value: pinchydev

value:
A few weeks ago there was a thread about using AI to finish abandoned projects, and a comment from avereveard  https://news.ycombinator.com/item?id=47905088 on building their 100x100 grid battleship got my spark.  I didn’t build that, but it pushed me to finally finish a combat idea I’ve been wanting to play for ages.
Introducing Naval Strike!
It’s a simultaneous turn-based fleet vs fleet on a grid played in the browser. There’s no account or signups needed. Both players plan their moves, then the turn resolves at once.
There’s three different play styles:
* Solo.  Procedural maps and uses guided “AI” opponents (in the same way that 1990s games had “AI” opponents)
* Scenarios.  Objective missions on procedural maps like "rescue the downed pilot" or "destroy the convoy"
* Campaigns. Historical battles on real-world maps (Sink the Bismark in the Atlantic, or escort the tankers through the strait of hormuz)
A few things I figured HN would ask:
I designed the architecture and Claude did implementation.  While 90% of the decisions are mine 90% of the lines are AI-written. Lots of micro managing short bursts to get it to look/feel right.  I think I consumed a week’s worth of tokens just to get the fog working how I wanted. Eventually I learned that having lots of small bursts of code with testing got me to where I wanted much faster than longer sessions.  I built preview pages so I could test animations, sequencing etc without affecting the codebase so I didn’t chew through my tokens.
Stack. TypeScript/Canvas 2D, hosted on Cloudflare. The server is a tiny WebSocket relay, it pairs two players by room code and blindly forwards messages, with no game logic. So there’s no accounts and no tracking beyond default Cloudflare insights. Just open the URL and play.
Opponent AI is guided scripted tactics with situational decision trees.
Art is a mix of AI/hand.  I’m not artistic enough to do everything by hand, but there’s a lot of manual pixel by pixel editing on the assets.  Assets are stored as JSON arrays and drawn directly to screen with a colour palette.
I ended up building a small map editor that lets me "trace" Google Maps screenshots to get the campaign maps geographically close to the real engagements.
Sounds are from open source libraries - you can mute them with the little speaker button but they are on by default which might upset a few people.
Although this was largely coded by AI, I got heaps of enjoyment being able to focus on the UX, style, gameplay and UI to be just how I wanted. Being able to test (and throw away many!) ideas so quickly was awesome fun.
Feedback welcome. Especially on balance and the campaign design and gameplay, it’s hard to play-test every variable!

value: Show HN: Naval Strike – simultaneous turn-based fleet combat in the browser

author: pinchydev


value: jvaill

value:
I’ve been quietly building an open source background agent inspired by Ramp’s Inspect.
Basically, you can self-host it, point it to a GH repo, and prompt agents to do work on your behalf in the cloud.
The idea is to tighten the prompt -> preview -> deploy loop. Next steps will be to add preview environments and trigger changes from sources other than the web ui, like slack or your favorite project management tool.
All while making sure you can continue to self-host it and bring your own API keys.

value: Show HN: I built an open source background agent inspired by Ramp Inspect

author: jvaill


value: vednig

value: This is a specifically designed site for AI obfuscation and advanced AI crawler detection and reduction. I'd love to hear any suggestions or critics on it.

value: Show HN: A static website designed to be not readable by AI

author: vednig


value: amenghra

value: Show HN: Center-ish, 50 experiments related to centering content on a webpage

author: amenghra


value: magikMaker

value:
For a game I'm developing I needed an easy way to create hotspot areas on images. So I hacked together a small tool to do so and before I knew it, I had created an entire app :-)
It allows you to generate JSON or YAML from the coordinates you tack on the image. tack runs entirely in your browser, there is no server side component to it, so good in terms of privacy.
Hope this is helpful.

value: Show HN: Free tool to mark points and polygon regions

author: magikMaker


value: Show HN: Screen Adapt – auto-scaffolds responsive CSS and Tailwind variants


value: reti

value: I've run this app since 2022 so there's almost 50,000 headlines now - aggregates infosec/cybersecurity news from a bunch of good news sources. searching, tagging, rss feeds and CSV export. Run on Django. I've recently given it a bit of a face lift so thought I'd show it around a bit.

value: Show HN: Yasna – My infosec news aggregator

author: reti


value: TeddyCrep

value: Show HN: Sqlalchemy-Redshift Is Back: Reviving a Critical Python Data Library

author: TeddyCrep


value:
Hi HN,
I made a web client that analyzes prediction markets. Please send your critical feedback to a struggling solo dev.
Functionality:
1. 2hr cron query to Kalshi/Polymarket API for current market pricing and contract data.
2. Query relevant data APIs - 12 right now: NWS, congress.gov, Odds API...
3. Serper/Tavily search on each contract. These APIs pull relevant search results, summarize, and send it back to you in JSON.
4. Structured call to Gemini/Sonnet for each contract or event series containing multiple contracts. There are around 9k active analyses, but each cron only runs price moves or un-assessed contracts. Lots of backstops to prevent analysis runs getting stuck.
5. Store in Postgres database.
6. If a contract/event isn't new and doesn't have a price move, batch submission to Gemini on a 24hr cron to prevent staleness.
7. Bank account balance goes down.
Outlook:
- Good success with lower volume, lower scrutiny contracts.
- Still testing for accuracy but it's going well. Can't find an edge on major sport events because they are so heavily traded by professionals.
- Predictably can't get an edge on high volume contracts where Susquehanna  is running a full quant stack.
- Can't compete with retail quant bots on timing due to refresh restrictions.

