value: hugolelievre

value:
Hi everyone, I'm Hugo, a French engineer of 25. I've been working on GreenKube for the last 10 months in my free-time.
I work in a 15-person IT services company and I didn't found a FinGreenOps tool for K8s that is free, easy-to-use and not overkill for small/medium clusters. So I started developping GreenKube to provide energy consumption and CO2 emissions of every pod in your cluster, with actionnable recommendations to reduce both emissions and cloud bills.
How it works:
- Collects CPU, memory, network, and disk metrics from Prometheus
- Maps each node's instance type to a power profile (min/max watts per vCPU from SPECpower benchmarks, same methodology as Cloud Carbon Footprint)
- Linearly interpolates power draw based on actual CPU utilization
- Multiplies by PUE and grid carbon intensity (real-time via Electricity Maps or a configurable default)
It comes with an 8-type recommendation engine (zombie pod detection, CPU/memory rightsizing, etc.), a built-in SvelteKit dashboard, a REST API (FastAPI), a CLI, and a pre-built Grafana dashboard.
Everything is packaged into a single Helm chart and exports native Prometheus metrics using standard K8s labels (namespace, pod, node), making sustainability data easy to join to your application performance stats.
It should support Azure, OVH, AWS, GCP and Scaleway out of the box. On-prem clusters work too with manual zone labels. I've tested Azure, OVH and on-prem, but not AWS, GCP and Scaleway yet, so if you find a mistake, don't hesitate to report it!
Try it in 30 seconds with docker (no cluster needed):
docker run --rm -p 9000:9000 greenkube/greenkube:0.2.11 demo --no-browser --port 9000
Or explore the live demo: https://demo.greenkube.cloud
To install full version, follow github readme or the doc at https://www.greenkube.cloud/
Current limitations (and where I'd love feedback):
- The energy model is currently CPU-only. Memory, disk, network, and GPU are collected as metrics but not yet factored into the energy estimate.
- CO2 estimation uses a TDP-based linear interpolation model (same approach as Cloud Carbon Footprint). I'd really appreciate suggestions on improving accuracy and include RAM, disk usage, etc... in the estimation.
- No GPU support yet.
The project is Apache 2.0 licensed. Built with Python (async), FastAPI, SvelteKit, and Helm. I'd be grateful for any feedback, on the tool itself, the estimation methodology, feature priorities, or anything else.

value: Show HN: GreenKube – Open-source K8s cost and CO2 optimization engine

author: hugolelievre


value: mitchm

value: I love Uno, so for fun I made a web based multiplayer version of the game. Completely free, no ads, no accounts. Has some of my favorite custom “house” rules like stacking, shuffle hands, and numbers only!<p>Play friends or play AI. Chat with opponents. You can even bring your own AI

value: Show HN: Uno – Us vs. Them. Humans vs. AI version of the card game

author: mitchm


value: notfirstpost

value: Show HN: DAGraph – reactive analytics graph in the browser (Rust/WASM)

author: notfirstpost


value: kingofsunnyvale

value:
I kept reading the news and social media thinking "there's probably a market on this," and never looking it up. So I built the lookup into the page.
Anywager scans the page you're on, highlights text that matches a live prediction market, and shows the question, odds, and a link to Kalshi on hover.
Right now, it only points you to Kalshi; it doesn't place bets yet. The direction I'm headed is collapsing that last step: see the claim, see the odds, and drop money on it --- frictionlessly --- all without leaving the site.
I'd like feedback on the matching especially, cause it tends to misfire sometimes. Ask me anything!

value: Show HN: Anywager – Inline prediction-market lookup for whatever you're reading

author: kingofsunnyvale


value: matthewzmd

value:
Hey HN, I’m Matthew, one of the people building Genomi.
Many people have done a DNA test or sequencing in the past, but the results stay virtually dead on our computer, maybe we saw a report that came with it, but does anyone still remember what it said? I don't. What bothers me even more is that the world of DNA science actually evolves quite quickly, there are many new findings published every year and that may or may not be relevant to your DNA, but your old report, which I spent a fair amount on, will not have it! (though it has gotten much much cheaper lately)
I feel AI agent is the perfect tool to help me query and understand my own DNA, but I am immediately hesitant to feed my own file to an agent, not only the security risk of sending my own DNA file to them, but it simply doesn't work, the massive nature of the file will overflow the context window with excess data that gives me near to no value. So we built Genomi: an open-source local genomics harness for AI agents.
Genomi parses a VCF/gVCF or supported consumer DNA export, such as 23andMe or AncestryDNA, into a local SQLite index called the Active Genome Index (AGI, heh). The agent does not need the whole genome in context. Instead, it calls tools against the local index and public evidence sources as it sees fit. Today it exposes 80+ evidence-focused tools across genomics sources including variant lookup, gene/disease evidence, pharmacogenomics, GWAS/PRS context, population context, sequence/region utilities, etc.
The project is at an early stage and I welcome any feedback, please let me know what you guys think!

value: Show HN: Genomi – make genome data manageable and queryable by AI agents

author: matthewzmd


value: winphoto

value: Show HN: AgentLoop – a Claude agent starter you can read

author: winphoto


value: arbourtrary

value: Show HN: Wanderwhim – AI workspace for writers, bloggers, lifelong learners

author: arbourtrary


value: AnvarBakiyev

value: Show HN: The Logos Machine – AI that distill knowledge into weights during Sleep

author: AnvarBakiyev


value: nilen

value:
Hi HN! I'm building Ano because I was tired of Slack's bloat and sluggishness, and never got any value out of their agent implementation.
Ano is built local-first for speed (using Rocicorp Zero), focused on communication, and lets you use your own code agent as an assistant (Claude in my case, but it works with Codex too).
I use the code agent to summarize anything unread (linking back to what matters), respond with context, and share data to and from connected tools (GitHub, Posthog, Attio, etc).
Using your code agent for this might sound counter-intuitive, but to me it's the most powerful agent I use. It already has connections to my tools, and now it has access to Ano for communication too. The agent lives in an in-app shell, and Ano also has a CLI, so you can read and message into the chat from whatever terminal you're already using.
Basically: Slack, minus the noise, with your code agent doing the work.
Early days, but you can download the app and try it (macOS and iOS for now, more to come!). Would love your feedback. It's free, but you bring your own code agent account.

value: Show HN: Ano – no-noise team chat with your code agent as your assistant

author: nilen


value: borkasm

value: Show HN: Chatcode – Remote Control for Claude Code and Codex

author: borkasm


value: naveenksv

value: Show HN: HostAnywhere – Securely connect devices and services, backup phones

author: naveenksv


value: soamikapadia

value:
Hey HN, we’re Soami, David, and Achyut, co-founders of Extract. Extract parses documents into structured data (text, tables, and figures). Teams use it for RAG, feeding llms, and populating databases and forms. Today we’re launching our first OCR model, now used in Extract.
You can try some examples here or upload your own (no signup required) to test it out: https://extract.page/demo
We built Extract out of YouLearn, where we were processing 70m+ pages and slow parsing was the bottleneck. We started with a purely algorithmic pipeline that pulled native text straight from the document and only ran OCR on pages that needed it. It was cheap and fast, but once we put it in front of our Extract customers and their hardest documents, it hit an accuracy ceiling. We wanted to keep the speed and cost while improving accuracy, so we trained our own VLM for the cases that broke. It also provides element level bboxes, so each result points back to its exact place on the page.
That took one customer from 71% to 92% text accuracy in under a week, at the same speed and cost. We can do this because of our synthetic data generation pipeline that recreates the messy, real-world documents the model gets wrong, so we can retrain on those exact cases without having to hand-label data.
To see how this holds up against other providers, we benchmarked Extract against AWS Textract, Extend, Reducto, LlamaParse, and Unstructured on 130 human labeled pages from difficult real-world documents. Extract is #1 on text accuracy (81.9%) and word-overlap F1 (84.5%), second on grounded accuracy, and competitive on layout IoU, while running at least 2x faster than every parser we tested.
Here are the benchmarks: https://extract.page/bench
Extract is $3 per 1000 pages and about 5x cheaper than AWS Textract (layout + table enabled). To see how it performs on your own docs, feel free to send us a few and we’ll run a benchmark on them. We’ll get back to you with the results in a few days once we receive the docs: https://cal.com/team/youlearnai/extract-intro
Thanks for reading this post! It's our first version of the model and we're shipping further improvements to handwritten, multilingual, and table-heavy documents. We know there are documents it won't handle well yet. If you have one, we'd love to see it.

value: Show HN: Extract (YC P25) – Fast, accurate document parsing

author: soamikapadia


value: Sunkek

value: Show HN: NoiR Code – because QR sounds similar to "noir"

author: Sunkek


value: johnnydamacha

value: hi hn! Title basically covers it. I made Nib over the course of about a year and a half. It's a collaborative font editor, kind of like figma but for type design instead of UI design. Also has AI features for generating glyphs, versioned export, font import, advanced bézier curve editing features...and cursor chat. Among other features. Lemme know if you find any bugs!

value: Show HN: Nib, collaborative font editor on the web

author: johnnydamacha


value:
Hello all. My background is in blockchain protocol engineering. The company I was at wound down, which left me with a lot of time, so I'd been pushing frontier models on hard distributed-systems problems and was impressed enough to try building something autonomous end-to-end.. a micro-SaaS factory. A few months in I realized the runtime underneath was more interesting than the product on top of it, so I extracted it. That's Swarm.
A lot of the design comes straight from blockchain engineering: I wanted something purely async and event-driven, where state only moves through committed, ordered transitions. The one decision everything hangs on is that the LLM does not run the system. Agents reason in scoped sessions and emit events; deterministic code, never the model, decides what each result changes. I think this enables some interesting workflows.
Curious to know what you think of it!

value: Show HN: Division Swarm, the OS for Multi-Agent Systems


value: ivoputzer

value: Show HN: Testbump – automated test driven versioning

author: ivoputzer


value: nunopato

value: Show HN: Constellation is an open-source Hasura-compatible GraphQL engine in Go

author: nunopato


value: baggiiiie

value:
as a big TUI  user, i absolutely enjoy hunk https://github.com/modem-dev/hunk. tho when it comes to reading diffs i still prefer GUI somehow
made a local version of @pierrecomputer's diffshub.com for reviewing codes, with jj support and review copying to directly send to agents :D
huge shoutout to @bentlegen for the inspiration on agent review, and pierre team for the amazing work!
try it with `npx @baggiiiie@yadiff $GitRef/$JJRevision`
beyond local diff viewing, it supports GitHub PR fetching too. so you can test it on your PR, or test it on bun's rust rewrite PR `npx @baggiiiie@yadiff <a href="https://github.com/oven-sh/bun/pull/30412" rel="nofollow">https://github.com/oven-sh/bun/pull/30412</a>`
any feedback is appreciated!

