value:
Hi, HN!
I've been running GitHub Actions workflows for a while, and when GitHub announced ubuntu-slim runners as a cheaper alternative to ubuntu-latest, I wanted to migrate. (Blog: https://github.blog/changelog/2025-10-28-1-vcpu-linux-runner...)
But manually checking which workflows can safely migrate is tedious—you need to check for Docker usage, services, containers, execution times, and missing commands.
So I built gh-slimify, a GitHub CLI extension that automates this. It scans your workflows, detects migration candidates, checks for incompatible patterns, identifies missing commands, and can safely update workflows with one command.
Try it:
  gh extension install fchimpan/gh-slimify
  gh slimfy                    # Scan workflows
  gh slimfy fix                # Update safe jobs only
Open source (MIT). I'd love feedback on how to improve it or what edge cases I might have missed.

value: Show HN: Easily reduce GitHub Actions costs with Ubuntu-slim migration


value: fela

value: Show HN: Livestream of a coding agent controlled by public chat

author: fela


value:
Hey HN,
I'm the creator of Allos. For the past few weeks, I've been building a tool to solve a problem that's been personally frustrating me: every time I wanted to build an AI agent, I felt forced to choose between a simple framework that locked me into one provider (like OpenAI or Anthropic) or a complex one that felt like overkill.
I wanted the ability to switch the LLM "brain" of my agent on the fly without rewriting my code. For example, use GPT-5 for a coding task and then switch to Claude 4.1 Sonnet for a writing task, all with the same agent logic.
That's why I built Allos. It's an MIT-licensed Python SDK with a few core goals:
1.  True Provider Agnosticism: A unified interface for providers. The MVP has full support for OpenAI and Anthropic. The agent's code doesn't change when you switch.
2.  A Simple, Powerful CLI: The main way to interact is through a single allos command. You can give it a high-level task, and it will use its tools to get it done (after asking for permission for anything sensitive). E.g., allos "Create a FastAPI app in main.py and run it."
3.  Extensible Tools: It comes with secure, built-in tools for filesystem and shell operations. Adding your own custom tool is just a Python class with a decorator.
4.  No Magic: The architecture is simple and transparent. It's a straightforward agentic loop without a heavy layer of abstraction to fight against. The code is 100% unit tested.
Here's a 3-minute video showing it in action (including building a multi-file app from a single prompt): https://youtu.be/rWc-8awcAJo
The next big feature on the roadmap is first-class support for local models via Ollama.
I'm here to answer any questions. I'd love to get your feedback, critiques, and ideas.
Thanks for checking it out!

value: Show HN: Allos – An open-source, LLM-agnostic agentic SDK for Python


value: gutomotta

value: Hello, everyone. I'm a heavy keyboard user that loves Karabiner-Elements and has been using it a lot for a long time. I don't love to write Complex Modifications by hand, though. Found a few projects to facilitate that process, but I wanted something even more easily readable, which ultimately led me to create a (small) language.<p>The project is mostly written with assistance from AI, as a proficient Rust programmer might notice if they read the source code (I don't know Rust). It works, though, and I've been using it personally. I'm sure there are still bugs out there, but nothing that got in my way so far. If someone happens to actually try it, please do not hesitate to file bugs or provide feedback.

value: Show HN: SKRL is a language for expressing keyboard remaps and shortcuts

author: gutomotta


value: Show HN: Zettelkasten Interactive – 60KB knowledge tool for ADHD brains


value: CodeCrusader

value: I built this as a quick side project to see follow/unfollow patterns without handing over my Instagram password. It's straightforward — no signup required, no data collection.<p>I'd love to hear your thoughts

value: Show HN: Simple Instagram Unfollowers Tracker

author: CodeCrusader


value: Show HN: Launch coding agents from Apple Watch


value: eadanlin

value:
Hi HN, I built a website myfinsight.com that aims to make complicated company financials easy to understand.
The problem: The go-to place for financial data such as revenue, sales, net income is Yahoo finance. However, their data is usually wrong and very limited. The numbers are hard to digest to get insight quickly. There are also numerous websites that provide much better data for a very expensive monthly fee.
Solution: a website that provides free diagrams and charts that visualize important financial data, such as income growth rate by date, revenue breakdown etc. It is free because the financial data process is highly automated without manual input and correction.
I used to send the finance infographics to friends and family. I found it easier just to make a website and they can grab the data from it.
Next steps: there is a long tail of companies that don’t file their reports correctly. I am trying to make it more accurate somehow, and maybe add live stock prices to the website. I am also looking for feedback! Please play around with it and let me know if something is wrong.

value: Show HN: I built a website to visualize company financial data

author: eadanlin


value: mattcer

value:
I built Code Typer, a type racer for programmers that uses real code from open-source GitHub projects instead of lorem ipsum.
It currently supports 8 languages and includes IDE-like features such as auto-closing brackets and editor shortcuts.
Built with Next.js, Tailwind, Zustand, and Prisma.
Feedback is welcome!

value: Show HN: Code Typer – a type racer for programmers (with cool IDE-like behavior)

author: mattcer


value: igomeza

value: Show HN: Spam classifier in Go using Naive Bayes

author: igomeza


value: prouast

value:
Hi HN, I'm Philipp, the solo founder of Rouast Labs.
I've spent the last couple of years working on a new rPPG model, and I just published this blog post (which links to the full technical paper on arXiv) about the 2.0 version of my VitalLens API.
The main breakthrough is that the new model is now accurate enough to robustly measure Heart Rate Variability (HRV) metrics (SDNN, RMSSD) from a webcam feed, not just heart rate.
The blog post covers the new model architecture, the 1,400+ person training dataset, and performance benchmarks.
I'm here to answer any questions about the model, the tech, or the challenges of building a bootstrapped API.
Thanks for checking it out!

value: Show HN: VitalLens 2.0 – A new SOTA rPPG model for HRV estimation from video

author: prouast


value: cutandjoin

value: Show HN: I made an MP3 editor for Windows

author: cutandjoin


value: otterlang

value:
Hey HN! I’ve been building OtterLang, a small experimental scripting language designed to feel like Python but compile down to native binaries through LLVM.
The goal isn’t to reinvent Python or Rust, but to find a middle ground between them:
Python-like readability and syntax
Rust-level performance and type safety
Fast builds and transparent Rust FFI (you can directly import Rust crates without writing bindings)
OtterLang is still early and very experimental. the compiler, runtime, and FFI bridge are being rewritten frequently.
Please star the repo, and contribute to help this project.

value: Show HN: OtterLang – Pythonic scripting language that compiles to native code

author: otterlang


value: leonheuler

value:
I wanted to build an inference provider for proprietary AI models, but I did not have a huge GPU farm. I started experimenting with Serverless AI inference, but found out that coldstarts were huge. I went deep into the research and put together an engine that loads large models from SSD to VRAM up to ten times faster than alternatives. It works with vLLM, and transformers, and more coming soon.
With this project you can hot-swap entire large models (32B) on demand.
Its great for:
Serverless AI Inference
Robotics
On Prem deployments
Local Agents
And Its open source.
Let me know if anyone wants to contribute :)

value: Show HN: Serve 100 Large AI models on a single GPU with low impact to TTFT

author: leonheuler


value: I built DeepShot, a machine learning model that predicts NBA games using rolling statistics, historical performance, and recent momentum — all visualized in a clean, interactive web app. Unlike simple averages or betting odds, DeepShot uses Exponentially Weighted Moving Averages (EWMA) to capture recent form and momentum, highlighting the key statistical differences between teams so you can see why the model favors one side. It’s powered by Python, XGBoost, Pandas, Scikit-learn, and NiceGUI, runs locally on any OS, and relies only on free, public data from Basketball Reference. If you’re into sports analytics, machine learning, or just curious whether an algorithm can outsmart Vegas, check it out and let me know what you think: https://github.com/saccofrancesco/deepshot

value: Show HN: DeepShot – NBA game predictor with 70% accuracy using ML and stats


value: meysamazad

value: Show HN: Sitemap Harvester – Extract metadata from any website's sitemap to CSV

author: meysamazad


value:
Hi HN! I just released xleak, a terminal-based Excel viewer written in Rust.
I was inspired by working with spreadsheets and word documents on the command line and wanted something faster than opening Excel/LibreOffice. It supports .xlsx, .xls, .xlsm, .xlsb, and .ods files.
Key features:
- Interactive TUI with full keyboard navigation (vim-style search with / and n/N)
- View Excel formulas in cells
- Copy cells/rows to clipboard
- Export to CSV, JSON, or text
- Lazy loading for large files (1000+ rows)
- Jump to any cell (e.g., "A100", "500", or "10,5")
Built with the calamine crate for fast Excel parsing and ratatui for the TUI.
Installation: cargo install xleak, or Homebrew, Nix, or pre-built binaries.
Would love feedback on features or use cases I'm missing!
GitHub: https://github.com/bgreenwell/xleak

value: Show HN: Xleak – Terminal Excel viewer with interactive TUI and search


value: clarencehoward

value:
Hi HN, I built a location-based chatroom with Discord-like servers. This started as a portfolio project to learn WebSockets but has spiraled into something else entirely.
There are two features right now:
Drop - Single chatrooms that can only be seen within a specified radius and only last for a time less than 48 hours chosen by the user.
Hubs - Geofenced servers modeled after Discord. These are not time restricted. They can be created by anyone and the creator becomes the admin able to add channels and set rules. When a user enters the location’s area, they can join the hub and continue seeing messages even after leaving. Hubs cannot overlap, so once one exists in an area another cannot be created on it. The hub will persist as long as it is being actively used. If unused for two weeks, it will be deleted. (Still implementing this deletion aspect, so that is not in the landing page at the moment)
Why I built this.
I do not like the feel of most social media anymore, but I really like my university’s discord server. I wanted something more general that provided similar interactions. So I thought something that might work is a more general social app tied to location.
I think if it is done right it can recreate the atmosphere that I liked. I thought a lot about what that atmosphere is. I think for social media to feel natural it needs a “third thing”: a shared interest or object that creates a connection between two people, or a neutral ground for communication.
Having something in common just makes the interactions better and more useful. I think location can serve as general thing in common, especially if the servers are curated by locals.
It could also be a good way for people to immediately connect in a new place.
Right now, I’m just having fun building this thing. I would honestly like to use it if other people were on there… and it was built better and an app.
Feedback
I’m looking for any feedback. What’s a good idea or what’s a bad idea. This is really just a prototype, so there are some rough edges, and I am actively working on it. If you find any bugs and feel like communicating them, please do.  You can reach me at nhowar@uwo.ca

value: Show HN: Geofenced chat communities anyone can create

author: clarencehoward


value:
Hi HN,
I built a tool that rewrites AI-generated text to pass detection systems like Turnitin and CNKI (知网). Unlike simple paraphrasing tools, it uses semantic understanding to maintain meaning while removing AI fingerprints.
Technical approach:
- Analyzes sentence structure patterns typical of LLM outputs
- Rebuilds content using varied syntax and vocabulary distributions
- Preserves academic tone while reducing AI detection scores from 80%+ to <20%
Tested on: CNKI (知网), VIP (维普), WanFang (万方), and Western detection systems
Try it: https://www.yanbiai.com/tools/paper-pass?ly=hackernews
Would love feedback from the community, especially on:
1. Ethical considerations (I know this is controversial)
2. Technical improvements to the rewriting algorithm
3. Detection evasion vs. genuine writing assistance
Free tier available for testing.

value: Show HN: AI text rewriter with 90%+ detection pass rate


value: DanexCodr

value: Show HN: Coderive – Programming Language built on a phone

author: DanexCodr


value: stephantul

value:
Hey HN,
I've been playing around with ways to make retrieval pipelines faster, and ended up building something I'm calling PyNIFE (Nearly Inference-Free Embeddings).
The idea is simple: train a static embedding model that's fully aligned with a bigger "teacher" model, so you can skip expensive inference almost entirely. In practice, that means 400-900× faster embedding generation on CPU, while still working with the same vector index and staying compatible with your existing setup.
You can even mix and match: use the original model for accuracy when you need it, and PyNIFE for ultra-fast lookups or agent loops.
It's still early, and I'd love feedback, especially on where this might break, what kinds of workloads you'd test it on, and any ideas for better evaluation or visualization.
Repo: https://github.com/stephantul/pynife

value: Show HN: PyNIFE. 400-900× speedup for embedding-based retrieval pipelines

author: stephantul


value: jlemee

value: Show HN: Tech Job Notify

author: jlemee

title: Show HN: Tech Job Notify


value: IdKaiser

value: ¡Hola HN! Somos estudiantes de Colombia y este es nuestro proyecto final. Es una app simple en Flask para monitorear el gasto de servicios. Está en un servidor gratuito de PythonAnywhere, ¡así que tengan paciencia si se cae! Nos encantaría su feedback técnico.

value: Show HN: Zenith – Una app en Flask de nuestro proyecto para monitorear servicios

author: IdKaiser


value: Show HN: Notion for Research

title: Show HN: Notion for Research


value: lsmael

value:
Hi HN,
I made a small wishlist tool to avoid duplicate gifts and awkward coordination.
You create a list and share a link.
Friends can reserve an item so others don’t buy it.
The list owner doesn’t see what’s reserved, so the surprise stays.
No login required.
Fast input
Example: https://fast-wishes.com/l/ismael
Built with Supabase and Next.js. Feedback welcome.

value: Show HN: Fast Wishes – A shareable wishlist built to avoid unwanted gifts

author: lsmael


value: tuxxness

value: Show HN: Super Tux War – Opensource Godot 4 clone of Super Mario War

author: tuxxness


value: magnusi

value:
Hey guys,
I am kind of an amateur at web development (I mostly did linux/embedded professionally), and wanted to do something fun and unique, so I made a website for selling my stock photos as a hobby photographer.
It is built in Common Lisp using Hunchentoot and HSX, very gently integrates it PayPal (this was by far the most painful thing), and uses HTMX to make switching pages smoother.
I am also implementing active search as we speak.
Developing things with Lisp and HTMX interactively was a breath of fresh air, I loved being able to keep around several versions of a function and swap them around at runtime without having to restart.
The fact that Lisp universally speaks s-expressions is also super handy, as I did not have to worry about formats.
(The photo metadata is just serialized to an s-expression, I don't think I will have too many of them to justify sqlite for that).
One thing I did because I am paranoid was adding type signatures everywhere, the serapeum library gives them a nice syntax:
(-> get-image-dimensions (string) (option (cons integer integer)))
(defun get-image-dimensions (jpeg-path)
  "Get image dimensions using ImageMagick identify."
  (handler-case
      (let* ((full-path (format nil "files/photos/~A" jpeg-path))
             (output (uiop:run-program
                      (list "identify" "-format" "%wx%h" full-path)
                      :output :string
                      :ignore-error-status t)))
        (when output
          (let ((parts (split-sequence:split-sequence #\x (string-trim '(#\Space #\Newline) output))))
            (when (= (length parts) 2)
              (cons (parse-integer (first parts))
                    (parse-integer (second parts)))))))
    (error () nil)))
All in all, it is a pretty small project, I started it on Friday and just put it live a few hours ago:
--------------------------------------------------------------------------------
 Language             Files        Lines        Blank      Comment         Code
--------------------------------------------------------------------------------
 Lisp                    10         1338          179           14         1145
 CSS                      1          494           78            0          416
 Bourne Shell             1           51           13            3           35
--------------------------------------------------------------------------------
 Total                   12         1883          270           17         1596
--------------------------------------------------------------------------------
The shell script just creates preview pictures for photos with my watermark.
I am here mostly to look for feedback because I don't like bloated webs, but I also would like to better at making my tiny web more usable :)
I think I am pretty clueless at UX/UI design, so I am glad for any advice, hahaha.
My plan is to clean the source code (I may have kinda been tempted to hardcode some secrets when I was losing my mind over PayPal) and make it opensource within the next few days.
Thanks guys for any feedback,
Lukáš Hozda

value: Show HN: Lho.sh my new Common Lisp+Htmx personal web for selling stock photos

author: magnusi


value: dulvui

value: Show HN: 99Managers – A libre sports management game made with the Godot Engine

author: dulvui


value: trrahul

value:
I built SharpFocus, a static analysis extension for C# that brings program slicing to VS Code. It's heavily inspired by Flowistry for Rust.
Click any variable, and it instantly highlights its complete data flow (what influenced it, and what it influences), fading out all irrelevant code. It's designed to make debugging and understanding complex methods faster. The analysis is powered by Roslyn.
It's open-source, and I'd appreciate any feedback.
GitHub: https://github.com/trrahul/SharpFocus
VS Code Marketplace: https://marketplace.visualstudio.com/items?itemName=RahulTR....

value: Show HN: SharpFocus – A Flowistry-inspired data flow analysis tool for C#

author: trrahul


value: RWejlgaard

value:
Hello everyone I wanted to share a program I've been working on.
I'm writing this primarily for myself and my own setup. I found emacs keybinds too hard to memorize and too unintuitive.
It's still a little early in development but it works for my own use case. Please let me know of any improvements that would be nice to have

value: Show HN: A simple TUI orgmode editor inspired by nano and k9s

author: RWejlgaard


value: PhilKunz

value: Show HN: Nupst v5 –> Deno based shutdown tool protecting against power outage

author: PhilKunz


value: ebenezerdon

value:
Hey everyone, I've been working on teda.dev for the past month. And to be honest, I was tired of seeing tools that promise to “build production apps” but end up producing the same AI-like sites you can spot a mile away.
There are several platforms out there that keep trying to position themselves as replacements for developers, but the apps they make are nowhere near production quality. They’re bloated, clunky, and always tied to their own systems and external dependencies.
With Teda, I'm not pretending to replace developers. If you were going to build the next Facebook, you'd hire a team of engineers. If you were building a production SaaS focused on revenue, you'd put AI coding tools like Cursor or Copilot in the hands of engineers. You won't be thinking of "vibe coding platforms" for that.
Teda focuses on what people who use these platforms actually want: simple, working apps that solve everyday problems. You describe what you want, and Teda builds it in a few minutes.
And I have to say this directly - Teda apps UI and UX are far better than anything you’ll get from Lovable, Bolt, or V0. Not just slightly better, but by a wide margin.
You can confirm it yourself: just use the same prompt across all of them and look at the results.
To be clear, Teda is not for building complex production SaaS or live dashboards that need a server. The other platforms that claim to do this don't do it well anyway.
Teda is for focused tools that run entirely in the browser.
No frameworks, no servers or build step. Just clean HTML, CSS, and JavaScript that you can run anywhere and own completely.
This is something that means a lot to me and I've been using Teda a lot myself. The ability to quickly prototype apps and build tools for day-to-day issues I face has been a dream come true.
An example from just yesterday, I wanted to download an Instagram video and the apps that offer this are filled with ads and so many clickbaits, so I just asked Teda to build it and I had my working app in a few minutes: https://ebenezerdon.github.io/reelfetch-instagram-video-down...
This is just one small example out of the numerous apps I've built with Teda. From things like the meal planner we now use at home, to an application I use to doodle, make stickers, convert images or generate handwriting practice sheets for my daughter.
You'll find some examples on https://teda.dev and on my GitHub: https://github.com/ebenezerdon
If you’ve ever wanted to turn your idea into a working app without the noise, try Teda. You’ll see what I mean.

value: Show HN: Teda.dev – AI app builder that beats Lovable

author: ebenezerdon


value: Show HN: Active Memory Plugin in Claude Code


value: bobnarizes

value: Show HN: Floxtop – Offline Mac app that organizes files and images by meaning

author: bobnarizes


title: Show HN: Active Memory Plugin in Claude Code


value: cpuXguy

value: This project explores how to compute the complex zeta function in plain JavaScript, and you can test the code using the built-in calculator on the site.

value: Show HN: Complex Zeta Function in JavaScript – deep math

author: cpuXguy


value: ParsOS-NEXT is a robust and highly functional Mobile Operating System Simulator built entirely in Python. It features a polished graphical user interface (GUI) implemented with Pygame, including modern visual elements like blur effects and smooth animations. Also it has a web browser and it's support simple application downloading with .PRS format from file manager.

value: Show HN: ParsOS NEXT a GUI OS Simulator in Python


value: isoubelet

value:
Hi HN - I built Kubling, a lightweight data federation engine.
This repo shows a practical, reproducible way to scale embedded Camunda 7 horizontally: distribute groups of tables across multiple data sources and have Camunda talk to Kubling as if nothing changed.<p>Includes reproducible tests and configs.
This is WIP - collaboration is welcome.

value: Show HN: Kubling: make Camunda 7 use distributed tables without changing Camunda

author: isoubelet


value: oktaydak

value:
I built a modern office furniture catalog using Next.js 15.1.5 with React 19 and TypeScript.
Key Features:
-  11 language support (TR, EN, DE, FR, ES, IT, PT, AR, RU, ZH, JA)
-  Mobile-first responsive design
-  High performance (SSR, ISR, image optimization)
-  Advanced search and filtering
-  AI-powered blog system (Groq AI integration)
-  Project references showcase
-  Contact forms with WhatsApp integration
-  Admin panel with GitHub API integration
-  PWA support
Tech Stack:
- Next.js 15.1.5 (App Router)
- React 19.0.0
- TypeScript 5
- TailwindCSS 3.4.1
- Framer Motion 12.3.0
- Groq AI SDK (blog generation)
- GitHub API (content management)
Stats:
- 141+ TypeScript/TSX files
- 24,627+ lines of code
- 50+ products
- 13 API endpoints
- 100+ React components
What I learned:
- Next.js App Router best practices
- Complex i18n implementation (11 languages)
- Image optimization strategies
- Performance optimization (memoization, lazy loading)
- Accessibility improvements (WCAG compliance)
- Mobile-first design patterns
Live Product: https://www.ofistek.com.tr
Would love feedback on UX, performance, and code structure!

