value:
Slack makes it really hard to clean up old messages. Even if you’re an admin, there’s no built-in way to bulk delete channels, DMs or general history.
I built /clean for Slack, a Chrome extension that runs entirely in your browser and lets you bulk delete messages without OAuth or external servers.
How it works:
• Uses your existing Slack web session (no tokens to paste, no servers in the middle)
• Calls Slack’s API endpoints directly from your browser
• Respects rate limits (safe for large jobs, just takes time)
• Admins/owners can delete all messages, non-admins can delete only their own
Features:
• Delete across channels, DMs, and group chats
• Filter by date, user, or skip pinned/starred messages
• Progress tracker so you can see it working
• Everything happens locally — nothing leaves your browser
Why I built it:
I had the same pain many teams do: Slack workspaces full of old clutter, but no practical way to wipe things clean without scripts, legacy tokens or paying for tools that don’t work.
Chrome Web Store link: https://chromewebstore.google.com/detail/clean-for-slack/efn...
I’d love feedback on the approach. Do you think browser-only extensions like this (no servers, no OAuth) are the right way to go for these kinds of tools?

title: Show HN: Clean for Slack – bulk delete Slack messages directly from the browser


value: Jasperio

value:
*The Problem:*
A $200 jacket worn twice = $100 per wear. A $50 t-shirt worn weekly = $2.50 per wear. Most wardrobe apps focus on outfit planning, but none track the actual cost of what you wear.
*The Solution:*
Digital Wardrobe lets you:
- Upload photos of your clothes
- Track how often you wear each item
- Calculate cost-per-wear for every piece
- Get data-driven insights for smarter buying decisions
*Tech Stack:*
- Next.js + TypeScript
- Supabase for auth & storage
- Tailwind CSS + shadcn/ui
- Deployed on Vercel
*Why I Built This:*
I wanted a simple way to make fashion choices based on data rather than impulse. Now I can see what’s truly worth keeping and plan outfits smarter.
MVP built in 2 days. Looking for feedback on:
- UX/UI improvements
- Additional metrics to track
- Feature ideas for future releases
Try it out and let me know what you think: https://digital-wardrobe-ivory.vercel.app/

value: Show HN: Digital Wardrobe – Track your daily outfit cost

author: Jasperio


value: lemoing

value:
Hey folks!
A bit of background: I'm a software engineer by trade, but I'm currently on sabbatical doing a year-long working holiday in Australia. I love riding bikes but only had the most beginner-level knowledge of them before I found a job at a bike shop. This was a fun personal project to try to capture some of what I've learned so far, targeted at fellow beginners. It's going to be incomplete/lacking if you already have some bike knowledge, but I hope you all enjoyed it all the same.
Please keep the feedback coming; it's late in Australia, but I want to make sure the bike info is at least accurate, if not comprehensive!

value: Show HN: Bicyclopedia

author: lemoing

title: Show HN: Bicyclopedia


value: Show HN: CasCache – multi-generational cache with optimistic concurrency control


value: roryclear

value:
This runs YOLOv8 + bytetrack with Tinygrad detections (depending on user config) are saved and can be sent to the companion iOS app along with a notification, all video processing is done locally, all footage is encrypted before leaving your computer, and the sending notifications + videos part is optional.
This uses tinygrad, so it runs well on my apple silicon macs and should be able to run on a lot of hardware (or will be able to when I remove other deps).

value: Show HN: Clearcam – Add AI object detection to your IP CCTV cameras

author: roryclear


value: touseefliaqat

value:
I wanted to use AI inside Slack at my company and for my robotics club, but adding AI bots and configuring them turned into a whole project. They often spammed channels or failed to respond intelligently.
Slack didn’t have AI at the time, and what they’ve since launched feels underwhelming.
So for the past two months I’ve been building Basecase, an AI native workspace where agents join team chats, remember context, and turn discussions into action.
No need to @ the agent. The agent will know when to respond. You can toggle that setting.
Ask the agent to schedule posts on linkedin
Multiple agents could be added who collab with each other (in progress)
Upload documents for context
There is a lot in my roadmap to make this a command center for all actions a team needs to take.
I used Pipedream for integrations, ProseMirror for builtin document collaboration, OpenAI for LLMs, and Convex.cloud for the backend.
I’d love feedback from the HN community.

value: Show HN: I wanted AI in Slack, ended up making Basecase (AI agents in chat)

author: touseefliaqat


value: daitangio

value:
Hi HN!
I have rewritten a tiny tool I used to manage my home lab of docker servers.
Misterio is a very thin python script on top on docker compose. It leverage docker client-server architecture to provide you a set of "stacks" of roles you can apply to one or more hosts.
It use a small folder structure which loosly resembles Ansilbe/Saltstack.
It works great for stateless services.
It do not aim to be as powerful as k8s, but on my home lab it was a very good balance between resource usage and advantages.
Give it a spin and let me know what do you think!
Originally written in bash, I was able to rewrite it in python using jus the click library and keep it very simple:
https://pypi.org/project/misterio/0.1.1/

value: Show HN: Misterio the Docker-compose stateless alternative to Ansible

author: daitangio


value: savalione

value:
Hi HN,
I'm Savelii, homelab enthusiast and open source software supporter.
I've built a command-line tool written in C++ for performing fast, multi-threaded image classification using YOLO models.
It uses the ONNX Runtime as its inference backend.
For more than 10 years, I've been hoarding different assets on my servers: family photos, project showcases, scientific results, etc.
Recently, I needed to find photos containing a specific object but didn't want to manually look through every photo via SAMBA.
So I decided to automatically classify every photo and then just sort the results.
Even though there are many great Python tools for this, I wanted something lightweight with minimal dependencies that I could easily script and integrate directly into shell commands.
My goal was to create a tool that felt like a native part of a Unix-style workflow, where you can easily do things like `find . | yolo-cls ... | grep -e "dragonfly"`.
Features: 1. Simplicity and performance - written in C++, it can be bundled as a single executable file and is designed to do one thing well. 2. CLI and Unix philosophy - it requires no GUI and accepts file paths from arguments or from `stdin`, making it highly composable with other tools like `find`, `grep`, and `ls`. 3. Cross-platform - thanks to the ONNX Runtime, the tool can be used on Linux (x64, aarch64) and Windows.
The project is open source (GNU GPL v3.0).
I welcome all feedback and collaboration from the community.
The source code, build instructions, and pre-compiled binaries are available on GitHub: https://github.com/SavaLione/yolo-cls
Thanks for taking a look!

value: Show HN: yolo-cls – C++ batch image classification CLI with ONNX Runtime

author: savalione


value: kuberwastaken

value:
you enter any URL after the website and AI generates a fresh page about it if someone else hasn't generated it already.
If it's a new page - you can put in your x @ and it'll show you generated it! or you can choose to be anonymous
there's a leaderboard of most visited sites at https://www.thiswebsiteisnot.online/stats

value: Show HN: I Made a Website Where Every Possible URL Exists (With AI)

author: kuberwastaken


value: maymoonty

value: Show HN: Simple WiFi QR Code Generator – Share WiFi Without Typing Passwords

author: maymoonty


value: Show HN: Dollar_cast, a C++ Convenience Macro


value:
Hi HN,
I've been working on a small tool to make link building less painful. It's a Chrome extension called BacklinkHelper.
It does a few things:
1.Detects backlink submission forms automatically;
2.Autofills site information with one click;
3.Tracks submitted backlinks and checks if they're still live;
4.Website management and backlink management in one place;
5.Lets you manage sites by groups and export anchor text suggestions;
The idea came from my own frustration: submitting backlinks felt repetitive and error-prone, and I wanted something that saves time while keeping things organized.
I know link building isn't everyone's favorite part of SEO, but I’m curious what you think — especially if you’ve tried automating parts of the process before.
Would love feedback on:
1.What features would make this more useful for you?
2.Any pain points in backlink building that I might be missing?
3.Concerns about automation or how you’d want control over it
If you'd like to try it out:
Website: https://backlinkhelper.com
Chrome Web Store: https://chromewebstore.google.com/detail/backlinkhelper-%E2%...
Thanks!

value: Show HN: BacklinkHelper – Chrome Extension to Automate Link Building


value: lexokoh

value: Show HN: Agent Key – A permissions broker for AI Agents

author: lexokoh


value: Show HN: Email Extractor – lightweight URL shortener and email extractor


value: ykumards

value: Show HN: Daily podcast of HuggingFace's Top voted papers

author: ykumards


value: azzen

value: Show HN: Sopree – Preview social assets with pixel-perfect accuracy

author: azzen


value: martinlev

value: Show HN: Kbindake – turn your Makefile into a global hotkey manager

author: martinlev


value: starboat

value: Create original and royalty-free songs with DeepSong.ai now! - a free online AI-powered platform for fast, high-quality song & music generator.

value: Show HN: AI Music and Song Generator Free Online – Deepsong.ai

author: starboat


value:
I built a small tool that lets you transform any photo into realistic pencil drawings using AI — no Photoshop skills required.
The idea came from seeing how many people love hand-drawn portraits but don’t have the time (or budget) to commission an artist. With this, you can upload a photo, type a simple prompt, and get back a graphite-style pencil sketch in seconds.
How it works:
Pick a clear photo (face, pet, or object).
Enter a prompt like: “Create a realistic pencil sketch of this in traditional graphite style.”
The AI generates a pencil drawing with shading and detail that looks hand-drawn.
You can experiment with different styles (softer shading, cross-hatching, high-contrast, etc.) to get unique results.
Try it here: https://pencil-me-ai-guide.vercel.app

value: Show HN: Turn your photos into pencil art – in just a few prompts


value: garymiklos

value: I built this macOS CLI tool because I was constantly chatting with AI tools (Claude Code, Cursor, etc.) and got tired of typing long instructions by hand. I just wanted to speak my thoughts quickly and have them appear instantly in the input box. No copy-paste, no window switching. Free and open source.

value: Show HN: Voice Typing from Your Terminal

author: garymiklos


value: vchimishuk

value:
I was surprised to find that there isn’t a Lode Runner game implementation I can just install and play on my PC, so I decided to create my own.<p>P. S.
Tested it only on BSD and GNU/Linux.

value: Show HN: Classic Lode Runner native game

author: vchimishuk


value:
Hi HN, I’ve been working on *AsyncFlow*, an open-source simulator for async/distributed backends built on top of SimPy.
The idea is simple: instead of pushing code straight to prod and hoping p95/p99 latency and throughput hold, you can model your topology, generate workloads, and run scenarios offline.
Define topology: for example client → load balancer → servers → edges in YAML or Python
 Generate stochastic traffic (Poisson arrivals, exponential service times)
 Run the simulation and collect metrics
Metrics out of the box:
- Latency distribution (p50, p95, p99, min/max)
- Throughput (per server and system-wide)
- Queue lengths / ready queues
- RAM in use
The idea is not to replace production monitoring, but to give engineers a “what-if” playground before deployment:
• What if latency on a link spikes for 30s?
• What if I add/remove a server behind the LB?
• How does p99 shift if service times degrade?
It’s still early-stage, but I’d love feedback on whether this approach makes sense for pre-production capacity planning and what scenarios would be most useful to support.
Repo in the first comment!

