stats.py:276

Hardcoded URL

uv run https://huggingface.co/datasets/uv-scripts/dataset-stats/raw/main/finepdfs-stats.py \\

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/finepdfs-stats.py:554

Hardcoded URL

" https://huggingface.co/datasets/uv-scripts/dataset-stats/raw/main/finepdfs-stats.py \\"

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/generate-responses.py:155

Hardcoded URL

uv run https://huggingface.co/datasets/uv-scripts/vllm/raw/main/generate-responses.py \\

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

scripts/generate-responses.py:580

Hardcoded URL

https://huggingface.co/datasets/uv-scripts/vllm/raw/main/generate-responses.py \\

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

SKILL.md:373

Hardcoded URL

hf_jobs("uv", {"script": "https://huggingface.co/datasets/uv-scripts/.../raw/main/foo.py"})

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

High

SKILL.md:376

Hardcoded URL

hf_jobs("uv", {"script": "https://raw.githubusercontent.com/huggingface/trl/main/trl/scripts/sft.py"

The example executes a remote script from a mutable main branch without a commit pin or integrity check. Upstream changes could run arbitrary code inside a credentialed job.

Risk Factors

🌐 Network access (45)

references/hub_saving.md:65 references/hub_saving.md:65 references/token_usage.md:243 references/token_usage.md:268 references/troubleshooting.md:11 references/troubleshooting.md:36 references/troubleshooting.md:190 scripts/cot-self-instruct.py:45 scripts/cot-self-instruct.py:407 scripts/cot-self-instruct.py:408 scripts/cot-self-instruct.py:427 scripts/cot-self-instruct.py:431 scripts/cot-self-instruct.py:700 scripts/cot-self-instruct.py:708 scripts/finepdfs-stats.py:34 scripts/finepdfs-stats.py:276 scripts/finepdfs-stats.py:282 scripts/finepdfs-stats.py:283 scripts/finepdfs-stats.py:527 scripts/finepdfs-stats.py:554 scripts/generate-responses.py:119 scripts/generate-responses.py:123 scripts/generate-responses.py:125 scripts/generate-responses.py:150 scripts/generate-responses.py:155 scripts/generate-responses.py:410 scripts/generate-responses.py:580 SKILL.md:538 SKILL.md:2 SKILL.md:54 SKILL.md:217 SKILL.md:373 SKILL.md:376 SKILL.md:473 SKILL.md:538 SKILL.md:702 SKILL.md:857 SKILL.md:1009 SKILL.md:1010 SKILL.md:1011 SKILL.md:1012 SKILL.md:1015 SKILL.md:1016 SKILL.md:1017 SKILL.md:1018

📁 Filesystem access (2)

references/hub_saving.md:184 SKILL.md:373

🔑 Env variables (47)

⚙️ External commands (50)

scripts/cot-self-instruct.py:430-437 scripts/cot-self-instruct.py:44 scripts/cot-self-instruct.py:707 scripts/finepdfs-stats.py:240-242 scripts/finepdfs-stats.py:242-270 scripts/finepdfs-stats.py:270-271 scripts/finepdfs-stats.py:271-275 scripts/finepdfs-stats.py:275-278 scripts/generate-responses.py:124 scripts/generate-responses.py:146 scripts/generate-responses.py:154-164 SKILL.md:19 SKILL.md:24 SKILL.md:41 SKILL.md:43 SKILL.md:55 SKILL.md:68-75 SKILL.md:75-77 SKILL.md:77 SKILL.md:86-111 SKILL.md:111-116 SKILL.md:116-119 SKILL.md:119-120 SKILL.md:120-132 SKILL.md:132-137 SKILL.md:137-151 SKILL.md:151-156 SKILL.md:156-159 SKILL.md:159-160 SKILL.md:160-161 SKILL.md:161-167 SKILL.md:167-183 SKILL.md:183-187 SKILL.md:187-188 SKILL.md:188-194 SKILL.md:194-197 SKILL.md:197-200 SKILL.md:200-205 SKILL.md:205-211 SKILL.md:211-212 SKILL.md:212-220 SKILL.md:220-221 SKILL.md:221 SKILL.md:222-231 SKILL.md:231-240 SKILL.md:240-269 SKILL.md:269-278 SKILL.md:278-296 SKILL.md:296-299 SKILL.md:299-301

⚡ Contains scripts (1)

SKILL.md:793-799

Audited by: codex View Audit History →

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Academic citations (APA · BibTeX · CFF)

APA citation

sickn33. (2026). hugging-face-jobs security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-hugging-face-jobs/audits/5

BibTeX citation

@techreport{sickn33-sickn33-hugging-face-jobs-2026,
  author = {sickn33},
  title = {hugging-face-jobs security audit report (audit version 5)},
  institution = {Skillstore},
  year = {2026},
  number = {5},
  url = {https://skillstore.io/skills/sickn33-hugging-face-jobs/audits/5},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "hugging-face-jobs security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
  - name: "sickn33"
date-released: "2026-07-24"
url: "https://skillstore.io/skills/sickn33-hugging-face-jobs/audits/5"
identifiers:
  - type: other
    value: "skillstore:sickn33-hugging-face-jobs:audit:5"
    description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: Medium

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Process Large Datasets

Prepare a managed CPU job that transforms data and persists results to a selected Hub repository.

Run Batch Model Inference

Configure a GPU job that generates responses for a Hub dataset and publishes the completed dataset.

Automate Recurring Workloads

Create reviewed schedules for periodic processing, monitoring, and Hub updates.

Try These Prompts

Prepare a CPU Test

Prepare a Hugging Face Job for [task] on cpu-basic. Estimate runtime and cost, then wait for my approval before submission.

Configure Batch Inference

Prepare batch inference for dataset [dataset] with model [model]. Recommend hardware, timeout, output repository, and a secure token configuration.

Design a Scheduled Pipeline

Design a scheduled job for [task] using schedule [schedule]. Show expected cost, persistence, failure handling, and approval details before creation.

Plan a Reproducible Multi-GPU Run

Plan a multi-GPU job for [workload]. Pin scripts and images, set least-privilege secrets, add checkpoints, and define monitoring and cancellation criteria.

Best Practices

Pin remote scripts, dependencies, models, and container images to immutable versions.
Confirm hardware, timeout, schedule, destination, and estimated cost before submission.
Use least-privilege secrets and persist required outputs before the job ends.

Avoid

Do not place access tokens in scripts, environment examples, shell substitutions, or command arguments.
Do not execute scripts or images from mutable branches and tags.
Do not submit paid or recurring jobs before the user approves the final configuration.