Show HN: Rust / Red Alert inspired WASM game in the browser (open source) https://ift.tt/jFaShpc

Show HN: Rust / Red Alert inspired WASM game in the browser (open source) https://punnerud.github.io/mpe-ra/ June 29, 2026 at 11:48PM

Show HN: HyperPaste – a free, open-source clipboard manager for macOS https://ift.tt/VqjPIrm

Show HN: HyperPaste – a free, open-source clipboard manager for macOS To me it always felt like clipboard history was one of the few things missing from macOS. There are already some excellent clipboard managers available, but after trying quite a few of them I kept coming back to the same goal: I wanted something that felt like it belonged on macOS. Fast, keyboard-first, private, and visually restrained. One thing I felt strongly about from the beginning was that it had to be open source. Clipboard managers have access to some of the most sensitive data we copy — passwords, API keys, personal information, financial details — and for something that sits in the background watching my clipboard all day, I personally wasn't comfortable using closed-source software. That ruled out a lot of otherwise great applications for me. The result is HyperPaste. HyperPaste is a free, open source clipboard manager for macOS, built with SwiftUI and AppKit. Clipboard data stays on your Mac — there are no accounts, cloud services, telemetry, or ads. Some highlights: - Instant search - Keyboard-first workflow - Rich support for text, code, links, colors, images, and files - Automatic color previews - Favorites for frequently used clipboard items - Native context menus and keyboard shortcuts - Local-first design with no ads or analytics One of the design goals was to avoid turning clipboard history into a productivity suite. I wanted HyperPaste to stay focused on one job: helping you quickly find and reuse things you've copied. The project is MIT licensed and the source code is available on GitHub. I'd genuinely appreciate any feedback, bug reports, feature suggestions, or criticism. I'll be around to answer questions throughout the day. https://hyperpaste.io June 29, 2026 at 10:13PM

Show HN: Sonar, local cited codebase briefings tailored to your role https://ift.tt/GTERy9V

Show HN: Sonar, local cited codebase briefings tailored to your role https://ift.tt/8hLglpq June 29, 2026 at 07:47PM

Show HN: NanoEuler – GPT-2 scale model in pure C/CUDA from scratch https://ift.tt/4bG8IU9

Show HN: NanoEuler – GPT-2 scale model in pure C/CUDA from scratch Hi everyone, I started working on nanoeuler after the ban of anthropic's fable because my ambition and dream is to work in the AI field in anthropic. The two interesting reasons that led me to create nanoeuler were (1) interfacing with llm does not mean understanding how they are composed and (2), working on llm with a very low-level layer to understand the correlation between parameters and data and growth of the model and how the GPU works and how some layers can be optimized. So I started working on it with a research aspect by making nanoeuler grow more and more but doing one step after another starting from Shakespeare.txt and understanding what a text generation model understands at 23 million parameters. For example, nanoeuler at that number had understood that Name: started a line and wrote that line with sense. I wrote everything in CUDA because I wanted to not use any intermediary between the model in training and inference and what it had to do. Then the use of SFT and much more, even if in small ways, were really useful to understand the various step to make an llm like a chatbot.Any feedback, help, or suggestions are absolutely welcome! https://ift.tt/RSq9ecG June 29, 2026 at 02:38AM

Show HN: Caliper – pass@k reliability testing for Claude Code and Codex skills https://ift.tt/XOrKvC8

