opus-video-prompts: Claude Opus 5.5 用代码生成视频:全网案例与可直接复制的提示词

by joeseesun · Claude Skill · ★ 724

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Security audit verdict: SAFE · quality 60/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

claudeclaude-codemotion-graphicsopuspromptsremotionvideo-generation

Quick Facts

Stars724
Forks65
CategoryClaude Skill
Quality Score60/100
Last Updated2026-09-27
Created2026-09-27
Platformsclaude-code
Est. Tokens~11k

About opus-video-prompts

Opus 5.5 Video Prompts Claude Opus 5.5 “用代码拍视频”:全网案例与可直接复制的提示词 18 份完整提示词 · 54 个公开案例 · 9 种技术路线 · 持续更新 提示词速查 · 精选提示词 · 案例总览 · 写法经验 · 资料来源 这是什么 Opus 5.5 本身不输出视频文件。它的做法是写代码画出每一帧:HTML Canvas、p5.js、Three.js、Remotion、Manim、Blender 脚本都有人用。然后用无头浏览器逐帧截图,再用 FFmpeg 合成 MP4;配乐一般用 Web Audio 或 Python 合成,旁白接 TTS。 所以它擅长动态图形、手绘/线稿/水墨动画、科普讲解、产品发布片、歌词 MV,不擅长写实的真人镜头。真要写实画面,常见做法是让它调用 Seedance、Runway、Higgsfield...

Compatible Skills

These tools work well together with opus-video-prompts for enhanced workflows:

  • mythos-agent-pipe — semantic(0.35)+complementary+rare_topics+similar_pop+shared_platform (57%)
  • lemo-opuscar — semantic(0.30)+complementary+rare_topics+similar_pop+shared_platform (55%)
  • AIEV — semantic(0.29)+complementary+rare_topics+similar_pop+shared_platform (54%)

opus-video-prompts alternative? Top 6 similar tools

Looking for a opus-video-prompts alternative? If you're comparing opus-video-prompts 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.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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