We read every Claude 4.x (Sonnet / Opus) prompt guide so you don't have to.
Paste your prompt below - we'll rewrite it using Anthropic's official best practices.
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- Built on Anthropic's official prompting guide
- Handles xml_tags, extended_thinking, artifacts, computer_use automatically
- Free, instant, no signup
What Claude 4.x actually rewards
We pulled this from Anthropic's official guidance and what works in production. The short version:
- →Use XML tags for sections (~30% accuracy gains documented).
- →Provide >=3 high-quality examples for complex tasks.
- →State motivation (the 'why').
- →Use literal instruction wording: 'implement this' vs 'suggest changes' produces different behavior.
- →If you want bullets/Markdown from 4.5+, ask explicitly — they're concise by default.
Before you hit send, check:
- ☐Did you use XML tags for sections (~30% accuracy gains documented)?
- ☐Did you provide >=3 high-quality examples for complex tasks?
- ☐Did you state motivation (the 'why')?
- ☐Did you use literal instruction wording: 'implement this' vs 'suggest changes' produces different behavior?
- ☐If you want bullets/Markdown from 4.5+, ask explicitly — they're concise by default?
Common mistakes we fix automatically
- AvoidDon't expect 4.5/4.6/4.7 to fill gaps as 3.5 did — be more literal.
- AvoidDon't include ellipses if output goes to TTS.
Ready to rewrite for Claude 4.x?
Frequently asked questions
- Which versions of Claude 4.x (Sonnet / Opus) does this support?
- We support claude-sonnet-4.5, claude-sonnet-4.6, claude-opus-4.5, claude-opus-4.6, claude-opus-4.7, claude-haiku-4.5. We apply the prompt patterns Anthropic recommends for each, so the rewrite is tuned to the version you're using.
- Is my prompt stored or used for training?
- No. Prompts are sent to the rewriter, scored, returned, and discarded. We don't train on them and we don't keep them around.
- Do I need to know prompt engineering to use this?
- Nope. That's the point. Paste what you have, click Rewrite, get back a version that follows Anthropic's official guidance.
- What makes this different from Claude 4.x (Sonnet / Opus)'s own "improve prompt" feature?
- Built-in optimizers use the model's own preferences. Ours is built on Anthropic's official documentation and patterns that consistently produce better results in production. Claude 4.x (Sonnet / Opus) works best with prompts in the 200-5000 token range, and we keep rewrites inside that window.
Optimizing for a different AI?