Show HN: Caliper – pass@k reliability testing for Claude Code and Codex skills Skills for Claude Code and Codex are hard to test. What I mean by hard is that there's no standard way to do it. You evaluate the skill once on something, it looks like it works. You publish it. Then the new super model releases (GLM 5.2 anyone?), it will quietly break for some part, and you won't find out until your users complain. I also faced the same problem, so I tried to build something lightweight to stop doing that. Caliper. It's a local and lightweight harness that runs a skill k times in isolated environments and gives you a pass@k score (How much times it succeeded in these k times). As a non-deterministic technology, you can't just say "it worked once". You need to answer how much it passed in k times. You define success in a YAML spec. I picked YAML to keep a schema and make it still readable for a human. You either use a LLM judge, a Python assertion, or both: Here's an simple evaluation example with a JSON extraction, so you write this in a YAML file: tasks: - name: Extracts action items as clean JSON prompt: "Read /tmp/transcript.txt and write the action items to /tmp/actions.json." expect: "A valid JSON array where every item has owner, task, due. No markdown fences." assert: | import json items = json.load(open("/tmp/actions.json")) assert isinstance(items, list) assert all({"owner","task","due"} <= i.keys() for i in items) Then with the CLI, you'll run it: caliper run extract-actions.eval.yaml --k 5 --baseline What's cool about the --baseline flag is that it will re-runs everything without the skill, so you can see whether the skill is doing the work or the base agent was going to pass anyway: ID Task k(5) pass@k task-1 Extracts action items as JSON 5/5 100% PASS With skill 100% No skill 60% Delta +40% Most models know how to get the JSON right most of the time (JSON extraction was solved by 2 years old already). But that's it, "most of the time" is the bug. That delta shows how the skill actually helped. (It's sometimes 0%, sometimes -100%!) I also created two skills you can get started right away with your favorite harness, e.g. Claude Code, Codex or Pi: - evaluate-skill: run and manage evals without leaving your workflow - grill-skill: reads your SKILL.md, interviews you about what "good" looks like, writes a 3-task spec (happy path, edge case, adversarial), and runs it You can install the skill with the command: npx skills@latest add edonadei/caliper I for now support claude-code, codex, pi, claude-api, openai-api. You can run the agent and the judge as separate backends, so you can run a skill on one and judge with another. GitHub: https://github.com/edonadei/caliper PyPI: https://pypi.org/project/caliper-eval/ Of course, it's a first step. I think the autorater layer can be vastly improved, more handholding to create and iterate on evaluation specs, supporting more harness, why not including this layer into a self-improvement bigger system? If you're also building agentic evaluations, I'm genuinely interested to hear how you are handling that. https://github.com/edonadei/caliper June 29, 2026 at 12:42AM

Show HN: DRM-Free Books https://ift.tt/jC3fAq1

Show HN: DRM-Free Books After several years of mandatory DRM lockdowns from most commercial book sources, now authors have a choice when it comes to DRM for their books. Pick authors and books that are DRM-free, or download DRM-free classics that are out of copyright. https://ift.tt/Qd3FKU6 https://ift.tt/Qd3FKU6 June 28, 2026 at 11:58PM

Show HN: Starglyphs - A constellation puzzle game based on Euler paths https://ift.tt/uPFYsq4

Show HN: Starglyphs - A constellation puzzle game based on Euler paths I am a big Dragon Age fan and sunk hundreds of hours into Inquisition. It had this minigame called astrariums where you had to solve these shapes based on constellation guides by tracing stars. I'm a hobby game dev and wondered if I could procedurally generate these puzzles so they were always solvable. Turns out you can, so I built a space puzzle game around it with a colorful aesthetic. I released it in web form here but I'm currently working on getting it on Steam and mobile. https://starglyphs.com June 28, 2026 at 04:50AM

Show HN: Wind particles on Mapbox from a single EXIF JPEG https://ift.tt/PyalHx1

Show HN: Wind particles on Mapbox from a single EXIF JPEG https://ift.tt/PkTWzYt June 28, 2026 at 01:16AM

Show HN: A Living Neural Web in HTML5 Canvas https://ift.tt/JEuR8AZ

Show HN: A Living Neural Web in HTML5 Canvas https://techoreon.github.io/verpad/canvas-playground.html June 27, 2026 at 11:35PM

Show HN: Puzzle with Strangers. A free multiplayer jigsaw https://ift.tt/pN4ghfb

Show HN: Puzzle with Strangers. A free multiplayer jigsaw I built this over the last few days. Me and handful of friends are successfully hooked. I recently went to a — for lack of a better word – social/collaborative performance at an art gallery in Berlin where a group of artists filled a huge industrial hall with wooden 10x10cm cubes for people to build structures with. It was beautiful how universal the concept of playing with wooden blocks is and how ephemeral the structures were, people of all ages were put back into a childlike play. The thought about what kind of games need zero explanation stuck with me and i built an anonymous multiplayer jigsaw. We've already spent hours in there and you're invited now as well. Hope you enjoy. https://ift.tt/gMmKZRH June 26, 2026 at 11:47PM