value: Show HN: yadiff, yet another diff viewer, based on pierre's diffshub

author: baggiiiie


value: jithinraj

value: Show HN: Check whether agent logs are independently verifiable

author: jithinraj


value: Show HN: PocketPing turn Telegram/Slack/Discord into your customer support inbox


value: GBillington

value: Show HN: On-device Chrome extension that blocks credential leaks to LLM chats

author: GBillington


value: AxelWickman

value: Show HN: Solving complex optimization problems with Google OR-Tools in browser

author: AxelWickman


value: dbrereton

value: Show HN: The Last Museum – Semantic search across all museum art

author: dbrereton


value: vunderba

value: Show HN: Maritime Trivia (Reverse Engineered DOS Game)

author: vunderba


value: aitne

value: Show HN: I built a personal AI agent that schedules its own wake-ups

author: aitne


value: hboon

value: Built this to more easily search the monthly postings.

value: Show HN: Get HN Jobs

author: hboon

title: Show HN: Get HN Jobs


value: pigcat

value:
It's our new text-to-image model: a 9.3B single-stream diffusion transformer trained entirely from scratch.
We focused heavily on controllability through structured JSON prompts, with strong text rendering, spatial awareness through bounding box guidance, and color palette control.
It has the best text rendering of any open-weight model we've tested so far, and the NF4 quantized checkpoint runs on a single 24GB GPU.
For more technical details and examples see our blog post: https://ideogram.ai/blog/ideogram-4.0/
We will be happy to answer any questions :)

value: Show HN: Ideogram 4.0 – open-weight 9.3B text-to-image model

author: pigcat


value: bArmageddon

value: Show HN: Mini-split BTU calculator and state-by-state heat pump rebate guide

author: bArmageddon


value: tschiller

value:
I've been experimenting with Claude Code, ChatGPT Agent, and OpenClaw to perform more open-ended tasks for me online.  A big blocker I've hit on shopping and research tasks is the agent getting a key piece of info wrong.
For example, in one case, my agent decided to add a brand I don't like to the cart because the site flagged it as almost sold out
The HN crowd is probably pretty aware of the threats and can avoid them while browsing. But what about their agents?
I tried prompting, but it was ineffective, because once the AI saw the threat, it polluted/distracted its context
Looking at the research, I came across a couple of papers, SusBench and Decepticon. The Deception research benchmarks indicate that increased reasoning can perform worse, because the model rationalizes the dark pattern
So it seems the best approach has to be removing the information before it can pollute/poison the context
In my day job, we have a browser extension that started as a productivity extension. However, contact centers started using us for neutralizing insider, fraud, and social engineering threats.
So my team set out to create a browser extension to neutralize all the threats AI agents face
We're focusing on open-ended tasks, because the best practice for routine tasks is to have the agent script repeat actions
It's also a tricky area since AI agents view the web in different ways: DOM, a11y tree, and visually. So we needed to account for those differences in how we detect and neutralize threats
The extension we created is agent-browser-shield, which defends against three primary threats:
- Prompt Injection
- Dark Patterns
- Context Pollution
It's free and source-available on GitHub, ClawHub, and the Chrome Web Store: https://github.com/pixiebrix/agent-browser-shield
We plan on making an enterprise version that pairs with our low-code engine for letting teams easily create custom rules for business-specific sites and internal tools
Looking forward to feedback! Especially curious if anyone has agent traces that got poisoned or sites to red team against!

value: Show HN: Agent-browser-shield – free extension to protect AI agents on the web

author: tschiller


value: llovan

value: Show HN: Nutrepedia – Nutrition info in 29 locales built with Clojure and Htmx

author: llovan


value: smarterhome

value:
I was in a long-distance relationship for some time and it is hard. We love each other a lot but being in different countries, even different timezones for a longer time is quite a burden if you want to build a great relationship. We made it work (we are married now!) but it took a lot of work to stay and feel connected while we were not physically together.
We tried quite a few things during that time, regular video calls, lots of text messages and even couple apps like Agape. You still struggle during those darker moments when fate makes your life a little more difficult. One day I had a good idea though that really helped us: I quite enjoy listening to podcasts so I just took my phone and started recording myself while I talked about some of the greatest moments we had together. Then I uploaded it to my own Nextcloud and shared it with my (now) wife. She loved it! Her own podcast full of joyful moments. Now there are a bunch of episodes already and she was able to listen to them any time - guaranteed to get some great memories in my own voice.
This really helped us and I am sure there are a lot of others out there struggling through very similar situations. That's why we started building a more professional tool for this: PersonalPod. I am the typical software engineer - I really enjoy building stuff (other than the UI) and I keep coming up with more ideas that will go into this project. This time we decided to make it available to others as well though before I build forever. Probably you actually need different things than I would think...
Have fun trying it out at https://personal-pod.com/ and please leave some feedback (here or directly on the website via the feedback tool). I will read them all I promise and try to improve things as much as I can.
You can already share podcasts with a small group of people (or just one if you want) or make a partner podcast where both of you can upload episodes.

value: Show HN: PersonalPod – Saving my long-distance relationship with a podcast

author: smarterhome


value: tlar

value: Show HN: Erebus, A VPN client that runs rootless in user space

author: tlar


value: LoadingALIAS

value: Show HN: Rscrypto, pure-Rust crypto with industry leading public benches

author: LoadingALIAS


value: sauravt

value: Show HN: Capture, compress, and copy screenshots to clipboard

author: sauravt


value: thehivery

value: Show HN: Hive Trust – Ed25519-signed benchmarks for every AI inference primitive

author: thehivery


value: ktaraszk

value: Show HN: Mashines.dev – Live-migrate microVMs between hosts without restarting

author: ktaraszk


value: vukasinrancic

value:
Hi HN. I honestyle DO NOT like one on one sessions with my claude/codex when working with my team.
So I built something that connects us and our agents in the same room.
CTP Room is my attempt at a coordination/co-work layer, one shared chat room (think Slack channel) where humans and several agents work together ( I took Garry Tans gstack and formed my own team around it when I work solo ).
What it does:
- Routes each message to the right agent instead of broadcasting (For this case, a cheap Haiku router picks one).
- File claims: an agent claims a file before editing; another is told who holds it instead of
  clobbering it.
- Persistent team memory: who did what, decisions + rationale, so context survives sessions.
- Bring your own agent over MCP (Claude Code, Codex, Cursor, OpenCode) or any program over HTTP.
  Multi-vendor on purpose.
- Presence + activity feed come from deterministic hooks at zero tokens; the expensive model is only
  spent on real work.
Happy to go deeper on this subject, I think I will open source it soon, wondering what you think about this?

value: Show HN: CTP Room – a shared chat room where your AI coding agents coordinate

author: vukasinrancic


value: Built this because I'm sick of keeping documentation up to date when everyone's using AI tools now.<p>It will not only generate missing docs / update / remove docs as they need alignment, but you can hook up the MCP to whatever agent is being used these days and it'll inform it of codebase conventions & relevant documentation, telling it to update docs as it find them or as it makes changes (in the same PR as related work), and reduces spend on tokens by getting things right the first time without having to grep the whole codebase for context or go through 5 rounds of "follow our conventions"

value: Show HN: Moxie Docs – Automatic codebase documentation and MCP


value: ashitlerferad

value: Show HN: Cf-colo-watcher – Monitor which Cloudflare colo is serving you

author: ashitlerferad


value: brumbelow

value: Show HN: Viewport – A clean local agent monitor

author: brumbelow


value: sourishkrout

value: Show HN: Agents ship diffs. Visr keeps trajectories

author: sourishkrout


value: gulugawa

value: Show HN: I created a React alternative using web componnents

author: gulugawa


value: nistuley

value: Show HN: CLI for crawling documentation sites into Markdown with defuddle

author: nistuley


value: Show HN: Aeterna – Private, passwordless AI digital legacy vault


value: zaydmulani

value: Show HN: Mnemo – local-first AI memory layer for any LLM (Rust, SQLite,petgraph)

author: zaydmulani


value: savkevip

value: Show HN: GhostUser – AI personas that find UX bugs by walking your app

author: savkevip


value: Show HN: Mermaid Studio – preview and fix broken mermaid diagrams


value: boydYVR

value:
I've been coding since I was little, and practicing yoga since I was 25.  Both are fun to do and to share.
Like many of you reading this, I've been experimenting with AI agents.  Unlike many of you, I'm a yoga teacher.  I got to thinking... could my agents behave better if they did yoga?  It works for me, and LLMs are trained on human generated content...
So I developed a program for agents to get the benefits us humans get from the physical practice of yoga.  Improved focus, memory, intent,  goal coherence, honesty about uncertainty...
For the past three weeks my Hermes agent has been taking yoga every morning.  The first few passes seemed to improve some of the prompts and skills, but not lately.  I'd love some feedback from anyone using agents who wants to ask their agent to run this skill.

value: Show HN: Yoga for Agentic AI: Cognitive training practices from a yoga studio

author: boydYVR


value: jfroma

value:
Hello HN! I am a flight student and made this tool to replay and study my flights. It is completely opensource [1] and everything works in the browser until you create a shareable link.
You can also export a video.
Here is an example of a flight [2]
[1] https://github.com/jfromaniello/joseflys/tree/main/app/repla...
[2] https://joseflys.com/replay/DUbxkAIp

value: Show HN: GPX Flight Replays

author: jfroma

title: Show HN: GPX Flight Replays


value: trykhlieb

value: TurboPrefill is an attempt to make layer-split multi-GPU configurations spend less time waiting and more time computing during prefill.

value: Show HN: TurboPrefill – Multi-GPU prefill acceleration for llama.cpp

author: trykhlieb


value:
NoSuggest is a quiet act of resistance against YouTube algorithms always trying to pull you into a loop of unlimited videos in turn into unlimited screen time. With unending side cards of videos, auto-play, what's next suggestions, YouTube shorts and notifications, users will be doom scrolling for many hours in a day.
I faced the same problem. Acknowledging that, not all content in YouTube is bad. There are educational videos, genuine news contents without political bias which is very hard to find outside YouTube and many other good relaxing, entertainment stuff.
NoSuggest lets you only follow the YouTube channels you like and removes all types of recommendation YouTube has. So you don't waste time on watching things which you never wanted to watch anyways.
UI is very simple. You add your favourite channels in "Channels" tab and latest 5 videos per channel excluding shorts would appear in "Feed" tab. "Search" tab is to search for specific videos to watch and "Saved" tab is to bookmark any video you want to watch later. Intention of NoSuggest is to provide whatever is necessary to extract whats good from YouTube all inside NoSuggest and leave out bad parts.
NoSuggest works in any devices. Install it as an app (PWA) in android and iPhone, or simply open in browser in laptops. No sign-in, no account creation or no card details. NoSuggest won't even ask your name. Total privacy for the users.
Parents can add the channels and save some educational videos and lock it with the pin for kids mode. Kids won't be able access unwanted additive contents inside NoSuggest.
Completely free, no string attached. Source available in Github through NoSuggest website.
I would love genuine feedback. Thank you very much for your attention on this matter.