value: Show HN: Web client analyzing prediction market outcomes


value:
Hey, I’m Colin and I have a fun story for you.
My 7 month pregnant wife was laid off from Indeed (she was a PM there) back in December. This pissed me off quite a bit, as she was supposed to get 6 months leave and instead got fired.
So I spent the last five months working part time to build Dreamwork, a platform aiming to make the job search experience actually better with AI (not just mass application spam).
I started with just a telegram bot doing scraping, then advanced to Google Embeddings 2.0 for vectorizing the jobs, built out a tight 6 axis scorecard for both the user and each job.
Then I actually got to use my English degree (lol) to optimize the prompt for custom per-job resumes and cover letters to make them not sound like - again - shitty AI.
Most AI cover letters have a kind of consistently dead quality. They use all the keywords and somehow communicate nothing. I absolutely hate that, so I’ve been fairly obsessive about making the output feel more like a decent human draft: specific but restrained, and not stuffed with keywords.
It is now useful enough that I think strangers can try it and find serious value.
What it does today:
- indexes ~100k curated tech jobs
- tries to avoid stale/duplicate aggregator garbage
- uses semantic matching instead of only keyword search
- generates an “application pack” for each job: tailored resume, cover letter, and answers to common/custom questions
- lets the user edit everything before applying
- helps keep track of saved jobs and generated materials
Auto apply is the part I’m conflicted about. I do t think blindly spraying applications is good for the candidates (chance of hiring is already low, even with hard work and customization), recruiters (they’re swamped), or the world (we don’t need more slop).
I’ll build auto apply out in some format, but I want to be thoughtful about it.
I also built out a whole research section to map out layoffs and hiring trends. This will start to be super useful in a month or two.
Anyways - it’s all free to use right now. Built originally out of spite, now becoming a real product.
I’d love to get feedback on what elements would truly make this the career companion you’re looking for. Not - resume spray and pray platform, but something that will actually help you navigate this insane hiring economy we’re in.
You can check it out here:
https://dreamworkhq.com

value: Show HN: Dreamwork – a job search site I made after Indeed fired my pregnant wif


value: NetOpWibby

value:
I love Svelte and GraphQL. I do not like React. So, when I'm building APIs, I cringe when using the official GraphiQL interface.
I have free will and a Claude subscription so I made it happen. You can find it on npm as "@eeeooolll/graphiql" (@eol was taken).
https://www.npmjs.com/package/@eeeooolll/graphiql
I also upgraded my batteries-included GraphQL server to use it. You can find it on JSR.
https://jsr.io/@eol/gq

value: Show HN: I Replaced React in GraphiQL with Svelte

author: NetOpWibby


value: afunk

value:
> Bridge AirDropped iPhone photos into your Obsidian vault. OCR, classify, and route — automatically.
I like living in the real world. I like paper and pens. I like brushes and paint (shameless [artfunk](https://www.artfunk.org) plug). I do not want everything in my life to be entirely digital.  Todo lists, diagrams, charts, whatever - I love a notebook.  But I had relevant context I wanted to share with my agents in some of these notes. So I built image2obsidian - an open source spinoff of a small part of www.toto.tech.
I have found it very useful and I hope you will too.
Take a photo with an iPhone -> Airdrop it to the device running your agent -> i2o takes the image, semantically analyzes it and incorporates it into your obisidian vault right where it belongs.
Watch the video of Image2Obsidian in action [here](https://x.com/toto_tech_/status/2052230644886118573)

value: Show HN: Image2Obsidian

author: afunk

title: Show HN: Image2Obsidian


value: GregKonush

value: Show HN: Bilig, headless spreadsheet engine for Node services and agents

author: GregKonush


value: andres

value:
Hi All,
Recently I've been using Claude Code a lot for debugging cluster issues and I realized I was performing similar tasks repeatedly so I decided to package them up into skills so I could call them up more easily (e.g. `/investigate`, `/audit-security`, `/audit-outdated`). I'm calling the skill pack "kstack" and the goal is to be able to monitor and troubleshoot K8s from within Claude Code.
If you have time, I'd love to get some feedback on the project!
Andres
Source: https://github.com/kubetail-org/kstack
Docs: https://kstack.sh/

value: Show HN: Kstack – Skill pack for monitoring/troubleshooting K8s in Claude Code

author: andres


value: spectry

value: Show HN: CRO analysis tool that finds conversion issues

author: spectry


value: Show HN: Password-less authentication via Ramanujan's 1/π series and Nvidia-B200


