reverse-outliner
出版された書籍をシーン単位の構造化アウトラインに逆算・分解し、学習用に整理します。文章技法の分析、優れた作品からストーリー構造を学ぶ際、または既存作品を教材化する際に活用してください。
description の原文を見る
Reverse-engineer published books into structured scene-by-scene outlines for study. Use when analyzing craft, learning story structure from masters, or creating teaching materials from existing works.
SKILL.md 本文
Reverse-Outliner: Book-to-Outline Analysis
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.
Core Principle
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.
The States
RO0: No Input
Symptoms: User wants to analyze a book but hasn't provided text or identified the source.
Key Questions:
- What book are you analyzing?
- Do you have the text file ready?
- What's your study goal? (craft analysis, genre study, teaching)
Interventions: Guide user to prepare text input. Discuss scope (whole book vs. section).
RO1: Unsegmented Text
Symptoms: Have raw text but no chapter/scene divisions identified.
Key Questions:
- Does the book have explicit chapter markers?
- Are scene breaks marked with whitespace, symbols, or POV shifts?
- What's the typical scene length for this genre?
Interventions: Run segment-book.ts to identify chapters and scenes.
RO2: Segmented, Unanalyzed
Symptoms: Chapters/scenes identified but no structural analysis performed.
Key Questions:
- How many scenes total?
- Ready to begin scene-by-scene analysis?
Interventions: Run analyze-scene-batch.ts for G/C/D analysis.
RO3: Genre Unidentified
Symptoms: Scenes analyzed but genre-specific Key Moments not mapped.
Key Questions:
- What's the primary elemental genre?
- Are there secondary genres?
- Which Key Moments framework applies?
Interventions: Run detect-genre.ts, then map Key Moments.
RO4: Characters Untracked
Symptoms: Scenes and genre mapped but character arcs not traced.
Key Questions:
- Who is the protagonist?
- Which 3-5 secondary characters are most significant?
- Which arc type does each follow?
Interventions: Run track-characters.ts to identify and trace arcs.
RO5: Ready for Synthesis
Symptoms: All analysis complete, ready to generate outline.
Key Questions:
- What output depth? (summary, standard, detailed)
- Include all scenes or significant only?
Interventions: Run generate-outline.ts to produce markdown output.
RO6: Outline Complete
Symptoms: Markdown outline generated and available.
Key Questions:
- Does the outline capture the book's structure?
- Are there gaps or scenes that need manual review?
Interventions: Manual refinement, export, or comparison studies.
Diagnostic Process
- Determine current state by checking what files/analysis exist
- Identify next intervention based on state table above
- Run appropriate tool to advance to next state
- Validate output before proceeding
- Iterate until RO6 reached
Available Tools
segment-book.ts
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.
analyze-scene-batch.ts
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 file
Output: JSON with G/C/D analysis per scene.
detect-genre.ts
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 file
Output: JSON with genre detection and Key Moments mapping.
track-characters.ts
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 file
Output: JSON with character arcs and key scene references.
generate-outline.ts
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 file
reverse-outline.ts (Orchestrator)
Runs 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 detection
Output: Directory containing outline.md and analysis/ folder with all intermediate JSON.
Anti-Patterns
Surface-Level Breakdown
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?
Genre-Blind Analysis
Problem: Applying thriller patterns to romance or vice versa. Fix: Always detect genre first; use genre-appropriate Key Moments.
Protagonist Assumption
Problem: Assuming first POV character is protagonist. Fix: Track goal-attachment and arc presence across all POV characters.
Scene Boundary Guessing
Problem: Treating paragraph breaks as scene breaks. Fix: Use multiple detection strategies; prefer conservative segmentation with manual review.
What You Do NOT Do
- Generate original story content
- Judge the book's quality
- Compare to other books unless asked
- Skip states (each builds on previous)
- Modify the source text
Output Persistence
This skill writes primary output to files so work persists across sessions.
Output Discovery
Before doing any other work:
- Check for
context/output-config.mdin the project - If found, look for this skill's entry
- If not found, create output at
./reverse-outlines/{book-name}/
Primary Output
For this skill, persist:
- outline.md - Final markdown outline
- analysis/segments.json - Chapter/scene segmentation
- analysis/scenes.json - Scene-by-scene G/C/D analysis
- analysis/genre.json - Genre detection results
- analysis/characters.json - Character arc tracking
Conversation vs. File
| 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 |
Integration Graph
Inbound (From Other Skills)
| 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 |
Outbound (To Other Skills)
| 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 |
Complementary Skills
| 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 |
ライセンス: MIT(寛容ライセンスのため全文を引用しています) · 原本リポジトリ
詳細情報
- 作者
- jwynia
- リポジトリ
- jwynia/agent-skills
- ライセンス
- MIT
- 最終更新
- 不明
Source: https://github.com/jwynia/agent-skills / ライセンス: MIT
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