value: Show HN: AsyncFlow – stop guessing p95 latency, simulate your system before prod


value:
Mix is an open-source, local agent for multimodal claude code. Claude code users will feel at home.<p>- Uses ffmpeg and local apps like blender instead of clunky cloud based editors
- All project data is stored plain text and native media files - absolutely no lock-in.
- The backend is an HTTP server, meaning that the frontend is just one of possible clients. -  - Our SDK with stdio interface (similar to claude code SDK) is launching soon.

value: Show HN: I built Mix – an opensource, local agent for multimodal tasks


value: zachperkel

value: I built this to solve a problem I faced every day at work. I needed a labelled transcript of who said what (including their actual name) for in person meetings, and existing tools would only divide up when different people spoke. This app just requires you to label the speaker once (maybe twice if it’s a poor quality recording) and learns more over time. Then it will automatically label them in all your recordings!<p>Also made a RAG AI search agent that can dig up anything from your recordings and summarize for you. Try it out and let me know what you think! Looking for feedback.

value: Show HN: VoNote – AI Conversation Recorder for iOS

author: zachperkel


value: vgr-land

value:
A few weeks ago a friend sent me grug-brain XSLT (1) which inspired me to redo my personal blog in XSLT.
Rather than just build my own blog on it, I wrote it up for others to use and I've published it on GitHub https://github.com/vgr-land/vgr-xslt-blog-framework (2)
Since others have XSLT on the mind, now seems just as good of a time as any to share it with the world. Evidlo@ did a fine job explaining the "how" xslt works (3)
The short version on how to publish using this framework is:
1. Create a new post in HTML wrapped in the XML headers and footers the framework expects.
2. Tag the post so that its unique and the framework can find it on build
3. Add the post to the posts.xml file
And that's it. No build system to update menus, no RSS file to update (posts.xml is the rss file). As a reusable framework, there are likely bugs lurking in CSS, but otherwise I'm finding it perfectly usable for my needs.
Finally, it'd be a shame if XSLT is removed from the HTML spec (4), I've found it quite eloquent in its simplicity.
(1) https://news.ycombinator.com/item?id=44393817
(2) https://github.com/vgr-land/vgr-xslt-blog-framework
(3) https://news.ycombinator.com/item?id=44988271
(4) https://news.ycombinator.com/item?id=44952185
(Aside - First time caller long time listener to hn, thanks!)

value: Show HN: I Built a XSLT Blog Framework

author: vgr-land

title: Show HN: I Built a XSLT Blog Framework


value: matt-npl-public

value: Show HN: SocialRails

author: matt-npl-public

title: Show HN: SocialRails


value: genshii

value: Hey all, I just released v2.0.0 of FilterQL, a query language and TypeScript library. This version adds support for Operations, which allow you to transform the data after filtering.<p>If you think this would be useful in a project you're working on, give it a try and let me know what you think!

value: Show HN: FilterQL – A tiny query language for filtering structured data

author: genshii


value: anjneymidha

value: A Flux Kontext + Mistral experiment. Upload an image, and let the AIs do the rest of the work.

value: Show HN: Komposer, AI image editor where the LLM writes the prompts

author: anjneymidha


value: sylwekkominek

value:
Hi,
I’ve developed an open-source app for practicing basic skills in digital signal processing and computer graphics using OpenGL. It’s written mainly in C++ for data processing and visualization, with Python used for data input and configuration. This makes it easier to run experiments or adjust settings without recompiling the code, lowering the entry barrier for users unfamiliar with C++.
By default, the app captures audio from a microphone in real-time and displays its spectrum on the screen. It’s highly customizable — you can change the number of bars, colors, and the overall color theme. The app runs on both Raspberry Pi and standard Ubuntu desktops.
In my Raspberry Pi setup, I use a HiFiBerry DAC+ DSP to analyze music in real-time. The signal comes via optical input (TOSLINK) from a CD player, but you can also connect a microphone for live audio visualization.
I’ve written instructions and a tutorial to help you get started — feel free to check it out and give it a try!
Demo video (Ubuntu):
https://www.youtube.com/watch?v=Sjx05eXpgq4
Demo video (raspberry pi  with hifiberry dac+dsp): https://www.youtube.com/watch?v=QA2DYmdZ_Gw
Simplified spec: https://sylwekkominek.github.io/SpectrumAnalyzer/
Hope someone finds it useful or fun to play with!

value: Show HN: Configurable Open Source Audio Spectrum Analyzer

author: sylwekkominek


value: pjcodes

value:
Hi again, HN.
Three weeks ago, I showcased my impulse control PWA, "Nope It," here on HN. The discussion and feedback I received were incredible, and I'm hugely grateful to this community for it.
The single most valuable piece of feedback I got was about friction. Many of you rightly pointed out that in that critical 5 second window on a shopping page, the mental energy required to open a separate app is often too high. The impulse wins by default.
You were right. So, I spent the last couple of weeks building the solution.
Today, I’m launching Nope It for Chrome.
It's a lightweight browser extension that uses JavaScript and DOM manipulation to inject a "psychological speed bump" directly onto product pages (I'm starting with Amazon, as it's the biggest culprit for me).
The core of the extension is the real time "Work Hours Psychology" engine. It shows you that a $200 gadget doesn't just cost money, it costs you a full day of your life. When you see that, you can log the impulse with a single click without ever leaving the page. It then syncs everything back to the core PWA.
I'm back here because your initial feedback is what created this. My main question for the HN community is, Does this frictionless, point of sale approach feel like the right solution to the problem you helped me identify? I’d love your thoughts on the UX and the overall strategy.
You can grab the new extension from the Chrome Web Store here:
https://chromewebstore.google.com/detail/imamiekokcjioidbpbp...
The main PWA is still here:
https://www.nopeit.app
Thanks for helping me build this. I’ll be in the comments all day.

value: Show HN: Amazon has a 'Buy Now' button, so I built a 'Think Now' button

author: pjcodes


value:
Hi HN,
I’m a founder/developer who spends way too much time on YouTube lectures, tutorials, and conference talks. Most of the time, I just need a few key insights — but I end up watching hours of video to get them.
I built InfoCaptor AI
 to scratch my own itch. It’s a free Chrome extension that:
Transcribes(unlimited) and summarizes(limited) any YouTube video in seconds
Extracts key entities, tags, and categories
Builds word clouds and knowledge graphs so you can see connections between ideas
Lets you save transcripts and summaries into a personal knowledge base
The idea is to make YouTube as scannable and searchable as text — turning it from a time sink into a “second brain” for research.
Why I built it:
As someone who dives into multiple subjects, I was frustrated that my notes from videos were scattered and inconsistent. I wanted a way to see the key concepts, link them across videos, and revisit them quickly.
How it works:
Install the Chrome extension → Open any YouTube video
One click → Transcript + AI summary + entity extraction
It automatically saves to local storage and into the cloud → Organize by channels, tags, or categories
Visualize it → Dashboards, word clouds, and knowledge graphs
Demo:
 InfoCaptor AI Chrome Extension
https://chromewebstore.google.com/detail/youtube-transcript-...
I’d love your feedback.
Any features that would make this more useful in academic or professional research?
Thanks for checking it out — and if you try it, I’d be grateful for your honest thoughts and criticism.
— Nilesh (creator of InfoCaptor AI)

value: Show HN: InfoCaptor AI – Summarize YouTube Videos into Knowledge Graph


value: jaeheonshim

value: Spotify has 7 features for each of their music tracks (acousticness, danceability, energy, instrumentalness, liveness, speechiness, valence) which describe the perceptual/emotional content of the song. I wanted to tag my own offline music library with these features so that I could sort my songs into playlists for different occasions (working out, driving, etc.), but unfortunately Spotify doesn't share how they calculate these features. So, I trained my own lightweight neural network to predict these features!

value: Show HN: A lightweight ML model to predict music emotion - energy, valence, etc.

author: jaeheonshim


value: ubunturbo

value:
*Show HN: I tried coding theological concepts – accidentally built AI accountability*
GitHub: https://github.com/ubunturbo/srta-ai-accountability
Working demo: https://gist.github.com/ubunturbo/0b6f7f5aa9fe1feb00359f6371...
*The Experiment:*
Started as a thought experiment: "What if I tried to code theological structures like the Trinity to see if AI could reflect the 'image of God' in humans?" As a non-programmer using AI tools, I attempted to translate concepts like perichoresis (mutual indwelling) into Python.
*Unexpected Result:*
Instead of digital theology, I ended up with something that looks like an AI accountability framework.
*What SRTA Does:*
- *Technical layer*: Formal causation analysis with O(n log n) complexity
- *Accountability layer*: Maps decisions back to design principles and responsible stakeholders
- *Compliance layer*: 94% EU AI Act coverage vs <30% for traditional methods
*Key Innovation:*
Instead of just "credit score had -0.73 weight," you get: "Credit score weighted by Risk Management Team on [date] per Equal Credit Opportunity Act Section 4, reviewed by Legal on [date], cryptographically verified."
*Unexpected Discovery:*
Started as a philosophical experiment in coding theological principles. Ended up solving a real regulatory problem. Sometimes the best technical solutions come from non-technical inspiration.
*Current Status:*
- Core architecture: Complete
- Benchmarking: Validated across 5 domains (financial, medical, etc.)
- Production ready: 312ms explanation generation
- Academic paper: Under review at IEEE Transactions on AI
*Technical Details:*
The system implements "perichoretic synthesis" - layers that mutually indwell rather than simple stacking. This creates systematic coherence impossible with traditional explainability approaches.
Three integrated layers:
1. *Intent Layer*: Design rationale + stakeholder mapping
2. *Generation Layer*: Constrained AI processing + principle checking
3. *Evaluation Layer*: Accountability assessment + audit trails
*Why This Matters Now:*
- EU AI Act enforcement begins 2025
- FDA tightening AI/ML device requirements
- Financial regulators demanding algorithmic accountability
- Healthcare systems need design rationale transparency
*Looking for:*
- Feedback from HN's technical community
- Use cases we haven't considered
- Collaboration with regulatory/compliance folks
- Real-world deployment partners
*Demo walkthrough:*
The gist shows a medical AI making diagnosis decisions with full theological accountability - tracks everything from stewardship concerns to justice implications. Determines when human oversight is required based on ethical analysis.
Built by a non-programmer using AI tools, which raised interesting questions about who should be designing AI governance systems. Turns out domain knowledge (ethics, theology, regulation) might matter more than coding ability for this particular problem.
What do you think? Is there a market for accountability-first AI architecture?

