Claude Prompt Generator

Claude is not ChatGPT with a different logo. It reads long inputs differently, it responds to structure in a way most models don't, and it will follow a well-organised brief almost literally. That last part is the catch: a vague prompt gets a vague answer, and a sloppy one gets a confidently wrong one. This free Claude prompt generator on GetEasyPrompt takes whatever rough idea you have and rebuilds it into the shape Claude actually reads well — role, context, task, constraints, and output format, in that order. It runs entirely in your browser. Nothing is uploaded, there is no account, and there is no usage cap.

What this Claude prompt generator actually does

You paste a scrappy request. The tool — the same Prompt Optimizer engine that powers the rest of the site, preset here for Claude — expands it into a structured brief. It adds the parts people forget: who Claude is meant to be for this task, what the audience is, what "done" looks like, and what to leave out. Then you copy the result into claude.ai, the Claude desktop app, or the API.

The Claude preset differs from the ChatGPT version in a few concrete ways. It leans harder on explicit sectioning, it suggests XML-style tags when your prompt contains pasted material, and it puts reference documents above the instruction rather than below. If you want a model-agnostic starting point instead, the general AI prompt generator produces something that works reasonably everywhere.

Claude rewards explicit structure

Most models tolerate a wall of text. Claude does better than tolerate structure — it uses it. Give it labelled sections and it will respect the boundaries between them: it treats your constraints as constraints rather than suggestions, and it stops blending your example data into its answer.

A useful default skeleton:

• Role — what expertise Claude should bring
• Context — who this is for, what already exists, what the stakes are
• Task — one clear instruction, phrased as a verb
• Constraints — length, tone, things to avoid, things that are non-negotiable
• Output format — bullets, table, JSON, five paragraphs, whatever you actually need

That is the whole trick, and it is boring, and it works.

Use XML tags to separate data from commands

This is the single most Claude-specific technique, and Anthropic recommends it directly in the official prompt engineering docs. When your prompt contains material Claude should *operate on* — a transcript, a contract, an email thread, a competitor's copy — wrap it in tags so the boundary is unmistakable.

Without tags, a document containing the words "summarise this in three points" can hijack your actual instruction. With tags, Claude knows which text is the command and which is the payload.

Tag names are yours to invent — <example>, <draft>, <style_guide>, <previous_version> all work. Consistency matters more than the specific words. If you use <document> in the prompt, refer to "the document" in your instruction, not "the text above."

Put long documents before the question

Order matters more with Claude than most people expect. For long inputs, put the reference material near the top of the prompt and the actual question at the bottom. Anthropic's own guidance is explicit about this for documents past roughly 20,000 words, and the effect is easy to reproduce: the same document with the question at the end produces noticeably better recall than the same question asked first.

The practical rule: document, then instruction. If you have several documents, tag each one and give it a short identifier so you can reference it later ("compare the pricing in <doc_a> against <doc_b>").

The context window is big — use it deliberately

Current Claude models carry very large context windows — hundreds of thousands of tokens on Haiku and up to a million on the Opus and Sonnet tiers. That means you can paste an entire codebase directory, a full contract set, or a year of meeting notes and ask questions across all of it.

Big does not mean careless, though. Two habits keep quality high:

• Give Claude a reason to care about each document. A one-line note above each tagged block ("this is the outdated version") is worth more than another 5,000 words of raw text.
• Ask one question per turn. Long context plus a five-part compound question is where answers get thin. Split it.

If you're pasting a lot and want to know how much you're actually sending, the token counter gives you a fast estimate before you hit send.

System prompts and Projects

The role and standing rules don't belong in every message. Put them once in a system prompt (API) or in Project instructions and custom instructions (claude.ai), then keep your per-message prompts short and task-focused.

Good system prompt material: the persona, the audience, the house style, hard constraints, and what Claude should do when it doesn't know something. Bad system prompt material: this week's specific task. Our system prompt generator builds these from a short description, and the guide to system prompts covers what belongs in each layer.

Tell Claude to think first, and be blunt about what you want

For anything involving analysis, comparison, or multi-step reasoning, ask for the reasoning before the conclusion. A single line does it:

Then be direct. Claude follows positive instructions ("write in short declarative sentences") far more reliably than negative ones ("don't be verbose"). Say what you want rather than describing what you'd like to avoid. If you need machine-readable output, don't ask nicely for JSON — specify the schema, which is exactly what the JSON prompt builder does for you.

Where this pays off

Three tasks where a structured Claude prompt beats a casual one by a wide margin:

• Long-document analysis. Contracts, research papers, discovery documents, support-ticket exports. Tag the document, ask one precise question, request citations back to the source.
• Drafting and rewriting. Give Claude the audience, the constraints, and one example of the voice you want. The example does more work than three paragraphs of adjectives.
• Code review. Paste the diff in <diff> tags with the surrounding file in <context>, and ask for issues ranked by severity with a one-line fix for each.

Paste your rough idea into the generator above and read what comes back — the structure it adds is the lesson. For the longer version, the Claude prompting guide goes deeper, and Anthropic's own documentation is worth an hour of anyone's time.