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 coffeefuelbump · Claude Skill · ★ 467
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is csv-data-summarizer-claude-skill safe to install? View the security audit →
Featured in: Spreadsheet & Excel AI Tools
-4F46E5?style=for-the-badge) 📊 CSV Data Summarizer - Claude Skill A powerful Claude Skill that automatically analyzes CSV files and generates comprehensive insights with visualizations. Upload any CSV and get instant, intelligent analysis without being asked what you want! 🚀 Features 🤖 Intelligent & Adaptive - Automatically detects data type (sales, customer, financial, survey, etc.) and applies relevant analysis 📈 Comprehensive Analysis - Generates statistics, correlations, distribu
| Stars | 467 |
| Forks | 68 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 65.6592391545909/100 |
| Open Issues | 3 |
| Last Updated | 2025-10-16 |
| Created | 2025-10-16 |
| Platforms | claude-code, python |
| Est. Tokens | ~1k |
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csv-data-summarizer-claude-skill is A Claude Skill that automatically analyzes uploaded CSV files — generating summary statistics, detecting missing data, and creating quick visualizations using Python and pandas.. It is categorized as a Claude Skill with 467 GitHub stars.
csv-data-summarizer-claude-skill is primarily written in Python. It covers topics such as claude-skills.
You can find installation instructions and usage details in the csv-data-summarizer-claude-skill GitHub repository at github.com/coffeefuelbump/csv-data-summarizer-claude-skill. The project has 467 stars and 68 forks, indicating an active community.
The top alternatives to csv-data-summarizer-claude-skill on Agent Skills Hub include pg-aiguide, awesome-llm-skills, awesome-claude-plugins. 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: