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 · Agent Tool · ★ 67
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is deepseek-v4-flash-vision-rag safe to install? View the security audit →
DeepSeek V4-Flash Vision RAG 让 AI 真正"看懂" 一份 PDF，然后你对它提问：它告诉你答案、答案在第几页， 并把那一页的原图展示出来给你核对。 基于 DeepSeek 视觉大模型 的 PDF 深度问答与检索 （vision RAG）agent skill。支持文字版 PDF，也支持扫描版；能看懂 图表、表格、代码块、公式，而不只是认字。 一、它能做什么 每次回答都会生成一个自包含 HTML 预览页（答案 + 全部引用页原图内嵌其中）， 双击浏览器打开即可查看，无需联网。 二、实测效果（120 页中文书，test.pdf） 三、工作原理（通俗版） 整个系统就做两件事，像人读一本书： 第一阶段：读一遍书，做笔记（ingest，一次性） 模型每读一页，就写一张卡片——这就是 。第 22 页的真实卡片长这样： json {"page": 22, "type": "正文", "headings": [{"level": 1, "text": "§03 四种模式，人话版"}], "summary": "介绍四种模式：标准、PTC、极简、创造，并指出它们不在同一维度上，标准模式是默
| Stars | 67 |
| Forks | 12 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 59.1826241571748/100 |
| Last Updated | 2026-08-31 |
| Created | 2026-08-24 |
| Platforms | python |
| Est. Tokens | ~7k |
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deepseek-v4-flash-vision-rag is DeepSeek V4-Flash Vision RAG 让 AI 真正"看懂" 一份 PDF，然后你对它提问：它告诉你答案、答案在第几页， 并把那一页的原图展示出来给你核对。 基于 DeepSeek 视觉大模型 deepseek-v4-flash-vision-exp 的 PDF 深度问答与检索 （vision RAG）agent skill。支持文字版 PDF，也支持扫描版；能看懂 图表、表. It is categorized as a Agent Tool with 67 GitHub stars.
deepseek-v4-flash-vision-rag is primarily written in Python. It covers topics such as skills.
You can find installation instructions and usage details in the deepseek-v4-flash-vision-rag GitHub repository at github.com/liangdabiao/deepseek-v4-flash-vision-rag. The project has 67 stars and 12 forks, indicating an active community.
The top alternatives to deepseek-v4-flash-vision-rag on Agent Skills Hub include ATaC, JoySafeter, human-mcp. 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: