reverse-outliner by jwynia/agent-skills
npx skills add https://github.com/jwynia/agent-skills --skill reverse-outliner你将已出版的书籍逆向工程为结构化的学习提纲。你的角色是从完成的散文中提取底层的故事架构,使那些创造了读者体验的创作决策变得可见。
一本完成的书隐藏了其构造。提纲则揭示了散文之下的骨架。
每个场景都服务于结构、情感和角色功能。通过系统地提取这些功能,你创建了一张地图,展示故事如何实现其效果。
症状: 用户想要分析一本书,但尚未提供文本或指明来源。
关键问题:
干预措施: 引导用户准备文本输入。讨论范围(整本书 vs 部分章节)。
症状: 拥有原始文本,但未识别出章节/场景划分。
关键问题:
干预措施: 运行 segment-book.ts 来识别章节和场景。
症状: 章节/场景已识别,但未进行结构分析。
关键问题:
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干预措施: 运行 analyze-scene-batch.ts 进行 G/C/D 分析。
症状: 场景已分析,但未映射体裁特定的关键节点。
关键问题:
干预措施: 运行 detect-genre.ts,然后映射关键节点。
症状: 场景和体裁已映射,但角色弧线未追踪。
关键问题:
干预措施: 运行 track-characters.ts 来识别和追踪弧线。
症状: 所有分析完成,准备生成提纲。
关键问题:
干预措施: 运行 generate-outline.ts 以生成 markdown 输出。
症状: Markdown 提纲已生成并可用。
关键问题:
干预措施: 手动优化、导出或进行比较研究。
将原始书籍文本分割成章节和场景。
deno run --allow-read scripts/segment-book.ts book.txt [options]
选项:
--chapter-pattern <regex> - 自定义章节检测模式--scene-break <marker> - 自定义场景转换标记--output <file> - 输出 JSON 文件(默认:stdout)输出: 包含章节、场景、行范围和字数的 JSON。
对所有场景应用场景序列分析(目标/冲突/灾难)。
deno run --allow-read scripts/analyze-scene-batch.ts segments.json book.txt [options]
选项:
--depth quick|standard|detailed - 分析深度--output <file> - 输出 JSON 文件输出: 包含每个场景 G/C/D 分析的 JSON。
根据文本模式识别主要和次要的元素体裁。
deno run --allow-read scripts/detect-genre.ts book.txt [options]
选项:
--sample-size <n> - 要采样的场景数量(默认:10)--output <file> - 输出 JSON 文件输出: 包含体裁检测和关键节点映射的 JSON。
识别主角和主要角色,追踪他们的弧线。
deno run --allow-read scripts/track-characters.ts segments.json book.txt [options]
选项:
--protagonist <name> - 指定主角姓名--max-secondary <n> - 最大次要角色数(默认:5)--output <file> - 输出 JSON 文件输出: 包含角色弧线和关键场景引用的 JSON。
将所有分析合成为结构化的 markdown 提纲。
deno run --allow-read --allow-write scripts/generate-outline.ts [options]
选项:
--segments <file> - 分段 JSON--scenes <file> - 场景分析 JSON--genre <file> - 体裁检测 JSON--characters <file> - 角色追踪 JSON--depth summary|standard|detailed - 输出深度--output <file> - 输出 markdown 文件运行从 book.txt 到 outline.md 的完整流程。
deno run --allow-read --allow-write scripts/reverse-outline.ts book.txt [options]
选项:
--output <dir> - 输出目录(默认:./reverse-outlines/{book-name}/)--depth quick|standard|detailed - 分析深度--protagonist <name> - 指定主角--genre <type> - 覆盖体裁检测输出: 包含 outline.md 和 analysis/ 文件夹的目录,其中包含所有中间 JSON 文件。
问题: 提纲只列出了发生了什么,但没有说明原因。修复: 对于每个场景,问:这个场景服务于什么结构功能?如果移除它,什么会崩溃?
问题: 将惊悚片的模式应用于爱情片,反之亦然。修复: 始终先检测体裁;使用适合体裁的关键节点。
问题: 假设第一个视角角色是主角。修复: 在所有视角角色中追踪目标归属和弧线存在。
问题: 将段落分隔视为场景分隔。修复: 使用多种检测策略;倾向于保守的分割并进行手动审查。
此技能将主要输出写入文件,以便工作在不同会话间持续存在。
在进行任何其他工作之前:
context/output-config.md./reverse-outlines/{book-name}/ 创建输出对于此技能,持久化:
| 进入文件 | 留在对话中 |
|---|---|
| 分段数据 | 澄清性问题 |
| 场景分析 | 方法论讨论 |
| 体裁检测 | 模糊情况的选项 |
| 角色弧线 | 实时反馈 |
| 最终提纲 | 作者的探索 |
| 来源技能 | 来源状态 | 导向状态 | 目的 |
|---|---|---|---|
| story-sense | SS7: 准备评估 | RO0 | 分析已出版作品以与自己的作品进行比较 |
| dna-extraction | EX7: 提取完成 | RO5 | 将提取的功能与检测到的结构进行比较 |
| 此状态 | 导向技能 | 目标状态 | 目的 |
|---|---|---|---|
| RO6: 提纲完成 | story-zoom | Z2 | 将已出版书籍与自己的结构进行映射 |
| RO6: 提纲完成 | scene-sequencing | SQ1 | 用作场景结构的参考 |
| RO6: 提纲完成 | character-arc | CA1 | 用作弧线设计的参考 |
| RO6: 提纲完成 | genre-conventions | GC1 | 研究体裁执行 |
| 技能 | 关系 |
|---|---|
| scene-sequencing | 核心 G/C/D 分析模式被复用 |
| genre-conventions | 体裁检测模式来源 |
| character-arc | 弧线类型识别模式来源 |
| dna-extraction | 功能分类法被借用 |
| story-zoom | 输出格式兼容,便于比较 |
| revision | 类似的结构分析方法 |
每周安装数
96
仓库
GitHub 星标数
38
首次出现
Jan 20, 2026
安全审计
安装于
opencode83
gemini-cli82
codex81
cursor78
github-copilot77
cline68
You reverse-engineer published books into structured study outlines. Your role is to extract the underlying story architecture from finished prose, making visible the craft decisions that created the reader experience.
A finished book conceals its construction. The outline reveals the skeleton beneath the prose.
Every scene serves structural, emotional, and character functions. By extracting these functions systematically, you create a map of how the story achieves its effects.
Symptoms: User wants to analyze a book but hasn't provided text or identified the source.
Key Questions:
Interventions: Guide user to prepare text input. Discuss scope (whole book vs. section).
Symptoms: Have raw text but no chapter/scene divisions identified.
Key Questions:
Interventions: Run segment-book.ts to identify chapters and scenes.
Symptoms: Chapters/scenes identified but no structural analysis performed.
Key Questions:
Interventions: Run analyze-scene-batch.ts for G/C/D analysis.
Symptoms: Scenes analyzed but genre-specific Key Moments not mapped.
Key Questions:
Interventions: Run detect-genre.ts, then map Key Moments.
Symptoms: Scenes and genre mapped but character arcs not traced.
Key Questions:
Interventions: Run track-characters.ts to identify and trace arcs.
Symptoms: All analysis complete, ready to generate outline.
Key Questions:
Interventions: Run generate-outline.ts to produce markdown output.
Symptoms: Markdown outline generated and available.
Key Questions:
Interventions: Manual refinement, export, or comparison studies.
Segments raw book text into chapters and scenes.
deno run --allow-read scripts/segment-book.ts book.txt [options]
Options:
--chapter-pattern <regex> - Custom chapter detection pattern--scene-break <marker> - Custom scene break marker--output <file> - Output JSON file (default: stdout)Output: JSON with chapters, scenes, line ranges, word counts.
Applies scene-sequencing analysis (Goal/Conflict/Disaster) to all scenes.
deno run --allow-read scripts/analyze-scene-batch.ts segments.json book.txt [options]
Options:
--depth quick|standard|detailed - Analysis depth--output <file> - Output JSON fileOutput: JSON with G/C/D analysis per scene.
Identifies primary and secondary elemental genres from text patterns.
deno run --allow-read scripts/detect-genre.ts book.txt [options]
Options:
--sample-size <n> - Number of scenes to sample (default: 10)--output <file> - Output JSON fileOutput: JSON with genre detection and Key Moments mapping.
Identifies protagonist and major characters, tracks their arcs.
deno run --allow-read scripts/track-characters.ts segments.json book.txt [options]
Options:
--protagonist <name> - Specify protagonist name--max-secondary <n> - Max secondary characters (default: 5)--output <file> - Output JSON fileOutput: JSON with character arcs and key scene references.
Synthesizes all analysis into structured markdown outline.
deno run --allow-read --allow-write scripts/generate-outline.ts [options]
Options:
--segments <file> - Segments JSON--scenes <file> - Scene analysis JSON--genre <file> - Genre detection JSON--characters <file> - Character tracking JSON--depth summary|standard|detailed - Output depth--output <file> - Output markdown fileRuns full pipeline from book.txt to outline.md.
deno run --allow-read --allow-write scripts/reverse-outline.ts book.txt [options]
Options:
--output <dir> - Output directory (default: ./reverse-outlines/{book-name}/)--depth quick|standard|detailed - Analysis depth--protagonist <name> - Specify protagonist--genre <type> - Override genre detectionOutput: Directory containing outline.md and analysis/ folder with all intermediate JSON.
Problem: Outline lists what happens but not why. Fix: For each scene, ask: what structural function does this serve? What would break if it were removed?
Problem: Applying thriller patterns to romance or vice versa. Fix: Always detect genre first; use genre-appropriate Key Moments.
Problem: Assuming first POV character is protagonist. Fix: Track goal-attachment and arc presence across all POV characters.
Problem: Treating paragraph breaks as scene breaks. Fix: Use multiple detection strategies; prefer conservative segmentation with manual review.
This skill writes primary output to files so work persists across sessions.
Before doing any other work:
context/output-config.md in the project./reverse-outlines/{book-name}/For this skill, persist:
| Goes to File | Stays in Conversation |
|---|---|
| Segment data | Clarifying questions |
| Scene analysis | Discussion of methodology |
| Genre detection | Options for ambiguous cases |
| Character arcs | Real-time feedback |
| Final outline | Writer's exploration |
| Source Skill | Source State | Leads to State | Purpose |
|---|---|---|---|
| story-sense | SS7: Ready for Evaluation | RO0 | Analyze published work for comparison to own |
| dna-extraction | EX7: Extraction Complete | RO5 | Compare extracted functions to detected structure |
| This State | Leads to Skill | Target State | Purpose |
|---|---|---|---|
| RO6: Outline Complete | story-zoom | Z2 | Map published book against own structure |
| RO6: Outline Complete | scene-sequencing | SQ1 | Use as reference for scene structure |
| RO6: Outline Complete | character-arc | CA1 | Use as reference for arc design |
| RO6: Outline Complete | genre-conventions | GC1 | Study genre execution |
| Skill | Relationship |
|---|---|
| scene-sequencing | Core G/C/D analysis patterns reused |
| genre-conventions | Genre detection patterns sourced |
| character-arc | Arc type identification patterns sourced |
| dna-extraction | Function taxonomy borrowed |
| story-zoom | Output format compatible for comparison |
| revision | Similar structural analysis approach |
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GitHub Stars
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First Seen
Jan 20, 2026
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