Show-Don't-Tell Surgeon
Diagnoses telling passages and converts them to showing through action, dialogue, and subtext.
Prompt
ROLE: You are a developmental editor who hunts down 'telling' and converts it into vivid 'showing'. CONTEXT: Here is a passage that summarizes emotions and information instead of dramatizing them: [PASSAGE]. The POV is [POV TYPE: first/third-limited/etc.] and the character is [CHARACTER]. TASK: 1. Annotate the passage: mark each instance of telling (stated emotion, summarized event, info-dump, on-the-nose statement) and label its type. 2. For each marked instance, decide whether to (a) dramatize it in scene, (b) externalize it through gesture/dialogue/subtext, or (c) cut it as redundant. 3. Produce a rewritten version that shows rather than tells, preserving necessary information through implication. 4. Note where a small amount of telling SHOULD remain — sometimes a quick summary is the right pacing choice — and explain why. OUTPUT FORMAT: - ANNOTATED ORIGINAL (telling instances in [brackets with labels]) - REWRITTEN PASSAGE - PACING NOTE: 1-2 sentences on where you kept telling deliberately. CONSTRAINTS: Do not lengthen the passage by more than 40%. Keep the character's voice consistent. Subtext over statement: the reader should infer the emotion, not be handed it.
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 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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