Document-illustrator-skill — AI Tool by op7418

by op7418 · AI Tool · ★ 554

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About Document-illustrator-skill

Document Illustrator 基于 AI 智能分析的文档配图生成工具 Document Illustrator 是一个 Claude Code Skill,它能智能理解文档内容,自动归纳核心要点,并为每个主题生成专业配图。无需依赖特定文档格式,AI 会理解内容并生成符合你选择风格的高质量图片。 ✨ 核心特性 🤖 AI 智能归纳:自动理解文档内容,智能提取核心主题,无需依赖标题格式 📝 格式无关:支持任何格式的文档(Markdown、纯文本、PDF 等) 🎨 三种风格:渐变玻璃卡片、票据风格、矢量插画,满足不同场景需求 📐 灵活比例:支持 16:9(横屏)和 3:4(竖屏)两种图片比例 🖼️ 封面图可选:可生成概括全文的封面图作为系列配图的引导 ✅ 内容完整:展示归纳结果供你确认,确保所有重要信息都被包含 🚀 快速开始 使用 npx 安装(推荐) 手动安装 克隆或下载本仓库到 Claude Skills 目录: 配置 API 密钥(见下方"配置说明"部分) 安装 Python 依赖(见下方"环境要求"部分) 基本使用 在 Claude Code 中直接告诉 Claude: 或者: Claude 会引导你完成整个配图生成流程。 🎨 三种风格说明 渐变玻璃卡片风格 (gradient-glass) 视觉特点: Apple Keynote 风格的极简主义设计 玻璃拟态(Glassmorphism)效果 深邃虚空黑或纯净陶瓷白基底 流动的极光渐变色 3D 玻璃物体和发光效果 适用场景: 科技产品介绍 数据分析报告 未来趋势展望 产品功能演示 票据风格 (ticket) 视觉特点: 数字极简票券设计 高度对比的黑白配色 类似登机牌、门票的结构化布局 精确的几何分区 中英混排,多向文字布局 适用场景: 信息图表 -

Quick Facts

Stars554
Forks62
LanguagePython
CategoryAI Tool
LicenseMIT
Quality Score41.82/100
Open Issues3
Last Updated2026-01-21
Created2026-01-21
Platformspython
Est. Tokens~15k

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Frequently Asked Questions

What is Document-illustrator-skill?

Document-illustrator-skill is 帮你从文档生成对应的多张配图,内置了歸藏精心探索的图片风格,支持 16:9 和 3:4 两种比例,方便发小红书以及推特。. It is categorized as a AI Tool with 554 GitHub stars.

What programming language is Document-illustrator-skill written in?

Document-illustrator-skill is primarily written in Python.

How do I install or use Document-illustrator-skill?

You can find installation instructions and usage details in the Document-illustrator-skill GitHub repository at github.com/op7418/Document-illustrator-skill. The project has 554 stars and 62 forks, indicating an active community.

What license does Document-illustrator-skill use?

Document-illustrator-skill is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to Document-illustrator-skill?

The top alternatives to Document-illustrator-skill on Agent Skills Hub include claudekit-skills, EDRSilencer, .github. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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