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 TseringYuu · Claude Skill · ★ 58
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is anyviz safe to install? View the security audit →
简体中文 · English anyviz 是一个面向 AI 时代的数据可视化规范与工作流库。 它为 AI 工具提供专业数据设计师级别的判断：图表选择、美学系统、 多技术栈渲染，以及同一画布下多图表的设计一致性。 官网 · <a href="https://www.
| Stars | 58 |
| Forks | 3 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 60.8851551282905/100 |
| Last Updated | 2026-08-06 |
| Created | 2026-06-16 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~15k |
These tools work well together with anyviz for enhanced workflows:
Looking for a anyviz alternative? If you're comparing anyviz with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Agent skill: Edward Tufte's data visualization principles for clean, honest, high-data-ink-ratio charts. Recha
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A virtual design studio for Claude Code — 27 slash commands, 13 specialist roles, full design-to-code pipeline
全球酒店预订&低价监控提醒Skill，200万+精选酒店，独家优惠价格，让你的Agent轻松预订品质酒店，支持支付宝下单+查询历史订单，24 小时客服支持，全天候响应。
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anyviz is 面向 AI 时代的数据可视化规范与工作流库 — specification & workflow library for AI-era data visualization. It is categorized as a Claude Skill with 58 GitHub stars.
anyviz is primarily written in Python. It covers topics such as ai, ai-agent, charts.
You can find installation instructions and usage details in the anyviz GitHub repository at github.com/TseringYuu/anyviz. The project has 58 stars and 3 forks, indicating an active community.
anyviz is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to anyviz on Agent Skills Hub include tufte-data-viz, utcp-mcp, design-studio. 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: