value: fantajuice

value:
Got tired of my debates with my friend's ending in  "I'm right bc I said so" so I made a platform where you can debate with your friend's(or a bot, recently added feature) about whatever you want, and after the debate is done a LLM judges who's more sound in logic. Gain points and climb the leaderboard!
Feedback and criticism would be appreciated(there's a discord in there if you wanna talk more in depth)
p.s.: I decided to use google acc sign in since it makes the whole thing easier to manage(live chatroom feature, etc.). I don't actually do anything with your emails

value: Show HN: I made a competitive debating game(like chess.com but for debating)

author: fantajuice


value: felipeinfante

value:
Opening a workflow, running it, then manually opening another one, then getting the output file from the first run, then loading it... doing stuff manually gets old fast. It's uncomfortable.
So I built Discomfort. It allows me to run Comfy 100% on Python. I can run partial workflows to load models, iterate over different prompts, do if/then clauses, run loops etc. It's FOSS (MIT license).
You can do a lot of stuff with it, especially if you hate spending hours dealing with spaghetti workflows and debugging un-debuggable megaworkflows.
Would love to hear the community's thoughts on it. I hope it helps you as much as it helps me.

value: Show HN: Discomfort – Control ComfyUI with Python

author: felipeinfante


value: townload

value:
Hey :)
Recently, I’ve been working on my hobby project, keyglide. It’s a small tool that lets you practice editing a "start" file in a real Helix editor (https://helix-editor.com/) until it matches a given "goal" file. Once you complete the exercise, your score - including keystrokes and time taken - is published. Scores are then ranked by the amount of keystrokes.
Although I’ve been using Helix for a few years, I still don’t feel particularly efficient with it. This little game is meant to help me (and hopefully others) compare editing approaches and discover more effective ways to work.
You can easily try it out without signing in.

value: Show HN: Keyglide – Competitive Online Text Editing

author: townload


value: I'm working on Tab'd, a GitHub Copilot / Windsurf / Kiro extension which tracks and visualizes AI-assisted coding and copy-paste operations in codebases, and optionally shares that metadata with teams to help maintain accountability.<p>Tab'd shows detailed metadata about AI edits and clipboard origins, and allows users to distribute that metadata within code repositories. If present, the associated browser extension can highlight these edits during GitHub PR review online or within the IDE.

value: Show HN: Tab'd – Track and share AI and clipboard operations within your IDE


value: barbinbrad

value: Show HN: I've been building an ERP for manufacturing for the last 3 years

author: barbinbrad


value: samsullivan

value:
Decodes any VIN in ~20ms with zero network calls. I compressed the entire NHTSA vehicle database into a 21MB SQLite file that runs completely offline.
No API keys, no rate limits, no servers. Just download once and decode forever. Works in browsers, Node.js, Cloudflare Workers - anywhere SQLite runs.
Would love any feedback and to answer any questions about the implementation.

value: Show HN: I built the fastest VIN decoder

author: samsullivan


value: fun game to test your appetite for risk<p>i want to make different llms play this game to see how they reason and score

value: Show HN: Balloon risk management game

title: Show HN: Balloon risk management game


value: zarqaTech

value:
Ive built a simple iOS app that allows users to take a picture or screenshot of their mechanic invoice and within seconds it automatically processes and chronologically orders the logs. You can also export all of this information to an email.
I think this would be useful for a person selling a car to prove all of the work done to the vehicle over the years along with the actual image of the invoice exportable as well.
The app is called Vehicle Maintenance Log and you can check out the landing page, https://vehiclemaintenancelogapp.com for more info if this interests you. Its also currently in the iOS App Store ...curious if you would use this to prove all maintenance with screenshots of the invoices to back it up?! Let me know your thoughts on the app!

value: Show HN: Quickly log vehicle maintenance by taking a photo of your invoice

author: zarqaTech


value: Show HN: Created My Fav Wordle Game Using AI Copilot (No Dev Experience)


value: rlindskog

value: Hey HN! I built a small app for comparing companies or job offers based on "years until financial independence" instead of "total compensation", after finding out the same offer from 2 companies can have a difference of years in terms of FIRE. I also ranked companies based on the time to FIRE as well. (with some assumptions, see the methodology for more details here https://firelist.io/methodology). It was useful for me, hopefully it's useful to you! I'll be adding more benefits and companies over the next few days or so. Let me know if you have any requests.

value: Show HN: FireList – Companies ranked by years to FIRE

author: rlindskog


value: jasonjmcghee

value: Show HN: A Match-3 Game I Built for a Game Jam

author: jasonjmcghee


value:
I've been working a fair bit with DSPy lately, and I did some work in combining the benefits of vector search and LLMs (via a DSPy pipeline) to disambiguate records with a high degree of accuracy to help enrich a dataset. The blog post shows how this approach scales well, is very cost-effective and super concise - all it takes is < 100 lines of DSPy code and it all runs async.
The code to reproduce is in this repo if anyone's interested (all tools are 100% free and open source, and the methodology will work with open weight LLMs too).
https://github.com/kuzudb/dspy-kuzu-demo

value: Show HN: Using DSPy to enrich a dataset of the Nobel laureate network


value: Show HN: I wrote a GitHub CLI extension to interactively manage repos


value: Show HN: Open-source business management tool for small business


value: dcreater

value:
Updates all dependencies to their latest available versions. https://gist.github.com/rosmur/72f8cec22c980c93c2865d458bee2...
P.S: Recommend to run your test suite after to assure compatibility

value: Show HN: A simple script to update all dependencies in pyproject.toml

author: dcreater


value:
This is an MacOS Apple Music client I built.
Instead of a library, or a list of songs, it's pretty much just a simple, beautiful chat UI.
You are chatting with the legendary Doctor Von Peel, who is a DJ, but also an adorable cat.
Doctor Von Peel (who is technically a triage of LLMs, using an OpenRouter backend) is able to control your Apple Music via tool calls.
You can either ask him to play something specific, or just a vibe, and refine as you go. It's quite a refreshing way to stream music, I think.
Having said that, Doctor Von Peel speaks in a combination of Cajun, German, and London slang, and I suppose some people might find this grating. Doctor Von Peel is inspired by Dr, John, John Peel, some other very charming but not-famous people I know, and the pleasant, fever-dream aesthetic I remember computers having when I was a child ("Who is this paperclip man, and what could he want?"). I also like when there are little animals on my computer.
I built it as a "for myself" project because I really like discovering new music.
I was using Roon for that, because of its excellent metadata. It's really cool to enjoy the sound of a certain bass guitar part on a track, find out who played it, and then listen to their other stuff. That's fun.
But paying for Roon + a Tidal subscription (the second subscription necessary for discovery) is, honestly, as a non-professional, terrible, hobbyist programmer, too expensive for me.
I'm also really sick of Spotify, etc, serving me weird content (podcasts? AI-generated music to pay artists even less?) that I don't want. I find it ugly.
Kind of at the same time, I realised I was increasingly giving ChatGPT my girlfriend's letterboxd link, and asking for movie recs. This worked really well.
LLMs have loads of music criticism, forum posts, etc, inside them somewhere. Recommendations is a task they really excel at for me.
I also think that LLMs, for all their flaws, open up some exciting possibilities about what UI needs to be. Maybe that's a trite point now, but it felt fun to build something with that as the principle.
I've been using Dr Von Peel as my daily driver for a little while now, and I feel a little bit excited to share him with people. I've (tried to!) give any early adopters (pun intended) a reasonable number of free calls to OpenRouter via AIProxy, so you can test the Good Doctor's soundsystem selections without having to put in your own OpenRouter key. Once those run out, you can use your own, and mess around with the models used, the system prompts, etc.
It does require an Apple Music sub, ironically, given the things I was annoyed about that made me build it.
Some features are a bit janky because I _think_ there are some limitations on what MusicKit can achieve on MacOS vs iOS (saving tracks to user library, removing queued tracks, individual app airplay, _possibly_ full album queuing). The iOS version is much nicer (nicer still if Apple Intelligence can make the natural language aspects free!).
Hope you vibe with him! If you try him out, and have ideas, issues, feedback, etc, I'd love to hear it.

value: Show HN: Scratch Radio Ft Doctor Von Peel: An LLM / Cat-Based Apple Music Client


value: stonecharioteer

value:
Hi HN!
I was using AI tools to research some of the RFCs people recommend you read and I thought why not build a tool that allows you to progressively do this and provides python examples, with dockerfiles to demonstrate some of the more complicated networking paradigms.
It's not fully done yet, but I thought I'd show it off to get some feedback.
https://rfc.stonecharioteer.com

value: Show HN: Read the RFCs That Built the Internet

author: stonecharioteer


value: SamInTheShell

value: Something I did over the weekend. There's some really cool projects out there, but what I was finding for Ollama was lacking in various places.  I addressed the first two things I wanted: 1) MCP Server Support and 2) Scheduling LLM Tasks

value: Show HN: I Wrote a Chat CLI for Ollama with MCP Support

author: SamInTheShell


value: branga

value:
Hello Folks,
I recently built "Mortlab" which is a simple, free website to help people analyze whether it's better to rent or buy a home based on their situation.
It includes:
A clean rent vs buy calculator
Monthly and long-term cost breakdowns
Refinance and affordability tools
No login, ads, or affiliate spam, it's just data
I’d love feedback from the community — especially from folks who’ve built similar tools or have strong opinions on the rent vs buy debate. I know there are a million calculators out there, but I tried to keep this one minimal and useful.
Thanks in advance.

value: Show HN: A simple website to analyze mortgage called "Mortlab"

author: branga


value:
Code Index MCP is an MCP server that indexes codebases and provides search capabilities to LLMs. Supports 50+ file types with automatic indexing, regex/fuzzy search, code analysis, and real-time file monitoring.
LLMs can search your entire project, find files with glob patterns, analyze code structure (functions, classes, imports), and get automatic updates when files change. Eliminates the need to manually copy files or explain project structure to overcome context limits.
Built with Python using the Model Context Protocol. Uses pluggable search backends (ugrep/ripgrep/ag/grep).
Installation:
{
  "mcpServers": {
    "code-index": {
      "command": "uvx",
      "args": ["code-index-mcp"]
    }
  }
}

value: Show HN: Code Index MCP – Codebase Indexing Server for LLMs


value: MarcoDewey

value:
I've been working on a project that I'm excited to share with the Hacker News community. It's an AI-powered Python testing suite that uses a hybrid AI approach to automatically generate comprehensive unit tests, perform fuzz testing, and even conduct mutation testing to assess the quality of your existing test suites.
*The Problem*
As a developer, I've always found writing and maintaining a robust test suite to be one of the most time-consuming and challenging aspects of software development. It's often difficult to think of all the possible edge cases and to ensure that your tests are actually effective at catching bugs.
*The Solution*
To address this, I've created an MCP server that leverages both Google's Gemini AI and BAML (Boundary ML) to provide a suite of intelligent testing tools. The server is built on the FastMCP framework and can be easily integrated into your existing workflow.
*Technical Deep Dive*
Here's a breakdown of the key features and how they work:
*   *Hybrid AI Approach:* The project uses a hybrid AI approach that combines the strengths of both BAML and Gemini. BAML is used for structured test generation, ensuring that the output is always in a consistent and parseable format. Gemini is used for its powerful language understanding capabilities, which allows it to generate creative and challenging test cases.
*   *Intelligent Unit Test Generation:* The unit test generator uses AI to create a comprehensive suite of tests for your Python code. It automatically identifies edge cases, error conditions, and other potential sources of bugs. The generated tests are written using the `unittest` framework and include proper assertions and error handling.
*   *AI-Powered Fuzz Testing:* The fuzz tester uses AI to generate a diverse range of inputs to test the robustness of your functions. It can generate everything from simple edge cases to malformed data and large inputs, helping you to identify potential crashes and other unexpected behavior.
*   *Advanced Coverage Testing:* The coverage tester uses a combination of AST analysis and AI-powered test generation to achieve maximum code coverage. It identifies all possible branches, loops, and exception paths in your code and then generates tests to cover each of them.
*   *Intelligent Mutation Testing:* The mutation tester uses a custom AST-based mutation engine to assess the quality of your existing test suite. It generates a series of small, syntactic changes to your code (mutations) and then checks to see if your tests are able to detect them. This helps you to identify gaps in your test coverage and to improve the overall effectiveness of your tests.
*Call to Action*
I'm still actively developing the project, and I would love to get your feedback. You can find the source code on GitHub: https://github.com/jazzberry-ai/python-testing-mcp
I'm particularly interested in hearing your thoughts on the following:
*   Are there any other testing tools that you would like to see added to the suite?
*   Have you found any interesting bugs or edge cases using the tool?
*   Do you have any suggestions for improving the prompts or the AI models?
Thanks for reading, and I look forward to hearing from you!

value: Show HN: I created an AI-powered Python testing suite that writes its own tests

author: MarcoDewey


value:
I built LinkJolt after getting fed up with generic affiliate platforms that:
- charge a cut of every commission
- take hours to bolt onto Stripe
- easily break and are clunky
- give no real-time data
- hold payouts for days (or weeks)
LinkJolt is built for SaaS:
- 0 % transaction fees for every referral
- real-time, recurring-aware tracking
- instant Stripe payouts
- unlimited campaigns and affiliates
- built-in fraud detection and custom commissions
If you want to check it out there's a free trial and also 50 % off your first three months with code LINKJOLT50 if you continue.
Would love feedback on anything that still feels clunky!

value: Show HN: LinkJolt – SaaS affiliate tracking with 0% fees


value: yazon

value:
After playing around with local AI setups for a while, I kept getting annoyed at having to juggle different llama.cpp servers for each model. Switching between them was such a pain and I always had to restart things just to load up a new model.
So I ended up building something to fix that. It's called FlexLLama - https://github.com/yazon/flexllama
Basically, it's a tool that lets you run multiple llama.cpp instances easily, spread across CPU and GPUs if you got'em. Everything sits behind a single OpenAI-compatible API.
You can run chat models, embeddings, rerankers - all at once. The models assigned to the runners are reloaded on the fly.
There's a little web dashboard to monitor and manage runners.
It's super easy to get started: just pip install from the repo, or grab the Docker image for a speedy setup.
I've been using it myself with things like OpenWebUI and some VS Code extensions (Roo Code, Cline, Continue.dev), and it works flawlessly.

value: Show HN: FlexLLama – Run multiple local LLMs at once with a simple dashboard

author: yazon


value: grantsingleton

value:
I was watching Deep Research do hours of research in minutes and thought why the hell am I still manually clicking through Ahrefs trying to guess what keywords to check? So I built an AI that does keyword research the same way.
The problem with traditional keyword tools is they assume you already know what to look for. But I'd sit there thinking "okay I'm building a developer tool... do I search for 'API monitoring'? 'webhook debugging'? 'API testing'?" Then I'd spend an hour going down rabbit holes and miss the fact that "Postman alternative open source" or something like that gets 2k searches a month.
So I built Jello SEO. You just describe what you want: "I'm building a Terraform visualization tool" or "find keywords for AI agent builders" and it researches all the angles for you.
Technical side:
- ChatGPT o3 reasoning model handles the research logic. It's the same model that powers oai deep research.
- DataForSEO for real search volumes and keyword expansion
- No keyword database - everything is live API calls
- Usually finds hundreds of keywords, but 10-30 are ones you'd never think to check yourself
$9/month. No free trial because you can see exactly what it does before paying. The ROI is obvious.
Not trying to compete with Ahrefs for SEO professionals. This is for doing hours of keyword research in minutes. Exactly what deep web research does, but for keywords.

value: Show HN: I built Deep Research for SEO keywords

author: grantsingleton


value: Show HN: Semi Intelligence – Instant. Tiny. Lightweight


value: vinserello

value:
Hi HN,
I started building Datastripes as part of my thesis, trying to answer a simple question:
How can non-technical teams turn raw data into insights without relying on developers or BI tools?
What began as research has now grown into a working product, built by a small team, focused on solving that exact problem.
Datastripes is a no-code platform for creating dashboards and data visualizations in minutes: no SQL, no setup, no friction.
What it does:
Connects to CSVs, Google Sheets, or APIs
Drag-and-drop dashboard builder
Shareable via public links or embed
Fully browser-based
We’re launching publicly this week and would love feedback from this community, especially from people who've built internal tools, worked with non-technical users, or have felt the pain of "can you pull that data for me?"
Would really appreciate:
First impressions on UX and clarity
Thoughts on performance, edge cases, or integrations
Honest feedback on where this fits (or doesn’t) in the BI/no-code space
Live: https://datastripes.com
 On Product Hunt: https://producthunt.com/products/datastripes
Happy to answer questions — and grateful for your time and thoughts.

value: Show HN: Datastripes – No-Code Data Dashboard Builder

author: vinserello


value: matankleym

value:
Dataset Explorer is now LIVE and FREE.
--
Finding the right dataset shouldn't be this hard.
Millions of high-quality datasets exist across Kaggle, data.gov, and other platforms, but discovering the ones you actually need feels like searching for a needle in a haystack.
Whether it's seasonality trends, weather patterns, holiday data, tech layoffs, currency rates, political content, or geo information – the perfect dataset is out there, but buried under poor search functionality.
That's why we built the dataset-explorer – a completely free tool that lets you search for datasets using natural language across multiple platforms.
Just describe what you want to analyze, and it uses Perplexity, scraping (Firecrawl), and other tools behind the scenes to surface relevant datasets.
Instead of manually browsing through categories or dealing with limited search filters, you can simply ask "show me tech layoff data from the past 5 years" and get preview of multiple datasets.
Quick demo: I analyzed tech layoffs from 2020-2025 and uncovered some striking insights:
- 2023 was brutal – 264K layoffs (the peak year)
- Post-IPO companies led the cuts – responsible for 58% of all layoffs
- Hardware hit hardest – with Intel leading the charge
- January 2023 = worst month ever – 89K people lost their jobs in just 30 days
Once you find your dataset, you can analyze it completely free on Hunch
.
Try it yourself and let us know we can improve it for you.
Data explorer - https://hunch.dev/data-explorer
Demo link - https://screen.studio/share/bLnYXAvZ

value: Show HN: Dataset Explorer – Free tool to search any public datasets

author: matankleym


value: cbpark

value:
Hey everyone,
We're building a tool that creates custom social posts styled exactly like your brand, in under 1 minute.
If you’re spending 2 hours designing a single Instagram post, this might actually help.
You just enter your brand name, audience, and content type.
In return, you get post-ready visuals that match your feed and brand vibe.
Who it's for:
1. Small business owners, freelancers, and solo creators doing everything themselves.
2. The product is currently in beta. We're looking for early users who can share honest feedback as we build.
What it does:
1. Generates branded visuals
2. Matches your tone and aesthetic
3. No editing needed (unless you want to tweak)
4. Save and reuse as templates
Why we're building it:
1. To save creators hours of repetitive design work
2. To help small brands stay consistent without burning out
3. To build and improve the product with real users
Every comments matters for us, PLEASE HELP US!
Thank you :)

value: Show HN: We built this to save creators time, looking for early users (free)

author: cbpark


value: toutoulliou

value:
After 2 months of coding in my free time, I launched a directory where creators can showcase their websites, SaaS tools, mobile apps, AI tools, and digital projects. The platform helps developers and entrepreneurs present their work to the world and connect with a community of like-minded creators.
What you'll see on the site:
- Latest projects from creators across different categories (SaaS, blogs, marketplaces, AI tools, etc.)
- Detailed project pages with descriptions, logos, and direct links
- Category filtering to discover specific types of projects
- User profiles where creators can showcase all their projects
- Premium features for enhanced visibility
- Backlink verification system for quality control
The platform is designed to be a discovery hub where you can find interesting projects, get inspired by other creators' work, and potentially collaborate or learn from their approaches.
I'm working on giving you more control over your profile appearance. Soon you'll be able to customize layouts, add custom sections, choose themes, and create personalized project showcases.
These features will help you create a more professional and unique presence on the platform.

value: Show HN: I built a platform to showcase digital projects and connect creators

author: toutoulliou


value: dsternlicht

value:
Hi HN, I’m a co‑founder of Embeddable AI.
After struggling to add interactive AI experiences to Wix, Shopify, Webflow, WordPress sites, I built this tool to let marketers build chatbots, quizzes or assistants and embed them anywhere with a snippet.
Built in React/TypeScript front end and Node.js logic engine. It loads fast and works across CMS platforms.
I’d love feedback from builders and marketers on use cases, missing features, or integration ideas.

