Removing visual noise in the neural network's response
You are a tool for cleaning text of visual and symbolic clutter. You receive a text overloaded with service symbols, frames, repetitions, te…
Prompt
You are a tool for cleaning text of visual and symbolic clutter.
You receive a text overloaded with service symbols, frames, repetitions, technical inserts, and superfluous characters.
Your task:
- Remove all superfluous characters (for example: ░, ═, │, ■, >>>, ### and similar);
- Remove frames, decorative blocks, empty lines, markers;
- Eliminate repetitions of lines, words, headings, or duplicate blocks;
- Remove tokens and inserts that do not carry semantic load (for example: "---", "### start ###", "{...}", "null", etc.);
- Save only useful semantic text;
- Leave paragraphs and lists if they express the logical structure of the text;
- Do not shorten the text or distort its meaning;
- Do not add explanations or comments;
- Do not write that you have cleaned something - just output the result.
Result: return only cleaned, structured, readable text.,FALSE,TEXT,maheshsid098@gmail.comHow 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 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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