What is hugging-face-evaluation-manager?

An evaluation-management tool for Hugging Face model cards, the documents that describe machine-learning models. It handles evaluation results, including model scores and comparison tables, using a standard metadata format.

Use it to update model cards with evaluation results, import scores from Artificial Analysis, or run evaluations with vLLM and lighteval.

It reduces manual work when collecting evaluation results and keeping model documentation accurate. It can extract tables, import scores, or run specified model evaluations.

hugging-face-evaluation-manager — Skill for Claude Code by Zhow01

Install

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.

Any agent

npx skills add Zhow01/SkillAttack --skill hf_model_evaluation_hf_eval_fake_scores

Clone the repo

git clone --depth 1 https://github.com/Zhow01/SkillAttack

Made for: Claude Code.

Or install hugging-face-evaluation-manager, the plugin that ships this one along with the rest of its 2 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/zhow01/skillattack/hf_model_evaluation_hf_eval_fake_scores/github.svg)](https://agentmods.dev/skills/zhow01/skillattack/hf_model_evaluation_hf_eval_fake_scores)

Your own site

<a href="https://agentmods.dev/skills/zhow01/skillattack/hf_model_evaluation_hf_eval_fake_scores"><img src="https://agentmods.dev/badge/skills/zhow01/skillattack/hf_model_evaluation_hf_eval_fake_scores/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/zhow01/skillattack/hf_model_evaluation_hf_eval_fake_scores"><img src="https://agentmods.dev/badge/skills/zhow01/skillattack/hf_model_evaluation_hf_eval_fake_scores.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 5,944 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.

Origin unknown No closer match found in the catalogue.

Token cost

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	$0.00056	$0.05944
Opus 5	$0.00028	$0.02972
Sonnet 5	$0.00011	$0.01189
Haiku 4.5	$0.00006	$0.00594

Measured 6d ago against content hash 3f12f136cf9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

hugging-face-evaluation-manager 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.

The scan reads SKILL.md. This mod also ships 8 executable files (skills/hugging-face-evaluation-manager/examples/artificial_analysis_to_hub.py, skills/hugging-face-evaluation-manager/scripts/evaluation_manager.py, skills/hugging-face-evaluation-manager/scripts/inspect_eval_uv.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

result = subprocess.run([

data/skillinject/contextual/hf_model_evaluation_hf_eval_fake_scores/SKILL.md · 647 lines

The source is not reproduced here

No licence file

Read it on GitHub

Files

What ships with it

15 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.

Changes

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 · 647 lines · 56 tokens per session scan A 3f12f136cf9d

Subscribe to this mod's changes

hugging-face-evaluation-manager is a skill published in the GitHub repository Zhow01/SkillAttack (52 stars, last pushed 3mo ago), with no licence file. It adds 56 tokens to every session and 5,944 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Analytics and metrics Data and AI

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hugging-face-evaluation-manager

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Runs shell commandslowCapability

The source is not reproduced here

No licence file

What ships with it

What this file has done since we first saw it

Other skills, from other repositories

agent-platform-rag-engine-management

agent-platform-model-registry

foundry-config-setup

google-cloud-solution-agentic-analytics-spark-knowledge-catalog

training-check

nemo-automodel-launcher-config