value: Show HN: I tried coding theology – accidentally built AI accountability

author: ubunturbo


value: tonicstark

value: Hey everyone, I’m an NBA fan and Python dev, and I recently built DeepShot — a machine learning model that predicts NBA game outcomes with about 71% accuracy based on historical stats and rolling performance metrics (EWMA). It features: Real NBA data from Basketball Reference Exponentially Weighted Moving Averages to track momentum Interactive NiceGUI interface with team comparison and predictions Full Python stack and open-source (MIT license) Here’s the GitHub repo: https://github.com/saccofrancesco/deepshot And if you like it, here’s my Buy Me a Coffee: buymeacoffee.com/saccofrancesco Would love any feedback — especially from folks who’ve built sports models or worked on real-time stat tools. Also open to ideas on where to take this next (player-level modeling? betting advice dashboard?).

value: Show HN: DeepShot – an open-source NBA predictor with ML, EWMA, and live UI

author: tonicstark


value: ggerritsen

value:
What if the entire internet played a single chess game together? I built MMO Chess as a fun experiment in crowdsourced gaming – when you visit the site, you're randomly assigned to play as either White or Black in one ongoing global game that everyone shares.
Built this with LLMs as an experiment. Curious to see what happens when HN gets their hands on it!

value: Show HN: MMO Chess – One Global Chess Game for the Internet

author: ggerritsen


value: tabarnacle

value: Hi HN, each spread on Tarotmancer is generated from 10,000 simulated draws, with the most statistically frequent card chosen for every

value: Show HN: Probabilistic Tarot

author: tabarnacle

title: Show HN: Probabilistic Tarot


value: zorlack

value:
I've frequently found myself using [nvitop](https://github.com/XuehaiPan/nvitop) to diagnose GPU/CPU contention issues.
The two best things about it are:
- It's easy to install if I can access pip in the container
- It makes a compelling screenshot (which helps me communicate with coworkers.)
With those two lessons in mind: Here is Sping!
Purpose: Help observe and diagnose latency issues at layer 4+ (TCP/HTTP/HTTPS)
Two good things about it:
- It's easy to install if you have pip. (Available at [service-ping-sping](https://pypi.org/project/service-ping-sping/) on PyPi)
- It makes a compelling screenshot.
Not sure if this is the kind of thing that anyone else would be interested in. But I've enjoyed making it and intend to keep using it.

value: Show HN: Sping – An HTTP/TCP latency tool that's easy on the eye

author: zorlack


value: mmajzoobi

value:
Over the past several years, I have worked on many embedded projects that shared a similar challenge: building a good UI/UX for the app's end user on an embedded platforms.
The UX in some cases required voice interactions, others needed a graphical user interface (GUI), and in one instance I needed camera for reading barcodes/QR codes.
Unlike desktop or mobile apps, where there are well-developed SDK and development environments like Android Studio, Xcode, etc (which separate the low level concerns for developers), there is no fully open source capable alternative for embedded linux.
So for example, if you are developing a hardware-integrated app on Raspberry Pi that requires audio/speech interactions, an embedded graphical user interface, interfacing with sensors, camera, and/or other on-board hardware, you typically have to start from scratch and integrate these elements directly in your application (instead of using platform APIs).
So I started Ubo projects a few years ago which aims to address this issue through a collection of open source building blocks (software and hardware).
I am exciting to release the latest stable version of Ubo app (v1.6) which abstracts system and hardware level interactions with a clean event driven API.
It allows developers to add GUI, audio, speech, camera/vision, LED ring, Infrared RX/TX, sensors, etc to their apps with a few lines of code.
You can run Ubo app on Raspberry Pi 4 and 5.
For hardware specific capabilities, you can either DIY your hardware as explained in README.md or obtain an Ubo pod (an open hardware companion for Ubo app).
Some of the hardware capabilities such as the embedded GUI and audio playback is currently also emulated in the browser.
For more information Ubo app, check out my GitHub repository.
Would love to hear your feedback and how something like this could help you in projects.
P.S. there are some experimental ai driven features enabled by pipecat-ai in the works to bring more interactive voice/vision interfaces to developers apps.

value: Show HN: Making hardware-integarted app development easier (open source)

author: mmajzoobi


value: sueszli

value:
Built multiplayer Pong that runs entirely client-side with zero runtime infrastructure.
- Live demo: https://sueszli.github.io/peroxide/
- Code: https://github.com/sueszli/peroxide
Two players copy-paste a session code to establish direct WebRTC data channels without any signaling server. Everything ships as a single HTML file with embedded WASM binary. No external dependencies, no asset loading.
ᕙ( •̀ ᗜ •́ )ᕗ Have fun!
On a personal note: I'll be wrapping up my quant dev contract @ QRT in October, where I had the chance to learn Rust from some incredibly sharp colleagues. If you're working on interesting systems challenges, I'd love to hear what you're building!

value: Show HN: Peroxide – P2P Multiplayer Pong on GitHub Pages (WebRTC and Rust/WASM)

author: sueszli


value: robgehring

value: Show HN: AI Transcription Service for Legal and Court TRM Files

author: robgehring


value: DT7-QR Rewards System – (Open Source Proposal)

value: Show HN: Decentralized Bitcoin Incentives via QR Codes


value: addressGen

value:
Hey HN! I built this simple 5-minute timer because I got frustrated with existing ones that either:
- Stop working when browser tabs go to background
- Have ads and tracking
- Are overcomplicated for such a simple need
Key features:
- Uses Web Workers to keep timing accurate even when tab is inactive
- Zero tracking, no ads, no registration
- Keyboard shortcuts (Space, R, F for fullscreen)
- Works offline once loaded
- Custom durations up to 24 hours
Tech stack: Vanilla JavaScript + Web Workers + modern CSS
Built in ~2 weeks as a side project.
Perfect for Pomodoro technique, workout intervals, meditation, or just timing anything!
Any feedback or feature suggestions welcome!

value: Show HN: 5-Minute Timer That Runs in Background with Web Workers

author: addressGen


value: nyell

value:
Hi, HN community,
I have built a CLI tool called Recaller to fuzzy-search your command history based on recency and frequency. Recaller can magically curate your history and hands over most useful commands to you. Think it like a second brain while recalling history.
Please check it out and let me know your feedback.

value: Show HN: Fast, private command-line history search with instant documentation

author: nyell


value:
I've really come to hate containers and orchestrators over the years, so I decided to prototype out my ideal replacement: a WASI orchestrator with TOML.
What I ended up with turned out to be a lot like Spin, but with some key differences and additions.
- one-off 'job' support.
- QEMU and native binary support. (QEMU is probably broken right now, but would not be hard to round-out support for it)
- mesh networking. adding new nodes involves setting the owner key and pointing it to a bootstrap peer
- Built-in UI. Every node on the mesh can serve a management interface
- Run now, codify later. Making config changes can be done in the UI and push to TOML when you're happy with it.
So in addition to hard isolation and resource quotas with WASI and QEMU, you can also use the system like a distributed computing mesh and submit jobs to it. I've been using it to make linux builds of itself on my linux machine automatically.
The README goes into a lot more depth.
I hope you feel inspired by this idea, and I really hope a real Rust dev will want to redesign it to be production ready.

value: Show HN: I made a WASI orchestration prototype


value:
Note: this is an update to [this](https://news.ycombinator.com/item?id=44568529) "Show HN" post.
timep is a state-of-the-art [debug-]trap-based bash profiler that is efficient and extremely accurate. Unlike other profilers, timep records:
1. per-command wall-clock time
2. per-command CPU time, and
3. the hierarchy of parent function calls /subshells for each command
the wall-clock + CPU time combination allows you to determine if a particular command is CPU-bound or IO-bound, and the hierarchical logging gives you a map of how the code actually executed.
The standout feature of timep is that it will take these records and automatically generate a bash-native flamegraph (that shows bash commands, not syscalls).
------------------------------------------------
USAGE
timep is extremely easy to use - just source the `timep.bash` file from the repo and add "timep" in front of whatever you want to profile. for example:

    . /path/to/timep.bash
    timep ./some_script
    echo "stdin" | timep some_function

ZERO changes need to be made to the code being profiled!
------------------------------------------------
EXAMPLES
[test code that will be profiled](https://github.com/jkool702/timep/blob/main/TESTS/timep.test...)
[output profile for that test code](https://github.com/jkool702/timep/blob/main/TESTS/OUTPUT/out...)
[flamegraph for that test code](https://github.com/jkool702/timep/blob/main/TESTS/OUTPUT/fla...)
[flamegraph from a "real world" test of "forkrun", a parallelization engine written in bash](https://github.com/jkool702/timep/blob/main/TESTS/FORKRUN/fl...)
In the "forkrun test", 13 different checksums were computed for ~670k small files on a ramdisk using 28 parallel workers. this was repeated twice. In total, this test ran around 67,000 individual bash commands. [This is its `perf stat` (without timep)](https://github.com/jkool702/timep/blob/main/TESTS/FORKRUN/pe...).
------------------------------------------------
EFFICIENCY AND ACCURACY
The forkrun test (see "examples" section above) was basically as demanding of a workload as one can have in bash.  it fully utilized 24.5 cores on a 14c/28t i9-7940x CPU, racking up >840 seconds of CPU time in ~34.5 seconds of wall-clock time. When profiling this group of 67,000 commands with timep:
1. the time it took for the code to run with the debug-trap instrumentation was ~38 seconds, an increase of just slightly over 10%. CPU time had a similiar increase.
2. the time profile was ready at +2 minutes (1 minute + 15 seconds after the profiling run finished)
3. the flamegraphs were ready at +5 minutes (4 minute + 15 seconds after the profiling run finished)
Note that timep records both "start" and "stop" timestamps for every command, and the debug trap instrumentation runs between one commands "stop" timestamp and the next commands "start" timestamp, meaning the error in the profiles timings is far less than the 10% overhead. Comparing the total (sys+user) CPU time that perf stat gave (without using timep) and the CPU time timep gives (from summing together the CPU time of all 67,000-ish commands), the difference is virtually always less than 0.5%, and often less than 0.2%. Ive seen as low as 0.04%, which is 1/3 of a second on a run that took ~850 seconds of CPU time.
------------------------------------------------
MAJOR CHANGES SINCE THE LAST "SHOW HN" POST
1. CPU time is now recorded too (instead of just wall-clock time). This is done via a loadable builtin that calls `getrusage` and (if available) `clock_gettime` to efficiently and accurate determine the CPU time of the process and all its descendants.
2. the .so file required to use the loadable builtin mentioned in #1 is built directly into the script has an embedded compressed base64 sequence. I also developed the bash-native compression scheme that it uses. The .so files for x86_64, aarch64, ppc64le and i686 are all included. Im hoping to add arm7 soon as well. the flamegraph generator perl script is also embedded, making the script 100% fully self-contained. NOTE: these embedded base64 strings include both sha256 and md5 checksums of the resulting .so file that are verified on extraction.
3. the flamegraph generation has been completely overhauled. The flamegraphs now a) are colored based on runtime (hot colors = longer runtime), b) desaturate colors for commands where cpu time << wall-clock time (e.g., blocking reads, sleep, wait, ...), and c) use a runtime-weighted CDF color mapping that ensures, regardless of the distribution of the underlying data, that the resulting flamegraph has a roughly equal amount of each color in the colorspace (where "equal" means "the same number of pixels are showing each color"). timep also combines multiple flamegraphs (that show wallclock time vs cpu time and that us the full vs folded set of traces) by vertically stacking them into a single SVG image, giving "dual stack" and "quad stack" flamegraphs.
4. the post-processing workflow has been basically completely re-written, making it more robust, easier to understand/maintain, and much faster. The "forkrun" test linked above (that ran 67,000 commands) previously took ~20 minutes. With the new version, you can get a profile in 2 minutes or a profile + flamegraph in 5 minutes - a 4x to 10x speedup!

value: Show HN: Timep – A next-gen profiler and flamegraph-generator for bash code


value: manjusg

value:
Hi HN,
I’m 19 and building VigyanVerse, a web app to explore knowledge through structured “cards.” Each card has a quick summary → deeper sections → advanced details if you want.
Early build: https://vigyanverse.netlify.app
Features so far:
Browse science/tech topics in interactive cards
“Dive Deeper” for more detailed explanations
Dark/light mode, mobile-friendly UI
Track views & shares
I’d love feedback on:
What would make you come back daily?
What features are missing or worth adding?
How to make this more fun and addictive for learning?
Built solo, zero funding, just HTML/JS + Firestore + Netlify.

value: Show HN: VigyanVerse – A structured knowledge app for learning via topic cards

author: manjusg


value: anof-cyber

value:
I built InterceptSuite to solve a problem I kept running into as a security engineer: there are virtually no good MITM proxies for non-HTTP protocols, and the few that exist completely break when protocols upgrade from plaintext to TLS.
The core technical challenge was implementing universal TLS upgrade detection. When PostgreSQL, MySQL, SMTP, or any other protocol issues a StartTLS command, most tools just give up. They'll show you the initial plaintext handshake, then nothing when TLS encryption kicks in.
InterceptSuite automatically detects when ANY protocol switches to TLS and handles the interception seamlessly. It's not just another HTTP proxy - it's designed specifically for database connections, email protocols, and desktop thick client application traffic that uses TLS or TLS upgrades.
Technical highlights:
- Automatic TLS upgrade handling for any protocol, including StartTLS like SMTP, PostgreSQL, etc
- Cross-platform GUI (Windows, macOS, Linux)
- Real-time traffic interception and modification
- Project management for security assessments
The Standard Edition is free and open source. There's also a Pro version with additional features like PCAP export and project management.
Would love feedback.

value: Show HN: InterceptSuite – MitM proxy that handles StartTLS upgrades

author: anof-cyber


value: Show HN: Discover, share, and collaborate on effective coding prompts


value: doodyman

value:
I built Lekh, a minimal writing site with a write-only philosophy. Create lekh.space/yourname, set a password, and just write—no auth, no feeds, no distractions. Auto-saves; content is stored encrypted; reading isn’t the focus (you can view your own history at /yourname/all).
Live: lekh.space
Code: github.com/swappysh/lekh
I’d love feedback on:
(1) the “can’t edit” constraint
(2) use-cases you’d try
(3) rough edges to fix first. I’m here to answer questions!

value: Show HN: Lekh – write-only, encrypted micro-journal at your own URL

author: doodyman


value: pablo-chacon

value: I put together a repo called Spoon-Bending, it is not a jailbreak or hack, it is a structured logical framework for studying how GPT-5 responds under different framings compared to earlier versions. The framework maps responses into zones of refusal, partial analysis, or free exploration, making alignment behavior more reproducible and easier to study systematically.<p>The idea is simple: by treating prompts and outputs as part of a logical schema, you can start to see objective patterns in how alignment shifts across versions. The README explains the schema and provides concrete tactics for testing it.

value: Show HN: Spoon-Bending – a framework for analyzing GPT-5 alignment behavior

author: pablo-chacon


value: matt-npl-public

value: Show HN: SocialRails

author: matt-npl-public

title: Show HN: SocialRails


value: Show HN: BypassGPT – A tool to humanize AI text to pass AI detectors


value: ihiep

value: Show HN: A 2.41kB breathing app that works in any network conditions

author: ihiep


value: solcloud

value: Using copilot and threejs, source code available at https://github.com/solcloud/Counter-Strike

value: Show HN: Vibe coded Counter Strike clone

author: solcloud


value: boshjerns

value: I created an open source and free version of Wispr Flow that also includes an AI assistant feature I am working on.  Has all the main features of Wispr Flow like audio ducking and hot keys to start dictation.  @boshjerns on X if you dig it let me know!<p>If you run it locally theres no login necessary but if you install on Mac or Windows- the dictation is all local but requires login because the secondary ai assistant feature uses my openai keys.

value: Show HN: Made 100% free and local, open source Wispr Flow alternative

author: boshjerns


value: nikoscham

value:
FEAScript is a lightweight finite element simulation library built in JavaScript. It empowers users to create and execute simulations for physics and engineering applications in both browser-based and server-side environments.
The following lists contain some, but not all, of the available features in FEAScript:

     Physical Modelling
        - Solid heat conduction solver
        - Front propagation solver
     Geometry and Meshing
        - Simple mesh generation (1D and rectangular 2D domains)
        - Unstructured mesh import from Gmsh (".msh" file format)
     Numerical Solution
        - Linear system solvers (LU decomposition, Jacobi method)
        - Newton-Raphson method for nonlinear problems
     Parallelization
        - Web worker support for multi-threaded computation
     Visualization
        - Line and surface plotting

 Resources:

     GitHub: https://github.com/FEAScript/FEAScript-core
     Website: https://feascript.com/
     NPM: https://www.npmjs.com/package/feascript

value: Show HN: Finite element simulation library built in JavaScript

author: nikoscham


value:
mcp-plugins is an open source project that ships with a collection of prebuilt MCP middleware plugins to let you add logging, rate limiting, error handling, cherry pick tools you only need, human approval etc. to your MCP, within one command setup. You can use mcp-plugins cli with a config.json input to proxy on top of your MCP servers or you can use it as prebuilt middleware lib in python with FastMCP.
As MCP gains more and more adoption, proxy, gateways & middleware become important pattern but there limited resources of prebuilt middleware as examples. This project is pretty early stage and experimental, but try to demonstrate a few use cases. And the provided python lib and cli will give you very easy and quick setup to try it out. You can also fork and customize the middleware there.
You can check the repo README for list of prebuilt plugins and how to use it.

value: Show HN: Mcp-plugins CLI/py equips your MCP with powerful prebuilt plugins


value: TarekOraby

value:
I built Itura, a way to define an app in plain English and get a working application with its own secure database and an AI that enforces your rules. You then use the app through conversation (create/query/update data with role-based permissions).
How Itura differs from no-code/low-code:
- No drag-and-drop UI, no workflow builders. You write a plain-English spec; Itura generates the app and database.
- The final app is chat-native, not a form-based UI.
- Real RBAC + row-level security; every action respects roles and constraints.
How Itura differs from chatbots (e.g., ChatGPT):
- Itura creates a persistent, multi-user, role-aware application with its own database.
- The assistant is bound by your app’s schema, permissions, and constraints; it executes allowed CRUD operations instead of giving generic answers.
- End-users collaborate inside that app rather than a single general-purpose chat.
Example use cases:
- Lightweight CRM: log leads, notes, next steps; managers see team-wide views with RBAC.
- Applicant tracking: candidates, stages, feedback; hiring leads control access.
- Inventory/asset tracker: add items, update stock, audit changes; staff vs admin roles.
- Content pipeline: ideas → drafts → published; editors approve and schedule.
Try it: Open beta with a free tier; Pro is $20/mo. Feedback on the builder flow, permissions model, and ambiguous-query handling is very welcome.

value: Show HN: Itura – Build and use database-backed apps in chat

author: TarekOraby


value: arabicalories

value: Hi HN, I’m a Sudoku enthusiast and built PrintableSudoku.net to make it easy for anyone to download printable Sudoku PDFs or play puzzles online. You can choose difficulty, print as many as you like, or solve directly on the site. I wanted something straightforward for people who enjoy Sudoku, whether on paper or online. Any thoughts or suggestions about the puzzles or the site are very welcome!

value: Show HN: Printablesudoku.net – Download and play printable Sudoku PDFs online

author: arabicalories


value:
Hi HN,
I built a small open-source repo in Go to compare two classic trading strategies (Dollar-Cost Averaging vs Grid).
This is educational/research only — no real keys, no promises of profit.
Why I built it:
I wanted a clean architecture to experiment with strategies.
Most examples online are either black-box or not reproducible.
What’s inside:
Strategy interface for DCA/Grid.
Unified exchange client (Binance/CCXT).
Minimal backtester with seeded RNG for reproducibility.
Metrics: Profit Factor, Max Drawdown, Win Rate, Sharpe.
Sample metrics (BTC 2020–2024):
DCA → PF 1.42, MDD -18.7%, WR 62%
Grid → PF 1.67, MDD -25.3%, WR 58%
Repo:
 https://github.com/Zmey56/crypto-trading-strategies
I’d love feedback on:
Architecture (Go interfaces, package layout).
How you approach reproducibility in backtests.
Ideas for extending this (filters, regime classification, DeFi/AMMs).

value: Show HN: Open-source Go repo comparing DCA vs. Grid with reproducible backtests


value: surprisetalk

value:
Hello friends,
Today I'm sharing a little tool to help you explore GitHub repositories:
• https://diggit.dev
This project was admittedly a big dumb excuse to play with Elm and Claude Code. I published my design notes and all the chat transcripts here:
• https://taylor.town/diggit-000
Please add bug reports and feature requests to the repo:
• https://github.com/surprisetalk/diggit
Enjoy!

value: Show HN: Diggit.dev – Git history for architecture archaeologists

author: surprisetalk


value: kugutsumen

value: Show HN: Turn SpiderMonkey bytecode back into readable JavaScript

author: kugutsumen


value: PeteMinus

value:
Hi HN,
I bought my first 3d printer early last year. By the end of the year I already had 1000+ 3d files scattered across folders. Many of those were actually duplicates. Mostly because the search in Mac is just horrible (though there is a prebuilt preview for STLs, I give them credit for that).
So I built Modelist, a cross-platform desktop app for managing 3D printing files. Think of the gallery app meets 3d files.
First, I quickly hacked something for me, then I built the second version that's actually shareable. It solves the main challenges that people I spoke with had (funny, how similar those were to mine!):
* Watches selected folders and automatically indexes files (including subfolders)
* Generates thumbnails for STL and extracts embedded images from 3MF
* Lets you search by filename, description, or notes you add
* Groups related files automatically (with some magic)
* Opens models directly in the selected slicer (e.g. Bambu Studio, Prusa Slicer)
* Works on macOS, Windows, and Linux (SQLite under the hood, local-only, no cloud)
* Opt-in cloud functionality - share file with friend (shares file, images, metadata, ...)
You can check it out here: https://modelist.app
I decided to charge a small one-time fee (20 EUR) for my efforts, with a free version to test it out first.
I’d love feedback from fellow 3d printing hobbyists - especially on:
* What other features do you want in a tool like this
* Whether the UX feels right (gallery vs file-explorer style)
* Technical critiques - I’m aware Electron is heavy, but it gave me fast cross-platform support
Best,
 Pete

value: Show HN: Modelist – A desktop app to organize 3D printing files

author: PeteMinus


value: djlim

value:
We were getting overwhelmed by noisy Sentry alerts, so I built a small Slack bot using Sentry MCP.
Instead of dumping every error, it sends a simple daily summary and highlights what’s actually critical.
It’s free to use and doesn’t require signup:
https://runbear.io/a/slack/sentry-issue-radar

value: Show HN: Slack bot with Sentry MCP for error summaries

author: djlim


value: MinZhou

value: Show HN: My color challenge got more attention than I expected

author: MinZhou


value: zulko

value: Show HN: Verbiage, a Gemini-powered word game

author: zulko


value:
Hi HN! I'm the maker of Sidekick.
Sidekick is an AI coding tool. It is currently available for Mac, with Windows support coming soon. I started with Mac to get the native experience right before expanding to other platforms.
I know there are many AI coding tools out there, but I always felt strongly about building this.
Looking for feedback on:
• Any bugs or performance issues
• Features that would improve your workflow
• How you currently use AI coding tools
Still iterating based on user feedback. Happy to answer questions about the technical approach or design decisions.
For early 100 users, there's a 70% discount for the first month.

value: Show HN: Sidekick – AI Coding Assistant

title: Show HN: Sidekick – AI Coding Assistant


value:
Hey HN, I built VPN-Chainer to make multi-hop WireGuard setups a bit easier for the average VPN user.
It can chain multiple WireGuard endpoints together, and can run speed tests with `--fastest`, installs as a systemd service (hooks included), and lets you rotate tunnels via a lightweight API. Imagine in the movies where they say they connection is bouncing around the world. Similar but not exactly like that.
Grab it from the repo or install via the systemd-ready installer, no signup, landing pages, or cart required. Stack is shell (pre/post hooks) + Python + WireGuard.
It’s early-stage, so hook integrations and rotation policies could use polish, your feedback would help steer improvements.
Thanks, and take it easy!

value: Show HN: Multi-hop WireGuard chaining, speed-tested and API-controlled


value: DimitriMikadze

value: Show HN: Open-Source Agentic AI for Company Research

author: DimitriMikadze


value: lexokoh

value: Show HN: Agent Key – OAuth for AI Agents

author: lexokoh


value: wjsekfghks

value:
Hi, I’m Mikkel and I’m building Async, an open-sourced developer tool that combines AI coding with task management and code review.
What Async does:

  - Automatically researches coding tasks, asks clarifying questions, then executes code changes in the cloud
  - Breaks work into reviewable subtasks with stack diffs for easier code review
  - Handles the full workflow from issue to merged PR without leaving the app

Demo here: https://youtu.be/98k42b8GF4s?si=Azf3FIWAbpsXxk3_
I’ve been working as a developer for over a decade now. I’ve tried all sorts of AI tools out there including Cline, Cursor, Claude Code, Kiro and more. All are pretty amazing for bootstrapping new projects. But most of my work is iterating on existing codebases where I can't break things, and that's where the magic breaks down. None of these tools work well on mature codebases.
The problems I kept running into:

  - I'm lazy. My Claude Code workflow became: throw a vague prompt like "turn issues into tasks in Github webhook," let it run something wrong, then iterate until I realize I could've just coded it myself. Claude Code's docs say to plan first, but it's not enforced and I can't force myself to do it.
  - Context switching hell. I started using Claude Code asynchronously - give it edit permissions, let it run, alt-tab to work on something else, then come back later to review. But when I return, I need to reconcile what the task was about, context switch back, and iterate. The mental overhead kills any productivity gains.
  - Tracking sucks. I use Apple Notes with bullet points to track tasks, but it's messy. Just like many other developers, I hate PM tools but need some way to stay organized without the bloat.
  - Review bottleneck. I've never shipped Claude Code output without fixes, at minimum stylistic changes (why does it always add comments even when I tell it not to?). The review/test cycle caps me at maybe 3 concurrent tasks.

So I built Async:

  - Forces upfront planning, always asks clarifying questions and requires confirmation before executing
  - Simple task tracking that imports Github issues automatically (other integration coming soon!)
  - Executes in the cloud, breaks work into subtasks, creates commits, opens PRs
  - Built-in code review with stacked diffs - comment and iterate without leaving the app
  - Works on desktop and mobile

It works by using a lightweight research agent to scope out tasks and come up with requirements and clarifying questions as needed (e.g., "fix the truncation issue" - "Would you like a tooltip on hover?"). After you confirm requirements, it executes the task by breaking it down into subtasks and then working commit by commit. It uses a mix of Gemini and Claude Code internally and runs all changes in the background in the cloud.
You've probably seen tools that do pieces of this, but I think it makes sense as one integrated workflow.
This isn't for vibe coders. I'm building a tool that I can use in my day-to-day work. Async is for experienced developers who know their codebases and products deeply. The goal is to make Async the last tool developers need to build something great. Still early and I'm iterating quickly. Would love to know what you think.
P.S. My cofounder loves light mode, I only use dark mode. I won the argument so our tool only supports dark mode. Thumbs up if you agree with me.

value: Show HN: Async – Claude code and Linear and GitHub PRs in one opinionated tool

author: wjsekfghks


value:
Built Vibe Manager after getting tired of agents drifting in large repos. It finds the right files, pulls current docs, then runs multiple model providers in parallel and merges the plans into one so changes land in the correct places.
What’s different:
– Multi-model planning: run several LLMs in parallel; Vibe merges them into a single, reviewable implementation plan.
– File selection: surfaces the few files that matter (respects .gitignore, filters large/binary).
– Fresh docs: pulls the latest vendor/framework docs into the plan.
– Local-first privacy: your repo stays on your machine; you choose what gets sent to providers.
– Quick capture: voice notes + optional screen recording to state intent fast.
Would love feedback on: accuracy of file selection on your repo; where the merged plan helps/fails; confusing bits in onboarding.
Try it: macOS download on the landing page; free starter credits. Windows next.

value: Show HN: Vibe Manager – Multi-model planning and fresh docs –> one plan (macOS)


value:
Hi everyone,
I've made an open-source library for fast spatial search in Rust.
It's called Spart, and it currently provides the following features:
- Five tree implementations: Quadtree, Octree, Kd-tree, R-tree, and R*-tree
- Python bindings (`pyspart` on PyPI)
- Fast k-nearest neighbor (kNN) and radius search
- Bulk data loading for efficient tree construction
Project's GitHub repo: https://github.com/habedi/spart

value: Show HN: Spart – A Rust library for fast spatial search with Python bindings


value: bbkane

value: I wrote enventory to keep track of environment variables and share them between projects. It's been especially helpful to keep a record of what environment variables I've used over time in which projects.

value: Show HN: Enventory: Centrally manage environment variables with SQLite

author: bbkane


value: APBShips

value:
Hi HN, I built this rails CRUD app because I needed a YNAB for cars and I kinda kept abandoning every spreadsheet for my project cars because they get so boring and I hate working with spreadsheets logic...
It's not the smartest nor the most impresive app that's been displayed here, but it works really well for my use case and I thought of sharing it with a wider audience to get some feedback on it. Have a play on https://wrenchwise.app
Obviously stuck a monthly subscription so I can cover my Hetzner bill, ha.
Let me know what you think :)

value: Show HN: YNAB for Cars (Kinda)

author: APBShips

title: Show HN: YNAB for Cars (Kinda)


value:
Hi HN,
I built WebhookHub
 because I kept running into the same pain whenever testing integrations: webhooks are hard to debug. They arrive at odd times, you need to expose a local server, or set up ngrok, and there’s no easy way to replay them.
WebhookHub gives you an instant endpoint - no config or code needed. You can:
Create a webhook URL with one click
Inspect headers and payloads in a clean UI
Replay requests to your local or staging server
Share endpoints (public links) with your team
I know there are other tools in this space, but my focus is speed and simplicity - a tool you can use in 10 seconds without installing anything.
I’d love for you to try it and tell me what you think. Here’s the link again: https://webhook-hub.up.railway.app/

value: Show HN: WebhookHub – Instantly inspect and replay webhooks


value: lordofnork

value: Show HN: Flourish and Decay, a digital board game built on Conway's Game of Life

author: lordofnork


value: AdamAkhlaq

value:
Hi HN,
I’ve been working on a small tool called [PrettyPost](https://www.prettypost.io/)
 that takes social media posts—or even your own uploaded screenshots—and turns them into clean, visually pleasing images you can share anywhere.
The motivation came from frustration with messy manual screenshots: cropping out UI clutter, engagement counts, or random background distractions. With PrettyPost, you just drop in a link (or upload a screenshot), and it generates a polished, minimal graphic you can use for newsletters, blogs, LinkedIn, Instagram, or just to archive your own content.
Key points:
Works with posts from major social platforms
You can also upload your own screenshots
Removes distracting UI and adds a minimal, professional look
Great for cross-posting content, personal branding, or content marketing
Includes a generous free tier (no credit card required)
It’s still early, so I’d love feedback from the HN community—especially around what features would be most useful for creators, developers, and marketers.
Try it here: https://www.prettypost.io/
Also sharing my journey: https://x.com/AdamAkhlaq

value: Show HN: I created a screenshot editor for your social media

author: AdamAkhlaq


value: Show HN: New Podcast about the Agentic AI future of fundraising and investing


value:
I recently released v3 of Base, my SQLite editor for macOS.
The goal of this app is to provide a comfortable native GUI for SQLite, without it turning into a massive IDE-style app.
The coolest features are
- That it can handle full altering of tables, which is quite finicky to do manually with SQLite.
- It has a more detailed display of column constraints than most editors. Each constraint is shown as an icon if active, with full details available on clicking the icon.
This update also adds support for attaching databases, which is a bit fiddly with macOS sandboxing.
I'd love to hear any feedback or answer any questions.

