Is this prompt free to use?

Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.

How do I get the best results?

Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.

Can I use this with Claude and ChatGPT?

Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.

Where can I find related resources?

Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.

Removing visual noise in the neural network's response

TEXT

Prompt866 chars · 140 words

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.

Overview

Removing visual noise in the neural network's response is a free prompt on OpenRuna. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor.

What this prompt does

"Removing visual noise in the neural network's response" is designed to help you get reliable results from AI assistants for real prompt tasks. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. It is catalogued in OpenRuna's resource graph so you can discover related prompts, tools, agents, and datasets in one place. Copy the content directly into ChatGPT, Claude, Gemini, or Cursor — or use it as a system prompt / skill instruction where applicable.

Use cases

Use "Removing visual noise in the neural network's response" when you need a repeatable prompt for professional workflows without writing instructions from scratch each time.
Adapt this prompt for team onboarding — paste into Claude or ChatGPT and iterate on the output with your project context.
Combine with related tools and prompts in the same OpenRuna category to build a full stack for your use case.
Reference during code review or planning sessions when you want consistent AI-assisted quality bars.

Example output

When you run this prompt, expect structured output similar to:

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 …

Outputs vary by model and temperature; treat the first response as a draft and refine with follow-up prompts.

Tips by platform

Claude

In Claude, paste the full prompt as the first user message or add it to Project instructions. Ask Claude to confirm assumptions before executing. For long prompts, use Claude's artifact panel to iterate on structured output.

ChatGPT

In ChatGPT, start a new chat and paste this prompt verbatim. Enable GPT-4o or your preferred model for coding tasks. Use follow-ups like "apply this to [your context]" for best results.

Cursor

In Cursor, add key instructions from this prompt to .cursorrules or a SKILL.md file. Reference it in Agent mode with @ mentions. Keep the original title in comments so teammates can find it on OpenRuna.

Frequently asked questions

What is "Removing visual noise in the neural network's response"?: It is a prompt listed on OpenRuna — A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.
Is this prompt free to use?: Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.
How do I get the best results?: Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.
Can I use this with Claude and ChatGPT?: Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.
Where can I find related resources?: Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.