The best Hacker News stories from Show from the past day
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Show HN: Omacosy – Omarchy-style tiling desktop for macOS, no SIP
I have been using omarchy on my tower since nearly a year now, shortly after it was released first. I really love the experience I am having with it but I still use my macbook for daly work, so I wanted to recreate a similar experience on it. Thats why I created omacosy, a setup for tiling windows, custom menu bar, some themes from omarchy, focus follows mouse, focus rings around windwos, some mac flavors with trackpad events and a custom mission control overview for your workspaces.<p>I used AeroSpace over yabai for the tiling window manager because I didnt wanted to compromise on SIP which is a mac security feature.
It is supposed to be keyboard first like omarchy to move windows organize workspaces etc
The setup runs around 157mb of ram and consists of AeroSpace, Karabiner (for the super key), and five small self build swift binaries.<p>I am running it daily on my M1 max macbook, currently on macOS26. I havent tested it much on other macbooks or macOS versions.
The install script creates a manifest file to backup what was installed before and what it installed itself, the uninstall script takes that into account to clean up the macbook to exactly the state it was in before.
It needs quite some permissions for it sfunctionality which I layed our in the project readme. I wanted to be really transparent about which permissions it uses and for what reason.<p>I would love to get some feedback or see people trying it out and hearing your opinion. Mostly about what still doesnt feel smooth in the experience or if you find any performance issues.
Show HN: Open-source Stripe Connect alternative
Hey, I'm Ben. I built Zoneless because I was paying so much to use Stripe Connect on my own marketplace. The fees were really, really bad, and it was also limiting in terms of the seller countries I could onboard. To give you an idea, I was paying around $9,000 per month in fees just to run payouts. Using Zoneless, that cost goes down to around $6.<p>I've been using it personally for the past few months, and onboarded 5,000+ sellers and done 3,000+ payouts. 74% of new sellers on my marketplace choose Zoneless over Stripe, which is really interesting. I appreciate crypto and stablecoins are a bit of a touchy subject, but for this use case of sending global payouts cheaply, it's perfect.<p>The project is open source with an Apache 2.0 licence, which means there's the benefit of no lock-in and no risk of your account getting flagged or shut down. It also has an almost identical API and dashboard to Stripe.<p>Would love to hear any feedback you may have in the comments.
Show HN: Check if any of the $656M in unclaimed royalties at The MLC is yours
Hi HN, I built this. Quick background on why it exists:<p>When music is streamed on digital streaming platforms (think Spotify, Apple Music, Pandora), there are two separate royalty streams: one for the recording, paid through your distributor (DistroKid, TuneCore, CDBaby), and one for the underlying work (generally known as publishing). The work side's mechanical royalties are collected by The MLC, a nonprofit that was created by the 2018 Music Modernization Act (MMA). If you haven't registered your songs with The MLC, there are issues with your metadata, or about half a dozen other reasons, that money will never reach you, it just collects in a big pile we call the "black box".<p>That pile is big. The MLC's own dashboard currently shows over $656M is held (themlc.com/blanket-royalties), and the biggest problem is the MMA dictates that The MLC cannot hold that money indefinitely. At some point, by law, The MLC must distribute this big pile of cash, and since they don't know who it's supposed to go to, they pay it out through a process called "market share" (themlc.com/marketshare). Market share means they pay it out, pro-rata, to the artists, songwriters and publishers that are in the system, which in practice means the largest publishers collect most of the leftovers.<p>This is slated to begin in January 2027 and will pay portions of the pool out monthly (themlc.com/unclaimed-accrued-royalties), as of this morning, the next 12 months of market share sums up to $76.61M, starting with $6.41M in January.<p>Full disclosure: I run Doubly, which is an independent publishing administrator, so I have a commercial interest in this space. That being said, we're a team of two people and we don't have the bandwidth to directly assist the hundreds of thousands of artists and songwriters who are going to start losing this money in January 2027.<p>That's why I built this self-service tool, no signup, no email, no paywall, the reports are completely actionable without needing anything from us.<p>The tool: paste a Spotify artist link (or search for a Spotify artist by name). It pulls every release on that profile, checks each recording against The MLC's public bulk data, and tells you per-song whether it's fully claimed, partially claimed, registered but unmatched, or missing entirely. It then provides a link to the exact MLC tool that fixes each case. It also estimates the dollars stuck, as a rough range.<p>Even if you're not an artist yourself, you probably know someone who is a musician, please share it with them.<p>Thanks for your time and I'm happy to answer any questions about the industry as a whole, The MLC, the tech, anything really.
Show HN: Huzzah – a novel approach to coding with AI
Hello everyone. I've been working on this experimental editor called Huzzah.<p>I've been working almost exclusively with coding agents since January of this year, and over the past few months I began to feel utterly exhausted by them. They're great, but I'm finding it more and more tedious to write full sentences for every change I want. Not only that, but it seems there's a complexity limit for codebases - beyond a certain point the agent begins confusing itself.<p>I'd like to go back to writing code, but I don't want to go all the way back to fully manual coding. So I've come up with this interaction paradigm where you:<p><pre><code> 1. write pseudocode in whatever way makes the most sense to you
2. on save, the editor synchronizes your work to real source code
3. the pseudocode is persisted alongside the generated code, making your prompt effectively a stored record of intent.
</code></pre>
It may not work for every use case, but in my initial playthroughs I've found it very enjoyable.<p>Right now it's just a proof of concept - installation instructions are here in the readme: <a href="https://github.com/danielvaughn/hz" rel="nofollow">https://github.com/danielvaughn/hz</a><p>You can also watch a video of it in action here: <a href="https://x.com/danielvaughn/status/2090456808431165715" rel="nofollow">https://x.com/danielvaughn/status/2090456808431165715</a><p>Cheers!
Show HN: I trained a 125M model to autocomplete piano on-device
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15).<p>The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device.<p>The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
Show HN: A sample dataset of computer-use tasks on professional software
Show HN: macOS data protection keychain for Electron apps
Hey HN,<p>I've been working on Hansel [1] (an encrypted personal data store you can query with agents), and there wasn't a good way to use the modern macOS Data Protection Keychain.<p>Electron's safeStorage [2] uses the legacy file-based keychain, which allows other apps/agents to query it with the `security` CLI. Not great when you have a dozen agents running in the background! The Data Protection Keychain is nice because it limits access via code-signing access groups and lets you set access rules like Touch ID and/or password.<p>1: <a href="https://hansel.so/" rel="nofollow">https://hansel.so/</a><p>2. <a href="https://www.electronjs.org/docs/latest/api/safe-storage" rel="nofollow">https://www.electronjs.org/docs/latest/api/safe-storage</a>
Show HN: Frugal Tokens – explore costs and usage across coding agents
I wanted to share a project I’ve been working on called Frugal Tokens. I originally built it because I was curious to see how much all of my sessions cost and how much cache misses affected that spend. I’d noticed people had widely different spend profiles and wanted to better understand what might contribute to that.<p>As I’ve worked on this, the tool has grown to show more usage patterns across all of your sessions. It shows overall usage, estimated working time and overlapping sessions, and where your spend is coming from across models and cache misses. I also have a few session level metrics with percentile breakdowns, along with a list of your sessions and high level info.<p>Clicking into a session opens an explorer where you can see individual model calls and tool inputs and outputs. You can also jump directly to where a cache miss happened. There’s also a rough cost comparison that shows what the recorded session would have cost with another model’s pricing, or for Anthropic, with 5m vs 1h caching.<p>In the future, I’d love to collect more information to see which patterns might make people’s workflows more expensive, e.g. long sessions, high context usage, many turns, etc.<p>The tool requires deno, but is just one command to run once that is installed. The demo provided has some of the data scrubbed, but helps to show what it looks like before running it.<p>Would appreciate any thoughts or ideas<p><a href="https://github.com/dpclark4/frugal-tokens" rel="nofollow">https://github.com/dpclark4/frugal-tokens</a>
Show HN: Nikon F100 Film Camera Repair Notes
Show HN: Interactive, animated architecture of any HuggingFace models
Show HN: Interactive, animated architecture of any HuggingFace models
Show HN: Automatically detect and patch walking-dead states in Sierra games
Hi HN, I've become lazier in my old age and struggle to replay my favorite Sierra games from the 80s and 90s because I keep getting into those situations where I need an item from 3 acts ago, I have no save game handy, and now I gotta make dinner.<p>So I'm building the Lucasartsifier: a static analysis tool that decompiles Sierra resource files, automatically finds those states, automatically generates code to prevent the player from getting into those states, then emits loose patch files that can be placed alongside the original game resources. There's no game-specific code involved; all the logic is generic, though of course Sierra introduces new idioms and mechanics in every game so every new supported game needs a bunch of engine work.<p>So for example in Leisure Suit Larry 2, the patched game prevents you from boarding the cruise ship until you have both the sunscreen and the Grotesque Gulp. Without them you die on the raft 3 play-hours later.<p>So far this works on Leisure Suit Larry 2 (SCI0), King's Quest 4 (SCI0), King's Quest 6 (SCI1.1), and Laura Bow 2 (SCI1.1). I'm currently working on King's Quest 5 (SCI1.0).<p>This is work done with Claude -- I do the design and playtesting and it does the rest :D<p>Any feedback, play testing, and suggestions would be great!
