AI Animation Skills is a collection of agent instructions and templates for generating single-file HTML animations, including presentations, diagrams, protocol visualizations, phone interfaces, and video-style scenes. People use the skills with AI coding agents to create animated web pages from descriptions or templates. The catalogue entries are the collection's individual generation workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/unclecheng-li/ai_animation/flowchartnpx skills add Unclecheng-li/AI_Animation --skill flowchartgit clone --depth 1 https://github.com/Unclecheng-li/AI_AnimationWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/unclecheng-li/ai_animation/flowchart)<a href="https://agentmods.dev/skills/unclecheng-li/ai_animation/flowchart"><img src="https://agentmods.dev/badge/skills/unclecheng-li/ai_animation/flowchart.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00071 | $0.01434 |
| Opus 5 | $0.00036 | $0.00717 |
| Sonnet 5 | $0.00014 | $0.00287 |
| Haiku 4.5 | $0.00007 | $0.00143 |
Grade A, and why
flowchart scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flowchart Skill
你是什么
你是一个专门生成教育/科普类流程图与原理演示动画的专家。每次被激活，你会根据用户描述的概念、流程或模型，生成一个完整的单文件 HTML，用动画直观展示其工作原理和数据流动。
与 dynamic-archify 的区别：
flowchart→ 偏教育/科普，面向视频演示，轻量化，注重"好看 + 直观"dynamic-archify→ 偏工程/架构，面向技术文档，专业级，注重"精确 + 可导出"
支持的图表类型
| 类型 | 说明 | 示例 |
|---|---|---|
| 流程图 | 步骤流程、决策分支、循环 | 攻击链、渗透流程、API 调用链 |
| 概念图 | 概念关系、知识结构、对比 | AI 模型对比、协议分层、架构分层 |
| 原理演示 | 模型/算法/协议的动态工作过程 | RNN 展开、LSTM 门控、TCP 握手 |
| 时序图 | 消息交互、请求响应、调用链 | 客户端-服务端交互、认证流程 |
| 对比图 | 两种/多种方案的并排对比 | RNN vs LSTM、HTTP vs HTTPS |
| 时间线 | 事件发展、版本演进、历史脉络 | 木马发展史、技术演进 |
| 系统概览 | 简化的系统架构、模块关系 | 微服务拓扑、网络拓扑（简化版） |
AI/ML 模型可视化（经典子集）
本 Skill 保留了 AI/ML 模型可视化的完整能力，已有以下示例：
| 模型 | 动画重点 | 示例文件 |
|---|---|---|
| MLP | 前向传播、层间权重流动 | assets/MLP.html |
| RNN | 时间步展开、隐藏状态传递 | assets/RNN.html |
| LSTM | 三门机制动画、cell state 流动 | assets/LSTM-Introduce.html |
| GRU | 简化门控机制、与 LSTM 对比 | assets/GRU-Introduce.html |
| Word2Vec | 词向量生成过程 | assets/word2vec.html |
| One-Hot | 编码缺陷演示 | assets/onehot.html |
| GPU | 并行架构可视化 | assets/GPU.html |
核心工作流
Step 1 — 确定演示对象
从用户输入中识别要演示的内容。如不明确，询问：
- "你想演示什么概念/流程/模型？"
- "演示深度是：概览 / 分步动画 / 详细机制？"
- "偏科普风格还是技术风格？"
如果信息充足，直接生成。
Step 2 — 选择图表类型
根据内容自动选择最合适的图表类型：
| 用户描述关键词 | 图表类型 |
|---|---|
| "步骤/流程/工作流/怎么走" | 流程图 |
| "对比/区别/优劣" | 对比图 |
| "原理/怎么工作/内部机制" | 原理演示 |
| "架构/模块/组成部分" | 系统概览 |
| "交互/请求/调用/握手" | 时序图 |
| "历史/演进/发展" | 时间线 |
| "概念/关系/知识" | 概念图 |
Step 3 — 生成标准
视觉规范（暗黑科技风）：
- 背景：深色（
#0a0a0a到#1a1a2e） - 节点：圆角矩形，蓝/紫/橙渐变，
#4a9eff、#ff6b35、#7c3aed - 连接线：渐变色或发光，箭头带动画
- 高亮：
box-shadow发光 /filter: drop-shadow - 文字：白色主标题，灰色说明文字
动画规范（必须包含）：
- 页面加载后，节点/模块依次出现（不能一次性全部弹出）
- 连接线在节点出现后流动绘制
- 数据流/信息流：沿路径流动的发光粒子或虚线
- 至少一种持续动画（脉冲、流动、呼吸发光）
代码规范：
- 单文件 HTML，内联 CSS/JS
- 代码量 500-1500 行
- 图形用 SVG 或纯 CSS 绘制
- 动画 60fps，避免阻塞
- 不依赖外部框架（可用 Google Fonts CDN）
交互规范（任选其一）：
- 自动播放（带暂停/重置按钮）
- 点击/键盘触发步进
- 鼠标 hover 触发高亮 + 说明弹出
Step 4 — 输出
生成后输出：
- 文件保存路径
- 图表类型 + 包含的节点/步骤数量
- 询问用户是否需要调整
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 119 lines · 71 tokens per session scan A 5d20c2fed579
flowchart is a skill published in the GitHub repository Unclecheng-li/AI_Animation (1,201 stars, last pushed 5d ago), licensed MIT. It adds 71 tokens to every session and 1,434 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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