Show HN: OxiSH, a modern, memory-safe SSH server https://ift.tt/EWP3anD

Show HN: OxiSH, a modern, memory-safe SSH server https://ift.tt/Lts4pqD August 13, 2026 at 07:36PM

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