We read every Google Gemini 2.5 / 3 prompt guide so you don't have to.
Paste your prompt below - we'll rewrite it using Google's official best practices.
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- Built on Google's official prompting guide
- Handles 1M_context, search_grounding, url_context_tool, code_execution automatically
- Free, instant, no signup
What Google Gemini 2.5 / 3 actually rewards
We pulled this from Google's official guidance and what works in production. The short version:
- →Use PTCF: Persona, Task, Context, Format.
- →Pick XML tags or Markdown headings — be consistent within a single prompt.
- →Use responseSchema for strict JSON output.
- →State grounding rules explicitly (e.g., 'rely only on the User Context').
- →Control verbosity explicitly for Gemini 3 — defaults to verbose code output.
Before you hit send, check:
- ☐Did you use PTCF: Persona, Task, Context, Format?
- ☐Pick XML tags or Markdown headings — be consistent within a single prompt?
- ☐Did you use responseSchema for strict JSON output?
- ☐Did you state grounding rules explicitly (e.g., 'rely only on the User Context')?
- ☐Control verbosity explicitly for Gemini 3 — defaults to verbose code output?
Common mistakes we fix automatically
- AvoidDon't use overly persuasive language with Gemini 3 ('It's URGENT…' hurts).
- AvoidDon't mix XML and Markdown delimiters in the same prompt.
Ready to rewrite for Google Gemini 2.5 / 3?
Frequently asked questions
- Which versions of Google Gemini 2.5 / 3 does this support?
- We support gemini-2.0-flash, gemini-2.5-flash, gemini-2.5-pro, gemini-3-pro. We apply the prompt patterns Google 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 Google's official guidance.
- What makes this different from Google Gemini 2.5 / 3's own "improve prompt" feature?
- Built-in optimizers use the model's own preferences. Ours is built on Google's official documentation and patterns that consistently produce better results in production. Google Gemini 2.5 / 3 works best with prompts in the 100-5000 token range, and we keep rewrites inside that window.
Optimizing for a different AI?