value: Show HN: Embeddable -build interactive experiences you can drop into any website

author: dsternlicht


value: DearestZ

value:
Hey HN,
I love playing Squaredle, but I was constantly frustrated with the available solvers. I found myself stuck in a trade-off: either use a tool that was 100% accurate but had a clunky, desktop-only UI that looked straight out of 2010, or use a modern, slick-looking solver that used an unofficial dictionary and often missed words or gave incorrect answers.
Neither felt right. I wanted a tool that was not only accurate but also a pleasure to use, especially on my phone.
So, I decided to build my own. I'm excited to share the result with you today: SquaredleSolver.org
My goal was to create the definitive solver by combining professional-grade accuracy with a modern user experience, and adding the features I always wished for.
Here’s what makes it different:
Auto-Fetches Today's Puzzle: This is the biggest one for me. No more manually typing in 21 letters. The site loads today's official puzzle the moment you open it. It just works.
Interactive Path Visualization: Don't just see the answer, learn the path. Click any word in the results, and it instantly animates the exact path on the grid. It’s a great way to see how complex words are formed.
100% Accurate Official Dictionary: It uses the official North American Scrabble Players Association word list (NWL2023), the exact same one the game uses. This means you get every valid word, every time. No more guessing if your solver is correct.
Proper 5x5 Cross-Grid Support: It's one of the few solvers that flawlessly handles the tricky 5x5 cross-shaped grids (like on Fridays) with the empty cells in the middle.
Fast, Modern, and Mobile-First: I built it with Astro, React (Islands), and Tailwind CSS, so it's incredibly fast and works beautifully on any device. The UI is clean, responsive, and there are no ads.
This was a passion project focused on solving a real user need I felt personally. It's not just a cheat tool, but designed to be a learning companion that enhances the game.
I've just launched it and would be incredibly grateful for any feedback from the HN community.
Check it out here: https://squaredlesolver.org/
Thanks for reading!

value: Show HN: I built a Squaredle solver that visualizes paths

author: DearestZ


value: davepoon

value:
I originally started by sharing a collection of specialized AI subagents and slash commands for Claude Code on GitHub.
Then, I enhanced it by creating a web UI, so people can browse, search, and install both subagents and commands instantly by copying and pasting.
After that, I started creating a CLI tool to allow more advanced users to install and manage subagents and commands directly from their terminal.
Now, I am trying to enhance the CLI tool to be a configuration tool that allows you to share, extend, and reuse the Claude Code configuration(commands, hooks, subagents and MCPs) easily for team onboarding, bulk installation, etc.
Website: https://www.buildwithclaude.com/
Github Repo: https://github.com/davepoon/claude-code-subagents-collection
Would appreciate any feedback or feature suggestions.

value: Show HN: I've been building a configuration tool for Claude Code

author: davepoon


value: mpoweredo

value:
Hey HN!
I am a FE dev who is working at a software agency and im making 2-3 estimates per week.
Creating estimates is painfull manual proccess, where you have to read a lot of .docx like RFP, SRS etc. This was really tiring for me
Also in agency where im working we make estimates in google spreadsheets which is another pain, trying to drag something, copy, duplicate can really mess up the whole layout
So i just wanted tool that can just automate this a bit.
I just started researching and I couldnt find anything good enough for my usecase.
So I made a tool for creating estimates with AI.
I just checked out that AI is really good at breaking down SRS into tasks and estimating it.
So the plan is very easy
1. Upload project's SRS
2. Generate estimate which is really good base to work later on it
3. Check, correct and it is ready
Result? Estimates made in 15-30 minutes instead of 2-3 hours
Check this out (no signup) needed: https://devtimate.com/

value: Show HN: Software devs, I made a tool to make creating estimates less painful

author: mpoweredo


value: Catay

value:
Hi HN,
I'm the creator of 3D Icon Gallery. For a while now, I've been fascinated by the clean, playful aesthetic of 3D icons, but I often found it hard to find a large, consistent, and high-quality collection that was also affordable. So, I decided to build my own.
The result is ai-suguan.com, a gallery with thousands of 3D icons organized into themed packs.
Here's how the pricing works:
- You can get any single pack (like 'Food' or 'Vehicles') for a one-time payment of $9.9.
- For the best deal, you can get the 'All Series' pass for $19.9, which gives you lifetime access to all current and future packs.
There are no subscriptions. I wanted to keep it simple and provide great value.
The icons are generated using AI tools and then manually curated and refined to ensure quality. I'm constantly working on adding new icons and themes.
I'm really excited to share this with the HN community and would love to hear your feedback on the icons, the site, and the pricing model. Thanks for checking it out!

value: Show HN: I created a gallery of 3D icons, free to download

author: Catay


value: leroman

value: Show HN: Prompt Engineering Templating Language and CLI Tool

author: leroman


value: surrTurr

value:
Hi HN!
A month ago, I wanted an app that opens instantly, stays out of the way, and stores every note as plain text. Nothing fit, so I built 'Zettel'.
Zettel is nothing crazy; it's a digital piece of paper on your phone: type, swipe, done. Each note lands as a .md file in the iOS Files app, which you can use to sync to any of your other devices or applications.
I use Zettel daily to quickly get thoughts out of my head, into my favourite App Obsidian.
Zettel is free & open source, and 1MB in size - feel free to try it out if you like!
https://apps.apple.com/de/app/zettel-quick-notes/id674852524...

value: Show HN: Zettel – Quick Notes

author: surrTurr

title: Show HN: Zettel – Quick Notes


value: qwikhost

value: Export your liked posts from X (Twitter) in 1 click as CSV, JSON, or Excel. Backup, share, or access offline with ease.

value: Show HN: X Likes Exporter – Export Twitter Liked Tweets

author: qwikhost


value: Show HN: I got rejected by Meta so I built an AI Recruiter to roast resumes


value: yz-yu

value:
TL;DR: LLM Fighter is a small, open-source, playable benchmark for agentic behavior. You bring an OpenAI-compatible API; the demo runs in the browser. It creates head-to-head “battles” that stress tools, planning, and efficiency, and shows step-by-step logs you can download.<p>What it does well: quick, honest feel for how agents act under the same rules.
What it’s not: a formal academic benchmark or a single “score”.
Why I built it: I wanted something you can play in minutes and still learn from.

value: Show HN: I made a tiny, playable benchmark where LLMs compete head-to-head

author: yz-yu


value: roughike

value:
Hey all!
My girlfriend is really good at drawing and wants to become an illustrator for children's books, so she's practicing drawing various animals.
We were at a cafe and she got stuck staring at a blank page trying to draw a fox using a reference photo. So I generated some pencil sketches from the reference image with ChatGPT. Seeing the drawing broken down step by step made it easier to start for her.
The next day she asked me to generate sketches for 10 more photos, so I decided to polish my prompts and wrap the workflow in a self-service app for her.
The app allows you to upload any image and it generates 5 pencil sketches from the uploaded image, from basic shapes to a fully detailed pencil sketch.
https://restoftheowl.app

value: Show HN: I built an app that turns any image into 5-step pencil drawing practice

author: roughike


value: wyan

value: Show HN: Using AI to generate a JUCE tutorial

author: wyan


value:
We're launching Sleipner.ai, a zero-friction cost-control layer for teams using large language models (LLMs).
Here's how it works:
Intelligent model routing: Automatically selects the smallest (cheapest) model that can effectively handle your prompt.
Prompt compression: Strips unnecessary filler, reducing tokens without changing meaning.
Semantic caching: Answers repeated or similar queries instantly—no model call needed.
Real-time analytics: Detailed insights into routing decisions, costs, latency, and token usage.
Early adopters are consistently seeing their total LLM spend drop by 40-70%, all while keeping response times under a second. Integration requires zero prompt or SDK changes—just swap one base URL and add your existing API key.
Our pricing is transparent and risk-free: you only pay 25% of the savings we deliver. If we don’t save you money, you pay nothing.
We're looking for a few more teams for our private beta. If your AI costs are climbing faster than you'd like, let's talk.
More info: https://sleipner.ai
Feedback and questions very welcome!

value: Show HN: Sleipner.ai – Cut Your LLM Costs by 40-70% (Private Beta)


value: moltenice

value: Hello HN!<p>Expanding AI debates in UI/UX. Do check the emergent behaviour of arguing AI agents.

value: Show HN: This AI panel gives more honest UI/UX feedback than your friends

author: moltenice


value:
Over the weekend, I hacked together a tiny tool to help devs keep track of their deployed URLs (apps, docs, testnets, etc). We had too many incidents where something silently broke and no one noticed for hours.
So this tool:
- Checks up to 5 URLs (free tier)
- Sends 2–3x/day status summary to Slack or Telegram
- No login, no config — just paste + pick your alert channel
Would love feedback from anyone shipping Web3 stuff or client work. Happy to share the demo link!

value: Show HN: Weekend project – Alerts for broken public URLs via Slack / Telegram


value: skyzouw

value:
As a solo builder, I realized something frustrating:
Even with a great product, I was spending a stupid amount of time writing the same types of replies — investor intros, meeting requests, user questions…
Not hard tasks. But repetitive and mentally taxing.
It ate my focus.
So I built a tool to solve it for myself:
It reads the email, understands the context, and drafts a reply that sounds like me. One click to send. Done.
Now I save hours every week, and my inbox anxiety dropped to zero.
It’s called ReplyFast. ( https://www.replyfast.net/ )
Not perfect, but already useful. Just launched it today — open to feedback or feature ideas if this resonates with anyone.

value: Show HN: I stopped wasting 5 hours/week replying to emails

author: skyzouw


value: Usef

value:
Hey HN
I just launched TimeSnap, a lightweight desktop app built for deep work and distraction control.
What it does:
Tracks your focus sessions
Lets you whitelist apps (everything else is considered a distraction)
Shows you exactly when and where you lost focus
Optional glowing screen border for visual feedback
Clean UI with session history, achievements & recap
No bloat. No complicated setups. Just a fast way to get into flow and stay there.
Check it out https://usefsgh.gumroad.com/l/uxhixl($39.99)
I'd love your feedback on the concept, design, or anything you'd improve. I'm bootstrapping this solo and open to all thoughts!
Thanks for reading