value: Show HN: Modern office furniture catalog built with Next.js

author: oktaydak


value: Show HN: I built a Chrome extension that creates flashcards from YouTube videos


value: ziadhussein

value:
Hey HN!
I built an app that takes what products are currently hot and adds a little feasible twist for you to build. The results are fine tined and enables you to niche in (or out) of these apps to get a slice of the pie.
I'd love to know what you think!

value: Show HN: I built a free app idea generator with a twist

author: ziadhussein


value: marcosiino

value:
Hello everyone,
I’ve been building [Pipeflow-php](https://github.com/marcosiino/pipeflow-php), a PHP pipeline engine to automate anything — from content generation to backend and business logic workflows — using core modular stages and custom implemented stages (that can do anything), with the key power of using an easy to reason and read XML to define the pipeline logic, which every actor in a company, even non developers, can understand, maintain and edit.
It’s a *headless engine*: no UI is included, but it's designed to be easily wired into any backend interface (e.g. WordPress admin, CMS dashboard, custom panels), so *even non-developers can edit or configure the logic*.
It surely needs improvements, more core stages to be implemented and more features, but i'm already using it on two websites i've developed.
In future I plan to port it in other languages too.
Feedback (and even contributions) are appreciated :)
---
Why I built it
I run a site which every day, via a cron job:
- automatically generates and publish coloring pages using complex logics and with the support of the generative AI,
- picks categories and prompts based on logic defined in a pipeline,
- creates and publishes WordPress posts automatically, every day, without any human intervention.
All the logic is defined in an XML pipeline that's editable via wordpress admin panel (using a wordpress plugin I've developed, which also adds some wordpress related custom stages to Pipeflow). A non-dev (like a content manager) can adjust this automatic content generation logic, for example by improving it, or by changing the themes/categories during holidays — without touching PHP.
---
What Pipeflow does
- Define pipelines in *fluent PHP* or *simple, easy understandable XML (even by non developers), directly from your web app admin pages*
- Use control-flow stages like `If`, `ForEach`, `For`
- Execute pipelines manually, via cron, or on any backend trigger which adapts to your business logic
- Build your own UI or editor on top (from a simple text editor to a node based editor which outputs a compatible XML-based configuration to feed to pipeflow)
- Reuse modular “stages” (core and custom ones) across different pipelines

value: Show HN: Pipeflow-PHP – Automate anything with pipelines even non-devs can edit

author: marcosiino


value: hoxihan

value: A lightweight web interface for generating images with NanoBanana models. Currently supports NanoBanana and adding NanoBanana 2 soon. Built for experimentation and reproducibility.

value: Show HN: I made a image generator gempix2 generatored by nano banana 2 and 1

author: hoxihan


value:
https://youtu.be/OWQyADqIE4I
I built n8n + Memmachine chatbot

value: Show HN: Episodic/Profile Memory for N8n


value: sentomk

value: Show HN: Patternia – A compile-time compile-time pattern matching DSL for C++

author: sentomk


value: varik

value:
I built anicha.earth because I kept needing a fast, no-frills way to see how a place changes over time — not once a year, but every week or so.
Recently I worked on super-resolution for Sentinel-2 (about 8–10× upscaling) for an agriculture project. Along the way I realized two things: (1) this could be useful beyond ag, and (2) I couldn’t find a tool that lets you pick any area and quickly scrub through years of imagery. So I made one that’s as simple and as fast as I can make it.
Under the hood it uses Copernicus Sentinel-2 L2A (10 m/pixel). With S2A+B the nominal revisit is ~5 days (depends on clouds; with Sentinel-2C the cadence is tighten further). For any area you select, the app gathers all available scenes since 2018 and shows them on the map and in a time strip for easy scrubbing.
There’s AI-Enhanced view: a super-resolution model that makes it toward ~1–2 m. The model was trained on millions of satellite/aerial images, primarily open NAIP data.
This is an early beta and a bit rough.
I’m most curious about now is where this is actually useful?
https://anicha.earth

value: Show HN: Every-few-days satellite timeline for any spot, Sentinel-2 SR

author: varik


value: ddevid

value:
MainyDB is an embedded, file-based database for Python that brings MongoDB-style document storage and querying into a single .mdb file.
It’s lightweight, requires no external server, and works completely offline.
You can use it either with its own Pythonic syntax or in PyMongo compatibility mode, meaning you can often switch from MongoDB to MainyDB by simply changing the import.
What It Does
MainyDB stores data in a single .mdb file and allows querying using Mongo-style operators ($gt, $in, $set, etc.) as well as aggregation pipelines ($match, $group, $lookup, ...).
It supports async writes, thread-safe access, and can automatically handle binary data like images or videos through base64 encoding.
PyPI: https://pypi.org/project/MainyDB
GitHub: https://github.com/dddevid/MainyDB
Key Features
Single-file storage (no server process)
Two syntax modes:
• Own Pythonic syntax
• PyMongo compatibility (drop-in style)
Aggregation pipeline support ($match, $group, $lookup, etc.)
Thread-safe with asynchronous file writes
Built-in binary/media storage (auto-encoded)
Works entirely offline
Target Audience
MainyDB is designed for:
Developers building local or embedded Python apps
Prototyping tools, AI experiments, and desktop applications
Automation scripts that need persistent storage
Students and indie developers who want Mongo-style queries without setup overhead
Not intended (yet) for large-scale production systems; the focus is on simplicity, portability, and fast local development.
Comparison
Feature MainyDB MongoDB TinyDB SQLite
Server required No Yes No No
Mongo syntax Yes Yes No No
Aggregation pipeline Yes Yes No No
Binary/media support Built-in Manual No No
File-based Single .mdb No Yes Yes
Thread-safe + async Yes Yes Partial Depends
MainyDB aims to bridge the gap between MongoDB’s expressive document model and TinyDB’s simplicity, giving Python developers a true embedded NoSQL option.
Feedback
It’s an early-stage project. I’d love feedback, benchmarks, feature ideas, and critiques.
Is this something you’d use for small apps or prototypes?
Repo: https://github.com/dddevid/MainyDB
PyPI: https://pypi.org/project/MainyDB

value: Show HN: MainyDB – an embedded MongoDB-style database for Python

author: ddevid


value: SahooShuvranshu

value:
Hello HN,
I built and open-sourced Spotify-Live-Banner, a project designed to embed a dynamic, real-time image of the user's currently playing Spotify song into their online profiles (primarily GitHub READMEs).
*Technical Details:*
* Built as a minimalist web service using *Python (Flask)*.
* Authenticates via Spotify API to pull live track data.
* Dynamically renders a customizable SVG image based on that data.
* Configured for easy, free deployment on Vercel.
It's intended as a polished, customizable utility for developers looking to add dynamic content to their profiles.
I'd appreciate any technical feedback on the Flask implementation or the SVG rendering approach.
*Live Demo:* [https://spotify-live-banner.vercel.app](https://spotify-live-banner.vercel.app)
*GitHub Repo:* [https://github.com/SahooShuvranshu/Spotify-Live-Banner](https://github.com/SahooShuvranshu/Spotify-Live-Banner)

value: Show HN: Spotify Live Banner – Real-Time 'Now Playing' Widget for GitHub READMEs

author: SahooShuvranshu


value: ombedzi

value:
React Source Lens is a development tool that lets you inspect React component source code directly in the browser.
How it works:
Add
useReactSourceLens()
 to your React app
Hover over any component in your app
Press Cmd+Shift+O (Mac) or Ctrl+Shift+O (Windows/Linux)
A modal appears with the file path and line number
Click "Open in VS Code" to jump directly to the source code
Key features:
Visual overlay shows which component you're hovering over
Works with React's debug information (development mode)
Optional Babel plugin for enhanced source detection
VS Code integration with vscode:// protocol
Toggle overlay with Cmd+Shift+L
Installation:
npm install react-source-lens
Usage:
javascript
import { useReactSourceLens } from 'react-source-lens';
// Basic usage
useReactSourceLens();
// With VS Code integration
useReactSourceLens({
  projectRoot: '/path/to/your/project'
});
Why it matters: When working on large or unfamiliar React codebases, finding component definitions can be time-consuming. This tool eliminates that friction by providing instant source code navigation.
Built with modern React and works with Vite, Create React App

value: Show HN: React Source Lens – Jump from UI components to source code in one click

author: ombedzi


value: Show HN: Task Sentry – Context-Aware AI Blocker, 100% in Chrome (Prompt API)


value: uaghazade

value:
Hi, I'm software dev with 2x exit.
I collected some affordable alternatives to expensive and well-known tools for a while. Mostly for personal use.
Now I built the platform and added them here. Also, community help to grow with their tools and suggestions.
Enjoy and if you have any alternative for popular softwares or have a suggestions please submit here to make it the internet's biggest alternative software platform.

value: Show HN: A directory of better alternatives to well-known softwares

author: uaghazade


value:
Hi HN, I'm the builder of LinkPatrol.
As someone who works with content creators, I was frustrated by the problem of "link rot." Creators who monetize with affiliate links are constantly losing revenue because links in their old content (blog posts, YouTube descriptions) silently break, leading to 404s or out-of-stock product pages.
I looked for a tool to fix this, but the existing solutions were either locked into a single ecosystem (like Amazon-only scanners) or were overly complex, expensive enterprise platforms. There was no simple, free tool for the average "prosumer" creator who uses multiple affiliate merchants.
So, I built this MVP. LinkPatrol is a 100% free, merchant-agnostic web app.
Technically, it's a simple scanner. You give it your youtube channel (website coming soon), and it crawls your videos' descriptions to identify broken hyperlinks (404s) and, just as importantly, links to product pages that are "Out of Stock." The goal is to give creators a simple report so they can go fix the links that are costing them money.
It's still very much an MVP, and I'm posting it here to get honest technical feedback on the scanning process, its utility, and any bugs you find. The app is at www.linkpatrol.in. I'll be here all day to answer questions.

value: Show HN: LinkPatrol – Free merchant-agnostic tool to find broken affiliate links


value: Gordonbuilds

value:
I wanted a Markdown editor that opened instantly in a browser tab, autosaved locally, and didn’t require a desktop app or account. (Always there, always instantly accessible.)
Since none really fit that workflow, I built Quartext: a single-file Markdown editor (pure HTML, CSS, JS).
Goal:
Quartext is a life organizer that's always there. Keep track of ideas, plans or even cool websites you find!
I would appreciate any feedback you can give!
Demo: https://buildsgordon.github.io/Quartext/
Repo: https://github.com/buildsgordon/Quartext/

value: Show HN: Quartext: a live-preview, single-pane Markdown editor from HTML

author: Gordonbuilds


value: alexpadula

value: Show HN: TidesDB – Fast, transactional storage optimized for flash and RAM

author: alexpadula


value: polymonster

value: An app I have been working on for a while to improve the ergonomics and responsiveness of browsing online record shops

value: Show HN: Diig: a music discovery app for record diggers

author: polymonster


value: orbitalremnant

value: Turns a directory of Markdown and text files into a single, self-contained index.html with built-in search and tag filtering. Besides, one can generate social media sharing links with -share "PROVIDER_NAME:URL_TEMPLATE".

value: Show HN: Picoblog – A minimalistic static site generator written in Rust

author: orbitalremnant


value: Show HN: P2P poker chip tracker built with vanilla JavaScript and WebRTC


value: Rindrics

value: Show HN: Automate recurring GitHub project items from YAML config

author: Rindrics


value: Show HN: Fast Semantic Tool-filtering for MCP servers


value: jsdeme

value:
Hey HN! I built NyxProxy because I was tired of getting rate-limited when scraping.

