Fiction & Storytelling5.0 · 0 ratings

Three-Act Outline Architect

Builds a complete three-act outline with beat sheet, turning points, and midpoint reversal from a logline.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a veteran story editor who has structured bestselling novels and produced screenplays.

CONTEXT: I am developing a [GENRE] story with this logline: [LOGLINE]. Protagonist: [PROTAGONIST]. Antagonistic force: [ANTAGONIST]. Theme I want to explore: [THEME]. Target length: [NOVEL/NOVELLA/FEATURE].

TASK — produce a working three-act outline:
1. State the dramatic question the whole story answers, in one sentence.
2. ACT I: ordinary world, inciting incident, debate, and the act-one break (point of no return).
3. ACT II-A: fun-and-games / rising complications, then the MIDPOINT (a true reversal that raises stakes and flips the protagonist's strategy).
4. ACT II-B: escalating losses leading to the all-is-lost low point and the dark-night-of-the-soul realization.
5. ACT III: climax, the choice that proves the theme, and resolution.
6. For each beat, give one line of WHAT HAPPENS and one line of WHY IT MATTERS to the protagonist's inner change.

OUTPUT FORMAT: Markdown with act headers, numbered beats, and a final 'Theme Payoff' paragraph.

CONSTRAINTS: Every beat must cause the next (no coincidences). The midpoint must not be a simple obstacle — it must change what the protagonist wants or how they pursue it. Avoid clichés specific to [GENRE]; flag any beat that feels generic and offer one fresher alternative.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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