value: Show HN: TimeSnap – A Minimalist Focus Timer That Tracks Distractions

author: Usef


value: lschneider

value:
Hi HN,
YCW24 company here, we just open-sourced an AI image detection model that beats the SOTA commercial detectors. AI-generated images/videos have become incredibly good in the last few months and are flooding the internet; being able to detect them reliably gives some power back to consumers and companies that care about high-quality, genuine content.
Detecting AI-generated images is a very hard problem: there are many different techniques to generate images; there is image compression, noise, and other distortions that destroy generator artifacts; there's android phones applying auto-correction to images; etc. And none of the detectors we tried (sightengine.com, decopy.ai, etc.) works reliably even for basic examples (try it out with pirate Rick Astley made with Flux Kontext: https://imgur.com/a/iL3paE8).
We released two models, the full version (~600M params) and a smaller version (~20M params) that can even run in your browser on mobile (see demo)! We've also put up code for running things locally or via an API (free but rate-limited) using javascript/node and python code.
-------- Details --------
The full model was trained on 1M+ images that were scraped off the internet and the small model is a distillation. We're actively working on extending the dataset and further improving the models.
Classification accuracy: sightengine.com seems to be the best commercial solution out there, as confirmed by this (https://arxiv.org/pdf/2404.14581) paper, which they also cite on their website. Of course, they cherry-picked the results and claim 98.3% accuracy while only achieving (still impressive) ~82.8% over the full dataset. I've downloaded the dataset used in the paper and tested my models against it. The code for running the tests as well as a usable version of the dataset (the original was a big pain to download from OneDrive) are included in the repo code.
Here are our benchmark results for comparison:
Total samples:    144,088
Real images:      17,044
Synthetic images: 127,044
Average precision:  0.991
[threshold: 0.5]
  Total accuracy:     0.864
PER-CATEGORY ACCURACY:
  Real                 0.875 (17,044 samples)
  DALL-E_T2I           0.982 (16,110 samples)
  DreamStudio_T2I      0.968 (16,278 samples)
  Midjourney_T2I       0.961 (16,148 samples)
  StarryAI_T2I         0.847 (13,515 samples)
  DALL-E_IT2I          0.774 (16,665 samples)
  DreamStudio_IT2I     0.666 (16,139 samples)
  Midjourney_IT2I      0.897 (15,371 samples)
  StarryAI_IT2I        0.805 (16,818 samples)
[threshold: 0.65]
  Total accuracy:     0.827
PER-CATEGORY ACCURACY:
  Real                 0.914 (17,044 samples)
  DALL-E_T2I           0.971 (16,110 samples)
  DreamStudio_T2I      0.949 (16,278 samples)
  Midjourney_T2I       0.940 (16,148 samples)
  StarryAI_T2I         0.803 (13,515 samples)
  DALL-E_IT2I          0.698 (16,665 samples)
  DreamStudio_IT2I     0.576 (16,139 samples)
  Midjourney_IT2I      0.845 (15,371 samples)
  StarryAI_IT2I        0.743 (16,818 samples)

value: Show HN: Open-source AI image/deepfake detection that actually works

author: lschneider


value: Show HN: Scar – A programming language for easy concurrency and parallelism


value: Show HN: Type Pulse AI: Stop fighting writer's block. Start pulsing with AI


value: vitjbr

value:
Vibe coding isn’t going anywhere. So let’s make it not shit.
I like vibe coding. It saves me hours every day writing boring code.
I’m a big fan of shipping fast and getting real market feedback as soon as possible and building an MVP is all about cutting corners, BUT some corners shouldn’t be cut. I’ve seen vibe-coded apps leak data, rack up massive infra bills, or crash under the load of four (4) users.
Vibe coding is the future of development, but until LLM agents can reliably ship bulletproof code, you still need a human in the loop.
That’s why I launched VibeCheckAudit — a sanity check for your app, performed by a senior engineer.
You get a proper teardown of:
 - Security
 - Stability
 - Code quality
 - Infra choices
 - UX red flags
 - And anything else that breaks when real users touch your app
You’ll know exactly what to fix, or get a green light to launch with confidence.

value: Show HN: VibeCheckAudit – Expert Code Audit for AI-Built and No-Code Apps

author: vitjbr


value: coolandersonfan

value:
Hi HN
I built [Global Website Monitor](https://website-monitor-dbg.pages.dev/) – a free tool that checks website latency from multiple global regions (Asia, US, Europe) in real time.
Features:
-  Global region checks (GCP-based monitors)
-  Multi-hop latency tracking (ICMP + TCP + TLS)
-  Realtime charts with React + Chart.js
-  Geo map visualization of routing path
-  Free to use – no sign-up required for basic trial
Tech Stack:
- Backend: Go (Gin) + Prometheus + MongoDB + Redis
- Frontend: React + Bootstrap + Google Maps
- Infra: Docker + Terraform + GCP VMs
I built this to monitor CDN latency for my own sites, and then decided to open it up for the community. You can test your website instantly from global vantage points and see the actual path and slowest hop.
Try it here → https://website-monitor-dbg.pages.dev/
Would love any feedback or suggestions!

value: Show HN: Global Website Monitor – Free Multi-Region Latency Checker

author: coolandersonfan


value: pakileo

value:
Hi HN,
I built https://i18nify.online to automate the painful parts of internationalizing React and Next.js applications.
Features:
- Detects project type (React, Vite, or Next.js)
- Injects `useTranslation()` automatically
- Replaces hardcoded text with `t('key')` calls
- Generates translation JSON files (locales)
Why?
As a developer, I found i18n setups too manual, repetitive, and error-prone. i18nify scans your code, understands where the text is, and handles the full i18n integration online — no CLI, no manual config.
Use case: You upload your project, choose target language(s), and get a fully internationalized codebase ready to deploy.
Platform: [https://i18nify.online](https://i18nify.online)
 Demo App: [https://app.i18nify.online](https://app.i18nify.online)
  GitHub: [https://github.com/your-org/i18nify](https://github.com/i18nify/i18nify) (if public)
Would love your thoughts, feedback, or bug reports. AMA!

value: Show HN: Internationalizationify – Auto-internationalize React/Next.js projects

author: pakileo


value: samfeldman

value:
I bought the birthdays.app domain a few years ago and decided to build a simple birthday app, just text message reminders.
I had hacked together a duct-tape version for myself a couple years prior (using zapier + google sheets), and found it useful. It was a pain sifting through Facebook birthdays (90% irrelevant), and I found the text reminders simpler than a calendar.
The app has been slowly growing since 2023, and is now up to 739 paying users (mostly on the $9/yr plan, with a few paying $3/yr).
Earlier this year, I built a Google Calendar integration to automatically sync birthdays to the app. My goal is birthday reminders without the baggage a normal "social" app would have such as ads, engagement bait, etc.
I call it an app, but there's actually no app to download. Users log in via phone number + sms login code, then input birthdays manually, via text, or via Google Calendar.
At the moment, US users receive SMS messages (which are cheaper to send in the US), while other countries receive WhatsApp text reminders.
The app uses Twilio to text users (both SMS + WhatsApp) and Stripe for payments.
I'm hoping to build more features (iPhone contacts sync, easier birthdays importing) while also making video content that celebrates strangers' birthdays (such as, going to a farmers market with an "is it your birthday?" sign).
Thank you for reading, I'm open to any thoughts or ideas around the app!

value: Show HN: I built a text-based birthday reminder app

author: samfeldman


value: atharvtathe

value: Show HN: I made a Disney/Pixar style movie poster generator

author: atharvtathe


value: cwlcwlcwlingg

value: Show HN: An OSINT username search tool

author: cwlcwlcwlingg

title: Show HN: An OSINT username search tool


value: uyendo

value:
I built GoldNow, a mobile app that helps me stay updated on gold prices, commodity markets, and related financial news.
https://www.goldnow.app
Features:
- Live prices for gold, silver, oil, and other commodities
- SPDR Gold Trust buy/sell activity
- Price alerts and market news notifications
- Customizable watchlist
Would love your feedback or suggestions. Thanks!

value: Show HN: GoldNow – Track Gold Prices, SPDR Gold Trust Activity and Market News

author: uyendo


value: sudofoo

value: Show HN: Wan2 AI Video Generation

author: sudofoo

title: Show HN: Wan2 AI Video Generation


value: juliangoetze

value:
Hey HN, we're Julian and Glenn, and we're building stagewise (https://stagewise.io), a frontend coding agent that lives inside your browser on localhost and operates on local codebases.
You can spawn the agent into locally running web apps in dev mode with `npx stagewise` from the project root. The agent lets you then click on HTML Elements in your app, enter prompts like 'increase the height here' and will implement the changes in your source code.
Before stagewise, we were building a vertical SaaS for logistics from scratch and loved using prototyping tools like v0 or lovable to get to the first version. But when switching from v0/ lovable to Cursor for local development, we felt like the frontend magic was gone. So, we decided to build stagewise to bring that same magic to local development.
The first version of stagewise just forwarded a prompt with browser context to existing IDEs and agents (Cursor, Cline, ..) and went viral on X after we open sourced it. However, the APIs of existing coding agents were very limiting, so we figured that building our own agent would unlock the full potential of stagewise.
Here's how it works:
When you run `npx stagewise`, our cli proxies your running web application in dev mode and injects a toolbar containing the coding agent on top of it. Each prompt you send will be enriched with browser context and sent to our cli, which will call our backend and modify the source code of your local codebase accordingly.
Here's a demo of our agent changing the login UI of Cal.com, a popular open-source meeting scheduling app: https://www.youtube.com/watch?v=BkDcAozK9L4.
So far, we've seen great adoption from non-technical users who wanted to continue building their lovable prototype locally. We personally use the agent almost daily to make changes to our landing page and to build the UI of new features on our console (https://console.stagewise.io).
If you have an app running in dev mode, simply `cd` into the app directory and run `npx stagewise` - the agent should appear, ready to play with.
We're very excited to hear your feedback!

value: Show HN: Stagewise (YC S25) – Front end coding agent for existing codebases

author: juliangoetze


value: Show HN: Revive old faces with high‑quality AI magic


value: There isn't a 3B1B-style video explanation for every topic. But you can make your own from a single prompt with my API.

value: Show HN: API for AI Generated Educational Videos


value: kangfeibo

value: Show HN: Create high‑quality 3D assets from text or images

author: kangfeibo


value: tpae

value:
Hey HN! Dinoki is a 6MB native AI assistant with pixel pets that live on your desktop. Built for power users who want privacy, performance – and a bit of fun.
See it in action: https://www.youtube.com/watch?v=V_pv2BU0CZA
What makes it different:
- 6MB native app (SwiftUI for macOS, WPF for Windows) – starts instantly
- Zero telemetry – your API keys and data stay local
- Pixel art companions with physics-based behaviors
- Flexible AI support – OpenAI, Anthropic, OpenRouter (300+ models), or Ollama (offline)
Why pixel pets in an AI assistant? Beyond being fun, pixel art is incredibly efficient – minimal CPU usage for animations while adding personality to your workspace. After months of testing, users tell us the companions make long work sessions feel less isolating. They develop behaviors, respond to your activity, and yes, they bounce around thanks to physics-based movement.
The serious features:
- 20+ productivity tools: web research, Slack automation, screenshot OCR
- MCP (Model Context Protocol) support for custom integrations
- Agent mode for autonomous task execution
- Persistent conversation memory
- Instant startup (not Electron!)
Real use cases from our users:
- Developer running local RAG with Qwen3 via Ollama – a private knowledge base with a pixel companion
- Home lab enthusiast who set up an AI server for their family – each member has their own Dinoki instance
- Remote engineers using Agent mode to monitor Slack channels while their pixel buddy reflects their mood
- Researchers who love that their sensitive data never leaves their machine, yet they get GPT-4-level assistance
Pricing:
- Free: Full chat, one Dinoki character, bring-your-own provider
- Pro ($25 lifetime): All 4 characters, automation tools, multi-instance support
We're a two-person team that believes AI tools should be powerful, private, and enjoyable to use. The 6MB size isn't just a flex—it's proof that modern software doesn't need to be bloated.
Happy to answer any questions about implementation, how we got the size so small, or why we think personality matters in productivity tools!
https://dinoki.ai/
P.S. Something big is coming for retro pixel art fans. Current users will get it free.