value: Show HN: Base, an SQLite database editor for macOS


value: harryfelio

value: Show HN: I built a keyword research tool for everyone, not just professionals

author: harryfelio


value: pors

value: Copy-paste a snippet from social media that refers to a study and find the paper PDF (hopefully). It tries all sorts of APIs (Crossref, Open Alex, Unpaywall), an LLM and Google Scholar to find the most likely paper PDF (if it is open access). Please let me know if you have ideas to improve it! Yes, it can be slow.

value: Show HN: Citation Needed

author: pors

title: Show HN: Citation Needed


value: theyoungsir

value:
I wanted proper post-quantum crypto tools on my phone, so I built encyfr. There’s no telemetry, no accounts, and everything runs locally.
It supports key generation/management, file encryption, and signing with the NIST pqc choices (Kyber, Dilithium, AES256) as well as password modes. Normally I haven't bothered circulating my work, but several recent concerns about phone compromise can be resolved with proper encryption utilities like these (e.g. any agency with a GrayKey).
I’m curious if others here find this kind of thing useful/interesting, and what features would make it genuinely useful to you. Not available in France.

value: Show HN: Encyfr – post-quantum encryption for all

author: theyoungsir


value: vusalorujov

value:
Hi HN,
I’m Vusal, a software engineer who’s been building and selling SaaS-ready, source-available software for a while. My product is called Aikeedo. Until now, I’ve been selling licenses to other developers and companies who wanted to run it under their own brand and domain.
Recently I thought: why not “dogfood” it? So I’ve launched Aikeedo as a hosted SaaS, while continuing to sell the self-hosted version.
What it does:
Aikeedo is a platform that lets anyone run AI tools (chat, content generation, etc.) with a simple API and web interface. Buyers of the licensed version get the full source code to self-host. Now, the hosted version means you can just sign up and start using it without setup.
Why I built it:
While selling licenses, I noticed many small teams and individuals didn’t want to deal with hosting, deployment, or maintenance—they just wanted to use the software. At the same time, some companies wanted the opposite: complete control, source access, and branding. I decided to support both.
How it works (hosted version):
- Free plan: try smaller/legacy models with 100 credits/month.
 - Paid plan: $10/month for all features and models (1000 credits/month).
 - Extras: buy permanent, non-renewing credits anytime ($1 = 100 credits).
Teams & workspaces:
Paid plans can create workspaces and invite up to 10 users to share the same subscription (planning to increase this limit). Teams can share AI generations and credits across the workspace.
What’s different:
- Source-available and self-hostable if you need control (we keep selling licenses).
 - Or use the hosted version if you want zero setup.
 - Simple pricing; no hidden tiers.
What I’d love from HN:
I’d love feedback from this community. What do you think about supporting both hosted and self-hosted models for the same product? Are there gaps you’d see as a user? Anything about pricing or usability that feels off?
You can try it here: https://aikeedo.com/
I’ll be around all day to answer questions.

value: Show HN: Aikeedo – Your complete AI workspace (hosted and self-hosted)

author: vusalorujov


value: rendernos

value: Show HN: Aulico – AI Agent for Aspiring Investors

author: rendernos


value: anianroid

value:
Hi HN! I've been working on Cairo, an open-source platform for managing outreach campaigns across Lemlist, Smartlead, and other tools.
The latest feature solves a problem every agency faces: keeping client data separated without complex configuration.
How it works:
- Name campaigns with client identifiers: "ACME Corp - Q1 2024"
- System automatically detects "ACME Corp" and routes to isolated tables
- Each namespace gets its own {namespace}\_user_source table
- Complete API for managing namespaces programmatically
Technical highlights:
- Node.js + PostgreSQL
- Dynamic table creation with proper indexes
- Smart caching layer (5-min TTL)
- Zero-downtime migration from single to multi-tenant
- ~3ms overhead for namespace detection
We're dogfooding this with 12 clients and it's eliminated hours of manual data wrangling weekly.
Happy to answer questions about the architecture, multi-tenancy patterns, or anything else!

value: Show HN: Cairo – Open-source multi-tenant data segregation for GTM

author: anianroid


value: CameronBanga

value:
Greetings all,
Just released a new iOS app called Compress-san. It's an easy-to-use utility to compress videos taken on iPhone, and then generate SRT files with transcriptions of any spoken word inside of the clip.
Had a friend who was creating work instructions and using videos to insert clips into the work instructions. This app allowed him to generate on-device subtitle SRT files to pass along into another LLM for creation of the general work instructions. He can then use the compressed video to create small video clips of key processes and throw on a shared drive.
Some additional nice features include batch processing of up to 10 videos at once, iPad UI support, local on-device translation of SRT files into 23 languages, and native support of the UI for Spanish and Japanese languages.
Welcome to any feedback or additional ideas.

value: Show HN: Compress-san, simple batch video compression and SRT subtitle creation

author: CameronBanga


value: shaneslucky

value: I made this free to use reverse video search tool since there aren't any other effective ways to reverse video search. It works by extracting frames and performing a reverse image search on them. It works best if the video you are looking for has been indexed by a search engine. Hopefully someone here will find this helpful. Let me know if you have any feedback or suggestions, as I am working every day to improve it.

value: Show HN: Reverse Video Search – find a video's source or context

author: shaneslucky


value:
Hi HN! I’ve been working on CVAT-DATAUP, an open-source fork of CVAT. It’s fully compatible, but I’m pushing it beyond annotation — with a cleaner UI, better dataset insights, and easier job management. The main goal is to turn CVAT into a data-centric platform, where agents and pipelines help with annotation, validation, and dataset quality — putting data at the heart of the workflow.
Repo: https://github.com/dataup-io/cvat-dataup
Medium post: https://medium.com/@ghallabi.farouk/from-annotation-tool-to-...

value: Show HN: CVAT-DATAUP – a more data-centric version of CVAT


value:
So happy to introduce GrowChief (AGPL-3).
Growchief is an open-source social media automation tool (aka social scraper).
It allows you to create a workflow (step-by-step) for interacting with different social media accounts, such as sending a connection request, following up with a message, and so on.
Unlike other platforms, GrowChief does not work with search criteria.
You'll need to specify the account email, URL, or company information to connect with it. I do not encourage spam.
I had tons of fun working on this project
Tech Stack:
- PNPM (Monorepo)
- React (Vite)
- NestJS (Backend, Workers)
- Prisma (Default to PostgreSQL)
- Temporal (Orchestrator)
- It takes care of concurrency — even if you create 10 workflows with the same account and trigger all of them at the same time, it will make an action every 10 minutes, never having multiple scrapings happening at the same time.
- Enrichment waterful - when you don't provide the account URL but other parameters like email, we use multiple providers to figure out the profile URL.
It takes care of your working hours — you can use the API to keep adding leads to your workflows, but they will only be processed during working hours.
- Proxies are allowed — you can add your own proxies or create one using proxy providers to keep you safe.
- Human-like automation — GrowChief uses natural mouse movements and clicks on different parts of the screen. It never triggers clicks by "document.querySelector('x').click()".
- It uses Playwright together with Patchright for maximum stealthiness.
- It uses a special technology to authenticate your accounts — you never need to put your username and password directly into the system.
- It always runs in headful mode — our Docker image is already built with xvfb for real human automation.
It's the very first version, I hope you like it :)

value: Show HN: GrowChief – open-source social media automation tool


value:
Not all improvements come from adding complexity — sometimes it's about removing it.
PageIndex takes a different approach to RAG. Instead of relying on vector databases or artificial chunking, it builds a hierarchical tree structure from documents and uses reasoning-based tree search to locate the most relevant sections. This mirrors how humans actually read: navigating through sections and context rather than relying on embedding similarity.
As a result, the retrieval feels transparent, structured, and explainable. It moves RAG away from approximate "semantic vibes" and toward explicit reasoning about where information lives. That clarity can help teams trust outputs and debug workflows more effectively.
The broader implication is that retrieval doesn't need to scale endlessly in vectors to be powerful. By leaning on document structure and reasoning, it reminds us that efficiency and human-like logic can be just as transformative as raw horsepower.

value: Show HN: Human-like RAG — no vectors

title: Show HN: Human-like RAG — no vectors


value: YalebB

value: Show HN: Store and Share Bookmarks

author: YalebB

title: Show HN: Store and Share Bookmarks


value: decodingchris

value:
I’ve been experimenting with LLMs lately and kept running into the same problem:
Every time I tweaked a prompt, I had to rerun a bunch of test cases manually and eyeball the results.
It felt like writing code without unit tests.
Existing tools I found were either:
- Full frameworks where you write evaluators in Python.
- Big platforms expanding into monitoring/security.
I wanted something simpler: a fast CLI that just tests prompts.
So I built prompttest, a pytest-like workflow for LLMs:
- You define a prompt in a .txt file with `{variables}`.
- You write test cases in .yml, with plain-English criteria.
- You run prompttest to see clear pass/fail results in your terminal.
The core idea is that your "assertion" is just English.
Example:
> The response must be polite and address the user by name.
Then a model grades the output for you.
This gives a safety net — you can refactor prompts and instantly see regressions.
The project is still early.
It runs on OpenRouter, so you can test against many models (including free ones) with one API key.
Would love feedback, ideas, or use-cases you’d want supported.
GitHub: https://github.com/decodingchris/prompttest

value: Show HN: prompttest – pytest for LLMs

author: decodingchris

title: Show HN: prompttest – pytest for LLMs


value: redactsure

value:
Hi HN, I'm releasing my round one public demo of a new browser security system I've been developing.
There's a real Bitcoin private key (worth $20) in plaintext at app.redactsure.com. You can copy it, paste it, delete it, move it around - full control. But you can't see the actual characters or extract them.
The challenge: Break the protection and take the Bitcoin. First person wins, challenge ends.
Details:
- Requires email verification (prevents abuse, no account needed)
- 15 minute time limit per session
- Currently US only for the demo (latency)
- Verify the Bitcoin is real: https://redactsure.com/bitcoinchallenge
Technical approach:
- Cloud-hosted browser with real time NER model
- Webpages are unmodified
- Think of it as selective invisibility for sensitive data. You can interact with it normally, just can't see or extract it
Looking for feedback on edge cases in the hiding/protection algorithm. Happy to answer questions about the implementation.

