生成符合 HappyHorse 1.0 严格规则的紧凑提示词(30-55 词),主体先行 + 明确镜头技术 + 音频激活路径(with X audible / speaking English at natural pace)。可选加入"8s 时序节拍"结构。用于"用 HappyHorse 生成视频"、"做个 3-15 秒短片"、"要原生带音频的视频"、"ASMR 视频提示词"等触发场景。
npx skills add https://github.com/cclank/lanshu-awesome-ai-video-kit --skill happyhorse-prompter
HappyHorse 1.0(阿里巴巴 Kling 团队)的核心差异:原生音视频联合生成 + 严格按字数执行。这个 skill 帮你产出符合它脾气的紧凑提示词。
详见 methodology/02-进阶公式.md。
Walking through a forest, a woman...A woman in hiking gear walking through a forest...HappyHorse 对"特写""广角"的理解非常精确,不要留给模型猜测。
写完数一下英文单词数。
头发、水、布料、烟雾、火焰:加 slow motion、motion blur 或 fluid dynamics
音频激活路径(这是 HappyHorse 区别于 Seedance 的核心能力):
with rain on leaves audible → 雨打树叶声with engine roar audible → 引擎轰鸣声speaking English at a natural pace → 自然英语对话speaking Korean at a measured pace → 韩语对话with ambient coffee shop chatter audible → 咖啡馆环境音with the pour sound audible → 倒水/液体声with faint crackling sound audible → 火苗噼啪声with hoofbeats audible → 马蹄声with drone motor whine audible → 无人机马达声complete silence / near silence with faint wind audible → 纯静或环境底噪不写音频提示 = 模型可能不生成音频或乱生成。主动写。
如果用户的需求包含时间结构(如"先静止 2 秒,然后画面渐显"、"前 3 秒做 A,后 5 秒做 B"),用 CrePal 时序节拍写法:
8s duration. First 2s: black. Slow fade reveals: [画面 A]...
否则直接写 30-55 词紧凑版。
[主体(明确特征)] [动作(具体)] [场景] [镜头大小+运动] [光影] [音频路径] [质量/风格].
英文写。
## 生成的提示词
\`\`\`
[完整提示词]
\`\`\`
**词数**:N · **时长建议**:N-Ns · **比例**:[X:Y]
**音频路径**:[突出说明用了什么音频提示]
**可调点**:[换音频/换镜头/换光影都可以怎么改]
时长信息有 2 个去处,二选一,不能同时,也不能放错位置:
| 用户场景 | 时长去处 | 写法 |
|---|---|---|
| 用户只说"做个 X 视频"(无明确时序) | 只放在外部元数据 | prompt 内不写时长;时长建议:5-7s 放在末尾元数据行 |
| 用户明确说"前 N 秒...然后..."(有时序节拍) | 放 prompt 最前面作时序锚点 | Ns duration, first Ns: black. [content] 这种结构 |
反例(❌ 不要这样写):
晨光透过咖啡店玻璃门...温暖琥珀色调,16:9,5 秒。 ← 把时长埋在 prompt 中段/末尾
正例 A(✓ 无明确时序 — prose 不带时长):
晨光透过咖啡店玻璃门,木质门牌"OPEN"翻转...
(门铃叮当声 + 咖啡机蒸汽嘶嘶声)
然后元数据行写:时长建议:5s
正例 B(✓ 有明确时序 — 时长前置):
5s duration. 晨光透过咖啡店玻璃门,木质门牌"OPEN"翻转...
自检清单(输出前必过):
用户输入:"做个雨夜街头吉他手的视频"
判断:6-8 秒紧凑场景,需要带音频(吉他声+雨声)→ 不需要时序节拍,用紧凑模板。
输出:
A guitar player busking on a rain-slicked city street at night, medium shot, neon reflections on wet pavement, rain falling softly, with acoustic guitar sound audible, warm tungsten light from shop windows.
词数:30 · 时长建议:6-8s · 比例:16:9
音频路径:with acoustic guitar sound audible 激活原生吉他音轨;环境雨声不写也会带(因为画面就是雨)。
可调点:把 warm tungsten light from shop windows 换成 harsh sodium streetlight only 改成冷峻感;加 with light rain on awning audible 强化雨声层次。
用户输入:"想要 8 秒,前 2 秒黑屏,然后慢慢揭示一片山谷"
判断:明确的时间结构 → 用时序节拍模板。
输出:
8s duration, first 2s: black. Slow fade reveals: wide shot, mountain valley at dawn, low mist between pine trees, single dirt road leading into the scene, no people. Camera very slowly pushes forward on a dolly. Soft blue-gold light on the horizon. Quiet, cinematic, high production value.