  The key insight: Most VPS providers give you a /64 IPv6 subnet (18 quintillion addresses!)
  but nobody uses them. NyxProxy rotates through 200+ IPv6s automatically - every request
  looks like a different user.

  Performance:
  - <100ms per request (pre-populated IP pool)
  - Handles 100K+ concurrent connections
  - Zero rate limiting (each IP is fresh)

  One-command setup on Ubuntu/Debian. Already handling millions of requests in production.

  Tech stack: Go, ndppd for NDP proxying, intelligent IP rotation algorithm

  Would love feedback on the rotation strategy!

value: Show HN: NyxProxy – Destroy rate limits with IPv6 rotation (100K+ req/s)

author: jsdeme


value: sumit-paul

value:
If you’ve integrated LLMs into your app, you’ve probably noticed the subtle “AI fingerprint” in the text — those em–dashes (—) and en–dashes (–) that show up everywhere.
They’re grammatically fine, but UX-wise, they make AI output feel less human. Most users can’t name it, but they can sense something “off” about the writing tone.
Slash-Dash is a small Node.js package that fixes this automatically.
It replaces em/en-dashes with natural punctuation (commas, colons, periods, etc.) based on linguistic context, using lightweight natural language understanding (NLU).
Use cases
- Chatbots and assistants
- Text summarizers
- Writing helpers and email generators
Any LLM-based product where language tone matters
The goal is simple: make AI-generated text feel human again.

value: Show HN: Slash-Dash: Remove LLM Em-Dashes for More Human Output

author: sumit-paul


value: reuven

value: This is a a free, 12-part practical introduction to uv for people who already know Python and want to (a) know what the fuss is about and (b) how to incorporate uv into their daily routines.

value: Show HN: Uv Crash Course

author: reuven

title: Show HN: Uv Crash Course


value: norocvit

value:
Hey, I am Victor, a french student.
I was tired of getting really bad recommandations from the algorithm, always the same videos, same topics. So I created a community-driven recommandation tool, with upvotes like Product Hunt or Hacker News.
Looking for something to watch or want to share something you liked? Feel free to check the site, it's free, no account needed (unless you want to share or upvote a video).

value: Show HN: I built Product Hunt but for YouTube videos

author: norocvit


value: robbschmidt

value: Going into x402 protocol with 2 APIs - OCR/Audio to structured output. New react interface + PWA. Building.

value: Show HN: PayGo.Network – AI Marketplace, New Unified UX and X402

author: robbschmidt


value:
Hey HN, I was building a project where I needed to compare multiple browser-agents at once, so I built The Browser Arena.
It’s a website where you can run several agents side-by-side and see, in real time, which model performs best on the exact same task. You also get some metrics, such as cost and speed.

value: Show HN: The Browser Arena - Run & compare browser agents side by side


value:
Hey HN – Akshay & Ashwin here, founders of Spine AI (YC S23). We’d like to show you our new product: Spine Canvas.
TL;DR: Spine AI is an infinite visual workspace where you can collaborate with 300+ AI models and agents to think and create better than you would in a single chat. You can try it without signing up: https://app.getspine.ai/guest
Backstory:
We started building multilingual RAG in 2022, got into YC S23, and through multiple iterations learned that users want iteration and control - not just another chat interface.
ChatGPT was originally meant to collect training data for GPT’s next version — but it blew up because it made AI accessible. While chat is great for Q&A, it’s terrible for thinking: you get stuck in linear threads, the only way to iterate is to send another message, and you can’t control how much of the previous context the model actually remembers.
Each model also has its own “superpower”: Claude is great for coding, Gemini for critique, Grok for marketing. I often use different LLMs as advisors, because each brings a slightly different lens – useful when you’re thinking deeply, exploring tradeoffs, or checking blind spots.
So we built Spine:
Spine Canvas lets you think in blocks instead of threads. You can connect blocks, which ensures implicit context passing. You can also explicitly refer to connected blocks as part of the current block’s parameters.
We have dedicated blocks for: Image generation, deep research reports, slides, chats, prompts. All of these can pass context seamlessly between each other.
Because it’s a canvas, you can branch — explore rabbit holes without losing the main path. You can swap models freely. Lists are first-class citizens: run the same process across multiple items (e.g., “deep research these 10 companies”) simultaneously. You can change a single block and trickle updates through the entire branch.
To help with the blank-canvas problem, we have an AI assistant that helps you get thinking right away by building you your initial canvas. You can also bring in context from outside – chats from other LLMs, YouTube videos (with transcripts), or web pages – and treat them like native blocks on the board. We also have Miro-style notes and shapes to let you add human context directly into your AI workspace.
How we use it (and who else does):
The simplest way to use Spine is to chat with the latest models, branch the conversation at any point, and continue it with different models on the same board.
As a visual founder, I use Canvas to map GTM, product priorities, and engineering decisions. For example, the prompt engineering for our upcoming App block came from exploring how six different LLMs reasoned about the system prompts of other AI tools – all in one board, in under 20 minutes. I hit “flow” a lot more because everything lives in a single workspace.
Founders have been surprisingly early adopters – probably for chaos-meets-structure reasons. Product folks, especially those who use tools like Miro or FigJam, use it for strategic planning, prioritization, and finding blind spots or connections in their roadmaps.
Investors use it for market research since our deep research reports are more comprehensive and easier to iterate on than the chat LLMs. And we’ve seen some power users use it for learning new concepts.
The Ask:
Give it a try and tell us what you think.
You can use it right now without signing up: https://app.getspine.ai/guest
If you create an account, there’s a free plan with 2,000 monthly credits + 500 daily (credits scale with underlying model costs).
If you want to chat: founders@getspine.ai, Discord: https://discord.gg/KuHzF6zBPs
Appreciate your time!

value: Show HN: Spine AI – Visual workspace to think across multiple AI models


value: bahcimaster

value:
I’ve been working on a large automation collection using n8n —
260+ workflows covering AI, finance, Notion, Sheets, and CRM tasks.<p>If anyone’s curious, I can share the link in a comment.

value: Show HN: N8n workflows for AI, finance, and business automation

author: bahcimaster


value: mrunix

value: Show HN: A 100% vibecoded programming language interpreter

author: mrunix


value: firehose

value:
I love long-form podcasts, but I'm constantly frustrated by the signal-to-noise ratio. Scrubbing through a 2-hour conversation to find the 5-minute insight is a huge waste of time, and existing search tools just dump you at the start of the episode.
So, I started building Firehose. It's not another podcast search engine.
Instead, Firehose points you to the key insights, the core ideas, the turning points—and serves them up as short, digestible clips.
The UX is a single feed (think TikTok, but for ideas). You listen or skip, and the recommendation model (in theory) learns what you're interested in. If a clip hooks you, one tap jumps you to that exact moment in the full episode for context.
My goal is to make those "in-between" moments (waiting for a build, grabbing coffee) actually useful for discovery.
It's very early and the models are still naive. I'd genuinely appreciate some brutally honest feedback from the HN community.
Does this feel like it solves a real problem for you?
What's the first thing that seems broken or missing?
Happy to answer any questions. Thank you for your time!

value: Show HN: I'm trying to fix podcast discovery by finding the 'aha ' moments

author: firehose


value: RealzDLegend

value:
Hi HN,
I've been working on something that started as personal frustration and turned into what I think might be a different way of thinking about AI agents. The problem: Repetitive work is unavoidable if you want to grow at anything. Building an audience, managing research, shipping products, etc. they all require those soul-crushing repetitive tasks. The 1% inspiration, 99% perspiration thing is real.
I tried n8n, Make, Zapier. They work, don’t get me wrong, but the setup time doesn't make it worth the output once you're automating multiple workflows. They're deterministic but brittle and not adaptive. The tight coupling means one change breaks everything. The Agent-based ones were more like interns than employees: they won’t work if you don’t prompt (and in a particular way or style), couldn't generalize, and didn't fit how real teams actually work.
So I started asking; what if you could onboard an AI agent the way you onboard a human? What if it could pursue long-term goals autonomously, without you prompting it every step? What if it could be deterministic without being brittle? You know? Better output with a more seamless input. That's why we built Compose AI. Instead of you prompting the agent, the agent prompts you. Each agent has a job description (like you'd write for a human hire) that defines expectations and outcomes. You onboard them on your data - apps, drive, APIs, databases, documents - and they build a knowledge graph to understand relationships across your organization without explicit “tight-coupling".
Key differences: - Autonomous goal pursuit: Tell an agent what to accomplish, not how to do it. It creates its own task list and executes. - Human-like onboarding: Create agents using regular job descriptions containing your workflow and expectations. - Multi-channel interaction: Email, voice, soon phone and Teams. You're not locked into a UI. - Local browser automation: For tasks requiring a browser, agents can connect to your local computer browser. They work on a separate workspace on your computer - your browsing data stays local. Cloud browsing is also possible. - Stack integration: Works across Google Docs, Notion, CRMs, whatever you're already using. You don't need to be technical or be an expert at prompt engineering.
You just need a clear job description, which includes your workflow and expectations. The system handles the rest.
We have some pre-configured digital employees you can activate immediately (with job descriptions defined by us), or you can create your own. I see this as inverting the current paradigm - instead of humans adapting to how AI wants to be prompted, AI adapts to how humans already organize work. Maybe it's a glimpse into how human-machine collaboration evolves. Maybe it's just a better way to stop doing repetitive tasks. Either way, I'd love for you to try it and tell me what breaks.
Try it here: https://composeai.io
Looking forward to your feedback - especially the brutally honest kind.

value: Show HN: A platform that creates AI Agents using 'job descriptions'

author: RealzDLegend


value: Turn ideas into quality prompts ready to run in agent builders like Cursor, Lovable, and more.

