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Claude handles prompts differently than ChatGPT. It follows instructions more literally, responds well to XML tags, and has a massive context window. Here is how to structure your prompts to get the best results from Claude Sonnet and Opus.
Build structured prompts for Claude in seconds. Free, no account needed.
Open Prompt BuilderStart with the same RTFC structure that works across all models (Role, Task, Format, Constraints), then add Claude-specific techniques:
You are a senior backend engineer who specializes in Python and PostgreSQL.
Review this database query and identify performance issues. For each issue, explain the problem, show the fix, and estimate the performance improvement. Use a numbered list. Keep each explanation under 3 sentences. Do not suggest changes that would require schema modifications.
Claude was trained to parse XML tags. When your prompt has multiple sections (context, instructions, examples, data), wrapping each section in tags helps Claude keep them separate.
<role>You are a product copywriter for a fitness equipment brand.</role>
<context>We sell premium resistance bands. Our customers are 25-45, active, and care about quality. Our brand voice is confident but not pushy.</context>
<task>Write 3 product descriptions for our new heavy-duty resistance band set. Each description targets a different audience: home gym beginners, physical therapy patients, and serious lifters.</task>
<format>For each description: a headline (under 10 words), a paragraph (under 80 words), and 3 bullet points.</format>
<constraints>Do not use the word "premium." Do not mention competitors. Each description should feel different in tone.</constraints>
The XML tags are optional but help when your prompt is long or has distinct sections. For short prompts, plain text works fine.
This is the biggest difference from ChatGPT. If you tell Claude "do not use bullet points," it will not use bullet points. If you say "respond in exactly 3 sentences," it will aim for exactly 3.
This is an advantage for structured tasks. But it also means you need to be careful with your constraints. If you say "keep it under 50 words" and the task genuinely needs 80, Claude will try to compress everything into 50, which can hurt quality. Set realistic limits.
Claude Sonnet handles 200,000 tokens of context. Opus goes up to 1 million. This means you can paste entire documents, codebases, or datasets directly into the prompt and ask Claude to work with them.
Practical uses of the long context:
When using long context, put the reference material first and your instructions at the end. Claude pays more attention to instructions at the bottom of long prompts.
Claude picks up on patterns in examples faster than most models. If you show two good examples, Claude matches the style very closely.
<examples>
Good: "Ship 2x faster with real-time editing. No more version conflicts."
Bad: "Our collaborative platform enables organizations to streamline their workflow processes for enhanced productivity."
</examples>
Write product copy for our new team chat feature using the style shown in the good example.
When you need Claude to work through a problem step by step, ask it to think through its reasoning before giving the final answer. This works especially well for math, logic, code debugging, and analysis tasks.
Think through this step by step before giving your final answer.
A SaaS company has 1,200 customers. Monthly churn is 4.2%. They add 80 new customers per month. What is their customer count after 6 months? Show your math for each month.
The free prompt builder generates structured prompts with all the right pieces. Fill in role, task, format, tone, and constraints. Copy the result into Claude. Works with both Sonnet and Opus.
If you need system-level prompts for the Claude API, use the System Prompt Generator instead.
Build better Claude prompts. Structured, clear, and copy-ready.
Open Prompt Builder