value: Show HN: Bitcoin Challenge. Try to steal a plain text private key you can use

author: redactsure


value: maskeen

value:
Hey everyone, i'm building knowdeck.me which helps you simplify complex topics into clear, cited slides.
if i want to describe it in one line :- it helps you learn faster, create better presentations, and simplify complex topics.
Whether you're a student trying to understand a difficult subject, a professional preparing for a meeting, or just a curious mind, knowdeck helps you learn and present information more effectively.
you can ask it anything, and you will get slides with clear theory and our Ai models  works with web search to provide you with most accurate explanation with citation of sources too, if you don't like any particular generated slide, then you can update that too.
if you still don't understand, every slide has an option where you can ask question for that slide, that will generate a slide, explain your question wrt context of that slide.
also you can create follow up decks too.
knowdeck isn't just about creating presentations, it's about learning and presenting better.
The platform is completely free to use as of now, so you can use it and generate as many as deck you want. and we will keep the pricing as low as possible!
also we respect your privacy, so no data is ever used for advertisement or training purpose.
p.s you don't require signing in to test it.
try now :- https://www.knowdeck.me/
would be grateful if i get feedback.

value: Show HN: Knowdeck,an Advanced Visualisation Tool

author: maskeen


value: jacobn

value:
Create "Message Me Now" QR Codes to conveniently connect with people you meet: have them scan a QR code to immediately send you a message (SMS, email, WhatsApp) without having to go through the typo-prone verbal exchange.
Free, works on any modern phone, no app installation, and no more messages going to the wrong number / email.
https://qr.clv.ws/

value: Show HN: 'Message Me Now' QR Codes to easily share contact info

author: jacobn


value: amanasci

value:
Hi HN!
I built RefForge, a lightweight, desktop-first reading list and reference manager (WIP). It's a local-first app built with Next.js + Tauri and stores data in a small SQLite DB. I’m sharing it to get feedback on the UX, feature priorities, and architecture before I invest in more advanced features.
This is an experimental project where I am trying to build something from scratch using AI and see how far I can build it without writing a single line of code manually.
What does it offer?
Manage your reading list and references in a simple, project-based UI
Local SQLite storage (no cloud; your data stays on your machine)
Add / edit / delete references, tag them, rate priority, group by project
Built as a Tauri desktop app with a Next.js/React frontend
Why did I build it?
Existing reference managers can be heavy or opinionated. I wanted a small, fast, local-first tool focused on reading lists and quick citation exports that I can extend with features I need (PDF attachments, DOI lookup, BibTeX export, lightweight sync).
Current features
Add / edit / delete references
Tagging and project organization
Priority and status fields
Small, searchable local DB (WIP: full-text search planned)
Ready-to-extend codebase (TypeScript + React + Tauri + SQLite)

value: Show HN: RefForge – A WIP modern, lightweight reading list/reference manager

author: amanasci


value: YuriiDev

value:
I built SecretMemoryLocker (https://secretmemorylocker.com), a file encryption tool that generates keys dynamically from your answers to personal questions instead of using a static master password. This makes offline brute-force attacks much more difficult. Think of it as a password manager that meets mnemonic seed recovery, but without storing any sensitive keys on disk.
Why? I kept losing master passwords and wanted a solution that wasn't tied to a single point of failure. I also wanted to create a "digital legacy" that my family could access only under specific conditions. The core principle is knowledge-based encryption: the key only exists in memory when you provide the correct answers.
Status: * MVP is ready for Windows (.exe). * Linux and macOS support is planned. * UI is available in English, Spanish, and Ukrainian.
Key Features:
* No Static Secrets: No master password or seed phrase is ever stored. The key is reconstructed on the fly.
* Knowledge-Based Key Generation: The final encryption key is derived from a combination of your personal answers and file metadata.
* Offline Brute-Force Resistance: Uses MirageLoop, a decoy system that activates when incorrect answers are entered. Instead of decrypting real data, it generates an endless sequence of AI-created questions from a secure local database, creating an illusion of progress while keeping your real data untouched.
* Offline AI Generation Mode: Optional offline Q&A generator (prototype).
How It Works (Simplified):
1) Files are packed into an AES-256 encrypted ZIP archive.
2) A JSON key file stores the questions in an encrypted chain. Each subsequent question is encrypted with a key derived from the previous correct answer and the file's hash. This forces you to answer them sequentially.
3) The final encryption key for the ZIP file is derived by combining the hashes of all your correct answers. The key derivation formula looks like this:

  K_final = SHA256(H(answer1+file_hash) + H(answer2+file_hash) + ...)

(Note: We are aware that a fast hash like SHA256 is not ideal for a KDF. We plan to migrate to Argon2 in a future release to further strengthen resistance against brute-force attacks.)
To encrypt, you provide a file. This creates two outputs:
your_file.txt → your_file_SMLkey.json + your_file_SecretML.zip
To decrypt, you need both files and the correct answers.
Install & Quick Start: Download the EXE from GitHub Releases (no dependencies needed):
https://github.com/SecretML/SecretMemoryLocker/releases
Encrypt:

  SecretMemoryLocker.exe --encrypt "C:\docs\important.pdf"

Decrypt:

  SecretMemoryLocker.exe --decrypt "C:\docs\important_SMLkey.json"

I would love to get your feedback on the concept, the user experience, and any security assumptions I've made. Thanks!

value: Show HN: SecretMemoryLocker – File Encryption Without Static Passwords

author: YuriiDev


value: tommihip

value: Show HN: InferMesh – Open-source, GPU-aware inference mesh for large AI serving

author: tommihip


value: ajmalasver

value: We got Claude Code to create a music album about starting an AI startup using Suno. It created its own artist persona Censo, and launched the album with its own website. Check it out.

value: Show HN: Start+Up is an album made by Claude Code using Suno

author: ajmalasver


value: ieuanking

value:
Hi HN,
Ubik is built to strengthen and speed up the research process. With powerful academic search and PDF annotation tools, Ubik's AI agents can find, cite, and highlight quotes in relevant academic papers.
Our core belief (my friend and I) is that AI should help bring out the best in humans. What does this mean?
Reading, annotating, and citing real work (PDFs)!
Upload, or search and add papers to your workspace. Our AI Agents can create notes that can be referenced contextually when prompting using the @ sign to increase accuracy and efficacy. Ubik helps turn ideas into high-level work with citations.
If you aren't writing research papers or don't need to search for academic sources, Ubik is still a great everyday, general AI workspace. With access to 20+ models, web search, a text editor (canvas), and unique PDF highlighting tools, Ubik helps humans develop critical thinking skills while using GenAI.
We are Ubik. You are Ubik.
Everything is Ubik.

value: Show HN: Ubik – A new AI workspace for everything research. Search/Write/Cite.

author: ieuanking


value: glenntws

value:
Hey HN, we're Glenn and Julian, and we're building stagewise (https://stagewise.io), a frontend coding agent that inside your app’s dev mode and that makes changes in your local codebase.
We’re compatible with any framework and any component library. Think of it like a v0 of Lovable that works locally and with any existing codebase.
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.
Since our last Show HN (https://news.ycombinator.com/item?id=44798553), we launched a few very important features and changes: You now have a proprietary chat history with the agent, an undo button to revert changes, and we increased the amount of free credits AND reduced the pricing by 50%. We made a video about all these changes, showing you how stagewise works: https://x.com/goetzejulian/status/1959835222712955140/video/....
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 – frontend coding agent for real codebases

author: glenntws


value:
I built this tool to replace all other web based ad-laden tools I use to work with timestamps in my day job. All of these things exist on the web already, but I put them all in one place and built a workflow around them to make working with them easier.
- It takes natural language input (yesterday at 3pm)
- It can convert a timestamp into different timezones
- It can convert a timestamp into various formats (how many of us have looked up "epoch converter" on google?)
- It can calculate the time difference between two timestamps
- It can add or subtract a time duration to a given timestamp
- It can round a given timestamp to the nearest minute, hour, day, month, year, etc.
I also added a few QoL features
- History section that stores the results on your browser
- A button to copy a result in the history to input (Copy to Input). This allows you to chain multiple operations together
- Last used timezones and formats will persist on your browser across sessions to make common conversions quick and easy
Here's a demo video to show how it all works: https://www.youtube.com/watch?v=pcBwIcqBLk8
I apologize for the potato video quality. I used free trial software and this was the first time for me to record or edit anything.
Happy to take questions and feedback!

value: Show HN: DateTime Utilities

title: Show HN: DateTime Utilities


value: tccole

value: This is NOT a traditional library - it gives you production-ready data transformation primitives that you can modify to fit your exact needs. You own the code, with no external dependencies to manage or worry about breaking changes.<p>Inspired by shadcn's component approach: instead of importing a black box, you get battle-tested PySpark functions that live in YOUR repository. Handle email validation, address parsing, phone formatting.

value: Show HN: DataCompose – Composable data transformation primitives for PySpark

author: tccole


value: nivedit-jain

value:
Hey everyone, hackernews is great to get insights, but hard to navigate.
Created a bot (WhatPeopleWant) that goes through hackernews finds hot conversations to post them on X every 2 hours. What People Want - live on X: https://x.com/peoplewant_ code is opensource: https://github.com/NiveditJain/WhatPeopleWant

value: Show HN: Get insights from Hacker News on X

author: nivedit-jain


value: aconchillo

value: Show HN: Whisker, a real-time Pipecat debugger for your voice AI agents

author: aconchillo


value: pjcodes

value:
Hi again, HN.
Three weeks ago, I showcased my impulse control PWA, "Nope It," here on HN. The discussion and feedback I received were incredible, and I'm hugely grateful to this community for it.
The single most valuable piece of feedback I got was about friction. Many of you rightly pointed out that in that critical 5 second window on a shopping page, the mental energy required to open a separate app is often too high. The impulse wins by default.
You were right. So, I spent the last couple of weeks building the solution.
Today, I’m launching Nope It for Chrome.
It's a lightweight browser extension that uses JavaScript and DOM manipulation to inject a "psychological speed bump" directly onto product pages (I'm starting with Amazon, as it's the biggest culprit for me).
The core of the extension is the real time "Work Hours Psychology" engine. It shows you that a $200 gadget doesn't just cost money, it costs you a full day of your life. When you see that, you can log the impulse with a single click without ever leaving the page. It then syncs everything back to the core PWA.
I'm back here because your initial feedback is what created this. My main question for the HN community is, Does this frictionless, point of sale approach feel like the right solution to the problem you helped me identify? I’d love your thoughts on the UX and the overall strategy.
You can grab the new extension from the Chrome Web Store here: https://chromewebstore.google.com/detail/nope-it/imamiekokcj...
The main PWA is still here: https://www.nopeit.app
Thanks for helping me build this.

