promptneat

Prompt language improver

Turn rough prompts into clear, model-ready instructions for ChatGPT, Claude, Gemini, Cursor and Midjourney. Free. No sign-in.

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Goal
Model
Depth
Format

no sign-in · nothing stored · free

How it reads to a model

One real example. The rough version works; the neat version works better, for reasons you can see.

write something about remote work for our blog make it good
Write a 700-word blog post on remote work for our B2B audience of engineering managers.Angle: what actually changed between 2020 and now, with two concrete examples.Structure: hook, three sections, one takeaway. Tone: direct, no hype.make it good Avoid: listicles, "in today's fast-paced world" openers.

The model was never going to guess the audience, the angle or the structure. Now it doesn't have to.

What it does and doesn't

Does

  • Clarifies the goal and keeps your intent intact.
  • Adds the structure, constraints and output format you implied but didn't state.
  • Makes assumptions explicit so you can correct them.
  • Tailors phrasing to your target model's conventions.
  • Shows you exactly what changed, and why.

Doesn't

  • Not a marketplace. Not a course. Not a workspace. A utility.
  • No accounts, no history, no saved prompts.
  • No invented facts and no padding. Shorter is often the improvement.
  • No "10x" claims. A clearer prompt gets a better answer; that's the whole pitch.

Why prompts fail

Most prompts fail for boring reasons. The goal is implied but never stated. Two tasks are fused into one sentence. The audience, length and format live in your head, so the model guesses, and models are confident guessers. A prompt improver fixes the boring things: it states the goal, separates the tasks, and writes down the constraints you already had. That's also why the improved prompt is rarely longer than yours. It's just arranged so a model, such as ChatGPT, Claude, Gemini, Midjourney, or a coding assistant like Cursor, can execute it instead of interpreting it.

Optimize for your model

For ChatGPTRole framing, numbered steps, explicit format.For ClaudeXML-tagged structure, data before instructions.For GeminiFront-loaded task, labelled sections.For CursorMinimal diffs, context files, reproduction steps.For MidjourneyVisual subject, composition, style and parameters.

Privacy, in five sentences

There are no accounts. Your prompt is sent to a model provider to generate the improved version and is not stored by us; there is no database to store it in. We keep aggregate counters only: how many prompts were neatened and how many results were copied. Cloudflare hosts the service, OpenAI handles model inference, and Anthropic is used only when the optional fallback is configured. That's the whole policy. The longer version is at /privacy.