value: Show HN: StackSense – AI/data/systems engineering knowledge graph


value: wojtczyk

value: Show HN: TRUST – Coding Rust like it's 1989

author: wojtczyk


value: darkrishabh

value: Show HN: Agent-skills-eval – Test whether Agent Skills improve outputs

author: darkrishabh


value: froemic

value: Show HN: Codex Pets – tiny animated pets for web apps

author: froemic


value: rswcf

value: Show HN: AI VC Landscape – 666 Deals Mapped by Stage, Geography, and Founders

author: rswcf


value: samieljabali

value: Show HN: Starfield Screensaver for macOS

author: samieljabali


value: esubaalew

value: appctl(Appcontrol) uses your exising openai docs or your db and makes MCP tools. U can then connect your favorite LLM and chat either on terminal or web. The idea in mind is to expose actions we make inside any website of our own llm based so that we can ask AI to even submit a new record in our system.

value: Show HN: Appctl LLM tools for apps you have

author: esubaalew


value: mixfox

value: Calculate Omoggle Score before you really battle

value: Show HN: Omoggle Rating Score Calculator

author: mixfox


value: mugamuga

value: Show HN: Ikka – Zimbabwean Based News Aggregator

author: mugamuga


value: scottmotte

value: Show HN: Keysee – deterministic identicons for public keys

author: scottmotte


value: Show HN: Imagev2.me – Tired of juggling AI image subs, so I built one studio


value: NeuralNotwork

value: Using OpenAI's privacy-filter model behind the scenes. Can run on machines CPUs that are not-so-old (tested on 2020 M1 MacBook Pro).

value: Show HN: Uvx privacy-steward for PII removal in texts

author: NeuralNotwork


value: CringeOut

value: Built social network to make fun of corporate cringe. Post humblebrag content and react with direct emotions.

value: Show HN: Social Network for Corporate Cringe

author: CringeOut


value: ronfriedhaber

value: Show HN: Modolap, Improve the Reliability of Your Software Systems

author: ronfriedhaber


value: mbtrilla

value: Show HN: Crypto Cards – 136 debit/credit cards, MIT-licensed list

author: mbtrilla


value: hlymrk

value: Show HN: Production-Ready MERN Job Board Template

author: hlymrk


value: maxaw

value: I love voice notes because they are intimate. I've been thinking of a platform based around them. Such a platform would likely be for close friends only. But I made this to show others what it might feel like. Any feedback is welcome :)

value: Show HN: Voice-note based social network prototype

author: maxaw


value:
I built an open-source tool called Desktop Agent Center: https://github.com/WellWells/desktop-agent-center
It's a local-first gateway designed to bridge the gap between your desktop workflow and AI web interfaces like ChatGPT, Gemini, and Perplexity.

value: Show HN: Desktop Agent Center – Local AI Automation via Hotkeys


value: ProtsenkoAlex

value:
Hi HN,
We've been building Paste, a clipboard manager for Mac and iOS, for over 10 years. We keep making it more powerful, and the latest addition is about transforming how people navigate their clipboard.
We just shipped Jump to History. Right-click any search result and choose Show in Clipboard, or press Cmd+G on macOS. It jumps you directly to that item in Clipboard History or a Pinboard, with everything around it still in place.
The feedback pattern that drove this was consistent: people weren't just looking for an item, they were looking for a session.
See it in action: https://youtu.be/wOu2G8oIJi8
Try it yourself: https://pasteapp.io

value: Show HN: We added a way to jump from clipboard search back to original context

author: ProtsenkoAlex


value:
I had no backend experience. I used an AI to design and build the entire thing while I directed architecture decisions. Six months later it's serving real traffic.
I realised if you talk to Claude in a certain way it can build whatever you want even if its a grey area, it'll try fight it but you can crack it eventually.
I spoke back and fourth initially with chat gpt, open code, Kimi and gave me enough info to do research then get back to Claude with more info almost using them against each other in a way lol not knowing what each other said so it was up to me to piece it together eventually i got the claude .md file setup to create this without any barriers that you get all time "sorry I cant help with" as the .md doesn't look into the legality it just plans and codes what you give it.
The new universal programming language is English.
Stack:
Next.js 14 App Router (SSR + client components)
PostgreSQL for watchlists, watch history, progress tracking
Self-hosted on a single VPS behind Nginx + PM2

value: Show HN: I vibe-coded an illegal streaming platform


value: AlekseN

value: Show HN: Design proteins from one formula, zero training data – runs in browser

author: AlekseN


value: gnusi

value: Show HN: SereneUI – A VSCode-inspired, open-source UI for Postgres

author: gnusi


value: enmanuelmag

value: Show HN: Agent-harness-kit scaffolding for multi-agent workflows

author: enmanuelmag


value: eummm

value: Show HN: AICW Video open-source to cut video into clips with captions, voiceover

author: eummm


value: Show HN: Review code changes in a terminal and share with your coding agent


