Show HN: Ctx, save tokens by loading only the relevant tools https://ift.tt/ySa6hgT

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 magic glasses that let you focus only on the tools you need. It does it by watching the repo and task, walks a graph of available tooling, and recommends a small top-scored bundle of skills, agents, MCP servers, and harnesses. How does it know? To make sure results are not hallucinated, and repeatable, I curated a list of 91k+ skills, 467 agents, 10.7k MCP servers, 207 harnesses, and built a graph to help ctx make decisions on what to recommend. While I used AI to generate it of course, I curated it and revised it to make sure the data is up to date. So how this is different from rtk, caveman, ponytail, and similar token-saving tools? As mentioned above those tools mostly reduce tokens after something is already being used. rtk compresses command output. caveman-style tools make the assistant respond with fewer words. ponytail, is, well, awesome, but again it focuses more on reducing code (YAGNI) ctx is upstream. It tries to avoid loading irrelevant skills, agents, MCPs, and harnesses into context at all. So it is not really a replacement. It should work side by side with them! Use ctx to choose the right tools. Use rtk to reduce terminal-output noise. Use terse-output tools if you want shorter responses. The goal is simple: save tokens without forcing the user to manually test and compare thousands of possible skills, agents, MCP servers, and harnesses. Repo: https://ift.tt/eR65bBJ https://ift.tt/eR65bBJ June 17, 2026 at 01:14AM

Show HN: Microlearning apps with a TikTok-style feed to beat doomscrolling https://ift.tt/vNoinqD

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/AN8chi7 ) Scroll: Learn AI ( https://ift.tt/QgZUTeu ) Scroll: Daily Microlearning ( https://ift.tt/STtqBjF ) https://usescroll.app June 17, 2026 at 12:06AM

Show HN: Claireon – MCP Server for Unreal Editor https://ift.tt/ZDPyUeJ

Show HN: Claireon – MCP Server for Unreal Editor https://ift.tt/JipYvef June 16, 2026 at 10:56PM

Show HN: Fata – Spaced repetition to fight skill rot from AI coding https://ift.tt/k3mWEvF

Show HN: Fata – Spaced repetition to fight skill rot from AI coding Hi HN, I'm Djoumé. I've been a developer for over 20 years, and like a lot of you I've been coding almost exclusively through an agent in the past few months. It's been amazing to vibe code prototypes in any stack, but when it comes to building something reliable/scalable, I couldn't effectively guide the agent unless I knew the technology. And the scariest part is that I'm seeing a lot of my technical skills decreasing due to AI coding. Reflecting on my journey, I also worry about how the new "AI native" generation of software developer is going to acquire technical depth. So I built fata.dev: short daily spaced-repetition sessions for programming skills (Rust, CSS, React, Python, TypeScript, Architecture). You can try it in the browser with no signup: https://ift.tt/9LiPlbU It's an offline-first mobile app built with Capacitor, RxDB and Firebase. The first courses were painfully written by hand, but most content is now AI-generated. It takes about 3000 LLM calls to generate a course, and every code samples goes through compilation, linting, unit testing, AI and a final manual review. Would very much appreciate any feedback on the product & website, what works and what could be better. Thanks! https://fata.dev June 11, 2026 at 06:57PM

Show HN: Steal-a-GIF – A browser tool to export GIFs from locked down platforms https://ift.tt/c2LZrWI

Show HN: Steal-a-GIF – A browser tool to export GIFs from locked down platforms Hi HN! I was super frustrated at apps like tiktok and wechat preventing me from saving or downloading the animated gifs, so I made a little tool to turn a screen recording into a slack-sized emoji. Hope you get some value from this! https://vorpus.github.io/steal-a-gif/ June 15, 2026 at 09:28PM

Show HN: Trace – Offline Mac meeting transcripts you can flag mid-call https://ift.tt/cw5QiYk

