New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Reverse Outliner

by jwynia in jwynia/agent-skills

Reverse-engineer published books into structured scene-by-scene outlines for study.

MITAuto-check passed

Install Reverse Outliner

skills CLI
$ npx skills add jwynia/agent-skills --skill reverse-outliner -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jwynia/agent-skills reverse-outliner --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jwynia/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/creative/fiction/structure/reverse-outliner .claude/skills/reverse-outliner && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
reverse-outliner
GitHub stars
169
Token cost
~2.3k tokens
SKILL.md length
943 words
Files
9 (incl. scripts)
Skills in repo
111
Repo updated
First seen
Licence
MIT

At a glance

Reverse-engineer published books into structured scene-by-scene outlines for study.

  • Works in 5 steps: Determine current state by checking what… → Identify next intervention based on… → Run appropriate tool to advance to next… → …
  • Analyzing craft
  • SKILL.md covers Core Principle, The States, Diagnostic Process and Available Tools, plus 4 more sections
  • Runs TypeScript scripts from its folder; calls deno

What it does

Reverse Outliner is an agent skill from jwynia/agent-skills. 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.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts (for example `data/key-moments-by-genre.json`, `data/scene-markers.json` and `scripts/analyze-scene-batch.ts`).

The licence is MIT.

When your agent uses it

  • Analyzing craft
  • Learning story structure from masters
  • Creating teaching materials from existing works

Example prompts

  • “/reverse-outliner”

Requirements

  • Node.js

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Determine current state by checking what files/analysis exist
  2. Identify next intervention based on state table above
  3. Run appropriate tool to advance to next state
  4. Validate output before proceeding
  5. Iterate until RO6 reached

What it can do on your machine

Read from SKILL.md and the folder at commit e02ec7e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 6 files in scripts/ (TypeScript), which the agent can run.

    Shell commands in SKILL.md call:

    • deno

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Reverse Outliner loads about 2.3k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 943 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from jwynia/agent-skills at commit e02ec7e, republished under its MIT licence (© jwynia). 943 words, ~2,251 tokens.

Download SKILL.mdSave it as .claude/skills/reverse-outliner/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
reverse-outliner
description
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.
license
MIT
metadata.author
jwynia
metadata.version
1.0
metadata.type
utility
metadata.mode
evaluative
metadata.domain
fiction

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

  1. Determine current state by checking what files/analysis exist
  2. Identify next intervention based on state table above
  3. Run appropriate tool to advance to next state
  4. Validate output before proceeding
  5. Iterate until RO6 reached

Available Tools

segment-book.ts

Segments raw book text into chapters and scenes.

bash
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.

bash
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.

bash
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.

bash
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.

bash
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
Show full SKILL.md (386 more words)Show less
reverse-outline.ts (Orchestrator)

Runs full pipeline from book.txt to outline.md.

bash
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:

  1. Check for context/output-config.md in the project
  2. If found, look for this skill's entry
  3. 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 FileStays in Conversation
Segment dataClarifying questions
Scene analysisDiscussion of methodology
Genre detectionOptions for ambiguous cases
Character arcsReal-time feedback
Final outlineWriter's exploration

Integration Graph

Inbound (From Other Skills)
Source SkillSource StateLeads to StatePurpose
story-senseSS7: Ready for EvaluationRO0Analyze published work for comparison to own
dna-extractionEX7: Extraction CompleteRO5Compare extracted functions to detected structure
Outbound (To Other Skills)
This StateLeads to SkillTarget StatePurpose
RO6: Outline Completestory-zoomZ2Map published book against own structure
RO6: Outline Completescene-sequencingSQ1Use as reference for scene structure
RO6: Outline Completecharacter-arcCA1Use as reference for arc design
RO6: Outline Completegenre-conventionsGC1Study genre execution
Complementary Skills
SkillRelationship
scene-sequencingCore G/C/D analysis patterns reused
genre-conventionsGenre detection patterns sourced
character-arcArc type identification patterns sourced
dna-extractionFunction taxonomy borrowed
story-zoomOutput format compatible for comparison
revisionSimilar structural analysis approach

© jwynia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (scripts) in skills/creative/fiction/structure/reverse-outliner of jwynia/agent-skills.

  • SKILL.md
  • data/key-moments-by-genre.json
  • data/scene-markers.json
  • scripts/analyze-scene-batch.ts
  • scripts/detect-genre.ts
  • scripts/generate-outline.ts
  • scripts/reverse-outline.ts
  • scripts/segment-book.ts
  • scripts/track-characters.ts

Open the folder on GitHubat commit e02ec7e

Compare with similar skills

Reverse Outliner next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Reverse Outliner compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Reverse Outliner this skilljwynia/agent-skills169—~2.3kAutomated safety check: PassMIT
Protocol Reverse Engineeringwshobson/agents40k8 repos~3.2kAutomated safety check: PassMIT
Reverse Engineering Malware With Ghidramukul975/Anthropic-Cybersecurity-Skills34k—~3kAutomated safety check: PassApache-2.0
Protocol Reversezhaoxuya520/reverse-skill40k2 repos~620Automated safety check: WarnMIT
macOS Reversezhaoxuya520/reverse-skill40k2 repos~366Automated safety check: PassMIT
Protocol Reversesickn33/agentic-awesome-skills47k1 repos~689Automated safety check: PassMIT

Similar skills

  • Protocol Reverse Engineering

    wshobson/agents

    Master network protocol reverse engineering including packet analysis, protocol dissection, and custom protocol documentation.