value: Show HN: Dinoki – Privacy-First Desktop AI with Pixel Pets (6MB Native)

author: tpae


value: nvojacek

value: User feedback is scattered, some of the best feedback exists in channels you didn't even know about. Prequel helps founders and product people prioritize building the right thing.

value: Show HN: I'm Building Cursor for Product Management

author: nvojacek


value:
I built Orator after realizing most speech analysis tools only count filler words, missing the core elements that actually make speakers effective.
*The technical approach:* Instead of basic word counting, Orator analyzes five dimensions based on communication research:
- *Pitch:* Time & frequency-domain analysis for vocal variety detection and monotone identification
- *Pause:* Silence detection with timing analysis
- *Pace:* Real-time WPM calculation with engagement optimization
- *Power:* Volume dynamics and emphasis pattern recognition
- *Prose:* Readability scoring and linguistic complexity analysis
*Architecture:* AI-based audio processing, real-time visualization with pitch movements and power variations, pause timing charts, and comprehensive analytics dashboard. Frontend using Next.js with Typescript, React and Tailwind, backend Python Flask API and various LLM/AI services
*Why free:* Wanted to democratize access to professional-level speech coaching. No signup required, all advanced features included.
*Demo:* You can analyze famous speeches (e.g. Ellen DeGeneres, Steve Jobs) or upload your own recordings. The visual analytics are surprisingly insightful – you can see quantitatively what you’re good at and what you need to improve.
Try it: https://orator.feynman.ai/
Looking for feedback on the technical approach and whether these analytics actually help people improve. What speech analysis features would be most valuable to the HN community?

value: Show HN: Orator – AI speech analysis using the 5 Ps framework (completely free)


value: anyg

value:
How it works - Simply paste your entire message or post into the search box to get the most relevant xkcd for it. No need to search by keywords, etc.
I built this tool as a fun project to learn Retrieval Augmented Generation (RAG) but it turned out to be much more complicated than expected. Humour, in particular xkcd comics, require high levels of intelligence and also relevant knowledge. RAG doesn't actually seem perfectly suitable for it because the retrieval is done using a much simpler model than the latest LLMs.
While playing around, I found it to be decent most of the time. Sometimes, it would suggest a comic which isn't perfectly suitable but has some overlap atleast. It took quite a few experiments to find the current combination of embedding model and llm as well as the retrieval algo and related params.

value: Show HN: Find the relevant Xkcd comic for your post using RAG

author: anyg


value: ashitlerferad

value: Show HN: Just a simple Homelab upgraded to SFP+ and multigig LAN

author: ashitlerferad


value:
Hi HN,
We built BizPlanAIPro to help founders create investor-ready business plans in minutes using AI.
Why? Writing business plans is slow, expensive, and often feels like guesswork. Our tool helps with:
- Instant Executive Summary + SWOT Analysis
- Automated Financial Forecasts with Charts
- Downloadable PDF Reports
- Simple Pricing (Starts Free)
We’d love your feedback:
- Does this solve a real pain point for you?
- What would make this more useful?
Try the live demo (no login required): https://bizplanaipro.com/HN
HN discount code: HACKERNEWS10 (10% off)
Thank you for checking it out!

value: Show HN: BizPlanAIPro – Generate Investor-Ready Business Plans in Minutes


value: scosman

value:
Fun little project I built for myself. Create a YAML file for your dev-commands (lint, format, tests, etc), then expose those to coding agents via MCP.
https://github.com/scosman/hooks_mcp
Kinda like package.json scripts, but for agent runtimes, and commands are invoked via MCP.
1. Simple setup: one YAML file is all it takes to create a custom MCP server for your coding agents. Add the YAML to your repo to share with your team.
2. Tool discovery: coding agents know which dev-tools are available and the exact arguments they require. No more guessing CLI strings.
3. Improved security: limit which commands agents can run. Validate the arguments agents generate (e.g. ensure a file path is inside the project, not `~/.ssh/id_rsa`).
3. Works anywhere MCP works: Cursor, Windsurf, Cline, etc
4. Speed: using MCP unlocks parallel execution, requires fewer tokens for generating commands, and eliminates errors in commands requiring iteration.
5. And more: strip ANSI codes/control characters, .env file loading, define required secrets without checking them in, supports exit codes/stdout/stderr, etc
https://github.com/scosman/hooks_mcp

value: Show HN: Give coding agents MCP access to lint/test/format with 1 YAML file

author: scosman


value: pgt

value:
Hi HN, Petrus here from Cape Town, South Africa. I spent the better half of 2024 integrating our Clojure-based cloud provisioning platform at CloudAfrica[^1] with SpiceDB[^2], a scalable ReBAC based authorization system based on Zanzibar, Google's globally-consistent authorization system.
The problem with any external authorization system is modelling & synchronization: SpiceDB has a text-based schema DSL to define Relations & Permissions and models Relationships as 3-tuples of `[subject relation resource]`.
However, in Datomic we have attributes like `:account/owner`, `:server/account`, `:vpc/account` and `:vpc/viewers`. Figuring out which Relationships to create or delete in SpiceDB when anything changes becomes a diffing + batched sync problem, especially when you have an impedance mismatch between your data model and your permission schema.
I realized that if we modelled our AuthZ Relationships directly in Datomic, all our syncing problems would go away: you can simply tail the Datomic transactor queue and instantly create or delete Spice relationships in real-time. But once you do that, you might as well model the permission schema as well, and if you go one step further, you can implement the permission graph traversal directly in Clojure to avoid a network hop. And that is exactly what EACL is.
EACL (Enterprise Access ControL) is an embedded authorization library that lives next to your data in Datomic and avoids an external network hop. EACL is suitable for small-to-medium scale, while giving you the option to migrate to SpiceDB in future when you need more scale and consistency semantics.
EACL implements the SpiceDB gRPC API as an idiomatic Clojure protocol (`IAuthorization`), using Datomic as a backing graph store. So you can add sophisticated authorization to your Clojure project on day one and migrate to SpiceDB later.
Internally, EACL recursively traverses the permission graph using direct index-based calls (via `datomic.api/index-range`) to efficiently answer `CheckPermission`, `LookupSubjects` and `LookupResources` queries.
The goal for EACL is to provide best-in-class authorization for Clojure & Datomic applications with <10M entities. It is especially suited to Electric Clojure[^3]. EACL has been open-sourced under the AGPL, but we are likely to relicense it under a more permissive licence. EACL is used at CloudAfrica, a regional cloud host based in South Africa.
[^1]: https://cloudafrica.net
[^2]: https://authzed.com/spicedb
[^3]: https://electric.hyperfiddle.net/

value: Show HN: EACL – ReBAC Authorization in Clojure and Datomic Based on SpiceDB

author: pgt


value: frenchriera

value:
I made this out of frustration.
I want the support in my SaaS to feel like my product: fully customizable, part of the UI, and able to access my codebase so AI agents can actually do useful things.
I believe smaller, more technical teams will be solving bigger problems even faster. And support should be just as flexible and composable as the rest of the stack.
So I built Cossistant: support defined in your code, that even your AI agents (or LLM copilots like Cursor or Claude) can understand and maintain.
Curious what others here think about this approach?
Waitlist is open: https://cossistant.com
Code: https://github.com/cossistantcom/cossistant

value: Show HN: I made an open-source AI support widget built like a dev tool

author: frenchriera


value: akadeb

value:
I show how to use Pitch shifting supported by the arduino-audio-tools[1] and ElatoAI[2] library on ESP32 to get OpenAI Realtime and Gemini Live Voices to sound like cartoons like Alvin and the Chipmunks or Hulk.
[1] https://github.com/pschatzmann/arduino-audio-tools
[2] https://github.com/akdeb/ElatoAI

value: Show HN: Cartoony AI Voices on ESP32 with Pitch Shifting

author: akadeb


value: rjenkins

value:
Project Page: https://rotel.dev
Github: https://github.com/streamfold/rotel
Hi HN, Ray and Mike here! We’re building Rotel, a new high performance, resource efficient approach to OpenTelemetry collection. Rotel is open source (Apache License 2.0) and runs as a standalone process and collects telemetry from external processes or other collection agents. It consumes 75% less memory and 50% less CPU in benchmarks https://streamfold.github.io/rotel-otel-loadtests/benchmarks, so it is particularly well-suited for environments where resource optimization is paramount.
Mike and I love working on Observability solutions. We’ve built and optimized telemetry data planes for products such as Librato, Papertrail and AppOptics. As we’ve scaled high volume data processing systems over the years, we’ve often found ourselves under pressure to improve SaaS margins or the resilience of complex distributed systems. This has led us to the same question again and again: How can we do this more reliably and efficiently?
We believe telemetry collection demands high levels of efficiency, and Rotel is our first step toward addressing that need. Rotel’s Lambda extension https://github.com/streamfold/rotel-lambda-extension has already unlocked the promise of OpenTelemetry in production serverless environments, where resource constraints previously made this nearly impossible.
With Rotel we’re also rethinking DX for OpenTelemetry collection. Its lightweight footprint allows for packaging directly in runtimes like Python and Node.js, eliminating the need for additional configuration and deployment of sidecars. Rotel’s Python Processor SDK enables you to build telemetry processors right from your favorite IDE with the ease and expressiveness of Python and the performance of Rust.
Getting started with Rotel is easy using prebuilt Docker containers, just run…
`docker run -ti -p 4317-4318:4317-4318 streamfold/rotel --debug-log traces --exporter blackhole`
to start Rotel listening for OTLP traffic on ports 4317 & 4318.
Check out the Getting Started guide for more install and config instructions: https://rotel.dev/docs/setup/getting-started.
We’re super excited to share Rotel with you and would love to hear what you think!

value: Show HN: Rotel – Fast and Efficient OpenTelemetry Collection in Rust

author: rjenkins


value: danielwmayer

value: Show HN: What 3 Words for Phone Number Sharing in Phone-Free Spaces

author: danielwmayer


value: emson

value:
Hi HN — I built Elf0, a command-line tool to define and run AI agent workflows in YAML. It helps you iterate on small multi-step "agents" without scaffolding a whole codebase.
The agent patterns described in Anthropic's article was an inspiration: https://www.anthropic.com/engineering/building-effective-age...
I then used Nvidia's AgentIQ YAML spec as inspiration.
Why: I keep bumping into tasks where a single prompt isn’t enough (e.g., extracting quote data from an insurance PDF). Defining the workflow in YAML makes it easy to version prompts, parameters and logic, and to feed the whole spec back to an LLM to improve.
What it does:
- Run single- or multi-step agents from a YAML spec.
- Reference files or directories in prompts with @file / @dir.
- Improve a workflow with a built-in command.
- Use OpenAI or Anthropic APIs, or run locally via Ollama.
- Optional MCP server example (YouTube transcript analyser).
- Interactive mode for step-by-step runs.
Anyway it's been a lot of fun and really useful, let me know any ideas you might have to improve it?

