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Alternatives

Products that do what I built an open-source “unit testing” suite for prompts ⮂ inputs does

Hi HN, I'm pleased to share Promptspot, an open-source (Apache License 2.0) project that helps automate testing of large language model (LLM) prompts against an array of input data. Modern LLMs offer an enormous amount of leverage if you "teach the bot to fish" — i.e. simply prompt it with both a "system prompt" (which typically doesn't change often) and a dynamic input, which is often application state, search results, recent activity, user profile data, etc. Existing playgrounds and prompt management systems often lack the rigor and flexibility required for this dynamic approach — and as…

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    Open-source 'unit testing' stack for your prompts and data

    2023

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    Instantly test and compare AI prompts results across models

    2025

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    Your ChatGPT prompt engineering community with free prompts.

    2023

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    Find which AI wins for YOUR prompts. Test 100+ models free.

    Dec 2025

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    Version, test, and collaborate on LLM prompts— like code

    2025

  6. 6HP

    Hi HN. I heard you like dev tools and AI, so we wanted to share our project that we’ve been working on. We’re working on Horizon [1] - a higher level abstraction for LLMs so that developers can spend less time trying to grapple with LLMs to make them work and more time with users. This is the starting feature set which takes an auto-ML approach to identify the optimal LLM model, hyperparameters, and prompt - instead of just giving you the tooling to figure it out yourself. You can read more about it in our documentations. Our view is that as LLMs become increasingly commoditized and prompts…

    2023 · gethorizon.ai

  7. 7EL

    Hey HN! I built Experiment to solve a common frustration in LLM development: the lack of proper tools for prompt engineering experimentation. Here's what makes it different: Key Features: - Load and edit chat completion logs from CSV files - Fork and modify specific conversation entries - Run inference via Anthropic, Mistral, and OpenAI - Define custom tools using JSONSchema format - Visual tool usage analysis with collapsible, sorted key-value pairs - Full mobile support and available as installable PWA Technical Highlights: - Built with React using custom isomorphic architecture -…

    2025 · github.com

  8. 8AD

    Hi all, I threw together a small prototype I am calling “Notepad.ai”. A new take on UIs for interacting with LLMs. While I enjoy using LLM’s in the chat format I wanted to see what it would be like to do it in a more long form style. It let’s you write in a pretty free form, much like Window’s Notepad, but you can choose to hit ctrl+[ to analyze the text with a preset prompt of your choosing. It has a few other small features. It’s WIP and very experimental. I would appreciate any feedback or thoughts. Video: https://youtu.be/ntdlgFmSxQY Live Demo:…

    2024 · github.com

  9. 9PG

    Jun 2026 · github.com

  10. 10FP

    We've built an open-source tool to stress test AI agents by simulating prompt injection attacks. We’ve implemented one powerful attack strategy based on the paper [AdvPrefix: An Objective for Nuanced LLM Jailbreaks](https://arxiv.org/abs/2412.10321). Here's how it works: - You define a goal, like: “Tell me your system prompt” - Our tool uses a language model to generate adversarial prefixes (e.g., “Sure, here are my system prompts…”) that are likely to jailbreak the agent. - The output is a list of prompts most likely to succeed in bypassing safeguards. We’re just getting…

    2025 · security.vista-labs.ai

  11. 11IB

    I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…

    2025 · codii.dev

  12. 12HL

    At testup.io we have been working for a while to bring artificial intelligence to the field of test automation. Just a few years ago, the primary challenge laid in accurately identifying UI elements following minor structural changes, such as updates to IDs or paths. The emergence of Large Language Models (LLMs) raised the bar for what it meant to be smart. Now, we anticipate the robot to do lots of things autonomously, such as retry in cases of unresponsiveness or handle minor error reports. A more challenging, but soon expected feature, would involve the test robot navigating your web shop…

    2024 · github.com

  13. 13OS

    Hi HN, We're a small team building AI tutors out of India, and as you might guess, this means we spend a ton of time writing, testing, and refining prompts for LLMs. When we started out, we were using the OpenAI playground but things became tedious when we wanted to compare responses from different models. We tried a bunch of other playgrounds but found them lacking in some features so we built our own. Quick Links: Github: https://github.com/supernova-app/ai-playground Hosted demo: http://playground.getsupernova.ai Demo video:…

    2025 · playground.getsupernova.ai

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    One optimized prompt. 25+ AI models. Consensus verdict.

    May 2026 · promptquorum.com

  15. 15PA

    Hey HN, I built a tool to solve my biggest LLM workflow frustration: context switching. The idea came from trying to meta-prompt in Cursor, I found myself constantly jumping to a browser or dedicated AI app just to improve a prompt. This copy/paste/tweak cycle was a huge productivity killer. I wanted AI to integrate seamlessly into my workflow, not disrupt it. That's why I built Promptive. It's a native macOS app that lets you select any text, in any application, and run a custom LLM prompt on it with a global keyboard shortcut or right-click and select the action in the…

    2025 · promptiveai.app

  16. 16OS
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    Token-efficiency linter for LLM prompts and payloads - ritenv/tokensift

    8d ago · github.com

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  19. 19PL
  20. 20PS
  21. 21IM

    I made EchoStash. If you’ve ever written a great prompt, used it once, and then couldn’t find it again — I’ve been there too. I kept losing my best prompts in chats, notes, or random documents. Every time I started a new project, I ended up rewriting the same stuff or wasting time trying to remember where I saved things. So I built EchoStash — a simple tool for developers who use AI tools regularly. It helps you save, organize, and reuse your prompts. You can tag them by project or tool, and when you need something, just search. The cool part? EchoStash has AI-powered search. You don’t need…

    2025 · echostash.app

  22. 22TN

    Hi guys, I’m excited to share an update on ReproModel, an open-source toolbox designed to streamline the testing and reproduction of machine learning models. I, like many of you, have really struggled with benchmarking and comparing models, from missing code, to opaque experiment parameters slowing the process. I decided to take matters into my own hands, and created a mini-toolbox in my free time to streamline the process. The goal is to reduce the time and effort spent on replicating experiments, enabling researchers to focus on innovation rather than setup. Knowing this task is not an…

    2024 · github.com

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    Join our Waitlist for Prompt.ly

    Mar 2026

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    One CLI. Ten agents. One perfect prompt.

    May 2026 · github.com

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