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 Supreme-Ultimate/novel-to-script-team --skill film-storyboard-skillgit clone --depth 1 https://github.com/Supreme-Ultimate/novel-to-script-teamWrote 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/supreme-ultimate/novel-to-script-team/film-storyboard-skill)<a href="https://agentmods.dev/skills/supreme-ultimate/novel-to-script-team/film-storyboard-skill"><img src="https://agentmods.dev/badge/skills/supreme-ultimate/novel-to-script-team/film-storyboard-skill/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/supreme-ultimate/novel-to-script-team/film-storyboard-skill"><img src="https://agentmods.dev/badge/skills/supreme-ultimate/novel-to-script-team/film-storyboard-skill.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 | $0.00057 | $0.01884 |
| Opus 5 | $0.00028 | $0.00942 |
| Sonnet 5 | $0.00011 | $0.00377 |
| Haiku 4.5 | $0.00006 | $0.00188 |
Grade A, and why
film-storyboard-skill 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.
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
影视分镜生成技能
必读
../../references/00-first-principles.md../../references/08-camera-and-cinematography.md../../references/09-storyboard-methodology.md
技能说明
影视分镜生成技能，将剧本、故事梗概或分场大纲转化为可用于 AI 出图的分镜提示词。采用分层渐进式流程：先进行节拍拆解识别叙事锚点，再生成 Beat Board 九宫格提示词，最后为每个锚点生成 Sequence Board 四宫格提示词展开段落动作。四宫格生成时以九宫格对应格作为参考图片（垫图），确保人物与场景一致性。
输入
- 剧本/梗概/分场文本
- 视觉风格（默认：真人风格，可被用户覆盖）
输出
beat-breakdown.md— 节拍拆解表beat-board.md— Beat Board 九宫格提示词（9格）sequence-board.md— Sequence Board 四宫格提示词（每个 Beat Anchor 一组，共 9 组 36 格）
执行流程
第一步：生成节拍拆解表
理解输入：
- 读取用户提供的剧本/梗概/分场文本
- 确认视觉风格（默认：真人风格，可被用户覆盖）
节拍拆解：
- 识别叙事曲线的关键拐点
- 创建 beat-breakdown.md，将节拍拆解表写入
第二步：生成 Beat Board 九宫格提示词
读取上游产物：
- 读取 beat-breakdown.md
生成 Beat Board 提示词：
- 将 Beat Anchor 转化为九宫格提示词
- 提示词采用叙事描述式，参考
references/11a-seedance-prompt-methodology.md的模板与示例 - 创建 beat-board.md，将九宫格提示词写入
第三步：生成 Sequence Board 四宫格提示词
读取上游产物：
- 读取 beat-board.md
生成 Sequence Board 提示词：
- 为每个 Beat Anchor 生成一组四宫格提示词
- 必须继承九宫格对应格的人物/场景/光色描述
- 提示词采用叙事描述式，参考
references/11a-seedance-prompt-methodology.md的模板与示例 - 创建 sequence-board.md，将四宫格提示词写入
分镜核心原则
一致性优先原则
- 四宫格提示词必须继承九宫格对应格的人物/场景/光色描述
- 发生变化必须显式说明原因
连贯性检查原则
- 参考
references/09-storyboard-methodology.md连贯性与剪接相关规则
工程约束原则
- 九宫格用于"选点与定锚"，生成后作为四宫格的参考图片（垫图）
- 四宫格生成时，使用九宫格对应格作为参考图片输入
节拍拆解（Beat Breakdown）
目的
识别叙事曲线的关键拐点，为分镜提供叙事锚点。
输出格式
| Beat Anchor | 叙事目的 | 情绪 | 时长估算 |
|---|---|---|---|
| B1 | [叙事目的] | [情绪] | [时长] |
| B2 | [叙事目的] | [情绪] | [时长] |
| ... | ... | ... | ... |
| B9 | [叙事目的] | [情绪] | [时长] |
拆解原则
- 识别 9 个关键拐点（Beat Anchor）
- 每个 Beat Anchor 对应一个叙事目的和情绪
- 时长估算用于后续动态提示词生成
Beat Board 九宫格提示词
目的
为 9 个 Beat Anchor 生成九宫格提示词，用于 AI 出图。
输出格式
## Beat Board 九宫格提示词
请生成一张 3×3 九宫格布局的电影分镜图像。每个格子代表一个关键叙事节点（Beat Anchor），所有格子必须保持视觉风格统一。请按照以下规范生成。
### 视觉规范
整体风格：[描述整体美术风格]
色彩基调：[描述全片色彩倾向]
材质质感：[描述关键材质表现要求]
### 宫格布局
第1行：格1-3 / 第2行：格4-6 / 第3行：格7-9
### Panel Breakdown（分镜拆解）
格1——【B1: [叙事目的]】
视角：[完整叙事描述：景别、环境、人物、动作、光线、色调、氛围，融合为流畅段落]
重点：[这个格子的核心视觉元素]
格2——【B2: [叙事目的]】
视角：[完整叙事描述]
重点：[核心视觉元素]
...（共 9 格）
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.
- 12d ago First seen · 184 lines · 57 tokens per session scan A d83f2e9449c0
film-storyboard-skill is a skill published in the GitHub repository Supreme-Ultimate/novel-to-script-team (167 stars, last pushed 4mo ago), licensed MIT. It adds 57 tokens to every session and 1,884 once invoked, about $0.0003 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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