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 wentorai/research-plugins --skill huggingface-inference-guidegit clone --depth 1 https://github.com/wentorai/research-pluginsWrote 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/wentorai/research-plugins/huggingface-inference-guide)<a href="https://agentmods.dev/skills/wentorai/research-plugins/huggingface-inference-guide"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/huggingface-inference-guide/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/wentorai/research-plugins/huggingface-inference-guide"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/huggingface-inference-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 11 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 34 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 Supply Chain · line 60 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 Supply Chain · line 71 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 Supply Chain · line 86 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.
- medium Data Exfiltration · line 34 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 60 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 71 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 86 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 108 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 114 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 147 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.01905 |
| Opus 5 | $0.00010 | $0.00953 |
| Sonnet 5 | $0.00004 | $0.00381 |
| Haiku 4.5 | $0.00002 | $0.00191 |
Grade A, and why
huggingface-inference-guide scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "https://api-inference.huggingface.co/models/bert-base-uncased" \ How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hugging Face Inference API Guide
Overview
The Hugging Face Inference API provides instant access to thousands of pre-trained machine learning models for natural language processing, computer vision, audio processing, and multimodal tasks. Researchers can run inference on state-of-the-art models without managing infrastructure, GPU resources, or complex deployment pipelines.
The API hosts models from the Hugging Face Hub, which contains over 500,000 models contributed by the research community. This includes transformer models for text classification, named entity recognition, summarization, translation, question answering, text generation, and image classification. For academic researchers, the Inference API is invaluable for rapid prototyping, benchmark evaluation, and integrating ML capabilities into research workflows without dedicated compute resources.
The free tier provides access to a broad selection of models with rate limits suitable for development and small-scale research. An API token is required for authentication, available for free at huggingface.co.
Authentication
A free Hugging Face API token is required. Create an account and generate a token at https://huggingface.co/settings/tokens.
Store your token securely in an environment variable:
export HF_API_TOKEN=$HF_API_TOKEN
curl -X POST "https://api-inference.huggingface.co/models/bert-base-uncased" \
-H "Authorization: Bearer $HF_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"inputs": "The goal of life is [MASK]."}'
Core Endpoints
Text Classification (Sentiment Analysis)
POST https://api-inference.huggingface.co/models/{model_id}
curl -s -X POST \
"https://api-inference.huggingface.co/models/distilbert-base-uncased-finetuned-sst-2-english" \
-H "Authorization: Bearer $HF_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"inputs": "This research methodology provides robust and reproducible results."}' \
| python3 -m json.tool
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 · 197 lines · 20 tokens per session scan A 066d5adba5f6
huggingface-inference-guide is a skill published in the GitHub repository wentorai/research-plugins (291 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 1,905 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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