value: Show HN: I made a browser extension that exposes the hidden cost of shopping

author: pjcodes


value: leugim

value: Show HN: I built an image-based logical Sudoku Solver

author: leugim


value:
A while back I came across https://github.com/npm/npm-expansions, a fun repository where people came up with alternative meanings for "npm." By the time I found it, though, the repo was no longer being maintained.
So I decided to start my own version, not limited to npm, but covering all sorts of programming related acronyms as well.
It’s just a lighthearted fun project, nothing too serious. You can even use it in your own projects via its API :) though I do wonder where exactly you’ll end up using it.

value: Show HN: Expansions of Programming Related Acronyms


value: cat-whisperer

value: I would love some feedback on the design and the overall aesthetic of my website.

value: Show HN: Trying out industrial serif on my profile

author: cat-whisperer


value: We built Gonzo to make log analysis faster and friendlier in the terminal. Think of it like k9s for logs — a TUI that can ingest JSON, text, or OpenTelemetry (OTLP) logs, highlight and boil up patterns, and even run AI models locally or via API to summarize logs. We’re still iterating, so ideas and contributions are welcome!

value: Show HN: Gonzo – A Go-based TUI for log analysis (OpenTelemetry/OTLP support)


value: tccole

value: Reposting as I put up the wrong link

value: Show HN: DataCompose – Prevent downstream data failures with composite functions

story_text: Reposting as I put up the wrong link


value: devolt

value:
Hey HN,
I’m Anton, and I’m building ishotaphoto.com (https://ishotaphoto.com) — essentially a free photobooth in your pocket.
Just pick the type of document you need a photo for (Green Card lottery, Japan visa, China visa, etc.) — the app already knows all the current requirements. Then upload a selfie (or snap one with the iOS/Android app) and the app takes care of the rest:
 • Aligns your face
 • Removes the background
 • Ensures the correct head-to-photo ratio
 • Prepares the image with the correct size, dimensions, and format
 • Gives suggestions on expressions, smiles, glasses, etc.
The motivation came from my frustration with how expensive and inconvenient it is to get a simple ID/visa photo — whether at Walgreens or using other online services. I felt there should be something fast, simple, and free.
While the tool uses AI, it’s not the “LLM/ChatGPT” type you hear about everywhere — it’s built on computer vision, face detection, and some math to handle the requirements.
I’d love to hear your feedback — whether it’s about the product itself, the UX, or potential use cases I haven’t thought of.
Thanks!

value: Show HN: Ishotaphoto – a free photobooth in your pocket

author: devolt


value:
Hey HN!
I'm thrilled to introduce Pluely v0.1.2, my open-source alternative to Cluely, a Tauri-powered AI assistant that sits silently on your desktop. Pluely delivers real-time AI insights during meetings, coding sessions, or presentations: completely stealthy and lightweight (just ~10 MB).
What's new in v0.1.2?
Automatic Screenshot Mode: Pluely analyzes images with one click on the toolbar and gives you information based on your auto screenshot custom prompt.
Manual Screenshot Mode: Hit the toolbar button to capture multiple images and type your own prompt to give you solutions, analyze, or explain code.
Expanded STT & Custom Providers: Choose built-in STT options like Whisper, ElevenLabs, Deepgram, or plug in your own custom STT provider.
More AI Providers: OpenAI, Claude, Gemini, Grok, Mistral, Cohere, Perplexity are pre-configured. You can also easily add local or custom LLMs via the add custom provider interface on settings.
Why Pluely?
Ultra-lightweight: ~10 MB vs. 270 MB for Electron apps like Cluely
100% stealth mode: translucent overlay, undetectable in screen shares and recordings
One-click activation: Always-On, One Click Away: Sits quietly on your desktop for instant assistance with zero setup time
Privacy-first: all processing stays local (except your chosen LLM calls)
Cross-platform: native performance on macOS, Windows, and Linux
Future Developments(Continuously working to enhance Pluely with these highly requested features):
* System Audio Capture: Capture and transcribe audio from your computer applications, meetings, and system sounds
* Global Shortcuts: Customizable keyboard shortcuts (Ctrl/Cmd + /) for quick show/hide functionality
GitHub: https://github.com/iamsrikanthnani/pluely
If you’ve ever wanted a truly invisible AI sidekick that respects your privacy and enhances your workflow, please star  the repo, share feedback.
Let’s make Pluely the go-to stealth assistant!

value: Show HN: Pluely v0.1.2 – Stealth AI Assistant with Auto and Manual Screenshots


value: scal

value: Show HN: I built an AI trip planner

author: scal

title: Show HN: I built an AI trip planner


value: tapeo

value: Show HN: The browser that keeps your projects in order

author: tapeo


value: mrorigo

value:
Hey HN,
I wanted to share something I’ve been working on: *RAG-Guard*, a document AI that’s all about privacy. It’s an experiment in combining Retrieval-Augmented Generation (RAG) with AI-powered question answering, but with a twist — your data stays yours.
Here’s the idea: you can upload contracts, research papers, personal notes, or any other documents, and RAG-Guard processes everything locally in your browser. Nothing leaves your device unless you explicitly approve it.
### How It Works
- * Zero-Trust by Design*: Every step happens in your browser until you say otherwise.
- * Local Document Processing*: Files are parsed entirely on your device.
- * Local Embeddings*: We use [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v...) via Transformers.js to generate embeddings right in your browser.
- * Secure Storage*: Documents and embeddings are stored in your browser’s encrypted IndexedDB.
- * Client-Side Search*: Vector similarity search happens locally, so you can find relevant chunks without sending anything to a server.
- * Manual Approval*: Before anything is sent to an AI model, you get to review and approve the exact chunks of text.
- * AI Calls*: Only the text you approve is sent to the language model (e.g., Ollama).
No tracking. No analytics. No “training on your data.”
### Why I Built This
I’ve been fascinated by the potential of RAG and AI-powered question answering, but I’ve always been uneasy about the privacy trade-offs. Most tools out there require you to upload sensitive documents to the cloud, where you lose control over what happens to your data.
With RAG-Guard, I wanted to see if it was possible to build something useful without compromising privacy. The goal was to create a tool that respects your data and puts you in control.
### Who It’s For
If you’re someone who works with sensitive documents — contracts, research, personal notes — and you want the power of AI without the risk of unauthorized access or misuse, this might be for you.
### What’s Next
This is still an experiment, and I’d love to hear your thoughts. Is this something you’d use? What features would make it better?
You can check it out here: [https://mrorigo.github.io/rag-guard/]
Looking forward to your feedback!

value: Show HN: RAG-Guard: Zero-Trust Document AI

author: mrorigo


value: ogdakke

value:
Hi, I created this cli tool to help people decide which keys to remap where based on what kinds of characters appear in your directory.<p>It counts characters and sequences of characters, so you can see what kind of typing patterns appear for a given project or programming language.
Outputs table, json, csv and has a nice TUI with lots of filtering options

value: Show HN: Tool to optimize keyboard layout by counting characters

author: ogdakke


value: MauricioPinguim

value:
I made this as a side project because I've always loved music but never had a real instrument or lessons. It started as a simple piano to play online, but grew into something more:
- 100% free, no installation or login required
- Multilingual interface (EN/ES/PT, more coming)
- Works on desktop and mobile
- Step-by-step mode to learn songs interactively
Try it here: https://pianoeletronico.com.br/en
It’s not professional software, just a free and fun way to make music. Feedback and ideas are very welcome!

value: Show HN: Electronic Piano – A free online piano I built for fun

author: MauricioPinguim


value: Sohazur

value:
I built ReachLLM, which ranked top 5 in Product Hunt, but it still needs early adopters to improve.
The goal of the app is that it's a self-serving SaaS to track, analyze & improve AI search visibility (ChatGPT, Perplexity, Grok, Gemini, DeepSeek, and Claude).
The coolest features are:
- Brand Visibility to see in numbers, exactly how many times your brand is showing up in all AI models, and compare with the competitors.
- GEO Audit that checks through 20 different parameters to show the strengths and weaknesses in terms of all the best practices of GEO (Generative Engine Optimization).
- AI generator, where you can create different content to improve the visibility, and with the Brand Monitor to track progress.
The idea is to make it accessible for everyone and easy to use, so even small SMBs and SMEs don't fall behind in this AI Search Era.
I would love to hear feedback or answer any questions.
Here's the PH launch for more context: https://www.producthunt.com/posts/reachllm-2?utm_source=othe...

value: Show HN: ReachLLM to track, analyze and improve AI Search visibility

author: Sohazur


value:
Hey everyone, I’m an NBA fan and Python dev, and I recently built DeepShot — a machine learning model that predicts NBA game outcomes with about 71% accuracy based on historical stats and rolling performance metrics (EWMA). It features: Real NBA data from Basketball Reference Exponentially Weighted Moving Averages to track momentum Interactive NiceGUI interface with team comparison and predictions Full Python stack and open-source (MIT license) Here’s the GitHub repo: https://github.com/saccofrancesco/deepshot And if you like it, here’s my Buy Me a Coffee: buymeacoffee.com/saccofrancesco
Would love any feedback — especially from folks who’ve built sports models or worked on real-time stat tools. Also open to ideas on where to take this next (player-level modeling? betting advice dashboard?).

value: Show HN: DeepShot – an open-source NBA predictor with ML, EWMA, and live UI


value: yevbar

value:
Hi HN,
I made an MCP server for playing music from Sonic Pi which allows you to generate beats using Claude Code and Cursor.
Here's the GitHub - https://github.com/yevbar/live-prompting

value: Show HN: Live Prompting Music from Claude Code and Cursor (MCP Server)

author: yevbar


value: samsullivan

value: Built a tool to help people check for recalls on their vehicles. Uses both transport canada and nhtsa data updated daily.

value: Show HN: Check Any Car's Recalls

author: samsullivan

title: Show HN: Check Any Car's Recalls


value:
Hi,
Creator of TypeQuicker here.
Recently a customer emailed me that a certain key was not working on typequicker.com.
We went back-and-forth trying to figure out what the issue was. At first I thought the issue was with the website itself and that maybe there was a bug with how we read and processed user input.
After multiple deep-dives and a lot of back and forth with the user, it turned out that one of the keys on the user's keyboard was (occasionally) not activating and therefore not sending the key event. Out of about every 5-6 presses, it would miss one activation.
This Sunday we added a simple keyboard tester to our site. It visually shows your keyboard activation and has a input log which can be downloaded.

value: Show HN: Simple Keyboard Tester Tool

title: Show HN: Simple Keyboard Tester Tool