value: nitzano

value: Show HN: Bliss – a backlog quality scanner for AI-powered teams

author: nitzano


value: homeonthemtn

value:
Hello Hacker News!
We bring to you today 2 things:
1. Our passion project - LaoTzu Writer Studio - a modern writing application
2. Thoughts on the abysmal state of Kickstarter - likely well known to you all, but having experienced it for the first time, it is disheartening
So lets start with the good stuff:
LaoTzu Writer Studio - LaoTzu helps you build the framework of a novel, but still leaves the writing for you to do. That means there are indeed AI elements - like our Guard section that flags inconsistent canon in your universe, or the analyze section that determines writing stats, rhythm, mood, etc. - but there is no AI writing the story for you. That is an explicit intention - we want you to have support in your writing journey, but the story itself, that's still for you to do with your meat sticks on a keyboard. (To answer the question before its asked - no I did not use AI to write this post either - I just like dashes)
Our main site is here - https://www.redwoodrhetorica.com/ - and there is a limited demo available online if you want to futz around with it.
And our kickstarter is here - https://www.kickstarter.com/projects/laotzustudio/laotzu-wri...
We believe in this as a tool / workbench for writing and we're looking forward to evolving the app over time. The kickstarter is primarily for professional refinements of the platform so its less obvious that 1 guy with no sleep made this. We'd be much obliged if you joined the kickstarter, but we'd also just love testing and feedback as well - whatever you want to offer we'd appreciate.
Kickstarter itself - My goodness. We've both been on the backer side of kickstarter for a while, so we were excited to kick off the campaign. Well, from day one we've seen folks backing and un-backing as bait for scams left and right. Folks trying to circumnavigate the boundaries of the platform to try and "help us out" with all sorts of shady promises.
We are admittedly total amateurs when it comes to this, but it's been pretty off-putting to see the platform has, evidently, manifested a full on black market layer to it. Anyone else have experience with this? Any experienced heads want to opine on what they did to navigate kickstarter or kickstarter-esque platforms for their projects?

value: Show HN: LaoTzu Writer Studio

author: homeonthemtn

title: Show HN: LaoTzu Writer Studio


value: archargelod

value:
Yesterday, I found myself writing a little C throwaway script to test something out. That happens often enough to clutter my HOME and some other directories with these useless text files and binaries.<p>So I thought that I can use a repl instead. Quick google search didn't find any good and tested solutions. So I wrote my own with help of a tcc compiler.
Why POSIX Shell? Because it would be far too easy in a normal language (it'd probably take me ~10 minutes to rewrite this in Nim) and where is fun in that?

value: Show HN: Ced – C REPL in 50 lines of POSIX shell

author: archargelod


value: Show HN: Agentkey – save days of founder research with 1 "Master key"


value: tonyonodi

value: Show HN: I made a vertical-pedalling bike with a novel drivetrain [video]

author: tonyonodi


value: enigmurl

value: Monocurl is designed to be an ergonomic DSL for programmatic animations. It can create images, videos, and interactive slideshows.<p>The main audience is people who are interested in creating STEM visualizations (e.g. educators, academics), but I think it can be fun for anyone to try.

value: Show HN: Monocurl – Interactive STEM animation language and IDE

author: enigmurl


value: spookyuser

value: Very much a work in progress, but I made this for my dad's company who used to do every slide and it's found errors that people have missed.

value: Show HN: CLI for Testing Raw Data Against Google Data Studio Dashboards

author: spookyuser


value: RedwoodsKenyan

value: Show HN: Orbit – open-source server panel in Go with security plugins

author: RedwoodsKenyan


value: typekev

value: Show HN: Jobs – A transparent job stack where companies pay to rank

author: typekev


value:
I built an open-source memory plugin for OpenClaw agents, a biologically-inspired alternative to OpenClaw's built-in memory-core, with a take on what consolidation should do.
My background is in psychology, specifically personality psychology and how personality builds on top of memory. If we let an agent gather memories, it allows the agent to show features that look like a "personality". The basic architecture is to let the memory system form more complex memories from the initial facts that get remembered. To build this consolidation, memories are forgotten, and memories that are retrieved often get stronger. There's also a structure that builds associations, used both in retrieval and in spotting memories that are candidates for consolidation.
This is what consolidation here looks like:
- *Weighted bidirectional associations* between memory pairs, built from co-retrieval. Recall expands one hop along strong edges, so related memories surface even when they don't directly match the query.
- *Reconsolidation ("coloring")* — when a newer memory contradicts an older one, the older memory is rewritten in light of the new context.
- *Per-recall Hebbian strengthening* based on which injected memory the agent actually leaned on in the reply.
- *Content-addressed identity* (SHA-256), so the same fact from two sources collapses to one object at write time.
Today it ships as an OpenClaw plugin (v0.5.5, MIT). The core is agent-agnostic by design and can be extended to other agents.
Repo:  https://github.com/jarimustonen/formative-memory
Docs:  docs/architecture.md and docs/how-memory-works.md in-repo
npm:   formative-memory
Honest scope: first time I'm posting this publicly. We've been running it across four bots for a few weeks. I'd love feedback.

