Show HN: WindStrap – Bootstrap 5.3.8 to Tailwind CSS Using DeepSeek V4 Flash https://ift.tt/Owq6BTo

Show HN: WindStrap – Bootstrap 5.3.8 to Tailwind CSS Using DeepSeek V4 Flash bootstrap to tailwinds using DeepSeek V4 Flash https://ift.tt/5rW0uh6 August 13, 2026 at 03:08AM

Show HN: Programmable timer web app (for gym workouts or stretching sessions) https://ift.tt/BLJFcWe

Show HN: Programmable timer web app (for gym workouts or stretching sessions) Over the last couple of months, I’ve been building a timer web app for myself that I use for workout and stretching sessions. My main use-case is gym routines that consist of repeatable sequences, e.g. where you are holding certain positions for a set time (rinse and repeat). The app counts down the program, beeps, and reads the activities out loud. Two things (I suppose) are special about it: - The timers are “programmable”, so you can freely express your own routines and procedures in a declarative notation. - The app is all static (no backend): the entire program is encoded in the URL and can be bookmarked or shared/transferred via QR-code. You can check it out at https://ift.tt/OcPiB8w , optionally with a demo program pre-loaded: https://ift.tt/N8IxEZH . Source code is at https://ift.tt/RdxLhYp . I’ve also written up a small behind-the-scenes on my blog: https://ift.tt/c7HN24i https://ift.tt/OcPiB8w August 12, 2026 at 10:27PM

Show HN: Mooneva Cycle – Offline period tracker with no servers and no accounts https://ift.tt/uK1YHzh

Show HN: Mooneva Cycle – Offline period tracker with no servers and no accounts Data stays encrypted on your device (PBKDF2/AES-GCM), no internet permission, nothing to breach or subpoena. GPL-3.0, TypeScript/React + Capacitor. Android & iOS. https://ift.tt/ISFt4BA August 12, 2026 at 11:10PM

Show HN: Pulp – Zero-allocation C11 telemetry engine (28M logs/SEC to disk) https://ift.tt/iNv4JIQ

Show HN: Pulp – Zero-allocation C11 telemetry engine (28M logs/SEC to disk) https://ift.tt/I0p6KcG August 11, 2026 at 10:45PM

Show HN: My local climbing gym from photogrammetry https://ift.tt/EQPy23D

Show HN: My local climbing gym from photogrammetry Commented on yesterday's Ask HN: What are you working on? (August 2026), thought I might as well submit a Show HN. If you see climbing world cup/championship, there is this 3D modelling thing [1]. I want that for my weekly bouldering. I scanned my local climbing gym into 3D mesh using iphone. Built a simple editor to trim, merge, move/rotate meshes. You can interact with the mesh, view routes, view climb, etc. So this is unlike many gaussian splatting projects where the main use is for viewing. I built a pipeline in updating climbing walls. Climbing routes are manually annotated. Climbing videos are registered against the 3D mesh. Based on one input video, body positions resolved into 3D/4D space. you can view the body landmarks from different angle. COLMAP, OpenMVS, fastapi, svelte, database is just local json files. A read only build is exported so I can host on github page If you climb, or know someone who climbs, would love to hear your feedback. Do you usually record your climbs? If I make this a service, what will make you use it? [1] https://www.youtube.com/shorts/8zdUOaCr6DY https://kmcheung12.github.io/climb-preview/tour/ae43c6e5 August 11, 2026 at 01:39AM

Show HN: Graph2agent; Mermaid diagrams, explained for agents https://ift.tt/RUe3V0p

Show HN: Graph2agent; Mermaid diagrams, explained for agents During the implementation of a huge high performance service. In order to keep context small (mainly for humans) I kept the specs into mermaid diagrams. When communicating with humans; diagrams were easy to follow and to remember. But when I asked the agent to implement what's in the diagram, most of the times it failed. So I came into conclusion that agents are good into writing mermaid diagrams but they are not good into reading them. I built graph2agent in order to deterministically (without inference :) ) convert mermaid diagrams into digestible rich text for agents. examples: https://ift.tt/qrPV2Eg... This gave us 50% error reduction for any class of diagrams and 80% error reduction for sequence diagrams specifically. Also Input tokens increased on avg by 8% (which is expected) but Reasoning tokens dropped by almost 50%. You can use it either with MCP so agents can call it with any mermaid diagram, and also can put it in pre-commit jobs and run it on every PR so all diagrams are agent ready! I hope you like it! Let me know your thoughts! https://graph2agent.github.io/ August 11, 2026 at 01:29AM

Show HN: 100% native Swift harness (NOT Electron) https://ift.tt/FwDpfki

Show HN: 100% native Swift harness (NOT Electron) hi everybody, I’ve been working on this harness that is all native Swift for macOS. It’s fully featured with every feature i could find in cline, codex, and claude code. There is all swift command line too It’s taking me a long, long time, a few months to build this, and it’s fully open source Apache 2 licensed. Hoping people fork this and make many branches I’m looking for people who want to work on something that has much lower memory usage and much more potential to be just more efficient. Every other single harness has is written in using electron, so this harness is really unique in this way. It’s connected to trusted router so that it has end-to-end encryption confidential mode as well as access to hundreds of models, any model in the world. It works great with Deepseek. it’s great for swift development ios development. and for people who love Linux, I also made a compatibility layer that lets you compile SwiftUI into native Linux so that you either can new or QT actually so that you can just compile all the code directly and make it run on Linux https://ift.tt/QxaEG5T August 10, 2026 at 05:26PM