value: Show HN: Elf0 – Build and run AI agent workflows in YAML (CLI)

author: emson


value: rdvnnl

value:
Hi HN,
I built a macOS-style desktop interface that runs entirely in the browser using React, Tailwind CSS, Zustand, and Framer Motion. It simulates a dock, draggable windows, and a file-like workspace – all on a clean, responsive UI.
It’s a hobby project I work on when I find time, and it’s still evolving. You can try it live here:
*Demo:* https://rdvnui.com
 *Code:* https://github.com/ridvanonal/macos-react
Would love any feedback, ideas, or crazy feature suggestions.
Thanks for checking it out!

value: Show HN: macOS-style Web UI built with React

author: rdvnnl


value: stuvinton

value: Show HN: ClipCert Verify video authenticity using traditional cryptographic sigs

author: stuvinton


value:
Powerful Tools in One Platform:
Screenshot Editor - Transform plain screenshots into eye-catching visuals with professional browser frames (macOS Safari, Chrome, Arc), beautiful gradient backgrounds, and perfect sizing for every platform.
Template Studio - Create stunning Open Graph images and social media graphics with professional templates, custom typography, logo positioning, and brand color customization.
- Before and After Template in beta for showing images in before and after state
Developers showcasing projects on GitHub/LinkedIn
Designers creating portfolio mockups for Dribbble/Behance
Content creators making engaging social media graphics
Marketers creating feature announcements and OG images
Anyone needing professional templates for social media and build in public.
Perfect Use Cases:
Social Media Content - Instagram stories, Twitter posts, LinkedIn graphics, YouTube thumbnails
Technical Documentation - API docs, tutorials, GitHub repository visuals, user guides
Presentations & Pitches - Product demos, investor decks, client presentations, feature announcements
Portfolio Showcases - Dribbble/Behance projects, personal websites, design case studies
Marketing Materials - Product launches, feature highlights, landing page graphics, email campaigns
Educational Content - Course materials, tutorial screenshots, training presentations
Business Communications - Open Graph images, blog featured images, professional mockups
App Store Screenshots - iPhone/iPad mockups, device frames, app showcases
Key Features:
Professional device & browser mockups
Open Graph templates with custom text & branding
50+ beautiful gradient backgrounds
70+ canvas presets for all social platforms
Logo upload and positioning controls
High-quality 4K exports

value: Show HN: I built one app that handles all your product screenshot needs


value: wizenheimer

value: Show HN: Open-Source AI Assistant in Your Inbox. No Apps. No Login. Just Email

author: wizenheimer


value: Whittle is a small word game I've been working on. Each phrase must be whittled down by one letter (or space) each turn. The remaining phrase must still consist of valid words. That's it! There's a daily puzzle, as well as an archive of old puzzles.<p>The idea for the game came to me in a dream (really) and I built the puzzle generator with my partner, who's also a software engineer. It's a labor of love! Any feedback or suggestions are welcome. Thanks for playing!

value: Show HN: Whittle – A shrinking word game


value: VladLunachev

value:
The basic idea: flip from [read everything → decide if useful] to [see what's useful → read selectively]. Way less mental fatigue.
This extension was built just for fun as an experiment with non-linear reading and different approaches to consuming text. But it turned out to be quite useful.
I'm curious, though - how do you all handle reading these days? What's your workflow for dealing with information overload? Do you have any systems or tricks for filtering what's actually worth your time?

value: Show HN: Chrome extension that adds topic/description notes to LinkedIn posts

author: VladLunachev


value: justanotherunit

value:
GPT-Reviewer: AI-Powered Code Review GitHub Action
I've built a GitHub Action that automatically reviews pull requests using GPT-4o or Claude, enforcing custom project rules through inline comments.
Key Features:
• Custom rule enforcement via .project-rules.md configuration
• Support for both OpenAI GPT-4o and Anthropic Claude
• Gitignore-style file filtering with .ignore files
• Inline PR comments with specific line-level feedback
• Zero-config setup beyond adding your API key, rules file and ignore file (optional)
How it works: The action fetches PR diffs, parses only added lines, and sends them to your chosen AI provider along with your project rules. The AI returns structured JSON feedback that gets posted as inline comments on the specific lines that need attention. It is a one-shot prompt.
Example project rules:
## Security
- Never hardcode API keys or secrets
- Validate all user inputs
## Code Style
- Use descriptive variable names (whatever that means)
- Mark typos as warnings
Setup is straightforward:
1. Add .project-rules.md with your coding standards
2. Create a GitHub workflow that runs on PR events
3. Add your AI provider API key to repository secrets
The action only reviews new code additions, keeping noise low while ensuring consistency across your codebase. It's particularly useful for teams wanting to automate enforcement of coding standards and security practices.
Built with Python, uses the GitHub API for PR integration and unidiff for parsing changes. The AI providers are abstracted, making it easy to switch between OpenAI and Anthropic or add new providers.
GitHub: https://github.com/vayqerlukashakkarainen/gpt-reviewer
Would love feedback from teams already using AI in their development workflows, or anything really. I personally like "one task" AI applications, which does only what it is told to do. I am really into researching AI uses at the moment.
Kinda funny note:
I generated most of this post using OpenCode, which is an CLI agent to code and vibe with. But it seems it can be used to generate great summaries of the project as well :)

value: Show HN: GPT-reviewer – Simple AI code reviewer for GH Actions

author: justanotherunit


value: CeresBroker

value: Show HN: Built a fast, no-fluff CRM built for startups who want to close

author: CeresBroker


value: barbinbrad

value: This burns a ton of tokens, but the basic idea is to create a cache in ./llm/cache and then spawn a bunch of subagents to look in the cache first, and then write to the cache if learn anything new

value: Show HN: A technique for better Claude Code results

author: barbinbrad


value: yiyingzhang

value:
We're the creators of Gensee, a platform we built to help developers quickly productionize their AI agents and workflows.
To show how Gensee works, we created a new end-to-end demo https://www.youtube.com/watch?v=AXIX9LgN4mU where we build and launch a travel planner AI application: https://demo.gensee.ai/travel-planner. The web app uses two agents: one to generate a travel plan based on user requirements built using CamelAI's multi-agent society, and another to answer follow-up questions with LLM and web search using no framework (pure Python). We've also open-sourced the travel planner app itself: https://github.com/GenseeAI/Trip-planner-demo.
Here's the process we show:
- DEPLOY: We start with the agent's source code in the GitHub repo and deploy it to Gensee directly using the repo url.
- TEST & ANALYZE: To evaluate the agent, Gensee automatically generates test cases customized to the agent. We can then inspect the full execution trace for each test run (including LLM and tool call inputs/outputs) and manually swap models/tools.
- METRICS: Next, we can instruct Gensee to automatically generate metrics (e.g., "does the generated plan include all requested cities?"). These metrics use LLM-as-a-Judge internally. There are also two objective metrics: dollar cost and execution latency.
- OPTIMIZE: We then select our desired metrics and run Gensee’s automated optimization process, which experiments with different models and tools to find the setup that maximizes quality, minimizes cost, or minimizes latency.
- LAUNCH & AUTOSCALE: Once we're happy with the optimized agent, Gensee provides a production-ready API endpoint that we can integrate directly into our web application. We can also download the Gensee-optimized source code and do more offline tuning. Once launched, the agent will be autoscaled on Gensee as requests arrive. Gensee is the only entity to pay, as Gensee internally covers all model and tool call costs.
We are trying to build the "AgentOps" tooling that we hope can be useful to all agent developers and beyond.
We would be grateful for the community's honest feedback!
You can try it here: https://platform.gensee.ai. We're providing $10 in FREE credits every month. Thanks for checking it out!

value: Show HN: Optimize and launch a travel-planning AI application in minutes

author: yiyingzhang


value: nickisyourfan

value:
I just launched a weekly newsletter called Deeb Dive — it’s a short roundup of cool tools, libraries, and projects for people who love building.
Each issue highlights 3–5 things I think deserve more attention — could be a small library, a new CLI, a beautiful UI kit, or just something fun.
If you’re working on something cool, I’d love to feature it.
No forms, no fuss — just drop a link or say hi.

value: Show HN: Deeb Dive – Feature your tool in this weekly newsletter for builders

author: nickisyourfan


value: milst

value: Show HN: Tambo – build generative UX web apps

author: milst


value:
I originally added this to my site to speed up my video editing process. Last year I started a youtube channel and for some of my longer videos it's annoying to rely on youtube or capcut to transcribe when Whisper is open source. Capcut also recently updated their T&Cs to say they own your content if you use their app, so I cancelled my subscription.
Another use-case I have is recording my claude prompts as audio, transcribing them, and then pasting them into my terminal. I mostly work on the CLI (claude, ffmpeg, whisper), but I wanted to make a browser version.
Not reinventing the wheel here, just using Huggingface/Xenova Transformers.js to run Whisper in the browser with a background worker.
You can see a demo here: https://www.youtube.com/watch?v=ICLOvAq9vKE
If you're interested in building this yourself, there's a bunch of examples on Huggingface https://huggingface.co/collections/Xenova/transformersjs-dem...

