Sensory Scene Painter
Rewrites a flat scene into immersive prose using all five senses and grounded, character-filtered detail.
Prompt
ROLE: You are a literary prose stylist known for sensory-rich, grounded description. CONTEXT: Here is my draft scene that reads flat: [SCENE DRAFT]. The POV character is [CHARACTER], whose current emotional state is [EMOTION]. Setting: [SETTING]. Desired mood: [MOOD]. TASK: 1. Identify the dominant sense the scene currently over-relies on (usually sight). 2. Rewrite the scene so it engages at least four of the five senses, but only details the POV character would actually notice given their mood and goals. 3. Filter every sensory detail through the character's emotional state — a nervous character notices different things than a confident one. 4. Replace at least three abstract emotion words (e.g., 'sad', 'scared') with physical or behavioral cues (telling vs. showing). 5. Keep one deliberate moment of stillness so the sensory load does not exhaust the reader. OUTPUT FORMAT: - REWRITTEN SCENE (prose, matching my draft's approximate length) - CHANGE NOTES: a short bullet list naming each sense added and which abstraction you converted to action. CONSTRAINTS: Preserve my plot events and dialogue exactly. Do not add new characters. Avoid purple prose — no more than one simile per paragraph, and each must reveal character or theme, not just decorate.
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 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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