No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by liangdabiao · Claude Skill · ★ 264
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-data-analysis-ultra-main safe to install? View the security audit →
Claude Data Analysis Skills 基于 Claude Skill 架构的智能数据分析平台。提供两套完整的技能体系： 通用数据分析技能 - 6阶段完整分析流程 互联网数据分析技能 - 7个专业分析模块 + 1个入口技能 🚀 快速开始 准备数据 将数据集放入 目录： 调用 Skills 分析 方式0: 小白一键模式（推荐） 方式1: 互联网数据分析（推荐） 方式2: 通用数据分析 🌐 互联网分析模式 (Internet Analysis Mode) 重要功能：专为互联网业务场景设计的专业技能体系，提供针对电商、内容、增长等场景的深度分析能力。 为什么使用互联网分析模式？ 场景聚焦：针对互联网业务特点设计 专业深度：提供 LTV 预测、归因分析、AB 测试等专业能力 灵活组合：可单独使用，也可通过入口技能协调组合 开箱即用：提供 templates/、guide/、examples/ 完整配套 互联网分析技能列表
| Stars | 264 |
| Forks | 45 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 57.111102121/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-10 |
| Created | 2025-12-24 |
| Platforms | claude-code, python |
| Est. Tokens | ~3967k |
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claude-data-analysis-ultra-main is 让小白都可以一键进行数据分析，搞互联网的，搞电商的，搞各种各样的，那么其实就会用到 互联网的数据分析， 例如互联网会关心 拉新，留存，促活，推荐，转化，A/B test, 用户分析 等等很多有用的数据分析。. It is categorized as a Claude Skill with 264 GitHub stars.
claude-data-analysis-ultra-main is primarily written in Python. It covers topics such as claude-code.
You can find installation instructions and usage details in the claude-data-analysis-ultra-main GitHub repository at github.com/liangdabiao/claude-data-analysis-ultra-main. The project has 264 stars and 45 forks, indicating an active community.
The top alternatives to claude-data-analysis-ultra-main on Agent Skills Hub include claude-codex-settings, awesome-claude-code-plugins, cclsp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: