TryYourPrompt
Playground to debug and optimise LLM prompts.
What it does
TryYourPrompt gives AI & prompt engineers a fast web playground to test, debug and optimise large-language-model prompts before deployment.
Does a similar job
all alternatives →- CAChainForge, a visual tool for prompt engineering and LLM evaluation2023 · chainforge.ai · ▲177
Hi HN! We’re been working hard on this low-code tool for rapid prompt discovery, robustness testing and LLM evaluation. We’ve just released documentation to help new users learn how to use it and what it can already do. Let us know what you think! :)
- PEPrompt Engine – Auto pick LLMs based on your prompts2024 · jigsawstack.com · ▲93
Nowadays, a common AI tech stack has hundreds of different prompts running across different LLMs. Three key problems: - Choices, picking from 100s of LLMs the best LLM for that 1 prompt is gonna be challenging, you're probably not picking the most optimized LLM for a prompt you wrote. - Scaling/Upgrading, similar to choices but you want to keep consistency of your output even when models depreciate or configurations change. - Prompt management is scary, if something works, you'll never want to touch it but you should be able to without fear of everything breaking. So we launched Prompt…
- PRPrePrompt – rewrites vague prompts before they reach the LLMApr 2026 · preprompt.org · ▲23
- PEPrompt-Engineering Tool: AI-to-AI Testing for LLM2023 · github.com · ▲37
Spelltest framework simulates conversations between AI ‘synthetic users' in an environment to test and refine LLM-based applications. It ensures your app converse with utmost accuracy and relevance. Post-chat, Spelltest assesses responses, providing qualitative and quantitative feedback on performance. Suitable for both chat and completion modes. When to use: - After modifying your prompt. - When your LLM provider updates. - As a CI step for you repo. All feedback and collaborations appreciated!
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