Show HN: Trace – Offline Mac meeting transcripts you can flag mid-call I'm the developer of Trace, a non-intrusive, shortcut-driven Mac app that records and transcribes your meetings on-device. I know, another meeting transcription app. Please bear with me though, I'm confident that this is at least a little novel. I primarily built Trace for myself. I'd been using MacWhisper, but there was enough fiddling before each call that I'd forget to start it and walk out of an hour-long meeting with nothing written down. So the things I cared about most were that it's quick to activate and stays out of the way. You activate Trace by pressing a global shortcut (configurable), which reveals a small bar at the bottom of your screen (there's also a keystroke and/or option to hide it entirely if you'd rather not see it at all). As I was building it I wanted to bake in a couple of workflows I'd wished for in other transcription apps. 1. Mid-meeting you can press another global shortcut to mark a "key moment" and type a note. The note shows up in the resulting transcript inline at that timestamp. I wanted to add this because I kept catching myself thinking "wait, that bit matters" in meetings and reaching to jot it down in a separate app like Obsidian, which I then needed to add context to, which took me out of the meeting. I use it all the time. If I paste the transcript into an LLM afterwards (which I find myself doing more and more these days) the important moments are flagged so it doesn't gloss over them. This is more noticeable in longer meetings with lots of topics. 2. With another keyboard shortcut you can summon a rough live recap (subtitles, basically) to quickly recap what's just been said. Trace uses standard macOS microphone and system recording APIs to capture both sides of the conversation as two separate tracks and then runs the system side through on-device diarization to identify speakers. Right now we only label them as "Speaker 1", "Speaker 2", etc but there are plans for speaker labelling in the future. You can also show a "live recap" as the call is happening to review what someone just said. All transcription models run on your machine. To be clear though, Trace doesn't do any of the summarising itself, it just produces a markdown transcript, so if you want summaries then you need to pass the output to an AI. The app is sandboxed and your audio/transcripts are never uploaded anywhere - they just exist as audio files and markdown on disk. The only network call Trace is required to make is on the first run to download the speech and speaker models (around 500MB) from Hugging Face, and after that it can be used fully offline. If enabled, a Google Calendar integration can auto-name sessions but that needs a network connection. The app is £9.99 on the macOS App Store. I've been using it every day for months now and I'm super happy with how it's improved my workflow. Feedback very welcome. https://traceapp.info June 14, 2026 at 03:41AM

Show HN: Philosophy for Kids https://ift.tt/sfR0B35

Show HN: Philosophy for Kids Sometimes my son asks me 'why' questions that could be answered well by a kid-friendly philosophy article. But I don't know where to find those, so I ask Claude or ChatGPT, and have a specific workflow for getting the type of output I want. I figured other people might find those AI-generated articles helpful, so I put them here: https://ift.tt/CXTfUYl There's a search box at the top. https://ift.tt/CXTfUYl June 15, 2026 at 01:15AM

Show HN: Kage – Shadow any website to a single binary for offline viewing https://ift.tt/HbNfdCk

Show HN: Kage – Shadow any website to a single binary for offline viewing https://ift.tt/pEVFqol June 15, 2026 at 12:25AM

Show HN: Bye-wk – Hide World Cup news from your feed https://ift.tt/GuXJThM

Show HN: Bye-wk – Hide World Cup news from your feed https://ift.tt/AxYkg7z June 14, 2026 at 04:50AM

Show HN: Galdor – a Go LLM agent framework with built-in tracing and replay https://ift.tt/zdrDoWl

Show HN: Galdor – a Go LLM agent framework with built-in tracing and replay https://ift.tt/78aPKuH June 14, 2026 at 02:04AM

Show HN: Verso – A $14.99 Mac word processor with no subscription https://ift.tt/UnThsfp

Show HN: Verso – A $14.99 Mac word processor with no subscription https://ift.tt/o3AZWBx June 14, 2026 at 12:43AM

Show HN: Lightweight C++23 S3 client with no extra deps (just curl and OpenSSL) https://ift.tt/ykbOI0Z

Show HN: Lightweight C++23 S3 client with no extra deps (just curl and OpenSSL) Attached is my attempt at making a small toy S3 client without any other dependency besides libcurl and OpenSSL. Was tested mainly on MinIO (RIP) locally, so I would expect some bugs when using it against AWS, although I was able to play with it on some open access buckets Be aware that I am not a C++ programmer and this project was indeed done to learn a bit of C++ myself :') Feedback on any of the code, either on gtest, or the benchmarking section or the core itself is welcome! https://ift.tt/ebP4ZyX June 13, 2026 at 11:40PM

Show HN: Squishy & Friends – Claude Fabel 5 coded a game and it is good https://ift.tt/50zjLN6

Show HN: Squishy & Friends – Claude Fabel 5 coded a game and it is good https://ift.tt/NlmEtzq June 12, 2026 at 11:43PM