Show HN: I built a hardware quantum RNG and wired it into a Magic 8-Ball https://ift.tt/D8gIXN3

Show HN: I built a hardware quantum RNG and wired it into a Magic 8-Ball Gday, author here! I've wanted to hack together a "real" quantum random number generator for another upcoming project, and I got carried away a bit, and went down the 'over-engineering' cliff. So, for your nerdy enjoyment, I have documented it all up, and I added something cool for fellow "Multiple World Interpretation" followers in the Quantum Mechanics debate. This QRNG uses sexy bits: Each is the decision of a photon to go left or right after hitting a 50:50 beam splitter. Standard kinda device, where you attenuate a light source down to single photons, offer them semi-mirror to bounce off, and see which PMT detector they hit (or which universe we ended up in ;) ). Basically, Through → bit=0. Bounce → bit=1. As I take the MWI interpretation of Quantum Mechanics (its the more fun options), I have also built a Quantum Magic 8-Ball. Ask it a questions, and you get and receive exactly one answer here, plus every possible answer across the multiverse. https://quantumlever.stream/oracle Enjoy! https://dnhkng.github.io/posts/building-the-beam-universe-splitter/ June 27, 2026 at 01:05AM

Show HN: A map of every UK railway, including stations that no longer exist https://ift.tt/uOrc5Hi

Show HN: A map of every UK railway, including stations that no longer exist Author here (Nathan). The goal for this site was to map the entire UK rail network: not just the parts a journey planner surfaces, but heritage lines, freight-only curves, named tunnels and viaducts, and the thousands of stations that have closed and were never mapped. The project is built entirely on open data. Lines and current stations come from OpenStreetMap via Overpass, closed stations from Wikidata (approximately 6,100 that fall outside a 250 m radius of a live OSM station), and postcode lookups from postcodes.io. The main challenge is that the sources rarely agree with one another, or even with themselves, so much of the work involved small reconciliation rules. For example, the heritage flag is propagated across every segment sharing a line name, so the Swanage Railway is coloured consistently. I shared an early version with a railway enthusiast community, and a large share of the fixes came from people who know the network considerably better than I do. A full write-up of the data challenges is available here: https://ift.tt/5dJPTvN No account or app is required. You can search by postcode, station name, three-letter code, or line name. Corrections are very welcome, as there is always a station someone knows I have got wrong. https://ift.tt/pYOXfT0 June 27, 2026 at 12:44AM

Show HN: Smart model routing directly in Claude, Codex and Cursor https://ift.tt/m5dw3QN

Show HN: Smart model routing directly in Claude, Codex and Cursor We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: https://www.youtube.com/watch?v=isKhAyivtfM . At Weave, we write ~all our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for everything but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided to build a model router to handle this for us. The Weave Router acts as an Anthropic/OpenAI endpoint specifically for coding agents. It looks at every inference request and intelligently (more on that in a sec) decides what model to send it to, handling all the translations required along the way. So it can use faster/cheaper models (e.g. DeepSeek v4, GLM 5.2, Kimi K2.6) when possible, and frontier models (Opus 4.8 & GPT 5.5 (& Fable whenever it's back)) when necessary. How do we know what model to route to? We trained an RL model on tens of thousands (so far!) of agent traces. We reward the routing model when it selects an LLM that successfully completes the given task. Here's an example: if you ask the router to plan a complex change, it will (probably) route that request to Opus 4.8. Subagents exploring the codebase to gather context will be routed to more suitable models (e.g. DeepSeek V4 Flash). Then when you have the plan ready to implement, it will be (most likely) be handed to a quicker model (e.g. GLM 5.2) to carry it out. We've been using this internally for the last month or so. We've saved 40% on tokens vs. what we otherwise would have paid, with no noticeable differences in quality or velocity. The router is source-available under Elastic License 2.0, so you can self-host it. Or if you prefer, you can also use our hosted version: weaverouter.com. I'll be here to answer any questions you may have! https://ift.tt/0EhpkNu June 26, 2026 at 11:40PM