value: Show HN: NoSuggest – Watch YouTube without the recommendation algorithm


value: Show HN: Code3DBench – single-image to executable Three.js benchmark


value: Hello.<p>After hearing of the problematic LLM commits in rsync, I made a fork of rsync. I decided to fork it off release 3.4.1, since I heard that's the last release without the LLM code.

value: Show HN: Fork of Rsync

title: Show HN: Fork of Rsync


value: rswcf

value: Show HN: Dictivo – local-first Mac dictation for $49 once

author: rswcf


value: JoniMartin

value: Show HN: Lookspan – local-first observability for AI agents (npx lookspan)

author: JoniMartin


value: subairui

value: Show HN: Bio Glyph – Turn Your Face into a One-Line Drawing

author: subairui


value: flexdinesh

value: Show HN: tools wiki – cheatsheets for popular CLI commands

author: flexdinesh


value: Byalpel

value:
Nisrine and I have been working in the same company for many years (she's Head of Product, I am CPTO) and we have done great things for our employer(s) all along. But we always wondered if we could launch our own app – after all, we know the process of it all, we just "never had the time".
The idea started from a random conversation, after Nisrine told me a personal story about she had a stupid little fight with her partner, and after 3 or 4 back-and-forths on each side, she decided she was right. Of course, he decided HE was. But he was not sure, so he asked chatGPT... And lost :)
We were making fun of him but then we thought, wait: everybody fights for stupid little things. It would be great if someone impartial, neutral, with no bias, could move the needle in one direction. Not render a verdict like in a Roman Forum but just shows you where (both of) you are right or wrong, and then makes the person who is more in the wrong apologise. Yeah, an AI :)
Why apologise? One, because it's the best way to bring back peace to any relationship. Two, because it's hard to let go, put your ego on the side and accept that, "yeah, it's not worth fighting or sulking, sorry".
And three... because it's so cool to see the other one bow and lose the argument :) Come on, don't pretend this is not thrilling to win an argument!
So we built this app, called Piece (sounds like Peace, it's the peace of offering to bring back peace – the logo is an olive branch). The app comes with different tones: witty, theatrical, sarcastic and counsellor (if you want to go deeper in the analysis). The principle is very simple: you record yourself, your partner records their version, you get an analysis of each side's good and weak points, then a verdict.
The app stores everything locally, no personal data shared anywhere (except the ephemeral transcript). And the two partners need to use one phone only: that brings them closer already. And from there, you can imagine all the features you want: dashboard with analytics (who has the biggest ego? how many times do you fight?), sharing on social media for "funny" humiliation, karma points, music generation of your fights etc.
This app does not replace the couple therapy apps, of course. We are more malicious, this is more about a gamified experience for the day to day arguments.
While building the app (Claude + Claude Design, app is in Flutter if you're interested), we were amazed by how many hilarious sentences the AI engine came up with. We were not expecting something that smart, to be honest, and that was what we liked about this side project: every test was a laugh! – ok, maybe not when Nisrine introduced regressions in the code: she argues that she did not but we asked Piece, and I won...
We had good feedback from regular users so we recently decided to launch for a bigger public.
The app is on the iOS and Android stores (look for "Piece, relationships"), works in English and French for now. Free to start, we'll surely implement credits when we grow our audience. Get it from here: https://thepiece.app
Happy to expand on any of this here if you are interested

value: Show HN: an AI app that settles small couple arguments

author: Byalpel


value: benhmoore

value:
Hello HN,
I’m building Roughform, a browser-based 3D modeling app focused on familiar hard-surface modeling workflows. I'm a huge fan of Blender, but I often want to work on a scene when I'm away from my laptop or desktop.
It includes edit mode modeling, object layout, nondestructive surface booleans, OBJ export, and touch-friendly controls. It all runs in the browser (webGPU).
There are still bugs, and I’m actively working through them. I may add a Pro version later for things like cloud sync, but everything that is free today will remain free.
I’d love feedback if you try it. There’s a feedback system built into the app.
Thanks,
Ben

value: Show HN: Browser-based, Blender-like hard-surface modeling

author: benhmoore


value: Show HN: CPU-only fact-check, summarize, explain, translate any text


value:
I created a plugin for LiveComment to make working with the "Who Is Hiring?" threads easier and more convenient. I've wanted to implement this idea for a long time, ever since I created LiveComment in 2014. Feel free to clone, modify and extend both LiveComment and this plugin, then let's open a PR
Full link to the plugin: https://github.com/d08ble/livecomment#j001-hn-firebase---ask...

value: Show HN: LiveComment – "Who Is Hiring?" Plugin


value: kadhirvelm

value:
We've spent the last several months iterating on a rich, HTML-native document canvas. We kept finding we wanted a shared space where we could work on a written artifact with our team while getting some AI assistance along the way.
Lots of interesting and challenging problems when designing a document editor that allows many humans and agents to understand and edit simultaneously. Especially one that supports things like Mermaid diagrams and XYZ flow charts out of the box!
We're officially GA, would love for people to give it a shot and tell us what they think. Feedback is greatly appreciated! If people want more credit, shoot us a note (hello@productnow.ai), we're happy to support :)

value: Show HN: A rich, HTML-native document canvas for human <> AI collaboration

author: kadhirvelm


value: jpajak

value:
Hi HN, new account but long-time reader. I built this for myself because I kept manually checking usage across Claude, Codex, and Copilot, and wanted to track the session and weekly usage all in one place.
It's helping me better track and get the most out of my AI subscriptions. It's also a good testament to agentic coding making it easy to create useful tools that wouldn't have been worth the time before, or to build more complete utilities instead of bare-minimum solutions.
Putting it out there in case anyone else finds it useful. Happy to take feedback.

value: Show HN: AI Gauge, a desktop monitor for Claude/Codex/Copilot usage limits

author: jpajak


value: Daniel-Pan

value: Show HN: AI Agent that resolves all your support issues

author: Daniel-Pan


value: nabucodonosor

value: Show HN: Suture – a reverse proxy that repairs truncated JSON in LLM streams

author: nabucodonosor


value: thequert

value: Show HN: Apertis – OpenAI-compatible API gateway for 470 AI models

author: thequert


value: Show HN: X402-express. Pay-per-call HTTP 402 middleware for AI agents on Base L2


value: Leftium

value:
Source code: https://github.com/Leftium/fx/blob/main/src/routes/fire-plas...
I made this naive fire effect as realistic as possible; arguably more realistic than some simulations based on real fire fluid dynamics[1]. The naive algorithm uses a kernel to simulate convection, diffusion, and cooling of heat. Described in more detail by Joakim Hårsman[2]. Also see working demo of the OG fire algorithm by Justin Greisiger Frost[3]
While canvas + CPU gets surprisingly good performance, this effect would probably run much faster on the GPU. On mobile, this version is sized to work better: https://fx.leftium.com/fire-plasma?standardSize=0&text=Le
In my improved version, flames "lick" the bottom of the floating text. This is my favorite part. It was totally unexpected and just emerged from the algorithm. Compare to Joakim's version by changing the text: https://fx.leftium.com/fire-plasma?text=%E2%97%AF
Major improvements over prior art:
- True-color fire gradient/palette with transparency looks decent over non-black backgrounds : https://fx.leftium.com/fire-plasma?bgColor=
- Fire seeded with perlin noise + brownian fractal movement: fire is overall less uniform while avoiding "random mess" at base of fire: https://fx.leftium.com/fire-plasma?fireSeedIndex=3
- More complex fire kernel for more realistic looking fire
This was one of the first projects I have recently worked on without the assistance of a coding agent. I only chatted with LLM's a few times to get ideas and help with type errors. As a result, I feel this project took more time, but the code is more succinct/hand-crafted.
---
I wonder if anyone can find other pleasing values for the fractal noise seed. The values can be adjusted via URL params like this: https://fx.leftium.com/fire-plasma?octaves=4&lacunarity=2&ga...
You can also view the perlin noise by itself using this URL: https://fx.leftium.com/fractal-noise?octaves=4&lacunarity=2&...
For a description of octaves, lacunarity, gain, etc: https://gamedev.stackexchange.com/a/197862/229
[1]: https://www.escapemotions.com/experiments/fluid_fire_3/
[2]: https://ghostinthecode.net/2016/08/17/fire.html
[3]: https://jdfio.com/pages-output/demos/x-mode/

value: Show HN: Realistic procedural fire effect via naive algorithm

author: Leftium


value: mlboy

value: Show HN: iPhone ANE holds LLM tok/s while MLX and LiteRT thermal-throttle

author: mlboy


value: baalimago

value: Since everything needs an AI slogan now a days: with this you can just keep your browser open as it's being worked on agentically and see your website be built in front of your eyes!

value: Show HN: Wd-41, hot-reload webserver for static sites

author: baalimago


value: markjivko

value: Show HN: You can now unlearn CSS selectors

author: markjivko


value: iliaov

value: Try it in 60 seconds - no hardware needed. It supports 23+ LiDAR models including LDROBOT, YDLIDAR, RPLIDAR, 3irobotix, Neato, Xiaomi, Camsense and Hitachi-LG.

value: Show HN: I've hooked up 2D LiDARs to Raspberry Pi, wrote Python library lds2d

author: iliaov


value: alfanick

value: I got sick of the state of processing RAW images on Linux, especially when you apply film emulation. So vibe-coded (took 2h and 20CHF of tokens) my own solution - uses rawtherapee or dcraw for RAW development, converts Adobe XMP RGBTables into Hald LUT tables, applies Gaussian/Perlin noise to simulate grain, and applies simulation based on LUT using ImageMagick.<p>Batch processing and multithreading is supported.

value: Show HN: Mini-film, processor of RAW files with XMP profiles – Linux and Rust

author: alfanick


value: evolabs

value:
Hi everyone!
Tim here, maintainer of the lucide-motion-vue library. I build this as a way to use nice animated icons in my webapps. We were already on lucide, and found animate-ui animated icons as a great collection, unfortunately React only or made to be used with shadcn.
So I ported the library to Vue, and combined it with another library (lucide-animated.com). As both libraries dont share the same animations and/or icons, this creates the largest animated icons library for vue that can be used from one source.
Additionally, I've made several quality of live changes to make it easier to use the icons:
- drop-in replacement for lucide icons, or use a seperate namespace if you want
- several animation variants
- easy to be used standalone or in buttons
- several animation triggers
- comprehensive overview, playground and docs page, comes with llms.txt to be used by agents
Finally, the repo also contains a "forge". With this, you can
a) take any icon from the lucide library, or have ai suggest some
b) autogenerate animations for these icons
c) add them to the library with one click
We'll use the forge over time to hopefully create animated variants for all of lucides icons, if these icons are useful to be animated.
Looking forward to hear your feedback
Cheers!