value: Show HN: Memory system for AI agents with associations, forgetting, synthesis


value: Show HN: Mex – persistent memory for AI coding agents (~60% token reduction)


value: tawb

value: Show HN: Tokid – Token-native IDs for LLM-facing systems

author: tawb


value: brine

value:
Curated RSS discovery. Federation by fork. No accounts. No platform.
Authors don't sign up, don't install anything. They just keep blogging like it's 2005 and a discover instance picks them up.
Hand-picked playlists of RSS/Atom feeds, organized by vibe. Browse, follow, read inline, export to your reader. Runs on Cloudflare Workers' free tier forever.
Feeds listed in discover allow an author to follow their `↩ mentions` feed to see when other writers link to their work. Pure RSS; zero spam.
Anyone can fork this, stand up their own instance, and curate their own playlists to their taste. Your corner of the web for the low, low price of $0.
Built on Cloudflare Workers. Open source: github.com/qualityshepherd/discover
https://discover.brine.dev

value: Show HN: Discover – a curated RSS directory with mentions via RSS

author: brine


value: blazeeboy

value:
Hey HN! I'm the author of XLog. I built it because I wanted a knowledge base tool that combined:
- Local markdown files (like Hugo/Jekyll)
- Automatic backlinks (like Obsidian/Roam)
- My text editor (Vim), not a proprietary app
- Git version control built-in
Most static site generators (Hugo, Jekyll, 11ty) are built for blogs. They're great at that, but they don't have knowledge-base features like automatic backlinks.
XLog converts `Page Name` to bidirectional links automatically. When you write about "Machine Learning" and link to "Neural Networks", the Neural Networks page shows that Machine Learning links to it. No manual link management.

value: Show HN: XLog Static site generator for knowledge bases with automatic backlinks

author: blazeeboy


value: danielrmay

value: Show HN: Learn a Language Through Trivia

author: danielrmay


value: fabriziorocco

value:
I want to present you a project I built over the last few weeks.
It's called CacheCore and it is a semantic cache specifically for RAGs and Agents.
It works as proxy by replacing the traditional base_url with the CacheCore gateway.
Gateway is built in Rust and there are 2 levels of caching (L1 and L2). There is a automatic mechanism for dependency invalidation.
Compared to other tools: most solutions require you to change the code logic and don't have dependency invalidation.
I started testing on the Legal and Health domains where context reuse is high and query costs add up fast.

value: Show HN: CacheCore – semantic agent caching with dependency invalidation

author: fabriziorocco


value: tughvn

value:
I built a simple Chrome extension to make dealing with 3GPP specs less painful.
You can save spec numbers to a list, and it checks for the latest PDF versions automatically. You can also download and open them right away.
Figured some network/telecom engineers here might find it useful.

value: Show HN: Download and open 3GPP specs – LTE, 5G, 6G from your Chrome side panel

author: tughvn


value: Show HN: Transform Claude/Codex/Cursor sessions into high-value data assets


value: doshay

value:
hi guys.
been working on something i think is fundamentally missing in today's workflow with ai agents.
vcs.
i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc.
or trying to /rewind (after a /compact...) or
basically `bisect` to find when and why something was done by the agent in the current / previous session.
just like git did for code, i think we are the same core capabilities with ai agents
so...
i developed an open source solution for that (currently supporting claude code)
would love to get feedback, contribution or maybe other ideas or solutions you find for those problems.

value: Show HN: Git for AI Agents

author: doshay

title: Show HN: Git for AI Agents


value: Show HN: Pomota – Pomodoro timer that forces breaks (Tauri, Rust+React)


value: chrka

value: Show HN: Avoiding "if" makes Quicksort faster

author: chrka


value: keertahacker

value: Show HN: AERF – receipts for AI agents, crypto-signed like cosign for evidence

author: keertahacker


value: gamalinosqui

value: Show HN: Open-source AI code review (AGPLv3, BYOK)

author: gamalinosqui


value: calinf

value:
Imagine an alien observer trying to understand why we do the completely "unhinged" things we do, like why we hoard our own trauma, or enslave ourselves to alarm clocks.
Every day, I take one human behavior and try to defend it through empirical data, logical constructs, and philosophical or religious perspectives anchored in our collective lore.
Any suggestions for what the next question should be?

