Prompt engineers
Cut the trial-and-error loop on production prompts.
Build production-ready prompts with systematic testing and refinement.
Research, build, score and refine prompts with AI guidance, then check them against a live model.
They read fine, then drift, ramble or miss the point. Here is what usually goes wrong, and what changes.
How it works
Five guided steps. Each one hands the next a better draft.
Research
Enter a topic. AI researches it and recommends one of six reasoning frameworks.
The explanation has one clear path. Branching would add cost without a better answer.
Step-Back. Would help if the lesson needed the underlying principle first.
ToT. Better when several competing routes need exploring.
One workflow, from the first question to a prompt you can trust in production.
AI researches your topic and recommends one of six reasoning frameworks, with the reason.
Recommended: one clear path to the answer.
Build structured prompts field by field, grounded in PDFs, spreadsheets, emails or a GitHub repo.
Five criteria, scored before and after each refinement, so you can see what improved.
Suggested rewrites, side by side, with the reason for each change.
Keep it simple. One metaphor only: a spinning coin.
Every version kept, searchable and exportable, so good prompts are never lost.
Different problems need different approaches. The research step recommends one for your topic, and you can always choose another.
One path, reasoned step by step.
A single reasoning pass. The baseline the other ratings are measured against. Ratings are relative estimates, not benchmarks.
Not sure? The research step recommends one for your topic.
Who it’s for
Cut the trial-and-error loop on production prompts.
Build production-ready prompts with systematic testing and refinement.
Test and document reasoning approaches side by side.
Run one topic through different reasoning frameworks and compare the prompts they produce.
Ship prompts into your app with confidence.
Ground prompts in your repo, then keep every validated version on hand.
Teach prompt engineering with hands-on examples.
Guide students through a structured process with real-time feedback.
Analytics are stored locally in your browser and are not sent anywhere.
Numbers fill in after your first run through the workflow.
A guided workflow to research topics and construct sophisticated reasoning prompts.
You need to sign in to access the prompt engineering workflow.
Test your generated prompt against live models to evaluate the results.
Generate a prompt in the workflow or load one from history to test
Review, inspect, and download your previously generated prompts. History is stored locally in your browser.
Your generated prompts will appear here. Start by creating your first prompt in the workflow section above.
Bring your Gemini API key. Your prompt history stays in this browser.