BlogViral

Show HN: NGB, an open-source .NET platform for document-driven business apps https://ift.tt/38UeX5p June 19, 2026 at 12:50AM

Show HN: SunCalc v2 – a tiny JavaScript library for sun and moon calculations SunCalc is one of my first open source projects — made the first commit 15 years ago and it had its share of wonderful uses ever since, but it's been somewhat neglected in recent years. Now that modern AI tools give me the ability to catch up on years of accumulated tech debt and user issues, I finally have the capacity to revive projects like this and keep them in excellent shape. v2 is a new version that improves the calculations accuracy by 5x for the Sun and by 20x for the Moon, verified by an extensive test harness vs ground truth from US Naval Observatory, in addition to fixing a ton of issues and modernizing the distribution with ESM. Hope you enjoy it. https://ift.tt/9fJbHSs June 18, 2026 at 09:47PM

Show HN: Relaymux, a tmux-based meta-harness for local coding agents Hey HN, There’s been a lot of interest recently in meta-harnesses, loops, and multi-agent orchestration. Obviously, there are already a lot of good tools: Conductor, cmux, the native Codex / Claude Code apps, etc. For my own use cases, I’ve felt that the orchestration layer tends to feel overengineered. I mostly wanted a simple local harness (i.e Pi) for running and tracking CLI agents with the ability to hop in (via tmux). Relaymux is my opinionated attempt at that. A few design principles: - The frontend is just Telegram / iMessage / CLI. If I want more visibility, I hop into tmux. - Subagents are normal interactive CLI agents running in tmux windows, usually with their own worktrees. - The harness owns the tmux session, so each longer task becomes a named tab/window. Subagents report back to the orchestrator via CLI when they’re blocked or done. Then the orchestrator just messages me on Telegram / iMessage - It wor...

Show HN: Deconvolution – a Rust image deconvolution and restoration crate I've been working on deconvolution, a comprehensive Rust image deconvolution and restoration library. Deconvolution implements 28 different image deconvolution/restoration methods which range from practical blur removal techniques to research-grade scientific imaging algorithms. Features: - Top-level functions use image::DynamicImage and return images - Inverse filters, Wiener, Richardson-Lucy, constrained, proximal, Krylov, MLE restoration - Blind Richardson-Lucy, blind maximum likelihood, parametric PSF estimation - Kernel2D, Kernel3D, Transfer2D, Transfer3D, Blur2D/Blur3D - Gaussian, motion, defocus, microscopy models, support utilities, PSF/OTF conversion - Edge tapering, apodization, range normalization, NSR estimation - Deterministic blur, noise, synthetic fixture generation - ndarray support for 2D image arrays and 3D volume this project is a WIP, of course:) https://ift.tt/3XviztL June 15, 2026 at 07:...

Show HN: Ctx, save tokens by loading only the relevant tools Hi HN! Token cost has started to become a high topic of concern to all of us. I tried a few (awesome) tools such as rtk, caveman, and the recent (hillarious but effective) ponytail. What they usually do, is in-line token reduction, e.g. try to compress requests / responses as much as possible. But then it hit me (and I’m sure others had similar ideas) - just like we have routers that pick the right model, why not have something that will also narrow down the amount of available tools, skills and mcps based on repo/context? People usually accumulate skills, agents, MCP servers, harnesses, prompts, repo instructions, and local scripts. I’m not saying we are all hoarders, but we sort of are. When did you remove a skill recently? After a while, the model has way too many options to choose from. ctx tries to fix that by selecting context before the session gets bloated.So no, it doesn’t cleanup your messy garage, but it gives you ...

Show HN: Microlearning apps with a TikTok-style feed to beat doomscrolling I wanted to kick my doomscrolling habit, so I built a microlearning app that uses a TikTok-style algorithm, same addictive feed mechanics, but you actually learn something. I started with a general version, Scroll: Daily Microlearning (microlearning.usescroll.app), but quickly realised it works better when focused on a single topic. So I split it into: Scroll: Personal Finance ( https://ift.tt/SCTqLNV ) Scroll: Learn AI ( https://ift.tt/nc1Fgqa ) Scroll: Daily Microlearning ( https://ift.tt/aXCubtO ) https://usescroll.app June 17, 2026 at 12:06AM