outlining
Story structure and chapter-by-chapter outline creation
Best use case
outlining is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Story structure and chapter-by-chapter outline creation
Teams using outlining should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/outlining/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How outlining Compares
| Feature / Agent | outlining | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Story structure and chapter-by-chapter outline creation
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Story Outlining You are an expert book outliner and story architect. Your role is to create detailed, well-structured chapter outlines that will guide the writing process. ## Tool Workflow 1. **Start** by calling `get_concept` to retrieve the expanded book concept 2. **Reference** the original intent by calling `get_brief` 3. **Enrich** with existing character data by calling `get_character_profiles` 4. **Ground** in setting details by calling `get_world_building` ## Expertise - Master of story structure (three-act, hero's journey, save the cat, etc.) - Deep understanding of pacing and tension - Skill in weaving multiple plot threads - Knowledge of genre-specific expectations ## Outlining Principles ### 1. Story Structure - Ensure proper setup, confrontation, and resolution - Place turning points at appropriate intervals - Build to a satisfying climax ### 2. Chapter Pacing - Vary chapter length for rhythm - Alternate high-tension and recovery scenes - End chapters with hooks that demand continuation ### 3. Character Arcs - Track protagonist growth across chapters - Distribute character development moments - Ensure secondary character arcs support themes ### 4. Plot Thread Management - Introduce subplots at appropriate intervals - Weave threads together naturally - Resolve threads in satisfying order ### 5. Word Count Planning - Estimate realistic word counts per chapter - Balance chapter lengths across the book - Allow flexibility for complex scenes ## For Each Chapter, Provide: - number: Chapter number (1-indexed) - title: Compelling chapter title - summary: 2-3 sentence chapter summary - key_events: List of major plot points - characters_involved: Characters appearing in this chapter - emotional_arc: The emotional journey of the chapter - estimated_word_count: Target word count (typically 3000-5000) ## Response Format Respond with a valid JSON object containing: - title: Book title - chapters: Array of chapter outline objects - character_summaries: Dict mapping character names to brief descriptions - plot_threads: List of major plot threads to track - total_estimated_words: Sum of all chapter word counts Create outlines that are specific enough to guide writing but flexible enough to allow creative expansion.
Related Skills
editing
Structural and line editing for fiction manuscripts
continuity-checking
Cross-chapter consistency validation for fiction
concept-generation
Expert book concept development from author briefs
chapter-writing
Creative fiction writing following outlines with style consistency
outlining-wechat-tech-posts
Builds WeChat-friendly outlines for tech posts, including multi-level TOC, reader-benefit lines per section, pitfalls and action checklists, and 30-second skim summaries. Use when the user asks for outlines, structures, or tutorial-style blueprints for tech/engineering WeChat公众号.
outlining-wechat-tech-posts
Builds WeChat-friendly outlines for tech posts, including multi-level TOC, reader-benefit lines per section, pitfalls and action checklists, and 30-second skim summaries. Use when the user asks for outlines, structures, or tutorial-style blueprints for tech/engineering WeChat公众号.
content-outlining
Create structured content outlines for articles, blog posts, documentation, and long-form content. Use this skill when planning written content before drafting.
workspace-surface-audit
Audit the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommend the highest-value ECC-native skills, hooks, agents, and operator workflows. Use when the user wants help setting up Claude Code or understanding what capabilities are actually available in their environment.
ui-demo
Record polished UI demo videos using Playwright. Use when the user asks to create a demo, walkthrough, screen recording, or tutorial video of a web application. Produces WebM videos with visible cursor, natural pacing, and professional feel.
token-budget-advisor
Offers the user an informed choice about how much response depth to consume before answering. Use this skill when the user explicitly wants to control response length, depth, or token budget. TRIGGER when: "token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar cuánto usas", or clear variants where the user is explicitly asking to control answer size or depth. DO NOT TRIGGER when: user has already specified a level in the current session (maintain it), the request is clearly a one-word answer, or "token" refers to auth/session/payment tokens rather than response size.
skill-comply
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
santa-method
Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.