Show HN: Automatically detect and patch walking-dead states in Sierra games
Hi HN, I've become lazier in my old age and struggle to replay my favorite Sierra games from the 80s and 90s because I keep getting into those situations where I need an item from 3 acts ago, I have no save game handy, and now I gotta make dinner.<p>So I'm building the Lucasartsifier: a static analysis tool that decompiles Sierra resource files, automatically finds those states, automatically generates code to prevent the player from getting into those states, then emits loose patch files that can be placed alongside the original game resources. There's no game-specific code involved; all the logic is generic, though of course Sierra introduces new idioms and mechanics in every game so every new supported game needs a bunch of engine work.<p>So for example in Leisure Suit Larry 2, the patched game prevents you from boarding the cruise ship until you have both the sunscreen and the Grotesque Gulp. Without them you die on the raft 3 play-hours later.<p>So far this works on Leisure Suit Larry 2 (SCI0), King's Quest 4 (SCI0), King's Quest 6 (SCI1.1), and Laura Bow 2 (SCI1.1). I'm currently working on King's Quest 5 (SCI1.0).<p>This is work done with Claude -- I do the design and playtesting and it does the rest :D<p>Any feedback, play testing, and suggestions would be great!
Show HN: Tesana – An AI game engine that builds quality games end-to-end
Hey HN! I built <a href="https://tesana.ai/en" rel="nofollow">https://tesana.ai/en</a>, a game generation platform that allows anyone to create full games with graphics, game logic, and animations from a simple text prompt - without coding.<p>Tesana has three key features
1. describe your game idea and have Tesana write a game plan for you
2. Build the game iteratively with AI, or let AI self-build the game in a build LOOP.
3) Launch the game on the web, without setting up an engine<p>Tesana has 250 000 builders on the platform today<p>I believe the democratization of game making is a good thing, and hopefully Tesana can help more people bring their game ideas to life.<p>Happy to chat about the AI or dev stack behind the product. Let me know if you have any
questions/comments/feature requests!
Show HN: A local MitM proxy to control TLS fingerprints
Show HN: I canceled my AI code reviewer and wrote a free local one
Show HN: Shoehorn – Quantize any model down to run on your machine
Working on Mac, Linux, and Windows now. I include a simple GUI to find new models and get things built and set up. It is working quite well across a few models for me. The GitHub README and DESIGN.md files go into detail of the how/why and it's working remarkably well so far. <a href="https://github.com/notactuallytreyanastasio/shoehorn" rel="nofollow">https://github.com/notactuallytreyanastasio/shoehorn</a>
Show HN: Shoehorn – Quantize any model down to run on your machine
Working on Mac, Linux, and Windows now. I include a simple GUI to find new models and get things built and set up. It is working quite well across a few models for me. The GitHub README and DESIGN.md files go into detail of the how/why and it's working remarkably well so far. <a href="https://github.com/notactuallytreyanastasio/shoehorn" rel="nofollow">https://github.com/notactuallytreyanastasio/shoehorn</a>
Show HN: Openleetcode – Local LeetCode runner where tests live in the repo
You write a standard solution, just like on LeetCode, and run it through the CLI. It identifies the problem by ID or title, executes your code against local test cases, and shows the result.<p>It currently supports around 1.4k problems and multiple languages, including Python, C++, Rust, Java, Go, TypeScript, Swift, and others.<p>The project is still an MVP. System design, SQL, and concurrency problems are not supported yet, but support for more problem types is planned.<p>Made in Haskell!
Show HN: Openleetcode – Local LeetCode runner where tests live in the repo
You write a standard solution, just like on LeetCode, and run it through the CLI. It identifies the problem by ID or title, executes your code against local test cases, and shows the result.<p>It currently supports around 1.4k problems and multiple languages, including Python, C++, Rust, Java, Go, TypeScript, Swift, and others.<p>The project is still an MVP. System design, SQL, and concurrency problems are not supported yet, but support for more problem types is planned.<p>Made in Haskell!