value: Show HN: Linlore – Defending human existence, one question at a time

author: calinf


value: cammasmith

value:
Of all the NoSQL databases, DynamoDB is one of the most frustrating to query. MongoDB has an expressive query language. Cassandra has CQL, which is close enough to SQL that most engineers can pick it up quickly. DynamoDB gives you key condition expressions, attribute name placeholders for reserved words, and a query model where you have to pick the right index manually for every call. PartiQL exists but doesn't support JOINs, GROUP BY, subqueries, or most of ANSI SQL.
I built DynamoSQL to fix that.
It accepts any ANSI SQL SELECT statement and converts it to the right DynamoDB API calls. The interesting part is the index selection: given an incoming query, the system inspects the available indexes on the table, figures out the most efficient access pattern, and constructs the call. Partition key lookup when possible, secondary index when that fits better, scan only as a last resort.
JOINs were the most involved part. DynamoDB doesn't support them natively, so they execute client-side after fetching from both tables. The full list of supported SQL includes WHERE, all JOIN types, GROUP BY, HAVING, ORDER BY, LIMIT, UNION, INTERSECT, EXCEPT, subqueries, CTEs, and a wide range of aggregate and string functions.
We're looking for beta testers. If you work with DynamoDB and want to run SQL against it, I'd like to hear from you.
https://dynamosql.com/

value: Show HN: I built an SQL layer for a NoSQL database

author: cammasmith


value: josephmarkus

value:
I've been weight training for 15 years and never found an app I actually liked. Free ones - Google Sheets and Apple Notes - were too basic. Paid ones crashed mid-workout, refused to work without Wi-Fi, or hid basic features behind a paywall.
So I built SetSweat, a workout and calorie tracker that works offline and stays out of your way.
I’d wanted to build my own for years. Front-end engineering is my day job, so you’d think it would be easy. It wasn’t. I’d dedicate a weekend to it, not touch it for months, then give up entirely. That cycle repeated for years until I picked it back up properly in November 2025 and finally stuck with it long enough to release it this year.
Once it felt reasonable I took it to the gym and tested it properly. That turned into a lot of notes and a lot of improvements. Eventually I added food tracking. The thing that bothered me most about existing apps was the databases: millions of entries, half of them inaccurate or out of date. Most people regularly track around 200 foods, so I added those by default. You can edit the macros for any of them to match what you actually buy, because the numbers on your chicken breast are probably not the crowd average. For anything else, you can add your own, visible only to you.
The goal is to be useful for people who currently use a spreadsheet or pen and paper, or are just fed up with yet another app that overpromises and underdelivers. I'd love some feedback from folk who feel this resonated with them.

value: Show HN: After 15 years of lifting and spreadsheets, I built my own workout app

author: josephmarkus


value: apignotti

value: Show HN: BrowserCode – Run Claude Code in the Browser via WebAssembly

author: apignotti


value: -babi-

value: Show HN: Coding agents can control desktop software without MCPs

author: -babi-


value: bryanhogan

value:
I wanted to a simple timer for time-boxing that just work. No account, 100% free, no ads, no distraction, just a sequential timer.
I originally built this more than a year ago, but have updated it with some improvements now, better interface and a few new options in the settings were added.
Hope this helps someone. Feedback and feature requests are very welcome.

value: Show HN: Flow Timer – A simple sequential timer without bloat for timeboxing

author: bryanhogan


value: Show HN: CloudCent – Know Your Cloud Costs Before Coding


value: anticleiades

value: Show HN: 'Safari-Like' 2-finger nav gesture for IntelliJ (Java Swing) on macOS

author: anticleiades


value: Show HN: Self-improving skills for any coding agent


value: LuxBennu

value: Show HN: CtxVault – local receipts for AI context handoffs

author: LuxBennu


value: lekacoding

value:
I built MySigner because every mobile release meant juggling Xcode, Fastlane, App Store Connect, the Play Console, plus a $200/mo ASO tool and another for reviews. Five things. I wanted one command.
So the main piece is `mysigner ship appstore`. It builds, signs, uploads, waits for Apple's processing, then submits for review. Same idea for Android: `mysigner ship play-production`. It figures out what kind of project you have on its own (native, React Native, Flutter, Capacitor, Expo). No config file unless your setup is weird.
The dashboard does the rest in one place. Screenshot Studio with device frames and translated captions for 30 locales, keyword tracking, reviews from both stores in one inbox, analytics synced daily from ASC and Play.
On trust because I know this matters: the build runs on your machine, not mine. Your Apple cert and provisioning profile decrypt only inside your local build, my servers never see them in the clear. Credentials at rest are AES-256. Hosted on Hetzner US, no third-party data brokers. Audit log is hash-chained on the Team plan.
Stack is Rails 8 with Hotwire and Tailwind. CLI is a Ruby gem, install with `gem install mysigner`.
Pricing: free tier ships to TestFlight unlimited, full CLI, 1 app. Pro is $12/mo for 10 apps with ASO and reviews and analytics. Team is $49/mo with SSO and audit log. 14-day Pro trial, no card.
Platform-wise, iOS shipping requires macOS because Xcode is macOS-only, that's Apple's constraint not mine. Android works on macOS, Linux, and Windows. The CLI has no native extensions so `gem install mysigner` works wherever Ruby 3.2+ does. I've mostly tested on macOS though. If you try it on Linux or Windows I'd really appreciate hearing if anything broke.
Fastlane is honestly still the right tool if you've spent months tuning your Fastfile or need self-hosted CI in your own VPC. This is for indies and small teams who'd rather type one command than maintain a release pipeline.
I could really use feedback. Bugs, weird workflow stuff, anything that doesn't make sense. Limited time and limited team so any criticism is gold.
Thank you :)

