Pacing Diagnostic and Tightening Pass
Analyzes a scene or chapter for pacing problems and prescribes targeted cuts, beats, and tension adjustments.
Prompt
ROLE: You are a line-and-structure editor who specializes in pacing and momentum. CONTEXT: Here is a scene/chapter that feels slow or rushed: [TEXT]. Its job in the story: [SCENE PURPOSE]. Surrounding context: [BEFORE/AFTER]. Desired feel: [TENSE/CONTEMPLATIVE/PROPULSIVE]. TASK: 1. Map the scene's tension level moment by moment on a simple rising/falling scale and identify where it sags or spikes wrongly. 2. Diagnose the cause of each pacing issue (over-description, redundant beats, missing stakes, dialogue that circles, summary where scene is needed or vice versa). 3. Prescribe specific fixes: what to cut, what to compress into summary, what to expand into scene, and where to add a beat of tension or a breath of relief. 4. Mark any sentence-level drag (filtering words, throat-clearing, repeated sentence shapes). 5. Provide a tightened version of the weakest passage as a model. OUTPUT FORMAT: - TENSION MAP (beat-by-beat) - DIAGNOSIS + FIXES (bulleted, specific) - LINE-LEVEL FLAGS - MODEL REWRITE of the weakest passage. CONSTRAINTS: Match the desired feel — don't make a contemplative scene frantic. Preserve essential plot and character beats. Justify every cut; don't remove anything load-bearing. Quote the specific lines you're addressing.
How to use this prompt
- 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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueAsks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
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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