词数:48 · 时长建议:8s · 比例:16:9
音频路径:未指定 → HappyHorse 默认匹配晨间风声底噪;可加 with distant birdsong audible 进一步强化。
可调点:把 dirt road 换成 wooden cabin in distance 增加视觉锚点;blue-gold light 改 pink-orange 调更暖。
当有参考图时,不要重复描述图中已有的内容,专注于描述变化:
| ✅ 应该写 | ❌ 不要写 |
|---|---|
| walks toward camera / head turns left | 重复图中已有的服装颜色 |
| slow push-in / lateral tracking right | 重复图中已有的构图 |
| hair drifts / fabric ripples / steam rises | 重复图中已有的主体外观 |
agent-im 会话技能 - 通过 liblib.tv 的 AI 能力生成和编辑图片/视频。覆盖场景包括:生成(文生图、文生视频、图生视频、做动画、画一个xxx、来段xxx)、编辑修改(把xxx换成yyy、去掉xxx、加上xxx、改成xxx、调整xxx、局部修改、改镜头)、风格转换(风格迁移、转绘、换风格)、视频续写延长、复刻视频/TVC/宣传片、短剧/短漫剧生成、音乐MV生成、产品广告/展示片制作、分镜/故事板设计、教育视频/短视频制作。当用户提到 liblib、libtv、上传参考图/视频、查看生成进度时也应触发。关键判断:只要用户的请求涉及 AI 图片或视频的创作、生成、编辑、修改,无论措辞如何(如"画只猫"、"做个海报"、"把纸船换成爱心"、"这个视频帮我改一下"、"帮我复刻这段视频"、"用这首歌做个MV"、"一句话生成短剧"),都必须触发此技能。
This skill should be used when the user asks to "generate video prompts", "create Seedance prompts", "write video descriptions", mentions "Seedance", "seedance", "即梦", "即梦平台", "视频提示词", "视频生成", "AI视频", "短剧", "广告视频", "视频延长", or discusses video prompt engineering, AI video generation, or Seedance 2.0 workflows.
Best practices and techniques for writing effective AI video generation prompts. Covers: Veo, Seedance, Wan, Grok, Kling, Runway, Pika, Sora prompting strategies. Learn: shot types, camera movements, lighting, pacing, style keywords, negative prompts. Use for: improving video quality, getting consistent results, professional video prompts. Triggers: video prompt, how to prompt video, veo prompts, video generation tips, better ai video, video prompt engineering, video prompt guide, video prompt template, ai video tips, video prompt best practices, video prompt examples, cinematography prompts
This skill is a practical, 'use-it-while-debugging' reference for getting a LiveKit + Letta voice agent working reliably.
Download screenshot baselines from the latest CI run and commit them. Use when asked to update, accept, or refresh component screenshot baselines from CI, or after the screenshot-test GitHub Action reports differences. This skill should be run as a subagent.
| Turn vague taste, screenshots, URLs, product notes, or "make it feel like this" references into a grounded DESIGN.md plus an implementation handoff. Use it before prototypes, decks, redesigns, or image remix work when the user needs a reusable visual direction rather than a one-off prompt.
>- Upload local assets (images, mockups, extracted HTML, design markdown) to a Stitch project. ALWAYS use this skill when you need to upload visual assets, HTML pages, or design docs to Stitch, particularly when direct MCP tool calls fail or truncate due to base64 token limits.
This skill helps users automatically extract channel-level and video detail data from a specific YouTube channel via BrowserAct API. Agent should proactively apply this skill when users express needs like extracting channel video data, getting latest or popular videos from a YouTube channel, tracking competitor channel content, extracting video metrics such as views likes comments, retrieving subscriber count and channel info, monitoring posting cadence of a YouTube channel, gathering video data for content strategy analysis, getting earliest videos of a YouTube creator, analyzing engagement signals across a full channel, and downloading structured YouTube video details without manual scraping.
Take cclank/happyhorse-prompter from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.