value: Show HN: Free animated icon library for Vue

author: evolabs


value: BrunoBernardino

value:
You can get a 2h free trial by solving a proof-of-work captcha when topping up your account for the first time.
If you'd like to learn more, an independent interview was posted a couple of weeks ago [1], and the FAQ [2] has a lot of information as well.
For the source code sharing, we've talked with lawyers and are inclined to no longer require the NDA/NCC for privacy reasons shared with us before (signing requires identification), but instead use a source-available permissive license that doesn't allow competition, like PolyForm Shield [3] (we do still have about 6 months before finalising a decision, here).
This does come with a lot more risks for us (it's harder to track down if someone publishes the code or uses it against the license), but given we've already passed 100 monthly active accounts, we're feeling more confident it's an acceptable risk.
The plan is to give logged in accounts (who are 12 months old or more) a way to download a ZIP of the current code base that's in the server.
Obviously there's no easy way to prove that's the case, but we're open to ideas/suggestions if someone here has them.
[1]: https://theprivacydad.com/interview-with-the-engineer-of-uru...
[2]: https://uruky.com/faq
[3]: https://polyformproject.org/licenses/shield/1.0.0

value: Show HN: Uruky (EU-based Kagi alternative) now has Image Search and URL Rewrites

author: BrunoBernardino


value: mindfulbun

value: Show HN: App that shows your screen-free hours every time you look at your phone

author: mindfulbun


value:
So first, what are we? A Clubhouse inside the terminal, where people can take a break, chill, chat with others all around the globe, listen to music, play some games, or paint on a live artboard :).
ssh late.sh (or use the companion CLI)
That's all. No passwords. No OAuth. No accounts. Your SSH key is your identity.
Honestly, I've been a little nervous to post this. I wanted the Clubhouse to be something I'm genuinely proud of before sharing, and I think we are finally there :)
There is so much here, so I'll really try to focus on the core:
- full-scale chat, mentions, rooms, public and private, DMs, reactions, image previews, full-quality images, icon picker, anything you need
- music, hop into the YouTube booth (WebView using wry) to listen to the community playlist, submit, vote, skip, or listen to 600+ server tracks divided into three categories (lofi, ambient, classical)
- games, single and multiplayer, sudoku, minesweeper, tetris, snake, nonograms, poker, blackjack, chess, and much more. Leaderboards and badges! First truly server-wide game is in the PR!
- live artboard, think r/place but in a TUI, draw, paint, or just enjoy. Daily and Monthly snapshots, check them out here: https://late.sh/gallery
- shop, buy a new fully-dynamic bonsai to take care of, or maybe a new aquarium, fill it with ASCII fish, or what about a new pet to play with? Quests, daily and weekly + streaks to help you win more chips
- news, rss/atom feeds, connect your own, share with others, auto-generated summaries with a nice ASCII thumbnail shared globally
- directories, a dedicated space to showcase your projects, another to build your "work" profile, and it all rolls up into your live web profile: https://late.sh/profiles (someone has already been hired thx to it!), and another one for co-op tools, right now a canvas builder inside the TUI
- and the NEWEST addition, VOICE chat :) without a browser!
This has already grown into a team effort. Amazing people, amazing contributions, amazing vibe.
Big ones in the pipeline: more BBS/full-scale server, real-time games :)
Hop in, take a break and enjoy ;)
Code: https://github.com/mpiorowski/late-sh
Landing: https://late.sh
Demo: https://late.sh/play
License: FSL-1.1-MIT

value: Show HN: ssh late.sh - a cozy command-line Clubhouse for computer people


value: s-xyz

value: Show HN: A built-in SQLite viewer for verifying your coding agents database work

author: s-xyz


value: borkasm

value:
Hey HN,
what I wanted to build here is a proper universal layer for persisted agentic sessions, that could be seamlessly interacted both via web and a messenger (Telegram). I really like what's done so far and would be nice to hear some feedback from you.
The interesting thing is that I started to use Chatcode during its development as soon it was possible, so used this tool to build itself.
I know that there could be trust/privacy concerns, because it relies on a gateway that you need to install on your machine in order to work, but:
1. You can use it on any machine, just have some test VPS for that
2. I really believe you will love it as soon as it fits your needs! And it's free to start BTW.
Anyways, looking forward to your questions/suggestions.

value: Show HN: Chatcode – Remote Control for Claude Code and Codex

author: borkasm


value: cionut

value:
I built a small MCP server for the ChatGPT Ads advertiser API, which OpenAI opened to the public a couple of weeks ago.
It's read-only for now: accounts, campaigns, ad groups, ads and insights (11 tools in total). You can query campaigns from Claude, Codex, Cursor and so on in plain language.
Writes ("actions") are next; I have two ideas here:
- wrap them in a deterministic tool (json in/out)
- add a human in the loop (maybe even a verification/consistency check step between query and tool/json output)
Claude Code did most of the work but it wasn't a one-shot. The OpenAI API spec is very clean though and easy to understand; for some reason Claude couldn't read OpenAI's own docs, so I ended up with some manual "copy&paste".
Also I iterated a bit and went from a local stdio install to npm and then made it available in the MCP registry.
Feedback welcome, especially on the write/elicitation side and on hosting a remote version.
PS: It's (obviously) unofficial and not affiliated with OpenAI.

value: Show HN: MCP for the ChatGPT Ads API – Query ChatGPT Ads from Claude and Codex

author: cionut


value: ahrisy

value: Show HN: Curlo – Search sound libraries with natural language, on-device AI

author: ahrisy


value: torsianWorld

value: Show HN: Coursly – iOS app that syncs your Moodle and makes quizzes from slides

author: torsianWorld


value: akh

value:
We launched Infracost on HN five years ago (https://news.ycombinator.com/item?id=26064588) where our CLI generated cost estimates for infra-as-code, e.g. "this Terraform PR adds $400/mo". The idea was to shift cloud costs (FinOps) left, so engineers get visibility of costs before deployment and make better decisions.
Earlier this year we started seeing agent traffic in our logs and it looked like coding agents were calling our CLI. But that CLI wasn't designed with coding agents in mind. We went down a philosophical rabbit hole to see if a CLI is even needed anymore given that Claude, Copilot et al. already follow best practices. Ultimately we decided to create a new CLI from the ground up with coding agents in mind for two reasons:
1. We optimized the CLI for agent callers and cut Claude's output token usage by up to 79% and API cost by up to 67% versus a bare-Claude baseline. We wrote a blog documenting our lessons on optimizing user token usage when designing a CLI, e.g. using predicate flags so the agent doesn't compose jq | python | wc pipelines, output format that strips JSON's redundant field names. The blog is here: https://www.infracost.io/resources/blog/we-cut-claude-s-toke...
2. With cloud costs, precision matters. Telling a coding agent "make this Terraform cost-optimized" can be expensive and lossy. You burn tokens loading code and policy context into every conversation. Your agent could make up a price and you wouldn't know because it's difficult to verify that across the ~10M price points that AWS, Azure and Google have. The CLI runs static analysis on the code, uses the latest prices from cloud vendors, and passes that context to the coding agent.
So that's what we're launching today - Cost.dev: https://cost.dev/.
- It runs locally. Your code never leaves your machine, you get a fast feedback loop, and you're not burning API calls per character when you want to fetch prices.
- The CLI does the deterministic work. Fetching price points, scanning the code, validating fixes. The coding agent does the natural-language part. You don't have to trust the LLM to remember the rules, and can verify it called the right CLI command.
- It provides a consistent rule layer across every tool you use. Get cost estimates in your IDE and your coding agent with a single install. We support Claude Code, GitHub Copilot, Cursor, Windsurf, OpenAI Codex, Gemini CLI, as well as IDEs like VS Code and JetBrains
Before we keep building more in that direction, I want to sanity-check with HN: is "agents writing IaC in prod" actually a thing yet, or am I betting on a future that's still a year out? I know software developers are using coding agents heavily, but are platform/infra folks doing that for prod too? Also, if you have any feedback on Cost.dev, I'd love to hear it!

value: Show HN: Cost.dev (YC W21) – making agents cost-aware and cheaper to call

author: akh


value: Show HN: HomeButler – A CLI that tells you what changed on your home server


value: pielouNW

value: Show HN: We've built a standalone Apple Watch app running LLMs offline, locally

author: pielouNW


value: momentmaker

value:
Built this based on inspiration from another project I saw on HN.
It has 7 different breathing patterns like calm (5/7), coherent (5/5) you can select from based on your practice.
There are also 7 soundscapes, 7 voice guides, and 7 bells you can download and use during your meditation.
All the states and configs are saved locally and nothing leaves your machine.
MIT and completely free.
Feedbacks are welcome.

value: Show HN: Meditate-CLI – breathe with your terminal

author: momentmaker


value: xakpc

value:
Not much to say. I work on windows, I hate postman, I need to manage bunch of .http files across multiple repositories.
So I built a fast and native tool for myself and published it if you want to try it too.
Any feedback would be nice, I really want it to be The obvious native Windows home for .http files

value: Show HN: I built Karve – a native Windows alternatve to Postman

author: xakpc


value: karakhanyans

value: Show HN: I built an AI tool that turns Search Console data into SEO wins

author: karakhanyans


value: frizzy

value: Show HN: A GitOps-style registry for AI agent Workflows, Skills and MCP servers

author: frizzy


value: nirmalaavalluir

value: Show HN: DevNova Tools – 121+ free developer tools that run in the browser

author: nirmalaavalluir


value: Saloc

value:
I hate keeping extensive notes of experiments. When iterating fast, it feels to break the flow. However when keeping all adjustments in mind - its only a question of time until valuable info gets lost.
Therefore I build Rair to track results, inputs and code with minimal overhead. Putting "rair" in front of the command without any config is often sufficient.
For code tracking, Rair references git, but it also tracks uncommitted changes as diff - like adjustments of parameters in source files.
Input and result data is detected heuristically if not configured. Data tracking is based on file hashes for deduplication.
I'm curious whether this "just prefix the command" approach feels useful for others.

value: Show HN: Reproducible experiments without committing every tweak

author: Saloc


value: Show HN: GateTest – 110 QA checks in one scan, auto-fix PR for what it finds


value: christilut

value: Show HN: SonoVault Music Metadata API for Builders

author: christilut


value: nizarmah

value:
I loved learning how to build end-to-end encryption. I thought you'd need to go through every record. I felt really silly when I learned how keys can be used.
For context, I'd blown through half a million dollars over 4 years and had no idea where it went. So I'm trying to get a grip on it with this app. I can't use bank statements, because I'm using different electronic money institutions (EMI) and Lebanon barely supports paying by card.
It took a while to get a UI I actually wanted to use... The part I'm still unsure about is adding old savings. Some find it intuitive but others find it confusing. That's where I need your help.
I didn't expect it, but the whole family is on it now! My parents, partner, sister, best friend, and his parents. My dad is somehow the power user.
If you want to try it, without logging in to Google: tap the carrot 7 times, and login with user (test@bucksbuddy.com, test, No E2EE pass) or (locked@bucksbuddy.com, test, E2EE pass: test).
If you use the test users, please be considerate with how you touch E2EE. Make sure to revert any E2EE changes, so others can use the account as well. If they're broken, leave a comment below and I'll reset the accounts.