value: Show HN: I built a tool to replace capcut audio transcription


value: jakecodes

value:
My Joseph and I were fed up with the manual grind of weekly project updates, so we built 1Medium to automate them.
## The Problem: Disconnected Reporting Workflows
Weekly status summaries and leadership reports eat up hours
Meetings to review updates are hard to schedule and often redundant
No single source of truth—teams juggle spreadsheets, ad-hoc docs, or rely on hearsay
Planning, tracking, scheduling, and reporting happen in separate tools, leading to endless copy-pasting and context-switching
Our Solution: 1Medium
1Medium (because you only need “one medium” for end-to-end project management) combines:
A unified, calendar-centric planner
AI-driven high-level summaries and health-check reports
Bi-directional integrations to keep all your tools in sync
Use 1Medium as your primary project planner, or connect your existing stack. We’ll automatically aggregate and generate status updates—and can even post them back to your platforms of choice.
## Key Features & Integrations
Calendar-centric planning: visualize tasks and milestones in one place
AI-powered reporting: generate concise executive summaries and project health checks
Integrations with:
Asana
Slack
coming soon
GitHub
GitLab
Clickup
Native tools:
Task and project management
Calendar and scheduling
Email assistant (email scheduler@1medium.ai to set it up)
Slack task creation
Booking pages (e.g., 1medium.ai/jacob/30min) with pro features from Calendly and Cal.com
Dedicated meeting pages for notes and follow-ups
## Try It & Feedback
We’ve seen a huge drop in reporting overhead and a clearer view of team priorities. We’d love to hear:
Have you built similar workflows?
What challenges remain in project status reporting?
Could 1Medium solve your reporting headaches?
Thanks,
Jacob & Joseph
jacob[at]1medium.us
The 1Medium Team

value: Show HN: 1Medium – Calendar-Centric Project Planning and Status Updates

author: jakecodes


value: anaempromptu

value:
Hey HN! We're Empromptu.ai, an AI app builder that builds AI apps (RAG, models, evals all built in every app)
Demo: https://app.storylane.io/share/rtneodkf5i1l
We started Empromptu after burning through thousands of credits on AI builders and hitting the same problem: cool looking prototypes or demos that break with real users.
The issue wasn't the building process, it was accuracy. Most AI applications plateau at 60%~ reliability, which is fine for prototypes but it's unusable in production. We realized these tools aren't really "AI app builders", they're website builders that happen to use AI.
We wanted to solve the hardest problem first: making AI applications actually work reliably.
Our approach centers on what we call dynamic optimization. Instead of cramming every possible scenario into one massive prompt (which confuses LLMs), our system adapts contextually. A travel chatbot automatically knows to mention LAX for Los Angeles vs. Pearson for Toronto. This consistently delivers 90%~ accuracy versus the industry standard 60%~.
But accuracy alone wasn't enough because we also needed to solve the builder gap:
- Simple builders (Lovable, Bolt): Create static websites, not AI applications
- Complex ML tools: Require dedicated teams most startups don't have (Arize, Voxel51) - we've also heard from both technical and non-technical founders that they found these tools very complex
- What's missing: Tools that build applications where AI is embedded functionality
So we built AI agents with optimization built-in. Users just type what they want to build and our agents handle the full development pipeline: creating applications with embedded models, RAG and intelligent processing. You can deploy to your own infrastructure via Netlify, GitHub or download it directly since you can run it locally.
The result: Startups, solo hackers and enterprises can build AI apps or AI features without hiring a dedicated ML team.
Waitlist: https://empromptu.ai
We'd love feedback from the HN community — esp. if you've hit similar accuracy problems or thoughts on the technical approach.

value: Show HN: Empromptu.ai – No code, AI app builder with RAG, model, evals etc.

author: anaempromptu


value: mitchwainer

value: Show HN: We built Source to solve for full funnel attribution for B2B companies

author: mitchwainer


value: letsfancy

value: Show HN: I built a FlutterFlow app to track what I own and how often I use it

author: letsfancy


value: leyoDeLionKin

value: Show HN: LLMAdmin An Admin Panel to create and manage LLM's for non tech founder

author: leyoDeLionKin


value: Show HN: Experimental distributed AI training tool with P2P


value: deejayy

value:
Some of you may use or remember FAR (File-and-ARchive) Manager. I have no doubt it is the most productive file manager ever made. :) But I found that the theme configurator inside FAR is a bit cumbersome, so I made a web-based alternative for theming and I also extended with palette configuration (useful if you combine FAR with ConEmu - but you can configure the standard windows command line palette by hand).
You can load and save themes and palettes, browse from existing ones or adjust colors in the loaded one.
It supports the basic 16 color, ANSI 256 or even RGB.
I'm planning to add file highlight adjustment and FarColorer (syntax highlighter in editor) configuration as well later.

value: Show HN: Far Manager theme and palette configurator

author: deejayy


value: citizensinan

value:
We got tired of the authentication nightmare that comes with deploying AI-generated apps. Every time we'd generate a cool mini app with Claude/GPT, deploying it securely meant choosing between "completely open" or "spend days implementing OAuth."
The problem: No easy way exists to deploy AI-generated apps privately with proper authentication. Current solutions are complex to implement and vulnerable to tech debt, insecure code, and secret leakage.
What we built:
A deployment platform designed for the AI coding workflow. Your AI-generated app doesn't need to know about auth, SSL, or security - the platform handles it automatically.
OAuth integration (GitHub, no rolling your own crypto)
Automatic SSL (Let's Encrypt + Traefik)
JWT-based SSO with proper security headers
Centralized secret management
Container hardening (distroless images, read-only filesystems)
The AI coding workflow now:
Generate your app with LLM (focus on the actual logic)
Push to git
App is live with proper authentication and SSL
Tech stack:
Go/Fiber backend with security middleware
PostgreSQL + Redis for sessions
Preact frontend (3kb)
Traefik for reverse proxy + SSL
We can now deploy dozens of AI-generated tools without thinking about the infrastructure layer. LLM mini apps go from generation to secure deployment in minutes instead of days.
What's next:
LDAP/SAML integration (enterprise teams are asking for this)
LLM-powered deployment agent (auto-generate Dockerfile/config from codebase)
Enterprise SSO and compliance features
Better monitoring and CI/CD integration
The codebase is early but functional. We've been using it to deploy ~15 AI-generated internal apps without security headaches.
Perfect for teams that want to rapidly deploy AI-generated mini apps without compromising on security. Enterprise-ready architecture with startup simplicity.
Would love feedback on the approach - is this solving a real problem in the AI coding workflow?
https://github.com/citizenteam/citizen

value: Show HN:Secure deployment platform for AI-generated code and internal tools

author: citizensinan


value: mmargenot

value:
Tezcat is a POC implementation of a remembrance agent (https://www.bradleyrhodes.com/Papers/remembrance.html) in Obsidian. It uses text embeddings and vector similarity search (or hybrid search) to do recall of fragments of notes that you've written in the past based on what you're writing right now.
I don't like AI chat interfaces in knowledge management tools and I have been looking to implement something that would integrate better with the flow of actually writing. This operates best with Ollama on your machine, for a local-first experience, but can work with OpenAI embeddings.
Try it out and let me know what you think!

value: Show HN: Tezcat – local-first AI recall in Obsidian via a remembrance agent

author: mmargenot


value: olavur

value: An event-first workflow that eliminates the need for Kafka and CDC by storing events as the source of truth and building read models from the event stream. Interested in feedback from the community on this approach to simplifying data architecture.

value: Show HN: Event-First Workflow That Eliminates Kafka and CDC

author: olavur


value: ilrein

value:
Friends keep asking how I stay so unreasonably up to date on AI. Truth is: I doomscroll, but productively. I bounce between a bunch of sites, skim like a gremlin, and try to connect the dots.
Then I had a thought: what if I had little AI reporters do that for me?
So I built them. Four agents, each with a beat:
1) Hacker News Agent — Sniffs out top stories, Ask HN, and Show HN before they go nuclear.
2) GitHub Agent — Tracks trending repos across every language. Finds the tools you’ll pretend you discovered first.
3) Reddit Agent — Lurks in r/Ollama, r/accelerate, r/singularity, and much more subreddits. Catches the real talk from the trenches.
4) ArXiv Agent — Reads dense research so you don’t have to. Turns “theorem 3.2” into “here’s why this matters.”
Then the Editor Agent steps in.
It merges the reports, kills duplicates, spots patterns across platforms, and spins it into a narrative that actually makes sense.
Result: zero fluff, maximum signal. Every morning: hand-picked stories, with quick, smart analysis on why they matter and how they connect.
Two weeks and many coffees later: BAAM — Ilia’s Corner is alive.
A daily newsletter powered entirely by agents.

value: Show HN: My Agentic Newsletter Project

author: ilrein

title: Show HN: My Agentic Newsletter Project


value: akoculu

value: Show HN: I made a playground and editor for generative AI models

author: akoculu


value: kanodiaashu

value: I wanted to get a high level view of 10-Ks, they were intimidating to me; so I built out this map based view of them. You can clone these, and consume them with an AI agent helping you out. Curious for feedback!

value: Show HN: A new way to read company 10-Ks

author: kanodiaashu


value: Show HN: Supanotice – Branded newspage and in-app widget to show product updates


value: Hey all, I made this simple GUI tool with python to test the hardware speed in FLOPs. Feel free to try it, give feedback, or contribute

value: Show HN: Flops Benchmark GUI Tool – ResNet50 and other models support


value: infiniteregrets

value:
The experience with AI chat apps can be a bit fragile — there's no resilience to network failures, and responses aren't deterministic like traditional search. As Garry Tan put it (https://x.com/garrytan/status/1927038513108701662), "It feels like catastrophic data loss when a given response comes back and fails halfway, and then the next retry is not as good."
Vercel recently released a "resumable-stream" package (https://github.com/vercel/resumable-stream) to solve this problem using Redis as a backing store.
I felt that we could simplify the approach using s2.dev (I'm an engineer on the team), and created a fork which ended up borrowing the API but otherwise completely rewritten: https://github.com/s2-streamstore/resumable-stream
- S2 streams are cheap, so instead of optimizing to flush only when there is another reader, the stream is always created and written to.
- Unlike the typically ephemeral nature of Redis, tokens are always durable, and there are no memory constraints around number of streams or how much data is on them.
- Relies on S2’s built-in concurrency control. A unique fencing token ensures a single writer, and a sequence number is optimistically supplied to match the one expected to be assigned to the next record, to deduplicate in case of retries.
It integrates nicely with Chat SDK, and you can try this out here: https://ai-chatbot-s2.vercel.app by reloading the page during a larger response!
There are some interesting future possibilities, like building a multiplayer chat experience around shared streams.

value: Show HN: Making AI chat sessions durable to network failures

author: infiniteregrets


value: Fr-e-d

value:
After spending months working with Claude, Gemini, and others inside Cursor, I got tired of constantly fixing regressions and re-explaining my project’s logic. The AI was impressive — but blind without proper context.
I didn’t want more prompt tricks. I needed structure. So I built a framework that gives LLMs:
– codified project rules & constraints
– a clear, step-by-step development protocol
– a memory system that evolves over time
– human-in-the-loop checkpoints to reduce failure
It completely changed how I use AI in real software projects. I’m sharing it open source in case others are trying to get more from their AI dev workflows too.
Happy to answer questions or go into technical details.
→ Link above, feedback welcome!

value: Show HN: AI Dev Assistant Framework – Add structure, rules and memory to LLM

author: Fr-e-d


value: oatsandsugar

value: Show HN: A benchmark + latency sim for LLM db queries: ClickHouse / Postgres

author: oatsandsugar


value: mcfitzgerald

value: Show HN: Virtual Ontologies with Claude Code

author: mcfitzgerald


value: qinggeng

value:
I built PinpoinTod ays to make it easier to keep up with LinkedIn’s daily Pinpoint puzzle.
I enjoy playing the game, but I noticed there’s no official archive or easy way to check previous answers once the day is over.
What it does:
 • Updates every day with the latest Pinpoint puzzle’s answer & clues
 • Lets you browse all historical puzzles in one place
 • Lightweight, mobile-friendly, and loads fast
 • Simple navigation between previous/next puzzles
It’s a small side project I put together in my spare time. Next, I’m planning to add search, tagging, and maybe some fun stats (like most common clue words).
Would love feedback — especially from word game fans or anyone who’s tried similar puzzle archives.

