PrompTessor - AI prompt analysis and optimization
Transform your AI interactions with PrompTessor advanced prompt analysis and optimization platform. Get detailed analysis, actionable feedback, and performance metrics to maximize your AI tool effectiveness.
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PrompTessor
🚀 Hey Product Hunt community!
I built Promptessor because I was frustrated with spending hours manually refining AI prompts without knowing what actually made them work better. As someone who relies heavily on AI tools, I realized there was a huge gap between "prompt engineering tips" and actually understanding what makes prompts effective.
What makes Promptessor unique:
✨ Advanced prompt analysis that goes beyond basic readability - analyze structure, context clarity, and optimization potential
🔄 Historical prompt versioning so you can see what changes actually improved results
🎯 Actionable recommendations, not just vague suggestions
🌍 Multi-language support for global teams
What I'm most proud of: Building a tool that doesn't just tell you your prompt "could be better" - it shows you exactly HOW to make it better and WHY those changes work.
Whether you're a solo creator or managing an AI-powered team, Promptessor turns prompt engineering from guesswork into a data-driven process.
Would love to hear your thoughts and answer any questions! 🎉
Congrats on the launch! Interesting premise, wrestling with prompts is a daily thing for most AI founders. One of the hardest things for is testing changes to see if the prompt generates consistently good output. Guidance is good, but is there a way to verify the results?
PrompTessor
@fedjabosnic Hi Fedja, thanks for the insightful comment and question!
You've raised a very important point. Currently, a feature to automatically test or verify results is not yet available. For now, the suggested workaround is to manually verify the output on your chosen AI platform (to test and verify the results).
This is excellent feedback and it is being considered for future development. Thanks again!
PrompTessor
@reid_crooks Hey Reid, love this question! It's actually a hybrid approach. PrompTessor first runs a rule-based analysis to catch common structural issues and ensure best practices are met. Then, a lightweight AI model assesses the prompt for nuances like clarity and tone. This two-step process provides feedback that is both consistent and context-aware. Thanks for asking
@rizki_murtadha I'm very interested in this and would love to talk more. My X is @ReidCrooks9460 if you're interested
Does it fine tune prompts given expected test cases ?
PrompTessor
Hi@asadaizaz, that's a really interesting question, and I want to make sure I'm understanding it correctly.
To provide some context, the way PrompTessor currently works is that it analyzes your initial prompt and provides an optimized version.
With that in mind, am I correct in thinking you're asking about a more interactive, multi-step process? For example, a workflow where you could provide feedback on a optimized version to 'fine-tune' the optimized prompt version again?
If you could provide a quick example, it would be very helpful just to make sure we're on the same page. Thanks for asking!
Smoopit
Turning prompt tuning into a data-backed process instead of trial and error is a huge time-saver. Does it also suggest alternative phrasing options, or just analyze and score what you input? @rizki_murtadha
PrompTessor
@rachitmagon Yes it also gives you a optimized prompt version