    40k GitHub starsUsed in 8 repos~3.2k tokens
    SecurityAuto-check passed

  • Reverse Engineering Malware With Ghidra

    mukul975/Anthropic-Cybersecurity-Skills

    Reverse engineers malware binaries using NSA's Ghidra disassembler and decompiler to study internal logic, cryptographic routines, C2 protocols, and evasion techniques at the assembly and pseudo-C…

    34k GitHub stars~3k tokensUpdated 1 mo ago
    SecurityAuto-check passed

  • Protocol Reverse

    zhaoxuya520/reverse-skill

    A skill your agent uses for authorized reverse engineering of custom binary protocols, Protobuf/gRPC, WebSocket frames, and PCAP-driven protocol recovery.

    40k GitHub starsUsed in 2 repos~620 tokens
    Backend & APIsAuto-check: warnings

  • macOS Reverse

    zhaoxuya520/reverse-skill

    A skill your agent uses for authorized macOS and Mach-O reverse engineering including codesign, Objective-C/Swift recovery, endpoint security surfaces, and Apple platform malware analysis.

    40k GitHub starsUsed in 2 repos~366 tokens
    SecurityAuto-check passed

  • Protocol Reverse

    sickn33/agentic-awesome-skills

    Authorized reverse engineering of custom binary protocols, Protobuf/gRPC schemas, WebSocket frames, and PCAP-driven protocol recovery.

    47k GitHub starsUsed in 1 repo~689 tokens
    Backend & APIsAuto-check passed

  • macOS Reverse

    sickn33/agentic-awesome-skills

    Authorized macOS and Mach-O reverse engineering: codesign inspection, Objective-C/Swift recovery, endpoint-security surfaces, and Apple-platform malware analysis.

    47k GitHub starsUsed in 1 repo~466 tokens
    SecurityAuto-check passed

More from jwynia/agent-skills

All 111 skills in this repo

  • Devcontainer

    jwynia/agent-skills

    Diagnose devcontainer configuration problems and guide development environment setup.

    169 GitHub stars~1.2k tokensUpdated 7 mo ago
    Auto-check: notes

  • Frontend Design

    jwynia/agent-skills

    Create distinctive, production-grade frontend interfaces with high design quality.

    169 GitHub stars~3.2k tokensUpdated 7 mo ago
    Auto-check passed

  • Gitea Workflow

    jwynia/agent-skills

    Orchestrate agile development workflows for Gitea repositories using the tea CLI.

    169 GitHub stars~3.8k tokensUpdated 7 mo ago
    Auto-check passed

  • Godot Asset Generator

    jwynia/agent-skills

    Generate game assets using AI image generation APIs (DALL-E, Replicate, fal.ai) and prepare them for Godot.

    169 GitHub stars~3.8k tokensUpdated 7 mo ago
    Auto-check passed

  • Mastra Hono

    jwynia/agent-skills

    Develop AI agents, tools, and workflows with Mastra v1 Beta and Hono servers.

    169 GitHub stars~2.9k tokensUpdated 7 mo ago
    Auto-check passed

  • PPTX Generator

    jwynia/agent-skills

    Create and manipulate PowerPoint PPTX files programmatically.

    169 GitHub stars~3.1k tokensUpdated 7 mo ago
    Auto-check passed

Questions about Reverse Outliner

What does Reverse Outliner do?

Reverse-engineer published books into structured scene-by-scene outlines for study. Reverse Outliner is an agent skill from jwynia/agent-skills. Reverse-engineer published books into structured scene-by-scene outlines for study.

When should I use Reverse Outliner?

Reverse Outliner fits situations like: analyzing craft; learning story structure from masters; creating teaching materials from existing works.

How do I install Reverse Outliner in Claude Code?

Run `npx skills add jwynia/agent-skills --skill reverse-outliner -a claude-code`. Or copy the skill folder (skills/creative/fiction/structure/reverse-outliner in jwynia/agent-skills) into .claude/skills/reverse-outliner in your project. Claude Code loads it when a task matches its description.

How do I install Reverse Outliner in Codex?

Run `npx skills add jwynia/agent-skills --skill reverse-outliner -a codex`. Or copy the skill folder (skills/creative/fiction/structure/reverse-outliner in jwynia/agent-skills) into .agents/skills/reverse-outliner in your project. Codex loads it when a task matches its description.

Can I use Reverse Outliner in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jwynia/agent-skills --skill reverse-outliner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reverse-outliner, .gemini/skills/reverse-outliner, .github/skills/reverse-outliner and .opencode/skills/reverse-outliner in your project.

What does Reverse Outliner need to run?

Going by SKILL.md and its folder, Reverse Outliner needs TypeScript for the scripts in its folder and the command-line tools its instructions call (deno). Our summary lists: Node.js.

Does Reverse Outliner access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Reverse Outliner safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Reverse Outliner use?

Reverse Outliner is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Reverse Outliner use?

About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Reverse Outliner?

Skills that share tags, products or a category with Reverse Outliner: Protocol Reverse Engineering (wshobson/agents, 40k stars), Reverse Engineering Malware With Ghidra (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Protocol Reverse (zhaoxuya520/reverse-skill, 40k stars) and macOS Reverse (zhaoxuya520/reverse-skill, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Reverse Outliner?

jwynia (a GitHub user) maintains it in jwynia/agent-skills, which has 169 GitHub stars. The repository holds 111 skills in this directory. The repository was last updated on February 24, 2026.

Source: jwynia/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.