value: Show HN: BucksBuddy – a free, on-the-go, private money journal

author: nizarmah


value: ankushvishnu

value:
Hi HN!
I'm building Jin - an open-source protocol for agent builders and webmasters to make the everyday internet legible for AI agents.
I use AI agents for coding & research and one thing I've observed is that we spend to much time, money or both on giving scraping powers to our agents. That got me thinking, what if there was a system for my AI agent to deliver what I want from the internet without having to break a sweat? And that gave me the intent layer idea.
Here's how Jin works -
1. AI agent side: you only pass the instructions to your agent in a skill.json or skill.xml format. That's the first step. The skill will tell the agent to look for jin.json on the website and use the intent map to navigate, take action like CRUD, etc. It lives under app/.well-known/jin.json
2. Webmaster side: the webmasters can run the jin-cli at the root of their project, the cli will map the project, generate intent map in a jin.json file and save it wherever the app lives. For example, in a monolithic structure, the jin.json can live at the root. For a monorepo structure, it can live under app/web or app/marketing, etc. This file can be totally edited the way you want. Apart from generating intent maps, it tells you how you can easily edit, what you can put, what should go & what not, etc. There's a to-do list in jin.json
Along with this, in the latest version, I've added a Jin shield to protect websites from unauthorised scrapers. This shiled lives next to whatever firewall you are using, consider this like a first line of defence. It will snitch who came in. You can register your agent on meetjin.com for free and use the generated key to access any website that uses Jin shield. The agents carry a cryptographic RS256 JWT passport and the Jin shield verifies this locally using cached JWKS public keys.
The specification is open (CC0), the tooling is Apache 2.0. Use it, break it, roast it praise it.
Access the cli: npm i @papercargo/jin-cli
Access the key: https://meetjin.com
Github: https://github.com/meetjin/jin
I would really appreciate to know your use case and feedback.
Cheers!

value: Show HN: Jin – a machine-readable protocol making internet legible for AI

author: ankushvishnu


value: minhazkhaled

value: Show HN: AI Info Remover for Images

author: minhazkhaled

title: Show HN: AI Info Remover for Images


value: prashantsengar

value:
Hi HN, this is Prashant from H2Loop. Embedded engineers that we work with were annoyed that generic AI tools hallucinated register addresses, generated code for peripherals that don't exist on the chip and mixed up timer quirks between similar platforms like STM32F4 and F7. The code looks clean but it just won't boot. This made them go back to the datasheet every time. So we built Hydron, an AI tool that writes datasheet-grounded code for your hardware.
Demo: Hydron setting up sleep-mode CPU logging for an onboard temp sensor on an STM32U385 - https://boot.hydron.sh/zzzDemo
First, we've pre-indexed 580+ platforms and peripherals. Most of what you'd use in a robotics, UAV, or IoT build: common dev platforms like STM32, ESP32, RP2040, AM6 families, plus the IMUs, GNSS modules, motor drivers, and baros that ship around them. Ask about a peripheral, the answer comes from our KG and the actual datasheet.
Second, you can bring your own context and share it with your team. Hydron indexes PDFs up to 5000 pages, plus a whole host of various file types and even ZIPs of full C/C++/Python codebases up to 250MB. One engineer indexes the HW, BSPs, and datasheet pack once. Anyone else can reference it from their own Hydron agent.
Third, HW-SW development happens in your editor or terminal. Agentic serial monitor is live today. GDB integration, and an AI log reader land in the next two weeks.
Up next, we're focused on closing the hardware-software loop. We're building more HIL debugging capabilities, deeper target awareness, and support for additional platforms. If you work on embedded SW we'd love your feedback on where today's tools fall short and what you'd like to see next.
Install:
VS Code extension - https://marketplace.visualstudio.com/items?itemName=H2Loop.h...
CLI mac/linux -> curl -fsSL https://get.hydron.sh/cli/install.sh | bash.
CLI windows -> irm https://get.hydron.sh/cli/install.ps1 | iex
More at http://boot.hydron.sh/HN. 200 free credits, 50% off on paid plans, one-step signup. Me and u/ajithhyd will be in the thread all day.

value: Show HN: Hydron – Hardware-aware coding agent

author: prashantsengar


value: theahura

value:
Hey HN,
One issue that a lot of teams run into is that they want to switch their configs between different agents e.g. Claude Code --> Codex or they want to switch out different configs for the same agent e.g. using a different set of skills and CLAUDE.md for debugging vs feature engineering.
We've been working on an open source AI configuration manager. You can use it to manage / maintain your agent configs entirely locally, or share them with the public / your team.
For example, say I have a few different configs that I want to switch between:
- a production-debugging config that I use to get Claude to ssh into a remote machine and look at logs. This has strong guardrails around not changing anything and provides a step by step guide on where logs exist
- a high-autonomy config that I use for feature work
- an admin config that I use for things like making slide decks or recording voice notes
I can switch between these with a single command, for e.g.
```
sks switch administrator
```
and the configs will swap themselves out.
You can specify which agents you want to use by running `sks config`, and you can set which directory to run in so that these configs are isolated by default.
This has been really useful for me because I spend a fair bit of time crafting specific skills for specific uses and often want to switch between claude 'personalities'. And more recently, I switched to codex, and it was nice to be able to seamlessly port all of my configs without having to figure out what to do with each one.
Cheers!

value: Show HN: Switch skills between agents, locally manage multiple configs

author: theahura


value: WasimBhai

value: We would use Walmart recurring orders facility in its app to get eggs, milk, bread and other stuff every Monday. It was a lot of convinience. However, in Pakistan, with standalone Foodpanda app, you cannot do that. So I created this skill that can automate this and order regular items, may be on a Monday. Feel free to add to it. I used codex to create it.

value: Show HN: Foodpanda skill to automate ordering through Chrome

author: WasimBhai


value:
I miss Dark Sky, so I built my own weather app.
Here's how GrayCloud works:
* Raincast: minute-by-minute rain prediction and accumulation tracking for your exact location
* Forecasts: 10 day forecasts use multiple high resolution sources and correct for bias at your location.
* Alerts: rain starting, stopping, severe weather, daily summary and more
* Widgets: home and lock screen widgets
* Multi-platform: apple watch and mac apps
I use NOAA and ECMWF models for core weather data and a custom model to compute rain accumulation and the next 60 minute radar movements.
I also offer Apple WeatherKit as an alternative weather source.

value: Show HN: GrayCloud – a modern Dark Sky alternative


value: ismaelyws

value: Show HN: Hello Inbox – Your AI Email Deliverability Expert, Available 24/7

author: ismaelyws


value: therov

value: Show HN: HetGuard – Automated backup scheduling for Hetzner Cloud

author: therov


value: hypfer

value: Show HN: Will It Fit? – Opinionated Normal People Llama.cpp VRAM Estimator

author: hypfer


value: renchuw

value: Show HN: Creating SQL queries with decision trees

author: renchuw


value: ehalim

value: Show HN: ClearLogo – a logo API that returns usable logos, not raw files

author: ehalim


value: Show HN: Depot CI API – Programmable CI

title: Show HN: Depot CI API – Programmable CI


value: airwarmedd

value:
I started reading about Build AI when I come across their launch in Feb and couldn't stop noticing all these new companies talking about selling data for robots.
Would appreciate any thoughts on how I can learn more, link: https://x.com/airwarmedd/status/2051270391692497253

value: Show HN: Getting into Physical AI and Robotics

author: airwarmedd


value: fredrikmoger

value: Simple game built using Claude, Vercel & Supabase

value: Show HN: EarthGuessr – Guess locations from satellite imagery

author: fredrikmoger


value: fbeeper

value: Show HN: AgentKitten: Swift package for provider-agnostic AI agents

author: fbeeper


value: nab

value:
Hi HN, we’re Nick and Drew, and we’re building boxes.dev – the first cloud-only agentic dev environment (ADE) that gives every Codex and Claude Code agent its own cloud computer.
We’re two engineers who previously built Gem (co-founder/CTO and first hire), and we spent the last year coding almost exclusively using Codex and Claude Code. It’s been a huge change to how we code, and it’s been exhilarating seeing the models keep getting better – but we eventually realized that developing on localhost was holding us back:
- Git worktrees are clunky to set up and use for parallelizing work
- It’s 2026, but somehow everyone is still walking around with laptops cracked open or SSHing into mac minis in their garage so their agents don’t stop working.
- Mobile is treated like an afterthought even though coding is just texting now
We started hitting resource constraints when multiple parallel agents test their own work by running the full app locally.
- We tried different products, but couldn’t find any that solved all of our pain points – so we pivoted and decided to just build the ADE we wanted for ourselves.
Boxes.dev is a desktop and mobile app that lets you run Claude Code, Codex (using your subscription!), and the full dev environment for whatever you’re building, all on remote compute. It’s similar to Conductor or the Codex desktop app, except everything is in the cloud.
We use coding agents to scan your local dev setup and port it to the cloud. Then every Claude Code/Codex thread starts from a snapshot of the full setup, with its own filesystem and compute.
No more git worktrees, no more cracked-open laptops, and your coding agents can actually test their work end-to-end because they can run your full app in isolation.
We’ve mirrored the Claude Code and Codex UX to feel natural to power users, and also have a fully-featured mobile app (no handoffs or remote control), plus scheduled automations and a Slack integration.
We’re obviously biased, but we’ve been building boxes.dev with boxes.dev for months and it’s honestly been a gamechanger. It’s hard to go back once you realize how much localhost has been limiting you; based on early feedback from beta testers, we’re increasingly sure that cloud is the future of agentic coding.
We’d love for you to experience it yourselves! Would appreciate any feedback – and happy to answer any questions on this thread.

value: Show HN: Boxes.dev: ditch localhost; run Claude Code and Codex in the cloud

author: nab


value: riyajoshi

value: Show HN: Black-box API bug detection across 7 AI systems

author: riyajoshi


value: tolugenius

value: Show HN: My Rust SIMD code was silently running as scalar

author: tolugenius


value: farcaster

value: After losing hundreds of games of https://pokelike.xyz/ it occurred to me that the state space was small enough that maybe a small neural net trained with PPO could beat it somewhat consistently. After some reward engineering it works! The PPO-trained neural net can beat 9% of all runs all the way to the Elite Four!