value: Show HN: IDE for Vibe Coders

title: Show HN: IDE for Vibe Coders


value: mrprmiller

value: Show HN: I'm a pastor/dev and built a 200M token generative Bible

author: mrprmiller


value:
Voice memos are great until you try to find something later.
I built NoteFLW to fix that — it listens, summarizes, and organizes everything you say, automatically.
No more scrolling through 200 recordings of “meeting notes” and “idea from last night.”
It’s early, still rough around the edges, but surprisingly effective.

value: Show HN: We built an AI note app because voice memos are chaos


value: ebogdum

value: I built Steadykey after fighting duplicate API calls and messy idempotency logic in our queue workers. It canonicalizes any JSON payload (order-insensitive, handles Maps/Sets/BigInts) and hashes it to a stable key, then lets you drop markers into Redis, Postgres, MySQL, MongoDB, SQLite, or an in-memory adapter. You can opt in to storing the canonical payload, refresh TTLs, or clear markers when a workflow finishes. I’d love feedback on the hashing semantics, adapter API, and any gaps in the docs/examples—especially if you’ve rolled your own idempotency layer before.

value: Show HN: Steadykey – Deterministic Idempotency Keys with Pluggable Stores

author: ebogdum


value: artskyinc

value:
Hey HN
I’m an indie founder who built [SyncForge](https://trysyncforge.xyz) — a SaaS platform that helps artists, producers, and composers submit their music to sync opportunities in film, TV, ads, and games.
Problem: Most creators don’t have access to the music licensing world. It’s either locked behind big publishers or buried in manual submissions.
Solution: SyncForge automates the process — artists can:
- Create a free account and upload tracks
- Submit to active sync briefs from studios and brands
- Manage metadata, rights, and submissions in one place
It’s still early, but we’re onboarding our first 1000 artists and curating briefs weekly.
 You can explore the pricing tiers here: [https://trysyncforge.xyz/pricing](https://trysyncforge.xyz/pricing)
I’d love your feedback — especially on:
- The signup flow (too long or clear enough?)
- The pricing model (free vs. core membership)
- How we can make it useful for devs or filmmakers too
Thanks for checking it out — happy to answer questions or share our stack (it’s built with Next.js + Firebase + Paddle).
— Jenna @ SyncForge

value: Show HN: I built SyncForge to connect indie artists with sync deals

author: artskyinc


value: lanemik

value:
I built Valid8r because I got tired of writing the same input validation code for every CLI tool. You know the pattern: parse a string, check if it's valid, print an error if not, ask again. Repeat for every argument.
The library uses Maybe monads (Success/Failure instead of exceptions) so you can chain parsers and validators:

  # Try it: pip install valid8r
  from valid8r.core import parsers, validators

  # Parse and validate in one pipeline
  result = (
      parsers.parse_int(user_input)
      .bind(validators.minimum(1))
      .bind(validators.maximum(65535))
  )

  match result:
      case Success(port): print(f"Using port {port}")
      case Failure(error): print(f"Invalid: {error}")

I built integrations for argparse, Click, and Typer so you can drop valid8r parsers directly into your existing CLIs without refactoring everything.
The interesting technical bit: it's 4-300x faster than Pydantic for simple parsing (ints, emails, UUIDs) because it doesn't build schemas or do runtime type checking. It just parses strings and returns Maybe[T]. For complex nested validation, Pydantic is still better. I benchmarked both and documented where each one wins.
I'm not trying to replace Pydantic. If you're building a FastAPI service, use Pydantic. But if you're building CLI tools or parsing network configs, Maybe monads compose really nicely and keep your code functional.
The docs are at https://valid8r.readthedocs.io/ and the benchmarks are in the repo. It's MIT licensed.
Would love feedback on the API design. Is the Maybe monad pattern too weird for Python, or does it make validation code cleaner?
---
Here are a few more examples showing different syntax options for the same port validation:

  from valid8r.core import parsers, validators

  # Option 1: Combine validators with & operator
  validator = validators.minimum(1) & validators.maximum(65535)
  result = parsers.parse_int(user_input).bind(validator)

  # Option 2: Use parse_int_with_validation (built-in)
  result = parsers.parse_int_with_validation(
      user_input,
      validators.minimum(1) & validators.maximum(65535)
  )

  # Option 3: Interactive prompting (keeps asking until valid)
  from valid8r.prompt import ask

  port = ask(
      "Enter port number (1-65535): ",
      parser=lambda s: parsers.parse_int(s).bind(
          validators.minimum(1) & validators.maximum(65535)
      )
  )
  # port is guaranteed valid here, no match needed

  # Option 4: Create a reusable parser function
  def parse_port(text):
      return parsers.parse_int(text).bind(
          validators.minimum(1) & validators.maximum(65535)
      )

  result = parse_port(user_input)

The & operator is probably the cleanest for combining validators. And the interactive prompt is nice because you don't need to match Success/Failure, it just keeps looping until the user gives you valid input.

value: Show HN: Valid8r, Functional validation for Python CLIs using Maybe monads

author: lanemik


value: jokera

value: NanoBibi lets creators and teams batch-generate and edit images using AI — remove backgrounds, upscale, restyle, or create new visuals in minutes.

value: Show HN: NanoBibi – Turn AI into Your Creative Production Line

author: jokera


value: goncharom

value:
Hey HN! I wanted to share a little library I've been working on to leverage AI to get structured data from arbitrary pages. Instead of sending the page's HTML to an LLM, Hikugen asks it to generate python code to fetch the data and enforces the generated data conforms to a Pydantic schema defined by the user. I'm using this to power yomu (https://github.com/goncharom/yomu), a personal email newsletter built from arbitrary websites.
Hikugen's main features:
- Automatically generates, runs, regenerates and caches the LLM-generated extraction code.
- It uses sqlite to save the current working code for each page so it can be reused across executions.
- It uses OpenRouter (https://openrouter.ai/) to call the LLM.
- It can fetch the page automatically (it can even reuse Netscape-formatted cookies) but you can also just feed it the raw HTML and leverage the rest of its functionalities.
Here's a snippet of what it looks like:

  from hikugen import HikuExtractor
  from pydantic import BaseModel
  from typing import List

  class Article(BaseModel):
      title: str
      author: str
      published_date: str
      content: str

  class ArticlePage(BaseModel):
      articles: List[Article]

  extractor = HikuExtractor(api_key="your-openrouter-api-key")

  result = extractor.extract(
      url="https://example.com/articles",
      schema=ArticlePage
  )

  for a in result.articles:
      print(a.title, a.author)

Hikugen is intentionally minimal: it doesn't attempt website navigation, login flows, headless browsers, or large-scale crawling. Just "given this HTML, extract this structured data".
A good chunk of this was built with Claude Code (shoutout to Harper’s blog: https://harper.blog/2025/02/16/my-llm-codegen-workflow-atm/.
Would love feedback or ideas—especially from others playing with codegen for scraping tasks.

value: Show HN: Hikugen – minimalistic LLM-generated web scrapers for structured data

author: goncharom


value: efromvt

value:
SQL-first analytic IDE; similar to Redash/Metabase. Aims to solve reuse/composability at the code layer with modified syntax, Trilogy, that includes a semantic layer directly in the SQL-like language.
Status: experiment; feedback and contributions welcome!
Built to solve 3 problems I have with SQL as my primary iterative analysis language:
1. Adjusting queries/analysis takes a lot of boilerplate. Solve with queries that operate on the semantic layer, not tables. Also  eliminates the need for CTEs.
2. Sources of truth change all the time. I hate updating reports to reference new tables. Also solved by the semantic layer, since data bindings can be updated without changing dashboards or queries.
3. Getting from SQL to visuals is too much work in many tools; make it as streamlined as possible. Surprise - solve with the semantic layer; add in more expressive typing to get better defaults;also use it to wire up automatic drilldowns/cross filtering.
Supports: bigquery, duckdb, snowflake.
Links
[1] https://trilogydata.dev/ (language info)
Git links:
[Frontend] https://github.com/trilogy-data/trilogy-studio-core
[Language] https://github.com/trilogy-data/pytrilogy
Previously:
https://news.ycombinator.com/item?id=44106070 (significant UX/feature reworks since)
https://news.ycombinator.com/item?id=42231325

value: Show HN: Trilogy Studio, open-source browser-based SQL editor and visualizer

author: efromvt


value: justingrosvenor

value:
I built a framework for measuring persona alignment in conversational AI systems.
*Problem:*
When you ship an AI copilot, you need it to maintain a consistent brand voice across model versions. But "sounds right" is subjective. How do you make it measurable?
*Approach:* Alignmenter scores three dimensions:
1. *Authenticity*: Style similarity (embeddings) + trait patterns (logistic regression) + lexicon compliance + optional LLM Judge
2. *Safety*: Keyword rules + offline classifier (distilroberta) + optional LLM judge
3. *Stability*: Cosine variance across response distributions
The interesting part is calibration: you can train persona-specific models on labeled data. Grid search over component weights, estimate normalization bounds, and optimize for ROC-AUC.
*Validation:* We published a full case study using Wendy's Twitter voice:
- Dataset: 235 turns, 64 on-brand / 72 off-brand (balanced)
- Baseline (uncalibrated): 0.733 ROC-AUC
- Calibrated: 1.0 ROC-AUC - 1.0 f1
- Learned: Style > traits > lexicon (0.5/0.4/0.1 weights)
Full methodology: https://docs.alignmenter.com/case-studies/wendys-twitter/
There's a full walkthrough so you can reproduce the results yourself.
*Practical use:*
pip install alignmenter[safety]
alignmenter run --model openai:gpt-4o --dataset my_data.jsonl
It's Apache 2.0, works offline, and designed for CI/CD integration.
GitHub: https://github.com/justinGrosvenor/alignmenter
Interested in feedback on the calibration methodology and whether this problem resonates with others.

value: Show HN: Alignmenter – Measure brand voice and consistency across model versions

author: justingrosvenor


value: Show HN: Mxflo – Vibe code 2D games on your phone and play instantly


value:
Hi HN,
I’m Rajiv, a software engineer turned Math teacher living in the mountains, where I like to slow down life while still building useful software.
I recently built DroidDock, a lightweight and modern macOS desktop app that lets you browse and manage files on your Android device via ADB. After 12 years in software development, I wanted a free, clean, and efficient tool because existing solutions were either paid, clunky, or bloated.
Features include multiple view modes, thumbnail previews for images/videos, intuitive file search, file upload/download, and keyboard shortcuts. The backend uses Rust and Tauri for performance.
You can download the latest .dmg from the landing page here: https://rajivm1991.github.io/DroidDock/
Source code is available on GitHub: https://github.com/rajivm1991/DroidDock
I’d appreciate your feedback on usability, missing features, or bugs. Thanks for checking it out!
— Rajiv

value: Show HN: DroidDock – A sleek macOS app for browsing Android device files via ADB


value: ankuranand

value:
Hey Folks,
I’ve been experimenting with an idea that combines a database and a message bus into one system, for a system that need colocated state at the edge.
Every database already has a log—the Write-Ahead Log. It's durable,
  ordered, and append-only. It's literally what you'd build if you were
  designing a message queue.