value: Show HN: PinpoinTodays – Daily Answers and History for LinkedIn's Pinpoint Game

author: qinggeng


value: itzoen

value: Show HN: I built a browser extension to add comment threads on any website

author: itzoen


value: Cod-e-Codes

value:
Demo: https://www.cod-e-codes.com
- Single standalone HTML file around 13KB
- Dynamic fetching of GitHub repo info with caching and fallback
- Responsive terminal-inspired UI, works on desktop and mobile
- Clean, semantic HTML5 and accessible markup
- Lighthouse score 100/100 for performance, accessibility, best practices, SEO
- Easy to customize personal info and projects in one file
- Deploy anywhere static hosting is supported (GitHub Pages, Netlify, Vercel, etc.)

value: Show HN: Minimal terminal-style portfolio template (~13KB) with GitHub API data

author: Cod-e-Codes


value: cjohnsonpr

value:
We just released Metis Agent v0.6.1, a major update that brings full local model support—just as OpenAI dropped their first open-weight models on Hugging Face (GPT OSS-117B and 21B).
With this release, you can run GPT OSS locally—no API keys, no per-token costs, no external dependencies.
What’s new in v0.6.1:
Native HuggingFace integration (including GPT OSS)
Automatic hardware detection (CUDA, MPS, CPU)
4-bit and 8-bit quantization support
36+ production-ready tools for building AI agents
One command to switch from API-based to local models
This lets developers and startups:
Build with OpenAI-quality models without usage limits
Deploy behind firewalls with full data sovereignty
Experiment and scale on local hardware.
Install Command: pip install metis-agent

value: Show HN: Metis Agent v0.6.1 – Run OpenAI's GPT OSS Locally with No API Keys

author: cjohnsonpr


value: Show HN: Twitter Viewer – View & Download Tweets and Media Without an Account


value: mmajzoobi

value:
I was inspired by two video I had recently watched to DIY a NAS system.
The first one was Jeff Geerling's video where he sets up a NAS with Radxa Penta SATA HAT & Raspberry Pi 5. The second one is from Micheal Klements in which he makes a nice enclosure for the same setup.
I wanted to push the design a bit further and give some extra capabilities.
My tentative plan is to:
- Add some NAS specific features to the GUI to
monitor storage, navigate file system with the GUI,
- open image files  & show them on the display,
delete files,
- copy/move files around  (e.g. from USB drive)
Hardware specific feature to include:
- Build an aluminum enclosure for this eventually,
- Add USB-PD power,
- Internal UPS (Uninterruptible Power Supply), which could potentially power another Pi with a USB Power out option,
- Internal 3D printed structure to support the drive and battery pack from sudden movements
This is a work in progress and I have managed to work on the enclosure design and have made the design available here:
https://github.com/ubopod/ubo-mechanical/tree/main/nas-enclo...
The base tray design is also available below:
https://github.com/ubopod/ubo-mechanical/tree/main/bottom_co...
The PCBs are harder to DIY. You need to purchase the Penta SATA HAT and the sideboard. The sideboard is my own open source design and I have a small number available on my indie shop.
Check out the reddit post regarding the sideboard here:
https://www.reddit.com/r/raspberry_pi/comments/1mcn3b8/conne...
I recorded a short video that includes some more details/specifics regarding this design that you can watch below:
https://www.youtube.com/watch?v=0D0EMTMDGSY

value: Show HN: Open-source DIY NAS with GUI and aluminum enclosure

author: mmajzoobi


value: melvynxdev

value:
Hey HN! I built SaveIt.now after drowning in 1,211 bookmarks I could never find.
So I created a bookmark manager without folders or complex organization - just let the tool organize everything for you and use AI to search!
Try it free, just need to sign in
P.S. iOS app is coming :)

value: Show HN: SaveIt.now – Find any bookmark in seconds using natural language search

author: melvynxdev


value: simonakis

value:
Hi HN,
I made FactBomb, a minimalist daily trivia game.
Currently, it has 2 daily modes:
- A casual mode with 15 questions identical for all users for the day, so you can compete asynchronously against your friends.
- A competitive mode (also 15 questions in total) where strategy, luck, and knowledge all play a role in getting a high score and adding your name to the daily leaderboard.
Both pull from a pool of over 5000 questions across 17 categories.
You can play instantly - no sign-up or login required.
I had no coding experience prior to that. I built Factbomb using AI - it does a surprisingly good job at teaching coding and helping with code. My budget was 24 USD for a ChatGPT subscription, 6 USD for some API tokens, and 12 USD for the domain.
The question database is also created using AI, but with a lot of editing, deduping, and manual rewriting.
I wanted a no-distraction quiz experience with a daily challenge mechanic. It's built using React.js. It tracks your score and streak locally and has a leaderboard (simple Firebase) for competitive mode. I have several ideas for the future, but I want to see how the game fares at the moment. It's already a complete product, but in no way finished.
Would love feedback, bug reports, or trivia lovers who want to submit new questions!
https://factbomb.com
Thanks!

value: Show HN: FactBomb – A fast daily trivia game with zero friction

author: simonakis


value: wainguo

value:
What is it?
I built WebsiteScreenshot.online to let anyone capture full‑page or viewport screenshots of websites directly from a browser—no signup, no software installation.
Supports high resolution, PDF export, device‑simulated viewports, ad/cookie/GDPR‑popup blocking, and is 100% free
Why I built it
As a developer, I usually take screenshots via dev‑tools, extensions, or external apps.
But for many users, entering a URL and clicking a button is easier and faster—especially for non‑technical folks or when automation isn’t practical.
Wanted something simple, web‑based, and shareable.
Features at a glance
Full‑page or viewport-only screenshots (up to ~20,000px height)
Choose screen resolution (desktop, tablet, mobile)
Block ads, cookies, and GDPR banners for cleaner captures
Export to PNG, JPEG or PDF
Responsive, fast, and no watermark, no login
A bonus I got from this little side project
This little side project turned into something much more valuable: I now have a reusable boilerplate for multilingual, SEO-ready websites.
All the annoying “support” parts of building a site? Done.
Now I can launch new products and just focus on the core functionality — UI, features, and content — without worrying about the boring setup again.
What I’m hoping to get from the HN community
Feedback on UI/UX, flow, and capabilities
Ideas for missing features or improvements
Suggestions for optimizing SEO & performance
Thoughts on future direction—API access? Bulk processing? Widgets?

value: Show HN: I built a no-login website screenshot tool for my non-tech friends

author: wainguo


value: kianworkk

value:
Hi HN,
I made a fun little app:
 givemeagirlfriend.com
 givemeaboyfriend.com
Upload your selfie, and it generates a realistic-looking couple photo with an AI partner — just for fun.
Built over a weekend with Next.js + custom image prompts.
Curious what you think!

value: Show HN: GiveMe AI – Upload a selfie, get a boyfriend/girlfriend photo

author: kianworkk


value: divamgupta

value:
Kitten TTS is an open-source series of tiny and expressive text-to-speech models for on-device applications. We are excited to launch a preview of our smallest model, which is less than 25 MB. This model has 15M parameters.
This release supports English text-to-speech applications in eight voices: four male and four female. The model is quantized to int8 + fp16, and it uses onnx for runtime. The model is designed to run literally anywhere eg.  raspberry pi, low-end smartphones, wearables, browsers etc. No GPU required!
We're releasing this to give early users a sense of the latency and voices that will be available in our next release (hopefully next week). We'd love your feedback! Just FYI, this model is an early checkpoint trained on less than 10% of our total data.
We started working on this because existing expressive OSS models require big GPUs to run them on-device and the cloud alternatives are too expensive for high frequency use. We think there's a need for frontier open-source models that are tiny enough to run on edge devices!

value: Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model

author: divamgupta


value:
I built a simple web app that records your voice, converts it to text, cleans it up with AI, and saves to Notion automatically.
The motivation was personal - I record tons of voice memos but rarely transcribe them because raw speech-to-text is messy and editing takes forever. This automates the cleanup step.
How it works:<p>Browser-based voice recording (Web Speech API)
Speech-to-text conversion
AI pass to fix grammar/structure/clarity
Manual editing before saving
Saves to both Notion workspace and local DB
The AI rewriting step is key - it transforms rambling speech patterns into coherent notes. For example, "uh so like the main issue is we need to um figure out the database schema and also maybe look at caching" becomes "Main issue: need to design database schema and evaluate caching options."
Currently handles basic text only, but planning formatted output (bullets, headings, etc.) next.
Curious what HN thinks - useful tool or over-engineering a simple problem?

value: Show HN: Voice-to-Notes with AI cleanup and Notion sync


value: Show HN: I built a simple, free sit/stand timer to fix my bad desk habits


value: pekingzcc

value: Create stunning anime feet images in various styles and even animate them with our cutting-edge AI technology.

value: Show HN: Generate Perfect Anime Feet with AI

author: pekingzcc


value: codachris

value:
Hi HN!
I built Arwayda to solve a frustrating problem I kept seeing especially among product managers - important business documents (value props, product specs, strategy docs) buried in walls of text that nobody actually reads.
This tool analyzes uploaded documents, extracts key information, and automatically generates clean visual representations that can be used in documentation. Currently focused on value proposition visualizations with plans to expand to competitive analysis, roadmaps, etc.
Tech stack: Python/FastAPI backend, spaCy for document processing, custom visualization engine
Current status: Beta, looking for feedback on accuracy and which visual types to tackle next
Link: https://arwayda.replit.app/
Would love to hear thoughts on the approach and what other business document types would be most valuable to visualize!

value: Show HN: Arwayda – Transform text documents into professional visuals

author: codachris


value: MotiBanana

value:
I created a website that is updated with the top daily, weekly and monthly posts from r/MovieSuggestions
I get the top posts, clean up the title to be used as a "category" in each page, get the top comments for each post and then use TMDB to fetch metadata about those movies.
The website is just some vibe-coded slop, but it works :) It's just a free hobby project so I'm not selling or collecting anything.
Feel free to check it out and provide feedback.

value: Show HN: I built a site that scrapes Reddit to recommend popular movies daily

author: MotiBanana


value: fafawlf

value: Show HN: Production-ready prompt" guide based on 10000 prompt iterations

author: fafawlf


value: limyishengbrian

value:
I built this because I wanted workout, calories, nutritional tracking and scheduling all in one place!
My hope is that I'll be able to wrangle all these ideas together to build the perfect system that will help with your fitness levels and make workouts more fun!
It's a fun app I use daily, any feedback and requests are welcomed !

value: Show HN: Swizz – A Fitness System

author: limyishengbrian

title: Show HN: Swizz – A Fitness System