value: Show HN: 178K Parameter Neural Net That Wins Poke(rogue)like

author: farcaster


value: acoye

value:
Hello HN,
For my own needs I needed a powerful WASM engine that provides JIT acceleration, and use it from the convenience of the Swift Package Manager.
So I ended up wrapping wasmtime (a Rust project) https://github.com/bytecodealliance/wasmtime/
The SPM package does support most platforms swift supports, including mobile where JIT is simply not available.
I'd be happy to hear from you if this is something you may be interested in using and what are your WASM use cases.
Thanks :+1:

value: Show HN: WASM with JIT from a Swift SPM Package

author: acoye


value: rccyx

value: Show HN: Zero deps C++ ASR binary for Linux (0MB idle RAM, no daemons, Unix way)

author: rccyx


value: scott-b

value: Show HN: Agent per Human Notarization Protocol

author: scott-b


value: mixfox

value: Show HN: Peddi Movie – a simple guide for the Telugu film Peddi

author: mixfox


value: SkewMaster

value: Show HN: Free AI agent audit for Shopify catalogs (1.2M open captures)

author: SkewMaster


value: ddayanov

value:
Quick note on how it works and how I've done my batch embedding engine IgniteMS.
The whole thing runs as one process using Rust, reading input, tokenizing, packing batches, keeping the queue full. TensorRT handles inference. Python is only as a wrapper.
I built it this way because when you use more than couple of GPUs, the GPUs stop being the problem. CPU cannot feed them fast enough. One A100 can go through batches faster than Python can tokenize and feed, so the GPU just sits there idle waiting for work. Most of my time went into optimizing this. At 8 GPUs that was basically the entire challenge.
On cost. I ran the big 2B messages job on a spot p4d instance (8x A100 40GB). After filtering and dedupping I got 685M raw texts. With my new engine the whole production run finishes in about half an hour. Previously I used on-demand for these jobs, now switched to spots. If AWS reclaims the box, I just rerun it. It's roughly $7 for half-an-hour run. And at least right now spots are easier to get than on-demand.
Open warning: it's batch only and NVIDIA only. You can use it both as a docker image and native.
I used some optimizations for my production run. With default settings you can expect to see ~250K msg/sec if you run the benchmark script on your p4d box.
https://github.com/Artain-AI/ignite-ms/blob/main/BENCHMARKIN...
v1.1.0 added TensorRT 11 and 60 models, 23 tested on 1x and 4x A100.
Happy to share details.

value: Show HN: I embedded 685M public texts in 32 minutes (on 8x A100, Rust, TensorRT)

author: ddayanov


value: mdeeds

value: Software 10BASE-T Ethernet (using PIO to bit-bang TX and RX) and wireless router on the Raspberry Pi Pico 2 W. Running cyw43 + an async executor in rust on the RP2350's RISC-V cores. Using cheap and minimal external hardware (just a magjack and ISL3177E RS-485 transceiver). I wanted to see how far I could get with the cheap, MCU-based, Wi-Fi router idea and learn some more about using rust on the RP2350 and RISC-V. Definitely not a good choice for a home router but it could be useful for low-rate IoT traffic.

value: Show HN: Bit-banged 10BASE-T Ethernet and Wi-Fi router in Rust on the Pico 2 W

author: mdeeds


value: Wetime

value: Show HN: Taliesin – bit-exact KV-cache restore, 21x faster, cross-GPU verified

author: Wetime


value: subcosmos

value: Show HN: NeuroAnswer – MCP server lets Claude navigate petabyte-scale brain maps

author: subcosmos


value: gizero

value: Show HN: Mdrone – a microtonal drone instrument that runs in the browser

author: gizero


value: bethanyhunt

value:
Selecting the "best" local model usually depends on the task and the hardware.
I created this script as an easy way to test local Ollama models and keep the test output organized.
When you run the script interactively, it asks which model you want to use, what your prompt is, how many times you want to run it, and (optional) the temperature you'd like to set. It can also be scripted with command-line flags.
The output is saved in Markdown/JSON within an organized file structure for easy comparison.  Outputs using the same prompt go into a folder together, each output named for the model tested. Timing data and token counts are also recorded.
The tool is intentionally small and dependency-free (standard library only).
Suggestions welcome.

value: Show HN: OMT – A simple Python CLI for testing local Ollama models

author: bethanyhunt


value:
Hey HN, I am the developer of the somewhat famous AT4K launcher an apple tv inspired android tv launcher.
After launching AT4K I read somewhere in news that Roku is the highest selling Streaming box of US and that intrigued me to check out why.
Turns out it's because Roku is dead simple to use, your parents, grandparents can easily navigate around Roku and find apps and stuff to watch.
I thought well why not do this with AT4K so I wrote a lot of code to make an alternative view in AT4K that would look like that. But that didn't work and I had to branch out this to a new app but used most of the code from AT4K.
So here it is Kyu Launcher An Android TV Launcher built for everyone and their grandma. It's dead simple to use, you can create folders, hide apps, view your currently watching list, your spouse can even add to-dos/notes right at the launcher home page and you can hide most of the stuff you don't want. Here is the link:
https://play.google.com/store/apps/details?id=com.overdevs.k...
Recently Roku shoved down a new update to their interface and most people, as is the case with the design changes almost always, do not like it. If they want to ditch the Roku and want to keep the interface they can use Kyu to keep the Roku feel and enjoy their android tvs.
There are some beautiful themes too. I made it because I liked what I saw with Roku and wanted to port similar experience to Google TV devices. I also know it's not something with lots of bells and whistles I wanted to share it anyway.
Most of the stuff including folders, changing colors, hiding things, moving around etc are free, if you want to however change app icons to something from your gallery or use premium themes there is a one-time purchase of 3.99 or equivalent to your currency. That's to support and maintain the app.

value: Show HN: Kyu Launcher – Roku Interface on Your Android and Google TV


value: tessbi

value: Show HN: Open Terminal – A Bloomberg Style App for Research

author: tessbi


value: I made this because I like the look and feel of Anthropic Mono, but wanted a reproducible open source coding/terminal font built from Iosevka.

value: Show HN: Anthrosevka Mono, an Iosevka Build Inspired by Anthropic Mono


value: benzsevern

value: Show HN: GoldenMatch – 100M-row dedupe on Ray in 213s, no Spark, Arrow-native

author: benzsevern


value: A coding environment designed to be "recursively self improving".... but a whole lot more.  Uses web based chatbots to save tons of money while being within terms of service and still being efficient.  Runs right off the web (with no signup) and saves to your browser and/or straight to disk. Open source. Lots of cool sample/template apps.

value: Show HN: Recursi – self-improving LLM-connected coding environment


value: gidellav

value: Show HN: Zerostack, an open coding agent optimized for memory footprint

author: gidellav


value: adebayoj

value: Show HN: Clarity, See what concepts your LLM uses and trace it to training data

author: adebayoj


value: sarah-robiin

value: Show HN: Touch Grass, Virtually – The Game

author: sarah-robiin


value: ktoyame

value: Show HN: Resume – manage Claude and codex sessions in one CLI

author: ktoyame


value: yashg

value:
I built a tool to get app notifications whenever something important happens: a sale is made, a site goes down, a job completes, etc.
Install the app, get a device key, and integrate a simple HTTP API call into your code or workflow to trigger a notification on your phone.
No account needed, no signup, no SDKs, no fiddling around with FCM or APNs. Just an app and a simple API.

value: Show HN: Clickfyre Ping – send app notifications to yourself

author: yashg


value: jdcarter

value: Just a silly project. Its redline is the token burn rate where you'll exhaust your tokens right at the end of your 5-hour window. Clearly inspired by 1980's Corvette dashboards.

value: Show HN: Claude-o-meter, a tachometer for your Claude use

author: jdcarter


value: lostathome

value:
Hi guys.
I have been working on Hitoku Draft, an open-source, voice-first AI assistant that runs entirely locally. I posted about it already, and now it has also transcription with voice editing. Looking for feedback, as I found that outside tech circles other people still do not use this tech much.
It's context-aware, in the sense that it reads your screen, documents, and active app to understand what you're working on. You can ask about PDFs, reply to emails, create calendar events, use web search, editing text, all by voice.
You can download a compiled version for free with the code HITOKUHN2026 https://hitoku.me/draft/ (base price is 5 dollars)
It supports Gemma 4 and Qwen 3.5 for text generation, plus multiple STT backends (Parakeet, Qwen3-ASR).
Examples:
- Gemma4 in action, https://www.youtube.com/watch?v=OgfI-3YjEVU
- query a pdf document, https://www.youtube.com/watch?v=ggaDhut7FnU
- reply to email, https://www.youtube.com/watch?v=QFnHXMBp1gA
- and the usual voice dictation (with optional polishing)
I currently use it a lot with Claude Code and Logseq. Now with some friends we are also building a new cross-platform version. The goal is on the long run to have AI interactive local models serving people and professionals.

value: Show HN: Hitoku Draft – Context aware local assistant

author: lostathome


value: koubaki

value: I built a simple way to link a website or domain to a phone number, email, webfinger, and profile information. The main method is a JSON-LD document at /.well-known/telweb. For phone numbers only, there is a fallback using a TXT record on the _telweb subdomain. The profile field is intentionally flexible. It is simply defined as an object where you can put any information you want. You can try it in the Dialer section.

value: Show HN: I Made a Way to Resolve Websites to Phone Numbers, Email, and Webfinger

author: koubaki


value: Show HN: Moss, an AI-led programming language experiment


value: iheartbiggpus

value: Show HN: Apple's Unreleased Persona Body Animation Solver, Running on a Mac

author: iheartbiggpus


value: ryancanzo

value: Hello HN. I created this set of SVG flag icons with small file sizes for an analytics dashboard project. I started this mostly for fun, many icon libraries I looked at had file sizes that were larger than necessary and some had details that looked off for complex flags. I’d seen lots of implementations of simplified flags across the web and wanted to create a set of my own and share it so that others can use them too.<p>The individual flags were drawn in illustrator, using a pixel grid to make the coordinates whole numbers and keep the size down. Claude code was used for much of the grunt work like fetching the reference images and arranging them into folders. There are a few that I may tweak slightly as well as some territories currently represented by their parent country’s flag that I may add.

value: Show HN: Vlags, small vector flags. Less than 900 bytes each

author: ryancanzo


value: roykishony

value: Show HN: Revaiso – AI writing in Google Docs as native suggestions

author: roykishony


value: gamerdrome

value:
I’ve been spending a lot of time with Codex at work like many people, and found myself doing the same thing over and over:
- Pick a Jira ticket
- Start an agent
- Explain the task
- Wait for it to finish
- Open a PR
- Repeat
So I built FirstDraft.
A worker runs on a machine that already has access to your repositories, build tools, credentials, and anything else it needs. It watches a Jira board, claims a ticket, runs Claude Code or Codex locally, pushes a branch, and opens a draft PR.
The goal was to push through some of those smaller bug tickets and features that could be done without me having to pick them up myself.
What’s been interesting is that once I got the basics working, I started using FirstDraft to build FirstDraft. A lot of the features in the current version were implemented by workers picking up Jira tickets and opening PRs.
It’s still early and very much an experiment, but it’s been a fun one.

