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Novel Outline

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suihe1
novel-outline

把小说或故事改编为短剧大纲,确定人物去留、分集因果、剧情重点与资产预算,产出可校验 JSON、Markdown 和评审报告。用于短剧大纲、改编方案和现有大纲诊断;不写完整剧本或镜头方案。

Overview

Publishersuihe1
Repositoryshort-drama-production
Skill namenovel-outline
Stars
184
Forks
24
Bundled files
10
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by suihe1 on GitHub. Read the source before you install it.

Installation

Install the Novel Outline AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/suihe1/short-drama-production/tree/main/skills/novel-outline
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/suihe1/short-drama-production.git /tmp/short-drama-production
mkdir -p .claude/skills
cp -r /tmp/short-drama-production/skills/novel-outline .claude/skills/novel-outline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Novel Outline in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Novel Outline on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Novel Outline is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

输入与创作权限

先读用户实际材料与目标,复用已确定的事实和规格;已有剧本、资产或分镜直接进入相关工作,不为流程完整重写上游。未授权的删线、合人、改变人物身份、主题、结局或重要表演意图,先展示原位置、具体方案与得失,再由用户选择;已授权的局部修正直接完成。

下面的类型经验、批次和创作预算是适配起点,不是用户接受过的创作要求。旧校验器可能仍将部分经验规则报为失败:区分实际数据/引用/模型接口错误与创作建议,说明不适用项,保留原稿;不伪造字段、不静默改戏或降低技术投产要求。总控可用时参考其 references/creative-agreement.md;独立任务按本段处理,不强制依赖总控。

novel-outline

输入一本小说 + 目标参数,输出短剧改编大纲五件套。四件模型写、一件脚本算(资产清单从分集数据自动汇总)。

{baseDir} = 本文件所在目录。脚本 {baseDir}/scripts/novel-outline.mjs,零依赖,node 直接跑。

边界(不做的事):不写剧本台词、不做分镜、不出图像/TTS 提示词。梗概按阅读与决策需要组织,必要的对白引用可以保留。想从小说拆角色设定(画像/形象提示词/设定图),那是 novel-characters 的活。


Step 0 — 复用项目参数,补齐真正缺失的信息

先读取用户本轮与既有约定、production.json 和输入文本。能确定的参数直接复用;只有会改变整部改编的缺失项才集中询问,并继续阅读源文、整理人物与冲突等不依赖答案的工作。

参数处理
总集数 × 单集时长优先继承已有约定;确实未知且影响改编规模时询问
题材从原文与创作要求确定;类型混合或目标不明时询问
改编幅度继承用户授权;未确定时先给具体取舍方案,不能默认抽核或借壳
已有偏好默认无(想保哪个角色、哪场戏)

角色、场景规模与叙事节奏由原作、用户目标和具体产能决定,不以默认数量阈值删合人物或增加爽点。默认不运行这类创作门;reviewPolicy: strict 仅在用户明确选择旧版整套规则时启用。

如果用户有 novel-characters 的产出(cast.json),直接拿来当人物原料——角色、别名、关系都是现成的,不用重拆原文。分档按 importance 映射:protagonist/major → lead,supporting → support,minor → functional。

Step 1 — 定位输入

按任务选择阅读顺序,以下是长篇定位的一种起点;完整短篇可直接通读:

  1. 用户点名的精读章节
  2. 章节目录 + 简介
  3. 全文分卷摘要(Step 2)

禁止凭书名脑补内容——一切判断基于给到的文本。落地手段:adaptation.keep 的关键取舍要附 evidence(原文逐字片段)。

直接粘正文的先落成 .txt。输出目录:用户指定就用,没指定用原书同级目录。

Step 2 — 分卷摘要(长文本才需要)

这一步是脚手架,不是交付物——分卷摘要是给没读过原文的模型压缩用的。两种情况直接跳到 Step 3:

  • 短篇,单卷装得下
  • 当前会话已经通读过原文(比如刚跑完 novel-characters 的分块扫描)——不用再压缩一遍,也不用事后补档

长篇且没读过原文:

bash
node {baseDir}/scripts/novel-outline.mjs chunk <book.txt> <workdir>

按章节标题分卷(默认每卷 15 章,--per-volume 可调),识别不出章节就按字数切。打印 {"volumes": N, ...};truncated: true 就明确告诉用户尾部没扫到,别闷着。

每卷一个子代理(支持并发就同一条消息里全部发出):读 {baseDir}/references/volume-pass.md,读 <workdir>/vol-NN.txt,把卷摘要写到 <workdir>/summary-NN.json,只回一句「done NN」。

Step 3 — 快版骨架 → 用户拍板 ⛔

读 {baseDir}/references/outline-pass.md 和 {baseDir}/references/schema.md,照着做。产出骨架四块(adaptation / characters / scenes / beats),写成 <workdir>/outline.json。

bash
node {baseDir}/scripts/novel-outline.mjs validate <workdir>/outline.json --stage beats

先展示原文依据、保留点、拟议删合与结局方向,以及推荐理由和损失。未授权的结构取舍由用户决定后再展开;若已有明确改编授权覆盖当前方案,直接推进,不重复确认。旧校验器的 beats 档若仅因类型规则不适用失败,仍可呈现方向提案,不为通过而凭空增加爽点。

Step 4 — 细版骨架

吸收用户意见改骨架,再过一次 validate --stage beats。用户没意见就直接进 Step 5。

Step 5 — 分集梗概(分批)