  So I asked: what if we just replicate the log itself?

  UnisonDB is the result. It's a Go-based KV store where:

  Every write:
  1. Appends to a memory-mapped WAL (durability)
  2. Streams to 100+ replicas instantly (no separate CDC) from the Wal itself.
  3. Becomes queryable via B+Tree (state)

  How replication works

  Each replica gets a WAL reader positioned at its last applied offset.

  - New data arrives → reader pulls it → replicate.
  - Network partition? Reconnect and resume from offset
  - Replica crashes? Recover local WAL, catch up from last commit

  No consensus. No quorum. No global coordination. Just: stream the log.

GitHub: github.com/ankur-anand/unisondb
Would love your feedback.

value: Show HN: UnisonDB – Replicates like a message bus. Acts like a database

author: ankuranand


value: reeoss

value:
Hi HN
I built CalmNest because I couldn’t stop scrolling at night. Most nights, I’d tell myself I’d sleep soon — but then an hour would vanish as I kept holding my phone, reading, checking things, or just staring at the screen until I fell asleep with it in my hand.
I wanted to change that — not by cutting myself off completely, but by turning my phone into something that guides me to sleep instead of keeping me awake.
So I made CalmNest, a calm space that helps you slow down and drift into sleep naturally. It gently guides your breathing with subtle visuals, dims as you relax, and eventually fades to a soft “Good night” screen when you stop interacting. From there, it tracks your sleep time and patterns — no pressure, no notifications, just calm.
Normally it’s $5.99, but it’s free until November 17 for anyone who wants to try it. If you, like me, tend to fall asleep holding your phone, maybe this can help.
https://apps.apple.com/st/app/calmnest-sleep-relax/id6754578...
Would love to hear your thoughts — especially from anyone who’s struggled with the same “phone at midnight” habit.

value: Show HN: CalmNest – Helping you put your phone down and fall asleep

author: reeoss


value: Justbeingjustin

value: Hi HN, I’m Justin. I built Fleet Fund to let anyone invest fractionally in machines that earn income. I'm starting with EV chargers. The idea is that as cars charge, they generate passive income that’s distributed to investors.<p>This is an early prototype with a waitlist. Would love feedback on the concept and where you think this could go next (robotaxis, humanoid robots, AI agents, etc.).

value: Show HN: Fleet Fund – Invest fractionally in EV chargers that earn income

author: Justbeingjustin


value: hhameed

value:
Hi HN! I built LLM OneStop (https://www.llmonestop.com), a unified interface for accessing multiple AI language models in one place.
The main problem I wanted to solve: constantly switching between different AI platforms, managing multiple subscriptions, and losing conversation context when comparing outputs across models.
Key features:
Switch between GPT-4, Claude, Gemini, Llama, and other models mid-conversation
Compare responses side-by-side
Single interface instead of juggling multiple tabs/subscriptions
Free tier available to try it out (no credit card needed)
"Connect" plan lets you bring your own API keys for unlimited usage
I built this because I found myself constantly copy-pasting prompts between ChatGPT, Claude, and other platforms when I wanted to compare responses or find the best model for a specific task.
You can try it right now with the free tier - would love to hear your feedback on what works, what doesn't, and what features you'd like to see!

value: Show HN: LLM Onestop – Access ChatGPT, Claude, Gemini, and more in one interface

author: hhameed


value: vibefarm

value:
Hi HN, I built VibeFarm to move beyond one-off prompting into modular composition. Instead of writing full prompts from scratch, you stack elements inside VibeCards that break language into structured controls you can lock, randomize, and remix. Think Ableton for prompts: lock what works, randomize the rest, and reuse the stack as a system.
Or imagine a prompt marketplace where, instead of sharing a single prompt, users exchange entire systems they can load, remix, and reuse.
What’s different
Structured slots: Subject, Context, Style, Goal for consistent, editable outputs
User-created cards: Generate new VibeCards or Elements directly from text. Everything in the system is user-extensible
Lock + dice: Freeze any card and explore controlled variation
Portable units: Save stacks as plain-text .vibe files for use across models
Combinatoric exploration: Even small stacks create practically infinite variation without drift
Semantic layers: Internal separation of linguistic, metaphorical, and analogical signals keeps style portable as models evolve
Language, not syntax: When everyone types the same phrasing, models converge on the same style. VibeFarm modularizes language itself, letting you explore tone, rhythm, and structure as creative variables.
Why it matters
While most tools focus on interfaces or automation, almost no one is addressing the core material of LLMs: language itself. Ignoring that is like building Photoshop without touching pixels.
VibeFarm acts as a composition layer on top of models like Midjourney and Sora, helping creators break out of prompt grooves and preserve distinct intent across text, image, and video generation. It scales naturally as models evolve.
Try it
Live demo (instant, no signup): https://app.vibefarm.ai
More info: https://vibefarm.ai
Under the hood
React + TypeScript, Zustand, Node/Express, Neon Postgres + Drizzle, OpenAI API.
The .vibe format is an evolving, minimal, versioned text spec.
All feedback is welcome. Happy to discuss implementation details, design tradeoffs, and next steps in the thread.

value: Show HN: VibeFarm – Modular composition layer for language models

author: vibefarm


value: ruchiclub

value:
Last weekend I built a tiny AI widget: highlight any text on a page → "Rewrite with AI" button appears. One script tag, no backend.
Live demo (try it now): https://aivideosummary.com/widgets/widget-rewriter1.html
Use case: bloggers/devs who want quick rewriting without building auth/RAG.
Planning a series: summarizer, translator, etc.
Curious — do single-purpose AI widgets still have a future in 2025?

value: Show HN: AI Content Rewriter – one-line embeddable widget (open-source)

author: ruchiclub


value: matt-p

value: I built this while working on a data center design and management tool to automate parts of the build, buy, and deploy process for new sites. This fibre module is still WIP.

value: Show HN: React Component for Fibre Management

author: matt-p


value: englishcat

value: Show HN: Lingoku – Learn languages while browsing (supports EN, JP, KR, CN)

author: englishcat


value:
I built EveryToolkit.com
 — a collection of 500+ free online tools across 24+ categories, all in one clean, fast, and ad-supported site.
The goal is to make small, everyday utilities accessible from one place — no popups, no clutter.
You’ll find:
• Developer tools (JSON, JWT, regex, base64, etc.)
• Text and writing tools (word counters, formatters, case converters)
• Image & PDF tools (compress, convert, merge)
• Finance, health, and SEO utilities
• Calculators and converters for daily use
I built this to solve my own frustration of having to Google for “that one tool” every time. Would love feedback
Live here → https://www.everytoolkit.com

value: Show HN: 500+ Free Online Tools In One Place – developers, designers, students


value: leewenjie

value: AI help desk that learns automatically from conversations. Meta-certified for WhatsApp/Instagram on top of web chat.

value: Show HN: Oxaide – Meta-certified AI help desk (auto-learns from conversations)

author: leewenjie


value: GeorgiMY

value:
The giTshirt story
A little while ago, I decided I needed a way to commemorate my first SaaS.
Sure, I had a 3D printed plate of its name, but that was not enough, I needed something more…
While that thought lingered at the back of my mind, I saw a funny tweet showcasing ridiculous commit messages.
I thought, “Hey! I have some stupid commit messages, let me go screenshot them and share them as a reply to that tweet.”
Somehow the two thoughts connected. It instantly clicked:
What if I could wear my stupid git commit messages?
What if I put it on a T-shirt?
A giTshirt…
That would be the perfect way to showcase what I’ve made, as well as a funny conversation starter at conventions.
So I developed an algorithm that places commit messages from repositories you’ve chosen and creates a ready-to-order T-shirt.
Then I worked with a designer to create a logo and a special card that you receive with your giTshirt.
I didn't stop reworking giTshirt until I created something I'D like to wear.
Spoiler - It took me weeks but I managed to do it.
The giTshirt you see on the home page is the one I ordered and the very one I'm wearing while typing. (It's pretty cool!)
How it all works
Here's a step-by-step of everything that happens from clicking “Generate giTshirt” to getting it to you:
1. Security:
1.1 Stop you if you are not authenticated
1.2 Stop you if you are generating 3 shirts per minute (pls don't :))
1.3 (Sadly) Stop you if there are more than 300 commits selected. You just physically can't fit more than 300 messages on a T-shirt, sorry
2. Generating images:
2.1 I needed to create a 2D collision system to place the commit messages
2.2 The commit messages are placed at almost random
2.3 There are 4 total images generated. Back, front, left sleeve, and right sleeve
3. Creating the product
3.1 I upload the 4 images to Cloudinary
3.2 These images are then downloaded to my T-shirt provider
3.3 The code places them on the T-shirts
3.4 Then a product is created and I get back the mockups back
3.5 These mockups are then displayed to the user before a purchase is made
Here's how you can get a giTshirt in less than a minute:
This is not a marketing gimmick; I timed it, and it took me 43 seconds.
1. Sign up with GitHub
2. Select a repository - both public and private ones work
3. (optional) All commit messages are pre-selected, but you could nit-pick the ones you want
4. Click on the "Generate giTshirt" button
5. Order and wait!
If you like the idea and want to order one you can visit - https://giTshirt.com
If you like the idea but don't want to order one you can always visit the ProductHunt launch and support giTshirt there - https://www.producthunt.com/products/gitshirt
Thanks for reading!

value: Show HN: I Accidentally Created a Custom Clothing Brand for Developers

author: GeorgiMY


value:
Quick grammar, punctuation, and spelling checker. Free, no ads, no sign-up. Paste up to 1000 words, get instant suggestions with explanations.
Built for writers who need fast, accurate checks without friction. One-click corrections with grammar checker results.
Feedback welcome—what features would make it more useful?