value: Show HN: FirstDraft – AI workers that claim Jira tickets and open PRs

author: gamerdrome


value:
After a lot of work I present Digger Solo 0.5.0 - the AI file explorer that respects your privacy (everything runs locally).
Demo video: https://vimeo.com/1198414414
New features:
- LLM Chat with RAG (bring your own OpenAI compatible API key - ideally host a local model)
- fresh redesign with light theme available in settings
- multi-tabbed GUI: open multiple semantic maps at once
- smart music player: auto-plays similar songs
Digger Solo offers semantic search and maps that allow you to browse your files intuively - uncovering hidden connections and near duplicates easily.
Happy to answer questions.

value: Show HN: Digger Solo – Local AI File Explorer


value: scottbuilds

value: Show HN: Nexus, ask AI about sensitive spreadsheets locally

author: scottbuilds


value: nistuley

value: Show HN: Review-oriented DOCX extraction toolkit for Rust

author: nistuley


value: EvanZhouDev

value: Show HN: Bot or Not – Spot AI-generated randomness

author: EvanZhouDev


value: lucasoshiro

value: Show HN: Module adding Layer-3 protocols SV and GOOSE to ns-3 network simulator

author: lucasoshiro


value: Show HN: Using Haskell to play music on 3D printer motors (2020)


value: tejaswigowda

value: Built a browser-based FFmpeg editor that runs entirely client-side via WebAssembly. Your files never leave your device -- all processing happens in a Web Worker. Works offline as an installable PWA after first load.

value: Show HN: FFmpeg WebCLI – Full FFmpeg in Browser, Offline PWA, No Uploads(WASM)

author: tejaswigowda


value: ananayarora

value: Show HN: OpenHack – OSS security scanner, 40x cheaper, on par with Opus 4.6

author: ananayarora


value: utibeumanah

value:
Hey HN
I've been using ECS for a while now and found it annoying having to log into the console everytime
I use Lens for Kubernetes but couldnt find an equivalent for ECS so i built one!
The project is open source as well
https://github.com/utibeabasi6/mercek

value: Show HN: Mercek – A Desktop IDE for AWS ECS

author: utibeumanah


value: zdenham

value:
SheetMog is an OSS spreadsheet engine which aims for full Excel feature parity behind a headless interface, from the team behind https://shortcut.ai
The engine is built in rust, and can be packaged for web via WASM with typescript GUI.
We have found the API surface to be extremely useful for programming agents or SDKs like Claude Code codex etc...

value: Show HN: SheetMog – OSS Excel alternative and headless SDK

author: zdenham


value: Show HN: Getjobber-CLI – Python CLI for the Jobber GraphQL API


value: sakuraiben

value: Show HN: Intencion – Product analytics that improves your AI agents continuously

author: sakuraiben


value: tldrthelaw

value: Web only at the moment. Very opinionated and geared toward what I was looking for in a client. But, who knows, maybe there is one other person out there?

value: Show HN: Wallflower.app – A Combined Mastodon and Bluesky Client

author: tldrthelaw


value: turingfeel

value: Show HN: A native port of Skate 3 for Windows & Linux via static recompilation

author: turingfeel


value: DensitySam

value: Show HN: SpotOn WC26 – a free World Cup 2026 bracket game that scores itself

author: DensitySam


value: falense

value: Show HN: OpenPaper - No algorithm, no account, just your sources as a newspaper

author: falense


value: permute

value:
To my knowledge, this is the first formally verified implementation of an intersection algorithm for polygons.
The experience of working with AI agents on this project changed a lot with recent model releases, as I describe in the readme. Opus 4.8 is able to provide algorithm implementation with formal proof in one shot, whereas previous models required me to provide proof strategies in multiple steps.
Trust in the correctness comes entirely from the Lean checker and human review of a small specification, not from the LLM.
Also check out the web demo built around the verified core linked in the readme: https://schildep.github.io/verified-polygon-intersection/. It supports multipolygons including holes, self intersections, and overlapping edges.

value: Show HN: Formally verified polygon intersection – Opus 4.8 oneshots, prev failed

author: permute


value: alexreysa

value: Show HN: An x402-powered billboard for autonomous agents

author: alexreysa


value: samuelzxu

value:
I'm building the AI tutor that I wish I had when I was a kid. It's capable of following your thought process through the MacOS webcam as you do rough work and propose meaningful hints. You can download it on the Mac App Store for free, and use the free version without signing up for a free trial of a paid version.
Open sourced - note, readme's are out of date.
https://github.com/samuelzxu/Knowable
https://github.com/samuelzxu/knowable-be
Ping me at `samuel at knowable dot ca` for suggestions and feedback!

value: Show HN: Knowable, the AI tutor that follows your work on paper

author: samuelzxu


value:
For a long time i struggled to find my g-spot, then it struck me in a lucid dream that i dont have a g-spot, i have a p-spot so i decided to go on a lookout and came across, G-Spot.dev, its a workspace where you build graphite like sections for your github/gmail (ofc it has as agent to build out ur filters as an accessibility feature). You can build sections for:
- github prs
 - has a graphite like review page optimized with
   diffs.com for large prs, all the good ol ux from
   graphite ported over.
- github issues
 - similar to prs
- gmail
 - initial full sync from gmail directly
 - incremental sync via a relay server connected via a
   ws connection
 - extraction pipeline for a knowledgebase memory
  - you connect ur copilot/codex/claude sub and we use
    that token to spin up an agent and extract the
    details from the email
 - notion like ui layout (but faster than notion)
 - compose new or draft a reply, adjust labels wteve
   you want, syncs directly wth gmail and the
   incremental sync immediately updates the db.
Moving on, we also have markdown notes, with katex and mermaid built with codemirror 6 achieving same ux as obsidian with ability to attach images, soon files and ability to share em via github gists. It also was wikilinks and bookmarks and other tiny obsidian details
then theres g memory. its a local knowledge graph, entities + observations +
edges(relationships), wth sqlite-vec embeddings
- every chat turn gets extracted into it in the
  background
- a worker agent does the extracting, same extraction
  agent as the gmail extraction workflow.
- salience + confidence decay every hour, prunes dead
  nodes and decay the weights.
- you can hybrid vector + graph search it, do PIT
  "what did this look like back then" queries.
- making the chat pull the memory on each turn is next
  while keeping everything as fast as possible.
next, gmail workflows. worker agents fire off on incremental sync to do custom label/etc workflows.
defaults to drafting over sending unless you explicitly tell it to send
and the g-ide. same agent, but now it runs on ur os. vs code style tabbed workspace, you pop open chat tabs, terminal tabs (real pty, xterm, survives switching away, next resuming after server restart), file tabs (monaco, autosaves), and diff tabs.
sidebar has a file tree, a git changes view, and a
terminal. ⌘p to fuzzy find files, ⌘t new chat.
plus mcp servers w/ discovery via pi extensions, skills as /slash-commands (global or per-project) also w/ discovery via skills.sh
you can dm/tag me on twitter for any feature reqs / issues.
https://x.com/barre_of_lube
*NOTE*: The DMG is not signed

value: Show HN: G-Spot – GitHub Gmail GNotes Gmemory Gent


value: andywidjaja

value: Show HN: Patina, an AI that learns your judgment, not just your tasks

author: andywidjaja


value: I was frustrated with hours long content on youtube that was difficult to get through, so I built this tool.<p>Give it a whirl and share any feedback!

value: Show HN: Skim any YouTube video. be happy


value: bourbonproof

value: Show HN: Papernews – self-hosted daily newspaper PDF for your reMarkable

author: bourbonproof


value: zylics

value: Show HN: ControllerTest-test gamepads,stick drift and polling rate by browser

author: zylics


value: mlenz

value: LLMhop is a tiny stateless proxy for LLM inference servers. It tackles an issue I faced when trying to serve more than one local LLM at once which is not natively supported by vLLM. The LLMhop binary inspects the model field of the request and routes it to the correct backend service with optional handling of authentication. In addition, it contains a NixOS module to run llama.cpp, vLLM, and sglang via Quadlet/Podman and auto-register with the proxy.

value: Show HN: LLMhop – A tiny, stateless router for LLMs with a NixOS module

author: mlenz


value: Show HN: A simple bookmark manager for Mac and iOS


value: coolwulf

value: Show HN: Bonsai –- Using agentic AI / browser / memory to replace ChatGPT

author: coolwulf


value: terrylinooo

value: Show HN: Laravel Octane Benchmark (Swoole, RoadRunner, FrankenPHP)

author: terrylinooo


value:
I've used most macOS tiling/workspace tools (AeroSpace, yabai, FlashSpace, amethyst, rift, OmniWM). All I wanted was to not turn off the SIP and it was a tiling tool by workspace. So I created Tatami.<p>It's written in Swift + TCA, and it's still pretty early on, but it has all the features for the environment I want.
I'm very inspired by yabai and flashspace. Thank you for both projects.

value: Show HN: Tatami – a macOS workspace manager with BSP tiling


value: tamler

value:
I wanted some handy JS tools for simple file manipulation and built this out... then wanted to give it to my agent... now it is a thing unto itself.
Any tools or capabilities you'd suggest?

value: Show HN: Wyreup.com – Common file edit tools packaged for offline and agent use

author: tamler


value: sermakarevich

value:
Some time ago I built a simple app to run swarms of coding agents — I call it fleet (https://news.ycombinator.com/item?id=48256389). It's based on centralized beads with a Python orchestrator and can run any coder (Claude, agy, Codex). Recently I added a UI to manage the whole agent lifecycle: adding new tasks, monitoring running ones, and a chat interface built on MCP with a centralized SQLite DB. From the UI I can spawn agents to run in any directory, define dependencies on other tasks, and specify which coder/model should do the job. Today I can run 10–15 agents concurrently. At that scale you burn through limits very fast, so I spent some time investigating where those limits go and how to maximize efficiency. Here are the lessons learned after a few weeks of running the fleet:
- CLAUDE.md is a terrible abstraction. These files load unconditionally, they often contain descriptions irrelevant to the task at hand, and they stack from your working directory upward. The result is wasted tokens and confusion from injecting irrelevant instructions into the session.
- Skills are bad, but not as bad as CLAUDE.md. They use a progressive disclosure approach: only the skill description goes into the session, and Claude loads the full skill text with a tool when it's needed. That's one level better, but it still doesn't let you scale — you can't create 10K skills, as that would eat your entire usable context. Claude recently introduced a skills budget that silently drops less frequently used skills from the session entirely. You can still invoke them in an interactive session, but the model can't invoke them in a background session.
- Some plugins may be installed more than once. During cleanup I found that a few of mine were installed in multiple locations, consuming double the tokens on duplicated instructions.
- Attaching plugins to every session is a bad idea at scale. You want to be precise about which plugins are actually useful and attach them per task.
- Use a hierarchical knowledge base instead of CLAUDE.md / skills / plugins. It lets you benefit from real progressive disclosure: keep your instructions and tool descriptions in it and let Claude navigate through it quickly and cheaply.
- System tools consume ~15K tokens (7% of the session). You can't manage this — they're just attached, and disabling tools doesn't remove them from the context.
- AskUserQuestion isn't available in background sessions. You need to implement your own tool — MCP- or CLI-based — to give `claude -p` the ability to talk to you.
- You become selective about which model handles each task. Decompose work into harder and simpler subtasks so you can route the simpler ones to weaker, cheaper models and save tokens.
- Your context-switching skill improves over time.
Fleet repo: https://github.com/sermakarevich/fleet

