video-shot-demos

video-shot-demos is a skill for Claude Code, Codex from Unclecheng-li/AI_Animation. It costs 166 tokens per session (1,598 once invoked), scanned A, original, MIT.

A workflow for creating animated HTML pages, one page per video shot, lesson segment, or narrated scene. It combines a shared player structure with different visual designs for each shot.

In plain words
What is it for?
Use it to create shot-by-shot demonstrations for technical videos, courses, explainers, and product presentations. It also guides the design and upgrade of existing shot pages.
Why use it?
It helps turn a script or outline into web-based visuals that can be recorded as video, while keeping timing, movement, sound effects, and visual continuity organized.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create shot-by-shot demonstrations for technical videos, courses, explainers, and product presentations. It also guides the design and upgrade of existing shot pages.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/unclecheng-li/ai_animation/video-shot-demos
About the project

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.

Unclecheng-li/AI_Animation · 1,265 stars · on GitHub

Install

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.

Any agent
npx skills add Unclecheng-li/AI_Animation --skill video-shot-demos
Clone the repo
git clone --depth 1 https://github.com/Unclecheng-li/AI_Animation

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for video-shot-demos

README.md
[![agentmods](https://agentmods.dev/badge/skills/unclecheng-li/ai_animation/video-shot-demos/github.svg)](https://agentmods.dev/skills/unclecheng-li/ai_animation/video-shot-demos)
Your own site
<a href="https://agentmods.dev/skills/unclecheng-li/ai_animation/video-shot-demos"><img src="https://agentmods.dev/badge/skills/unclecheng-li/ai_animation/video-shot-demos/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for video-shot-demos

Your own site · 80×15
<a href="https://agentmods.dev/skills/unclecheng-li/ai_animation/video-shot-demos"><img src="https://agentmods.dev/badge/skills/unclecheng-li/ai_animation/video-shot-demos.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 166 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,598 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00166 $0.01598
Opus 5 $0.00083 $0.00799
Sonnet 5 $0.00033 $0.00320
Haiku 4.5 $0.00017 $0.00160

Measured 12d ago against content hash cd086ff24724, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

video-shot-demos 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 12d 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.

skills/video-shot-demos/SKILL.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

视频分镜演示动画(每镜头一个 HTML)

一个镜头 = 一个独立 HTML,统一播放器底盘 + 每页一种完全不同的视觉风格,全屏录屏即成片。内容开放(技术实测/产品发布/课程/叙事皆可),不变的是电影化机制、镜头语言与完成度标准。

创作哲学

  1. 风格轮换:连续镜头绝不同风格。问"这段内容若是一件实物/一个场所,它是什么"——复古报纸、POS 小票、审讯室、像素游戏……把抽象内容具象成一个世界观,页面就活了。
  2. 禁默认科技暗色:黑底+霓虹+玻璃拟态的"乌漆墨黑油光锃亮"两页即疲劳,除非内容本身是终端主题。
  3. 想象力优先:底盘之上放开写——会砸下的印章、会掉进存钱罐的硬币,用户要惊喜感。
  4. 完成度是纪律:元素有入有出(或定格)、无重叠遮挡、无孤儿元素、结尾有重播暗示、数据有出处角注。
  5. 音画同步:关键动作有音效、镜头移动配 whoosh;安静也是设计。

Token 纪律(硬性)

  • 禁止通读 assets/template.htmlassets/examples/ 下任何成片页(单个 20–50KB,读完耗尽预算)。
  • 模板一律 cp 复制后只读标记区域(第 1 步);成片页仅当写完仍卡壳时,grep 定位后按行号窗口读 ≤80 行。
  • 机制与风格知识优先取自 references/ 三份浓缩文档,不要现场读源码反推。

工作流

第 0 步 · 输入与风格分配表:通读素材(大纲/口播稿/画面设计/口述),拿到分镜列表 + 口播时间戳(时间轴对齐基准)+ 角色素材。排表 镜头|时长|视觉风格|字体组合|主色:相邻不同风格、整辑不重复、同一实体全系列锁同一颜色(观众靠颜色跨页追踪)。表给用户确认后再动工。素材复制(勿读内容):

cp -r "assets/examples/<项目>/anan - emotion rename" <输出目录>/    # 安安 15 情绪立绘;图标同理
cp -r "assets/shery - emotion rename" <输出目录>/                   # 橘雪莉 20 情绪(笨蛋吐槽役,重点页与安安同框)

第 1 步 · 逐页实现(cp 起步,只读标记区):

cp assets/template.html "<输出目录>/shot-x-x_名称.html"
grep -n "改这里\|DUR=" "<输出目录>/shot-x-x_名称.html"    # 行号地图(7 处改这里 + DUR)

用 Read 的 offset/limit 只读标记行附近区域(字体 link+舞台底色 / 画面层 CSS / 画面 HTML / cue 表+DUR),逐一替换:① 字体与配色(Google Fonts 随风格);② 重画画面层;③ 按口播时间戳写 cue(注释引用口播句,如 // 5:20「正常充值」);④ DUR=规定时长±0.5s。底盘(引导脚本/音效引擎/时间轴/镜头调度/HUD)不动。

按需读参考(都很小):references/mechanics.md 播放器+镜头+音效机制 | references/style-cards.md 40 种风格卡片(字体/主色/材质/样板页号) | references/character-reactions.md 双角色吐槽体系(安安×橘雪莉情绪表、中段快闪切立绘、双人同框 cue、气泡强约束模板)。

第 2 步 · 质检node scripts/shot.js 页面.html <毫秒> _t.png [fx fy scale] 多时间点无头截图,逐张查重叠遮挡/中间态穿帮/收尾定格,最后完整播一遍。

第 3 步 · index 总览:按章节分组的导航卡(编号/时长/标题/风格标签),自成一种风格。

翻新已有页面时:先盘点并列清单(用户点名保留的页面一字不动)→ 底盘统一注入 → 逐页重设计画面层 → 补角色/镜头/音效 cue → 质检。

交付标准

  • 黑场「启动播放」起手,2s 渐变后开演;1920×1080 自适应;HUD 底部唤出;可暂停重播;DUR 准确
  • 相邻镜头风格/字体/配色不同;无默认科技暗色;emoji→内联扁平 SVG
  • 关键节拍有镜头运动(推/拉/跟/摇)+ whoosh;关键动作有音效;计数滚动有连击键音
  • 角色出场每页 ≥2 次(中段 30–45% DUR 快闪 + 结尾 75–85% 定场,短页仅结尾):快闪=同一元素换台词换立绘、160ms 闪换重弹;重点页双角色(雪莉先吐槽→安安 1.2s 后接茬,同框退场);气泡必须用统一强约束模板(形态锁定,仅 4 配色可调,见 character-reactions.md)
  • 无底部字幕条(口播只以 cue 注释对齐,不上屏);截图验证无重叠遮挡;数据角注出处;index 可逐页打开

Read the full file on GitHub · 57 lines

Files

What ships with it

60 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.

Changes

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.

  1. 12d ago First seen · 57 lines · 166 tokens per session scan A cd086ff24724

Subscribe to this mod's changes

video-shot-demos is a skill published in the GitHub repository Unclecheng-li/AI_Animation (1,265 stars, last pushed 12d ago), licensed MIT. It adds 166 tokens to every session and 1,598 once invoked, about $0.0008 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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