批次按篇幅、上下文容量与用户审阅需要确定。先固定各批交接状态:人物知情范围、道具归属、时间推进与前后钩子,再处理可独立的分集;存在未决因果的批次顺序编写。每个子代理拿到:拍板后的骨架四块、自己负责的集数区间、区间内的爽点,读 {baseDir}/references/episode-pass.md 照着写,产出写到 <workdir>/eps-NN.json。

合并时按 ep 排序拼进 outline.json 的 episodes。

Step 6 — 校验 ⛔ 不能跳

bash
node {baseDir}/scripts/novel-outline.mjs validate <输出目录>/<书名>-outline.json

默认校验结构与实际引用,不要求固定角色数量、每几集有爽点、第一集钩子、结尾悬念、三人必须拆解或梗概禁止引号。没有爽点可用空 beats;无需改编删线时 cut 可为空,不因“抽核”标签强迫砍戏。用户选择旧版 strict 时才检查这些旧模板规则。

结构与引用错误必须修复;题材或平台节奏与默认阈值冲突时,先记录创作依据,再用已支持的 params.thresholds 调整并重新校验,不能为过门硬塞爽点或删掉必要角色。

Step 7 — 输出与汇报

bash
cd <输出目录>
node {baseDir}/scripts/novel-outline.mjs render <书名>-outline.json --md   > <书名>-outline.md
node {baseDir}/scripts/novel-outline.mjs render <书名>-outline.json --html > outline-report.html

报告界面默认中文;用户要英文界面就加 --lang en(或在 outline.json 顶层写 lang 字段,--lang 优先)。只翻译界面文案,数据内容(爽点类型、梗概、质量门文案)原样出。

report 里自带:KPI 带、关键决策(拍板三件事,大爆点列表和角色位统计自动算)、爽点时间轴(空档标在轴上,超阈值变红)、每集调度矩阵、场景概览卡、资产量折算、质量门(✓/✗ 烘进页面,未过弹病灶横幅)、导出 JSON 按钮(下载的就是 outline.json 原样)。

汇报一句话说清:几集、几个角色几个场景、爽点分布、报告路径;被截断或有没过的门要明说。

最终落地:

<输出目录>/
├── <书名>-outline.json
├── <书名>-outline.md
└── outline-report.html            ← 双击就能开

体检模式

用户贴一份已有大纲只想要诊断:转成 outline.json(缺的字段问用户或标注缺失),然后:

bash
node {baseDir}/scripts/novel-outline.mjs checkup <outline.json>   # 终端 ✓/✗
node {baseDir}/scripts/novel-outline.mjs render <outline.json> --html > outline-report.html

质量门面板就是诊断书。未过的门不阻止渲染——要的就是把病灶摆出来看。

联动更新

用户改了上游就跑一次 validate,报错会点名下游哪里断了:合并人物后哪些集还引用着被删的 ID、砍场景后哪些集空转、爽点挪动后哪里出现真空区。不要靠记忆提示联动,靠校验器。

边界

  • 单次上限 60 卷(每卷 15 章约 900 章)。超了明确报 truncated,不静默截断
  • 阈值是参数不是圣旨:平台不同就用 params.thresholds 覆盖,别改代码
  • 报告界面内置中英(--lang,默认中文、或跟 outline.json 的 lang 字段):界面文案与质量门标签翻译,数据内容(爽点类型、梗概、人名)与门的失败详情保持原文
  • 五件套的第五件(资产清单)永远是算出来的,模型手写必漏

自测

bash
node {baseDir}/scripts/selftest.mjs

219 项断言,不调模型、不花额度。13 道质量门每一道都有击穿用例——证明它真的会拦。改完脚本先跑这个。

自带样例

{baseDir}/examples/渡口-outline.json:把短故事《渡口》(novel-characters 的自带样例)改编成 6 集 × 2 分钟的微型大纲,四角色三场景四爽点,全部质量门通过。当质量基准,也是自测夹具。

制作交接

独立使用时,自检后主动打开当前报告并给绝对路径链接,说明本轮范围、检查重点和下一步;需要锁定内容时在对话中收取通过或修改结论。已有确认覆盖当前版本就不重复询问,打开页面或下载 JSON 不算批准。总控已接管时,由总控统一收取这次结论,不另开重复审批。当前内容、依赖或源图改变后,不因旧文件仍存在就跳过复核;输出新版本并保留原审阅笔记。

本项目的阶段职责、变更记录和交付顺序由 short-drama-production 的 references/company-workflow.md 统一维护;未安装总控时按本 skill 的输入和交付范围独立完成,不将总控变成硬依赖。

涉及尚未授权的创作取舍时,给用户 2–3 个有具体差异的选项,说明收益、损失与推荐,允许保留原稿或自定义。模型先完成阅读、诊断和短样段,不把准备工作推给用户;已经明确授权的范围直接执行。未经用户选择,不把暂定片长预算升级成删词、删情绪段落的理由。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Novel Outline AI skill do?

把小说或故事改编为短剧大纲,确定人物去留、分集因果、剧情重点与资产预算,产出可校验 JSON、Markdown 和评审报告。用于短剧大纲、改编方案和现有大纲诊断;不写完整剧本或镜头方案。

Why use Novel Outline on TypingMind?

Because you install it once and use it with any model. Novel Outline is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Novel Outline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/suihe1/short-drama-production/tree/main/skills/novel-outline. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Novel Outline?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Novel Outline?

As many as you like. As long as a model supports skills, you can use Novel Outline with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Novel Outline AI skill free?

Yes. It is published on GitHub by suihe1 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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