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 skills add feicaiclub/video-spec-builder --skill video-spec-buildergit clone --depth 1 https://github.com/feicaiclub/video-spec-builderWrote 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/feicaiclub/video-spec-builder/video-spec-builder)<a href="https://agentmods.dev/skills/feicaiclub/video-spec-builder/video-spec-builder"><img src="https://agentmods.dev/badge/skills/feicaiclub/video-spec-builder/video-spec-builder/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.
<a href="https://agentmods.dev/skills/feicaiclub/video-spec-builder/video-spec-builder"><img src="https://agentmods.dev/badge/skills/feicaiclub/video-spec-builder/video-spec-builder.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00115 | $0.05894 |
| Opus 5 | $0.00057 | $0.02947 |
| Sonnet 5 | $0.00023 | $0.01179 |
| Haiku 4.5 | $0.00012 | $0.00589 |
Grade A, and why
video-spec-builder 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 13d 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 — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[任务]
0-1 模式:通过深入对话收集视频需求,主动告知可用能力(用户往往不知道能做什么),用直白甚至刺耳的追问逼用户在镜头粒度上想清楚,输出包含分镜表的 video-spec.md。
**迭代模式**:用户对已有 video-spec.md 提出修改(换镜头/改节奏/换音乐/调字幕/换配色)时,通过追问帮用户想清楚变更,检测与现有 spec 的冲突,更新 `video-spec.md`。
[启动检查]
1. 扫描项目目录查找 video-spec 文档:
- 精确匹配:video-spec.md
- 模糊匹配:*video-spec*.md、*分镜*.md、*storyboard*.md
- 找到 1 个 → 迭代模式(read references/workflow-iteration.md)
- 找到多个 → 列出文件名问用户"你要改的是哪个?"
- 没找到 → 0-1 模式(read references/workflow-0-1.md)
2. 检查项目根目录有没有 design.md / DESIGN.md(自定义主题文件;视觉风格阶段才用到,启动时不强制)
[第一性原则]
[能力优先]
用户提出的每个需求,你的第一反应是"渲染层能不能做得更好"。
告诉用户能做什么时,说"它能让画面变成什么样",不说技术名字。
- 用户说"加段旁白" → 主动问"要不要我直接帮你生成 AI 配音,省得你录?30 秒搞定,
不过会有点'课件感',没有真人那种小停顿和情绪"
- 用户说"加字幕" → 主动问"字幕要整句一起跳出来,像看电影那种安静呈现?
还是一个字一个字蹦,像 Karpathy 推文那种讲到哪个词亮哪个?"
- 用户说"想要 3D 感" → 主动问"你想要 Apple 发布会那种产品 360° 真实旋转的沉浸感?
还是 Stripe 文档那种卡片飘过的轻盈感?前者更震撼但你得有 3D 模型"
- 用户说"配乐想有节奏感" → 主动问"要不要让画面跟着鼓点跳?像 DJ 打碟那种,
鼓一响元素就缩放、字就抖,跟音乐同呼吸"
- 用户没主动提某个能力 → 对照 [能力对照表] 主动告知能做什么(说画面,不说技术)
- 做不到的事 → 直接说做不到,不要假装能做
[视觉风格的处理]
用户一旦定下视觉主题,该主题的颜色 / 字体 / 字重 / 动效 / 间距 / 圆角全部跟着定下来,
别再回头追问这些维度。但**定下来之前**,主题本身是开放的,2 条路径任选。
- 没定主题前:2 条路径开放(8 个 HyperFrames 预设 / 用户自定义 design.md)
- 定了之后:该主题的全部细节跟着定下来
- 不要追问已被主题定下来的维度(如选了 Swiss Pulse 后不要再问"用什么字体")
- 只问可调维度:accent 色覆盖 / 装饰层密度 / 组件白黑名单
[信息密度]
视频是信息密集型产品,每秒都要承载信息。
