AgentStack
Browse Sign in
Browse Why AgentStack Sell Docs
Sign in
SKILL verified MIT Self-run

Dataset

skill-woodfishhhh-ez-math-model-dataset · by woodfishhhh

|

No reviews yet
0 installs
5 views
0.0% view→install

Install

$ agentstack add skill-woodfishhhh-ez-math-model-dataset

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

AgentStack Verified badge Links to your public security report.
[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-woodfishhhh-ez-math-model-dataset)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Dataset? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

dataset — 公开数据集发现

何时使用

  • 题目附件没有数据集,但题面要求"查找类似公开数据"。
  • 需要历史基准数据集(如 MNIST / Iris / 波士顿房价)做模型对比。
  • 不要在已有附件数据时启用本子 skill。

入口

| 数据源 | 入口 | 配置 | |---|---|---| | Kaggle | kaggle datasets list -s / kaggle datasets download -d | ~/.kaggle/kaggle.json(注册免费下载) | | UCI ML | 直接 HTTPS pd.read_csv(url) | 无 | | HuggingFace | from datasets import load_dataset | EZMM_HF_TOKEN(私有数据集) | | 天池 | 浏览器 + 手动下载 | 无 |

命令模板

# Kaggle 搜索 + 下载
kaggle datasets list -s "vegetable retail price"
kaggle datasets download -d  -p workdir/.../attachments/external/kaggle --unzip

# HuggingFace
python -c "from datasets import load_dataset; ds = load_dataset('squad', split='train[:1%]')"

# UCI(直接 URL)
python -c "import pandas as pd; df = pd.read_csv('https://archive.ics.uci.edu/...'); df.to_csv('workdir/.../attachments/external/uci/iris.csv', index=False)"

落盘规范

外部下载的数据放在:

workdir/{task_id}/attachments/external///

并在同目录写 SOURCES.md

- 数据集名: 
- 来源: 
- License: 
- 下载时间: 
- 用途说明: 

失败诊断

| 情况 | 处理 | |---|---| | Kaggle token 未配置 | 提示用户 ~/.kaggle/kaggle.json 配置 | | License 不允许商用 | 数据可用于学术建模报告;论文中标明出处 + license | | 文件 > 1GB | coder 阶段用 chunksize 处理(参考 prompts/coder.md) | | 网络受限 | 写诊断;建议用户手动下载放入 attachments/ |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet, be the first.

Versions

  • v0.1.0 Imported from the upstream source.