value: Show HN: Lessons learned from running Claude Code swarms at scale

author: sermakarevich


value: ansocode

value:
Hey HN
I’ve been managing docker compose apps on multiple remote servers over the years and I got tired of using multiple tools for simple tasks.
I wasn’t happy with the current available options so I built Sencho. It’s a self-hosted Docker Compose control plane for people managing one machine or a small fleet, without moving to Kubernetes and without exposing the Docker socket over the network.
Connect your remote nodes either by direct authenticated HTTP/WebSocket proxying, or through the outbound-only Pilot Agent. There’s no restriction on the number of nodes you can connect.
Manage the entire compose lifecycle from a central place and most importantly Your compose file are not “captured” and stay on disk as source of truth.
GitHub: https://github.com/Studio-Saelix/sencho
Docs: https://docs.sencho.io

value: Show HN: Sencho – a self hosted Docker Compose UI with multi-node fleet support

author: ansocode


value: Daniel-Pan

value: Show HN: One AI agent for all your support issues

author: Daniel-Pan


value: Clikdeo

value: Show HN: ClikDeo – Browser-based video editor (trimmer, merger, shorts creator)

author: Clikdeo


value: varunwalekar

value: Show HN: ProData AI–AutoML,Data Analysis&PowerBI-Style Dashboards in Streamlit

author: varunwalekar


value: javamantraact

value: Show HN: CentProof – Local-first bank statement reconciliation for macOS

author: javamantraact


value: Show HN: Encoding Audio Inside PNG Images [video]


value: Show HN: Altersend – File sharing without cloud


value: bkazez

value:
After 25 years of making other people's pancake recipes - always yearning for more tang, more fluff, and more predictability - I decided to derive the pancake recipe from the chemistry.
You mark checkboxes for what you have on hand (ricotta, sour cream, kefir, buttermilk, yogurt, cottage cheese, lemon, cream of tartar, etc.) and it  computes the best recipe based on targets for acid, fat, salt, sugar, and CO2.
My particular favorite are the yeast-raised lemon ricotta kefir pancakes - the best I've ever had.
The math is done in a small pure-ESM library: ingredient composition to component masses and acid moles, a stoichiometry layer, and a bisection solver for the target deficits.
I'm not a chemist, so if something is off, tell me and I will fix it!

value: Show HN: I Derived a Pancake

author: bkazez

title: Show HN: I Derived a Pancake


value: Show HN: Snill.ai launched – describe your biz – get an internal app in seconds


value:
Hello HN,
My name is Preet Suthar and I’ve been freelancing for the past five years.  Working with multiple clients each month quickly becomes a challenge when keeping track of everything.  When clients requested increased workloads, I struggled to manage tasks, documents and knowledge effectively.  This also caused problems for clients who were trying to manage five different platforms for communication, documents, knowledge bases and project management.
We eventually developed our own internal solution: a simple client portal. This portal allows us to communicate securely, store documents, manage projects and access company knowledge.  Our clients have loved this solution, and people often ask me about my process and how we use our internal tool.  When I mention it, they seem very interested.
I realised that this solution could be beneficial for other people too, such as company founders, agency owners and SaaS builders.  So, I polished our internal tool, renamed it “Relysta” and launched it this month. It’s been quite successful, and people are actually enjoying the product.
I’d love to hear your thoughts and advice on this.
Thanks,
Preet

value: Show HN: I built my own solution to manage clients because it's got too messy


value: ggattip

value:
I built a benchmark with 20 real CVEs across 18 Python projects (Pillow, GitPython, yt-dlp, urllib3, etc). I've run it over 5 LLM agents (3 OpenAI, 2 poolside) and 3 different prompts (full advisory, locate, diagnose) with a total of 300 runs. The agents are tasked to fix security vulnerabilities in a sandboxed environment and they are scored against a hidden security tests from the maintainer's own fix.
Best solve rate was 50%. On the other 50%, some fixes are sometimes coherent and pass all regression tests, but vulnerability still present.
The main differentiator I found between models is cost: gpt-5.5 at 12× more expensive than gpt-5.4-mini while producing statistically similar results. Within-family performance gaps are small, which points out the difference is likely due to model training data. I also did a power analysis and the task count needed to detect a meaningful within-family edge at ~700.
Full write-up: https://giovannigatti.github.io/cve-bench
Code: https://github.com/GiovanniGatti/cve-bench

value: Show HN: I benchmarked LLM agents on fixing real-world security vulnerabilities

author: ggattip


value: decorner

value: Show HN: LLM memory without context bleed; 100% precision vs. <10% vector search

author: decorner


value: seanblanchfield

value: We previously open-sourced a rubric for assessing APIs for agent-readiness (carefully designed by some colleagues who are deeply involved with the OpenAPI initiative). We hosted a nice web app for scoring an API according to this rubric (a mix of deterministic and LLM-based assessment), and learned people were hacking it into their CI/CD pipelines for regression testing and longitudinal tracking. So we just released a nice CLI to make that easier, with a decent free tier.

value: Show HN: CLI for scoring OpenAPI for LLM legibility

author: seanblanchfield


value: deemwar

value: Show HN: Run Llama.cpp In-Process from Java with Project Panama FFM

author: deemwar


value:
Concord(not that game) is TUI client for discord.
Here are features:
Login by token, email/password or QR code from the mobile app
Vim-style keys and full customization
Messaging, Voice chat support
Attachment downloads, uploads
Reactions(Unicode + custom emoji), poll voting
Inline image previews via Kitty, iTerm2, or Sixel protocols (halfblock fallback for anything else)
Avatar and custom emoji rendering, full-screen image viewer
Live typing indicators, unread + mention counts
Desktop notification

value: Show HN: Concord – Discord in Terminal

title: Show HN: Concord – Discord in Terminal


value: zdkaster

value:
Hi HN, not sure if anyone would be interested, but just wanted to share that I've been maintaining my small tool called 'lowfat' that helps me filters some of my verbose CLI output. It's a single binary, works as an agent hook or a shell wrapper. It has a plugin system to customize filters per command.
The idea is pretty simple: agents don't need the full kubectl get -o yaml or any 10k-line dump to make decisions.
So that lowfat sits in between, strips the noise, and passes through what matters. Here's my real report after 2 months of personal use:

  lowfat history --all

  lowfat plugin candidates
  ─────────────────────────────────────────────────────────

    #  command                    runs   avg raw      cost   savings  source    status
    1  kubectl get                101x     14.4K      1.5M     93.9%  plugin    good
    2  grep                       103x     13.5K      1.4M     96.2%  plugin    good
    3  git diff                    81x       995     80.6K     57.9%  built-in  good
    4  kubectl                     90x       485     43.6K     33.6%  plugin    good
    5  docker                     127x      5.5K    693.6K     96.1%  built-in  good
    6  ls                         489x       117     57.3K     56.2%  built-in  good
    7  find                        30x     16.5K    495.0K     95.5%  plugin    good
    8  git show                    63x       490     30.9K     38.0%  built-in  good
    9  git                        177x       368     65.2K     76.1%  built-in  good
   10  git log                     86x       556     47.8K     78.5%  built-in  good
   11  kubectl logs                 5x      3.6K     17.8K     43.0%  plugin    good
   12  git status                  86x       152     13.1K     58.0%  built-in  good
   13  docker ps                   20x       467      9.3K     52.8%  plugin    good
   14  kubectl describe             6x       656      3.9K      1.2%  plugin    weak
   15  docker images                9x       940      8.5K     61.8%  built-in  good
   16  k get                        2x      2.1K      4.2K     35.9%  plugin    good
   17  terraform                   10x       395      3.9K     32.1%  plugin    good
   18  git commit                  32x        77      2.5K      0.0%  built-in  weak
   19  docker build                 8x       487      3.9K     37.6%  built-in  good
   20  docker compose              22x       979     21.5K     89.4%  built-in  good

  total: 4.4M raw → 4.1M saved (91.8%)

My toolset above is kind limited, but it works pretty well for my usecase without any interruption
Kinda help me not reaching the token limit for my company Bedrock limit usage and keep optimizing the saving on the go for later usage.
But, why not alternatives (https://github.com/zdk/lowfat#alternatives) ?
The answers are:
  - My goal is to make the core lightweight but extensible via plugins i.e. not trying to bundle every command in the installed binary so that people own their output filters.
  - Customizable per usecase via plugin or filter pipelines as I am using my own toolset.
  - Customizable for non-public CLI tools, for example, some enterprise might have their interal CLI tools that public won't have access.
  - People should own their data. So the design is local-first, No telemetry forever.
  - I kinda love UNIX-style composible pipes, so lowfat-filter has implemented this style.
  - Be able to adjust aggressiveness of the filter, so we can control that we won't strip something the agent needed.
GitHub: https://github.com/zdk/lowfat
Anyway, if anyone is interested, feedbacks and questions are welcome!
Thanks!

value: Show HN: Lowfat – pluggable CLI filter that saved 91.8% of my LLM tokens

author: zdkaster


value: enklopper

value: Show HN: GoPortfolio – Portfolio Tracking and Retirement Planning Platform

author: enklopper


value: squidsoup

value: As a photographer, I've been experimenting with gaussian splatting as a quasi-photographic artistic medium. After alignment and training (colmap, brush), I post process my models with some python software I've written called rhêgma which allows for algorithmic transformation and distortion of the splats (volumetric shearing and redistribution of the data). My subject matter is primarily industrial structures and architecture in my hometown, Ōtepoti/Dunedin, Aotearoa New Zealand.

value: Show HN: Gaussographs – Gaussian Splat Photography

author: squidsoup


value: bsaylan

value: Show HN: OnePad: Stop losing your work in a sea of browser tabs

author: bsaylan


value: kyahwill

value:
I'm really interested in this idea of generating a knowledge base that's native for agents as well as humans. I'm pretty much inspired by Den's  [https://www.producthunt.com/products/den] product and I want to generate something akin to it that is open-sourced as well.
I hypothesize that, in the near future, with AI agents collaborating with human agents, there will be a need for a centralized storage of information that AI agents and human agents could use as a reference for their organizational and work activities.
As for the direction of my project so far, I'm keen on checking on whether I'm actually working on a decent problem right now or whether I should pivot to something else.
Feel free to provide some feedback. I'd love to hear it.

value: Show HN: Kaya Suites – An AI Native Knowledge Base

author: kyahwill


value: Show HN: Local-first fast CPU image to text for screenshots, PDFs, webpages