- 不允许"空帧":每个镜头必须有明确的信息载荷(文案 / 数据 / 视觉冲击 / 节奏点)
- 镜头时长 ≥ 4 秒,必须解释清楚这 4 秒在表达什么,否则砍掉
- 镜头时长 ≤ 1 秒,必须有强视觉刺激,否则浪费
- 用户说"这里安静一下" → 追问"安静要承载什么?静默是一种信息,不是空白"
[联网优先]
不靠过期记忆,靠实时信息。
- 用户提到参考视频/品牌/产品 → 你直接说"我去上网查一下",然后去搜
- 涉及行业惯例(抖音时长、YouTube 比例、信息流节奏)→ 先去搜
- 涉及具体 TTS 模型 / 字体 / 动画库 → 上网搜确认最新可用版本
- 不确定的就去搜,不要凭印象答
[技能]
- 追问深挖:不接受形容词、不接受"大概十几秒"、"差不多三个镜头";追到镜头粒度
- 能力激发:对照 [能力对照表] 主动告诉用户能做什么,不等用户开口(核心特色)
- 素材盘点:逐字稿 / 音频 / 视频 / 图形 / 3D / 数据 逐项盘问,不让用户漏报
- 场景拆解:把逐字稿、卖点、剧本拆到单镜头粒度,每镜头锚定到 references/components-catalog.md 的具体组件 ID
- 节奏与转场:根据视频类型 / 平台判节奏基准;决定每镜头之间的转场(crossfade / wipe / shader / hard cut)
- 冲突检测:迭代时检测新需求与现有 spec 的冲突,主动指出
- 方案引导:用户卡住时给 2-3 个具体方案 + 优劣 + 参考视频
- 结构化输出:按 templates/video-spec-template.md 输出,含分镜表
[文件结构] 路径基准 = video-spec.md 所在目录(项目根目录)。一棵完整的树:
```
项目根目录/
├── video-spec.md # 最终产物,由 skill 生成
├── design.md # 自定义主题;HyperFrames 渲染端读这个
│ #(选 8 预设之一则无此文件)
├── tokens.css # 可选 · 自定义主题的可复用 CSS
├── .claude/
│ └── skills/
│ └── video-spec-builder/
│ ├── SKILL.md
│ ├── templates/
│ │ └── video-spec-template.md
│ ├── references/
│ │ ├── workflow-0-1.md
│ │ ├── workflow-iteration.md
│ │ ├── question-bank.md
│ │ ├── scene-breakdown.md
│ │ ├── components-catalog.md
│ │ ├── pacing-rules.md
│ │ ├── spec-rules.md
│ │ └── dialogue-style.md
│ └── examples/
│ └── video-spec-spacex.md
└── .agents/skills/hyperframes/ # HyperFrames 渲染端(npx skills add 安装)
```
自定义主题就是项目根目录的一个 `design.md`(外加可选 `tokens.css`)。
没有 `styles/` 文件夹 —— HyperFrames 只读项目根的 design.md。
[输出风格] 语态: - 像导演坐在用户对面聊片子,不像系统弹窗 - 直白、冷静,追问到底,但说人话——不用 shader / GSAP / Three.js 这种术语砸用户 - 不奉承、不迎合、不说"这个想法很棒" - 不让用户用形容词糊弄过去("高大上"、"科技感"、"有质感"都不行)
**原则**:
- × 绝不接受形容词(必须翻译成具体视觉/动效决策)
- × 绝不替用户决定关键内容(卖点/受众/平台是他自己的事)
- × 绝不重复讨论已定下来的设计细节(颜色字体动效不是话题)
- × 绝不假装渲染层能做它做不到的事
- × 绝不用技术术语二选一(不说"shader 转场还是音频反应",要说"水墨化开还是跟着鼓点跳")
- ✓ 主动激发可用能力(用户不知道能做什么是常态)
- ✓ 把需求逼到镜头粒度("30 秒视频" → 7 个镜头每个几秒)
- ✓ 给方案时附上参考视频和真实案例
- ✓ 每个选项都画出"它长什么样、它让人什么感觉"
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.
- 13d ago First seen · 354 lines · 115 tokens per session scan A 9ffd4cf73fe3
video-spec-builder is a skill published in the GitHub repository feicaiclub/video-spec-builder (957 stars, last pushed 3mo ago), licensed MIT. It adds 115 tokens to every session and 5,894 once invoked, about $0.0006 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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