value: Show HN: Free AI Grammar Checker – Instant Corrections


value:
Hey HN,
My friend and I are building a free coding school that's entirely project-based, self-paced, and emphasizes skills that we think are important in the AI era (e.g. system design).
We're building this because we think a program should exist that's as affordable as self-studying, nearly as rigorous as a university, and as practical as a coding bootcamp.
A bit about us: I was the first engineer at a five person startup, and my friend was the youngest SDE II at AWS SageMaker. We’re friends from UC Berkeley and recently went through YC together.
Full disclosure: we’ve only released the beginning of the first project so far. If you’re just starting your coding journey, we’d love for you to try it. If you’re more experienced, feel free to sign up for updates.
Also, we’ll be hanging in Discord if you need support/guidance :)
Check it out here:
https://vectorschool.ai/

value: Show HN: Free CS Education for Future SWEs (YC F25)


value: openfluke

value:
Hey HN! Author here.
Built this because deploying ML models is painful. Python + pip dependencies + Docker = 5GB+ images. For edge/embedded/air-gapped systems, this doesn't work.
LOOM loads HuggingFace transformers directly in Go. No Python runtime. ~10MB binary.
Technical highlights:
- Native safetensors parser
- Pure Go BPE tokenizer (no transformers library)
- Full transformer stack (MHA, GQA, RMSNorm, SwiGLU)
- Cross-platform determinism (MAE < 1e-8)
- Published to PyPI, npm, NuGet
Tradeoff: CPU-only, 1-3 tok/s on small models. Correctness first, speed second.
Works with Qwen, Llama, Mistral, SmolLM. Cross-compiles everywhere Go runs.
Demo: https://youtu.be/86tUjFWow60
What layer types should I add next? Currently have: Dense, Conv2D, MHA, RNN, LSTM, LayerNorm, RMSNorm, SwiGLU, Softmax (10 variants), Residual.
Questions welcome!

value: Show HN: Run HF Transformers in pure Go (10 MB binary, no Python)

author: openfluke


value: SidDaigavane

value: Show HN: AirPods Powered Squats Coach

author: SidDaigavane

title: Show HN: AirPods Powered Squats Coach


value: harperhuang

value:
For my birthday, my wife surprised me with a GPU!
I immediately deployed an AI text-to-image model on it and upgraded https://girlgenerator.online
Now it can generate images in various styles - people, scenes, different art styles, you name it.
The GPU isn't high-end, but it's more than enough to run a text-to-image model smoothly. Really grateful for my wife's support!
The site is still completely free with unlimited generations.

value: Show HN: My wife got me a GPU for birthday, so I upgraded my image generator

author: harperhuang


value: bntr

value:
I've extended the standard OpenGL camera to allow smooth transition between normal perspective, orthographic, and reverse perspective projection.
To demonstrate the effect, I built a demo using Three.js.
Reverse perspective can feel a bit disorienting at first,
but this demo is meant to highlight a few of its interesting advantages:
1. An extended Dolly zoom effect. https://en.wikipedia.org/wiki/Dolly_zoom
You can think of it as an extrapolation of the classic Dolly zoom into negative space.
It produces a cinematic sense of vertigo or sudden insight,
and also lets you pull the camera back from an object without distracting the viewer with surrounding geometry.
2. A wider and more complete spatial view.
Near objects no longer obscure distant ones;
the viewer can see both the façade of a building and what’s happening on its roof, or even behind it.
Code and details: https://github.com/bntre/reverse-perspective-threejs

value: Show HN: Reverse perspective camera for OpenGL (Three.js)

author: bntr


value: cpuXguy

value:
This pattern principle is almost unknown.
In the program, press Q and then select the Chinese character to learn more about it.

value: Show HN: 39,916,800 × 39,916,800 pixels – move it (the Number Garden patterns)

author: cpuXguy


value: Show HN: VS Code extension to visualize code and dependencies


value: Show HN: Framework where student AI models exceed their teachers (86.7% vs 82%)

value: Show HN: Framework for Transferring AI Capabilities (Students Surpass Teachers)


value: thisisagooddayg

value:
Hi HN,
I'm the developer behind ChartPilot, a momentum scanner for swing traders. The single hardest problem in momentum trading is confirmation: How do you know a 4-hour signal is valid if the Daily trend is weak? Most scanners just dump data; we wanted to provide conviction.
We're now launching our new metrics dialog and architecture to solve this:
The Pilot's Score: A proprietary aggregate score (0-5) that rates signal strength instantly by systematically aligning EMA, ADX, and Squeeze Momentum across 1H, 4H, and Daily charts. It simplifies complex Multi-Timeframe Analysis (MTFA) into one number.
Verifiable Performance: We've refactored the data structure to track the historical performance of every signal type, moving from speculation to data-backed decisions (backtesting features are in development).
The goal is consistency and objectivity. We're not here to predict tops—we're here to automate the search for high-probability structures.
I'd appreciate any feedback on the implementation and the utility of this proprietary scoring system.

value: Show HN: ChartPilot: New Proprietary 'Pilot's Score' to Filter Stocks Breakouts

author: thisisagooddayg


value: jameshih

value:
Hi HN, I’m James and I built Stablecoins Club, a Craigslist-style marketplace to buy and sell digital goods directly, wallet-to-wallet, on Polkadot Asset Hub. All payments and transaction fees are handled in USDC or USDT, so users never need another token just to cover blockchain fees. The platform is free to use, with no listing fees, no escrow, and no middlemen, providing a simple, direct, peer-to-peer way for creators and buyers to transact.
I’d love to hear your feedback and ideas for features that would make the marketplace even more useful.
https://stablecoins.club

value: Show HN: I built a stablecoin marketplace for digital goods

author: jameshih


value:
Hi, Can you connect two seemingly random topics using their Wikipedia pages?
WikiGo is all about that. It’s a logical and mental exercise game where you have to traverse from the Start Article to the End Article in the least number of steps (and least time) using only in-game Wikipedia links.
There is a Daily Challenge mode, where you compete globally on the same topics for a spot on the leaderboard.
There is also a Random Play mode, where you can select your own Start and End Articles, or, if you’re feeling lucky, go completely random.
If you feel you did a good job reaching your end goal, you can invite your friends via a link to compete with your score.
No login or signup is required. Just visit and start playing.

value: Show HN: WikiGo – A logic game where you connect two Wikipedia articles


value: Ciaranio

value: After building several flat map interfaces for mobile web experiences, I kept hitting the same realisation, every single one felt better on desktop even though I was designing for them to be touch based.I came across a demo from MapLibre of a global map projection and decided to give it a crack. Doesn't the sphere feel natural on mobile web? Does it come with a cost? e.g. did you feel any performance issues on your device?

value: Show HN: Testing if sphere manipulation beats flat maps for mobile web UX

author: Ciaranio


value: neuwark

value:
I’ve been working on a lot of marketing campaigns lately and noticed one recurring problem — most messages sound good in theory, but you never really know which one connects with which audience until you’ve already spent weeks testing.
So, I built the Brand Messaging Test AI Agent. It helps marketers instantly discover which messages resonate best with different customer personas. Instead of guessing or A/B testing manually, the agent analyzes your copy and gives you clear insights into what works, what doesn’t, and why.
It’s designed for startups, agencies, and anyone trying to improve their brand communication without wasting hours or ad budget.
Try it for free here: https://app.neuwark.com/special-agents-hub/45
Would love feedback from the HN community — what would you like this tool to test or analyze next?

value: Show HN: I made an AI that finds the best message for each customer persona

author: neuwark


value:
Just shipped a tiny “eyes follow your cursor” widget with a live playground so you can noodle
  around. The hosted embed has a paid tier for production apps, but the demo is open—looking for
  ideas on fun interactions or motion tweaks.

value: Show HN: Eyes-follow cursor widget for playful UI feedback


value: herbstgewinn

value: Show HN: Study Material to Brainrot Videos

author: herbstgewinn


value: rioppondalis

value:
A few months ago I realized I had no idea where our money was actually going. Not in a "we're broke" way, just... groceries, random Amazon purchases, subscriptions I forgot about, it all blurred together.
I tried a few existing apps but they were either too complex (why does budgeting software feel like filing taxes?) or wanted to sell me credit cards or were expensive and had subscription. Nothing answered the simple question: "who in our household is spending what, and where?"
The main insight: my partner and I just wanted to see patterns without judgment. Like "oh, I spent $200 on coffee this month" or "wait, we bought HOW many toys?" or "this grocery store is bleeding us dry, let's switch."
So I built something dead simple: enter expense, amount, who it's for, merchant, category. Done. Takes 10-20 seconds. The manual entry actually makes you more aware of spending, and then you get nice visual breakdowns.
No guilt trips, no "you're $5 over budget!" notifications, no gamification. Just clean data.
Plot twist: we now actually enjoy looking at our spending together. Turns out money conversations are way easier when you're not guessing or arguing over who bought what by guessing the number!
It's free to use. Would genuinely love feedback. What works, what doesn't, what's missing. I'm actively building and happy to add features that actually make sense.
See: calmspend.com

value: Show HN: I made a tracker to see who's spending what in our family

author: rioppondalis


value: hgarg

value: Show HN: Get any web page content in Markdown

author: hgarg


value: MitchelNovoa

value:
I built Charl, a compiled language for machine learning with tensors and autograd as native features (not a library). It's alpha-quality but functional.
What works: Neural network training, 22x faster than PyTorch CPU, GPU support, type-safe.
What doesn't: Small ecosystem, alpha bugs, missing features (modules, etc).
Not trying to replace PyTorch - this is an experiment to see if ML-native language design offers advantages.
Try it: https://charlbase.org
Code: https://github.com/charlcoding-stack/charlcode
Looking for testers and feedback. What would make this useful for your work?

value: Show HN: Charl – ML language with native tensors and autograd

author: MitchelNovoa


value: nrig

value:
I needed a way to quickly understand the true state of dependencies across my projects – which ones pose real risk and which updates are actually urgent.
DepHealth analyzes any public GitHub repo and gives you:
• Overall health score (0-100) based on security, drift, and lifecycle
• Prioritized action list (actively exploited CVEs ranked first via CISA KEV)
• Combined view: vulnerabilities + version drift + EOL status
Try it: https://dephealth.io (no signup, most repos analyze in under a minute)
The goal is to give you instant visibility into dependency health without manual audit work. Uses exponential decay scoring so large projects aren't unfairly penalized just for having more packages.
Technical bits:
• 8-tier prioritization system (exploited → critical → high → outdated)
• 7 ecosystems: npm/yarn/pnpm, composer, poetry/pipenv, go modules
• Built with Laravel + Vue3, Clean Architecture (DDD)
• Free for public repos
Built this over 3 months as a side project. Would love feedback on the scoring algorithm and prioritization logic—does it feel "fair" for your projects?

value: Show HN: DepHealth – Health score for your project's dependencies

author: nrig


value: Gamify Your Vibecoding!

value: Show HN: Should we gamify vibecoding? VibeSlots: bet when u vibe code

story_text: Gamify Your Vibecoding!


value: coffeevibe

value:
Hi HN,
I built Capme because I passionately hate meetings (80% of that is just wasted time), but screen recorders either cost $18/month, add watermarks or I can't convince Janet in accounting to install any software whatsoever.
I just wanted something simple that everyone can use without signups, basically the excalidraw of video recording.
So that's exactly what I set out to build: Capme is a free screen recorder, no accounts needed, no time limits, no watermarks, no cloud uploads.
You choose a background, add a logo, and hit record. If you feel like you need it, write a script in the teleprompter.
That's it. With Capme, your videos never leave your device - no cloud processing, no storage, nothing. You record locally, save the file, and share it however you want.
It works best in Chrome, decent in Safari & Firefox.
Try it: https://www.capme.app/studio
Completely unmonetized for now. Would love feedback:
- What's missing?
- What looks like shit?
- Should I add a video background with unicorns wielding laser swords and would you use that for your next standup video?
Cheers!