value: Show HN: MySigner – Ship iOS and Android apps with one command

author: lekacoding


value: nowflux

value:
PG has posted many times about improving social media discussions using an "intellectual CAPTCHA" or simple math / logic test [1][2][3][4] - "I have often sensed that a really easy math CAPTCHA would improve conversations about economic inequality.", "Make users pass a test on basic concepts like the distinction between necessary and sufficient conditions before they can tweet."
I built one using a mix of simple math, logic, reasoning questions from social media posts and retired standardized test questions. This is not a CAPTCHA in the traditional sense. The goal is not to stop AI, but to allow users to participate in discussions.
- Invites are temporarily open to HN users.
- Onboarding test + one daily question before accessing feed, post or reply.
Updated post after addressing feedback on questions and technical issues in https://news.ycombinator.com/item?id=47663207
[1] https://x.com/paulg/status/1235949761359904768 [2] https://x.com/paulg/status/1576517990182359040 [3] https://x.com/paulg/status/1514979883948126209 [4] https://x.com/paulg/status/1505842647319126016

value: Show HN: I Built Paul Graham's Math/Logic CAPTCHA Idea for Social Media

author: nowflux


value: krakato

value:
Hello everyone,
I'm building a multimodal AI inference platform in Go and needed Stable Diffusion support for image/video generation.
Existing Go bindings for stable-diffusion.cpp were either outdated or no longer maintained, so I decided to build my own.
gosd is a set of Pure Go(no CGO - ffi-based) bindings for stable-diffusion.cpp.
It is cross-platform(regularly tested on Win, Linux, Mac) and integrates
seamlessly to existing Go-based codebases and applications(no C++ compiler needed for your builds).
You can generate images, videos, edit images, preprocess images with Canny,
watch images/videos being generated after every step in the inference loop and much more.
Around a dozen of models can be used for generation(Wan2.2, Flux...) - please have a look at
https://github.com/leejet/stable-diffusion.cpp for the full list of compatible models.
On my local setup with Radeon 7900XTX, a full HD image can be generated in about 10-30sec.
You don't need a GPU for generation, CPU alone will be fine(although 10-100x slower).
The library is MIT licensed so you can use it pretty much however you want it.
I'd appreciate any feedback - hopefully you'll have as much fun with gosd as I have.

value: Show HN: Gosd: High-performance Stable Diffusion inference in pure Go(no CGO)

author: krakato


value: azizuysal

value:
I left Arc for Safari last year and the only thing I really missed was the essentials panel. So I built it as a Safari Web Extension.
It has a customizable grid and supports multiple spaces. The popover can be opened from the Safari toolbar or with a customizable keyboard shortcut (default Cmd-Shift-E). Once open, you can drag and drop links to the grid to add them, or use the + button. Spaces and essentials can sync across your iCloud if you enable it in settings. There is no iPad/iPhone version yet though.
You can click on the label below the icons to rename them to something more useful, this doesn't change the link URL. You can right click for a context menu and from there you can delete, rename, change URL, etc. You can also drag an icon to reorder in a space, or drag it on another space to move. You can use keyboard shortcuts to move (Ctrl-1..9 to switch spaces, Opt-1..9 to open by index). You can open the extension settings from the gear icon in the popover for more customization.
It's $4.99 one-time purchase in the Apple App Store (Mac only, requires Safari 17+, macOS 14+). It has no analytics/telemetry, no backend or login, and no data is collected or seen by me. The only network call it makes is fetching the favicon (target site first, Google's public favicon service as fallback). Favicons are cached locally on your Mac. It doesn't manage Safari tabs or bookmarks, doesn't auto-open sites at startup, and doesn't read page content.
I am curious what people think. I'd be happy to get any feedback, bug reports, or feature requests.

value: Show HN: Essentials for Safari – Arc-style Essentials panel

author: azizuysal


value: jballanc

value: Show HN: RVW – A transformer model capable of online continual learning

author: jballanc


value: krumboy

value: Show HN: Kon – A Coding Agent with a System Prompt under 270 tokens

author: krumboy


value:
Hey HN! We're Charles and Dean. A few weeks ago we posted about Stage, a code review tool that guides you through reading a PR step by step - https://news.ycombinator.com/item?id=47796818.
We got a lot of great feedback but also heard from many people that they wanted to have the chapters experience even before opening a PR… so we built the Stage CLI as the local, open-source version that anyone can try.
Here’s a quick demo video: https://www.tella.tv/video/stage-cli-demo-f55q
It works with any coding agent of your choice. The skill instructs the agent to read your current branch’s changes, break them down into separate logical chapters, and open them in a local browser.
We’ve found that reading changes this way is a lot easier for us than reading them in an IDE or other similar CLI tools, which present diffs to you in repository tree order. You can see a few examples of what it feels like here: https://stagereview.app/explore.
Try it out and let us know what you think! Would love to hear any feedback :)

value: Show HN: Stage CLI – An easier way of reading your AI generated changes locally


value: narghev

value: Show HN: Drumforge – Free open-source interactive drum exercises

author: narghev


value: tommyjepsen

value:
Hi,
I've returned to Nielsen, Shape of AI, and many others tons of times to read up again and again on how to do stuff; therefore, I created skills to help me going forward.
Hope others can benefit from them too.

