shuohao-skills is a collection of agent skills for turning a novel into production materials for an AI short-drama pipeline, including character profiles, outlines, art references, scripts, and storyboards. It is for creators using Claude Code or Codex to plan and prepare AI-generated short videos. The catalogue add-ons implement the separate stages of this workflow and can also assemble their reports.
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 eternityspring/shuohao-skills --skill novel-storyboardgit clone --depth 1 https://github.com/eternityspring/shuohao-skillsWrote 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/eternityspring/shuohao-skills/novel-storyboard)<a href="https://agentmods.dev/skills/eternityspring/shuohao-skills/novel-storyboard"><img src="https://agentmods.dev/badge/skills/eternityspring/shuohao-skills/novel-storyboard/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/eternityspring/shuohao-skills/novel-storyboard"><img src="https://agentmods.dev/badge/skills/eternityspring/shuohao-skills/novel-storyboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00353 | $0.03878 |
| Opus 5 | $0.00177 | $0.01939 |
| Sonnet 5 | $0.00071 | $0.00776 |
| Haiku 4.5 | $0.00035 | $0.00388 |
Grade A, and why
novel-storyboard 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
novel-storyboard
给 AI 短剧出分镜——管线里第一个直接面对视频模型的层。前提刻在骨子里：镜头是生成出来的，多切一镜的成本几乎为零，所以这里不心疼镜头数量，上限只有一个：视频模型单段生成的时长（默认 15 秒）。
核心机制：镜头认领节拍。 每个镜头声明它覆盖剧本某场的哪几个连续节拍（sceneIndex + beats: [起, 止]），镜头不许跨场次——换景必换镜。这让分镜和剧本的关系变成可机械对账的：
| 交付 | 解决什么 |
|---|---|
| 节拍认领 | 每个节拍被恰好一个镜头认领、顺序不乱——剧本改了重跑 validate，失效的镜头当场点名 |
| 单镜头 ≤ 15 秒 | AI 视频单段生成上限，长对话在这里被强制拆镜（params.maxShotSeconds 按模型改） |
| 台词装得下 | 认领节拍的台词秒数 ≤ 镜头秒数——逐镜检查，不是拍脑袋 |
| 首帧 + 运动双提示词 | 首帧给图像模型（配合参考图），运动是模型无关的过程描述；景别、运镜是枚举，英文短语必须写进对应提示词 |
| H3 视频提示词（每镜一段） | MiniMax H3 的 I2VA 结构：固定对齐指令 + integrated_multimodal_description + overall_soundscape + non_diegetic_music。认领节拍的台词逐字进 <d>[Chinese] …</d> 块——对白、声景、配乐一段提示词全带上 |
| 生成批次单 | 同场景 + 同光照的镜头归一批，共用同一张环境参考图——AI 版的顺场表，脚本自动汇总 |
| 配音对齐单 | 每句台词对到镜号——TTS 音频贴到哪一段视频，脚本自动汇总 |
{baseDir} = 本文件所在目录。脚本 {baseDir}/scripts/novel-storyboard.mjs，零依赖，node 直接跑。
边界（不做的事）：不写戏不改台词（novel-script 的活）、不出场景/角色/道具设定图（novel-art / novel-characters 的活）、不做视频生成与剪辑合成。口型/唇形同步暂不管——那是生成管线的事。
Step 0 — 定输入与范围
script.json 是硬前提——分镜离开剧本没有意义，validate/render 都必须给 --script。其余上游按有则用：
--outline/--cast：提示词禁人名检查 + 报告里 C01 显示成人名--art：报告里 S01 显示成场景名 + 批次单嵌场景设定图--shots <卡片目录>：可选挂载 shot-recipes 的镜头配方卡库（指向shot-recipes/references/cards，只接受目录不接受导出的 JSON），开第 17 道shot-recipe门。没装 shot-recipes 就别给——本 skill 自包含，不依赖它
一次切几集：跟剧本的批次走（剧本写到哪就分到哪），默认一批 ≤ 3 集。
Step 1 — seed 工作底稿
node {baseDir}/scripts/novel-storyboard.mjs seed <script.json> --eps 1-3 > <workdir>/storyboard.json
确定性展开：每场的节拍清单（编号、动作/台词、每拍秒数、说话人）进 seedScenes，这就是切镜时的工作底稿。每拍几秒是算出来的，不要让模型重新估。 shots 留空，切镜才是模型的活。
Step 2 — 逐集分段切镜
每集一份任务，能并发就并发。每份任务拿到：
{baseDir}/references/storyboard-pass.md和{baseDir}/references/schema.md（读它们，照着做）- 该集的 seedScenes 底稿 + 场景卡（art.json 的锚点与光照提示词）+ 角色卡（cast.json 的形象要点）
流程：先按剧情单元分段（每段 9–15 秒、不跨场），段内切 2–5 秒的分镜（对话正反打、关键动作插入特写、进场三件套——切镜语法都在 storyboard-pass.md），每切写一条分镜图提示词。
每段写一条 h3Prompt，照 {baseDir}/references/h3-prompt.md 写（官方方法论的内化版，不依赖任何外部 skill）。官方口径默认英文（promptLang 可切中文），每个镜头独立一行。要点：首行对齐指令和 [Shot k] 切点时刻由分镜秒数推导，一个字符都不许漂（validate 逐字对账）；认领台词逐字进 <d>[Chinese] …</d>；每切的运镜词写进自己那一行；声景与配乐分进后两个字段——声景也是动作指令，画面改了声景一起改。
What ships with it
14 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.
- assets/report.webp 186 KB
- examples/渡口-storyboard.json 35 KB
- README.en.md 11 KB
- README.md 11 KB
- references/frame.md 3.8 KB
- references/h3-prompt.md 3.9 KB
- references/report-style.md 3.1 KB
- references/schema.md 5.8 KB
- references/storyboard-pass.md 4.8 KB
- references/test-fixtures/shot-recipes/hands-tell.md 184 B
- references/test-fixtures/shot-recipes/insert-beat.md 191 B
- references/test-fixtures/shot-recipes/ots-shot-reverse.md 217 B
- scripts/novel-storyboard.mjs 89 KB runs code
- scripts/selftest.mjs 34 KB runs code
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 · 191 lines · 353 tokens per session scan A 5e7a52d78cbb
novel-storyboard is a skill published in the GitHub repository eternityspring/shuohao-skills (3,208 stars, last pushed 17d ago), licensed Apache-2.0. It adds 353 tokens to every session and 3,878 once invoked, about $0.0018 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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