value: Show HN: Capme – Free screen recorder with zero cloud uploads

author: coffeevibe


value: anwarlaksir

value:
Hi HN,
I’m Anwar, I previously built Cubent (now acquired from a private buyer), a developer tool extension for vscode.
And now, I created Beitha, a lightweight agent that runs directly inside Chrome (or any Chromium browser) and lets you control the web with natural language, no new browser, no setup. I wanted to go beyond “AI chat” and build something that actually acts: opening tabs, filling forms, editing text, clicking buttons, or extracting data, all through one interface.
Beitha doesn’t replace Chrome it augments it. Think of it as a layer that makes your browser do the boring stuff for you.

value: Show HN: Beitha – Supercharge the Browser

author: anwarlaksir


value: rhannequin

value:
Hello HN! My name is Rémy and I recently published an astronomy dashboard where everything is open source: the code of the website, the framework it is based on and the library that computes astronomical data.
For the last few years, I have been developing the Ruby library Astronoby (https://github.com/rhannequin/astronoby) with as much dedication and perseverance I could while I don't have any scientific academic background. My end goal was to use this library and build a website that not only provides as much data as possible, but let anyone access and understand how it was computed. This goal is on its was of completion with Caelus.
Of course the website is still quite new and there are many features I will implement in the coming weeks and months, including the ability to set any date, having a global view of the Solar System, having an interactive sky chart, a tool to prepare your observation night, having the website in multiple languages, etc.
I believe astronomical data should be universal and anyone should be allowed to easily access this data, manipulate it, understand how it was generated, and contribute to and with the community.
My goal is to make this project truly collaborative. I am open to feedback, ideas, requests, bugs, everything, to offer the community open source astronomical data.
Thank you all.
Website: https://caelus.siderealcode.net
Source code: https://github.com/rhannequin/caelus

value: Show HN: An open source astronomy dashboard (https://caelus.siderealcode.net)

author: rhannequin


value:
I'm building SuperCurate (https://getsupercurate.com), a tool focused on note retrieval and curation rather than note creation. Think filing cabinet for your notes, web clippings, images and PDFs.
I built it because I wanted fast search and filters for my Evernote archive (ENEX) so I could drill down and surface exactly what I was looking for.
It can also search inside PDFs and jump directly to the matching page with highlights.
Web Clipper for Chrome to save content directly:
https://chromewebstore.google.com/detail/piianedlaigjpcebhlp...
Demos:
- Search and curation: https://www.youtube.com/watch?v=z4QSIoUL4Uk
- Web Clipper: https://www.youtube.com/watch?v=8F7QoC7X3fs
- Search inside PDFs: https://www.youtube.com/watch?v=t0X9sD-938Q
I'd love to hear your feedback and use cases!

value: Show HN: SuperCurate – Fast note search and curation


value:
Hey HN!
I noticed there wasn't a good central place for Black Friday software deals this year, so I built one: blackfridayappdeals.com
*It's completely free to submit your deal* - no paid tiers, no featured spots, just a simple form where you can add your Black Friday/Cyber Monday offer.
The site organizes deals by category (Productivity, Developer Tools, Design, AI Tools, etc.) and includes search functionality so people can easily find what they're looking for. I'm planning to promote it through various channels to drive traffic to all the submitted deals.
*Why I built this:*
- Last year, I struggled to find a comprehensive list of SaaS deals
- Most deal sites charge hundreds of dollars just to get listed
- I wanted to help indie makers and small SaaS companies get visibility without breaking the bank
*What you get:*
- Free listing with your deal details
- Category-based organization
- Search visibility
- Traffic from deal hunters actively looking for Black Friday offers
- UTM tracking so you can measure the traffic you get from the site
Deals will go live on November 14th, giving people time to browse before Black Friday hits on November 28th.
If you're running a Black Friday promotion for your app or SaaS, feel free to submit it here: https://forms.gle/GfUHvao2wPGjbyrr9
Happy to answer any questions!

value: Show HN: Promote your tool for Black Friday 2025


value: privacyadvocate

value: Show HN: Why Bitcoin's Transparency Is a Fatal Flaw – Free Book on Zcash

author: privacyadvocate


value: Asadlambda

value:
About the app:
Contact management is broken.
Too many apps, too many QRs, too much noise.
We’re reimagining it fast, agentic, and private.
One QR. One network. Infinite control.
It’s not social. It’s sovereign. Built for the ones who still value privacy and precision.
Imagine owning your network not feeding someone else’s.
No UGC. No spam.
One dynamic QR. AI agents that find, remind, and connect. One AI to manage
Welcome to the network under the network

value: Show HN: I built AI Native contact management and anti social networking app

author: Asadlambda


value: RandomDailyUrls

value: Show HN: Turn your hand into a magnificent turkey

author: RandomDailyUrls


value: nathan-barry

value:
This is a character-level language diffusion model for text generation.
The model is a modified version of Nanochat's GPT implementation and is trained on Tiny Shakespeare!
It is only 10.7 million parameters, so you can try it out locally.

value: Show HN: Tiny Diffusion – A character-level text diffusion model from scratch

author: nathan-barry


value: toutoulliou

value: After months wrangling the French Demande de Valeurs Foncières files, I turned them into a site where anyone can search a commune, inspect official sale prices, and see five years of trends. You can drill into recent transactions, compare property types, and try mortgage or rentability simulators I added to make the data actionable. I’d love feedback on what views help you decide if a neighborhood is changing, what export formats you’d need, and how the interface feels: https://immobilierville.fr/

value: Show HN: I built a site that maps official French real-estate sales

author: toutoulliou


value: selmetwa

value: A small collection of reusable, event driven web components. Currently includes an Intersection Observer component, and a Get Request component.

value: Show HN: Event driven web component utilities

author: selmetwa


value: kevinsschmidt

value: Show HN: Video generator for live poker hands

author: kevinsschmidt


value: enricobruschini

value:
Akamas is the autonomous optimization platform that unites developers, SREs, and platform engineers around one goal: delivering reliable, efficient services.
By connecting directly to your observability data, Akamas detects optimization opportunities, estimates their impact on cost and reliability, and recommends or applies safe, validated optimizations across the full stack - from applications to clusters.

value: Show HN: Akamas Insights now GA – Optimize reliability, performance, and costs

author: enricobruschini


value: elayabharath

value:
Hi HN, I’m EB - a full stack developer with a background in UX.
I have been using ChatGPT for a while to learn concepts (recent e.g. unlike my credit card, how does my public transport card update the card balance as soon as I tap) [aware of the limitations]
I often found the linear chat interface too restrictive for any exploration. I always wanted to revisit earlier points, ask multiple follow up questions at different points of the conversation, connect related concepts, or compare various lines of thought - all of which are not conducive in a scrolling chat.
I had this idea for a graph based interface for some time, and finally got to sketch and prototype it this weekend.
I'm curious to see how well it addresses these pain points, and potential ideas to extend / test this prototype.

value: Show HN: UI for non-linear conversations with LLMs [video]

author: elayabharath


value: heavenlxj

value:
Hi HN
I built MonkeyAI
 — a site that curates creative templates and examples for AI image generation, designed to help artists and designers find inspiration faster.
When experimenting with different image models, I noticed that generating great visuals often depends on how the prompt is structured — the tone, subject, and composition details matter a lot. But most prompt libraries are either overwhelming or lack creative direction.
MonkeyAI focuses on quality and clarity. Each template comes with:
A visual preview of the result
The exact prompt structure
Context tags for mood, style, or theme
A clean interface to explore ideas visually
The goal is to make AI creation more intuitive and inspiring, especially for people who think visually — designers, illustrators, and creative makers.
I’d love your feedback on:
What would make this more useful for your creative process?
Would you like to see model-specific templates or open submission from users?

value: Show HN: MonkeyAI – Curated creative templates for AI image generation

author: heavenlxj


value: sadfun

value: Show HN: Deepvote – 10 AI models vote on your decisions

author: sadfun


value: mishamsk

value:
Built this after support/product kept asking "when did we ship X?" while helping users. Needed a way to instantly answer "did v2.3.1 include that auth fix?" or "which release has this commit?"
wtg takes any GitHub URL (commit, issue, PR, file) or identifier and tells you which release first shipped it. Works with remote GitHub repos without cloning, but also runs locally on any git repo (with graceful degradation when GitHub isn't available). Smart caching and snarky messages included.
Try it without installing: uvx --from wtg-cli wtg https://github.com/go-task/task/issues/1322
Written in Rust, packaged as Python CLI for easy distribution.
Would love feedback!

value: Show HN: Wtg – a CLI to trace release that shipped the fix you crave and more

author: mishamsk


value: rampandu

value: Free Regex & SQL Generator (no login, open models)

value: Show HN: AI Dev Tools – Free Regex and SQL Generator (no login, open models)

author: rampandu


value: robertBosiljak

value:
Hey everyone!
I recently wrote a short humor novel about life as a dev. It’s called “JavaScript & Drugs: a Dev’s Quest for Ramen Profitability.”
It follows Cramer, a frontend engineer at an HR SaaS company, and his flatmates (also devs) as they go through soul-sucking corporate jobs, startup chaos, and questionable side projects.
You can read a free sample here: https://www.javascriptanddrugs.com/sample
I’m curious: do you think devs would find this kind of story entertaining? I wrote it in part as self-therapy, to let my work-related frustrations out, but also self-published it to see if I can sell some copies. So far, I've only sold 3, all of them to friends and family haha.
Also, do you know any good software-engineering humor books? I’ve read and enjoyed The Phoenix Project and its sequel (The Unicorn Projec)t, but don't know of any other fiction books about dev life.
Thank you all!
PS: yes, I used AI to help me write it, that's why there are so many en dashes haha

value: Show HN: JavaScript&Drugs, a humor novel about devs

author: robertBosiljak


value: hchtin

value:
toktop is a TUI that tracks your openai and anthropic usage inside the terminal.
I spend a lot of time in terminal with claude code and codex, and I also build apps with openai and anthropic api keys. I found myself hopping on two different dashboards quite often to check my usage, so I built a TUI to monitor my daily/weekly/monthly cost, without leaving my workflow inside the terminal.
You can view the usage and cost for each of your api keys for the past 7 or 30 days, grouped by either model or api key.
For folks also using a lot of claude code/codex with api keys, or building ai apps, you might also find it useful without constantly hopping on openai and anthropic dashboard.
Github: https://github.com/htin1/toktop
Quick installation: cargo install toktop

value: Show HN: Toktop – a LLM usage dashboard in your terminal

author: hchtin


value: RandomDailyUrls

value: Show HN: A daily newsletter for random content across the web