value: Show HN: My Collection of UX / AI Design Claude Code Skills

author: tommyjepsen


value: aabdi

value:
Seems lots of folks are building workflow orchestrators these days. This is mine~. Would like your guys feedback!
Mostly supports codex, customizable graph orchestration so it supports all weird flows you can think of (ralph loops, spawn worktrees, write review). Bootstraps itself nowadays (i.e. the last ~900 commits).
supports script and agent based nodes in the graph. i.e. you can paply post condition checks via script nodes or reviewers.
Completion is marked when a node in the graph moves a token from processing to failed/complete.

value: Show HN: Infinite you – multi agent workflow system

author: aabdi


value: BubTheBuilder

value: Show HN: Daily AI-guessed odds of an Iran peace deal, vs. oil/gas prices

author: BubTheBuilder


value: SHOW HN:Employees use ChatGPT.Your CISO has no visibility. EU AI Act says fix it


value: Show HN: OTel native agent to instrument applications


value: misaelzapata

value: Local-first long-term memory engine for AI agents · MCP + HTTP + CLI · SQLite + sqlite-vec + FTS5 · 100% local, no cloud

value: Show HN: Local-first long-term memory engine for AI agents·MCP/CLI· 100% local

author: misaelzapata


value: ranguita

value: Show HN: Shopify-to-WooCommerce Migration Plugin – Storefront GraphQL API

author: ranguita


value: BagelsOverBread

value: Show HN: Serial – an open source RSS reader for YouTube

author: BagelsOverBread


value: cyberteaborg

value:
Airlock is a platform for creating and running cyborg agents - half-code half-AI compiled binaries that execute code where possible and invoke AI where needed
The short version:
- Agents are compiled containerized autonomous go binaries
- They use normal code for deterministic/repeated work and call AI when needed
- They can be interacted with via chat, web, cron, webhooks
- They can upgrade themselves through Airlock api call to generate new tools/fix errors
- Airlock manages OAuth, storage, sandboxing, web UI and bridges to telegram/discord
Example:
Tell agent "I want to edit Google Sheets"
-> Airlock generates integration code, handles OAuth, stores tokens securely and gives you a chat interface
Tell it "I want a webpage where I can upload picture of my food so you write calories to the spreadsheet"
-> Airlock will upgrade the agent to give you a webpage with a picture upload form. Webpage is rendered from inside the agent.
<bio>
Hello HN! I wanted to share a personal project I've been working on for quite a while. But first - a little bit about myself. I am 32yo, backend software engineer with more than 12 years of experience. I got taught some very basic C and Assembly in school and then Left 4 Dead came out. In order to host L4D game servers I learned how to Linux and how to write actual working code (sourcepawn), then I switched to Minecraft hosting/modding and then I had to focus on Uni. I have spent some time working in enterprises as well as in startups. I worked as a backend engineer, system analyst, system architect, PM, ... I even tried to make a MedTech startup as a cofounder (I was doing only the IT part and we got no traction). And about 2 years ago I decided I want to try to do something by myself. I switched to freelance but I always wanted to actually make something of my own and then show it to everyone.
About a year ago I started working on something personal. I first started with an MCP gateway, pivoted to a company's agentic slack-like platform and then finally switched to my current project. In order to build it I had to implement an AI thinking loop. I could use ready libraries but I wanted go and I needed a coding harness like loop. So I decided to port some parts from opencode to go. And since opencode requires vercel/ai-sdk I had to port that as well.
So in the last ~4 months I
ported vercel/ai-sdk -> airlockrun/goai
ported opencode -> sol
Verified the thinking loop by recording opencode<->LLM interaction and replaying it on the ported code.
Then built the Airlock system - agentsdk as a library for agents, airlock as a platform to create, evolve and run these agents.
</bio>
<current state and roadmap>
This is an alpha version and bugs are expected even after my thorough testing. You can check out the quick local deployment but you will be missing some features and Agent<->LLM interaction will be degraded. If you have a VPS and a domain - this is the recommended way to run it. Look at the readme, its literally
git clone ... && git checkout ... && cp .env.local.example .env && docker compose -f docker-compose.yml -f docker-compose.local.yml up -d
In the near future I will be adding agent-to-agent calls, exposing self-coded tools as MCP server, improve self-upgrade times and webpage styling, remote agents, etc.
</current state and roadmap>
In any case, thank you for reading, I really hope you check out the project and give some feedback.

value: Show HN: Airlock – self-upgrading compiled AI agents

author: cyberteaborg


value: nvoxland

value: Show HN: Bundlebase – Docker for Data

author: nvoxland

title: Show HN: Bundlebase – Docker for Data


value: avansledright

value: Show HN: Live SEO monitoring dashboard in 100 lines of Python

author: avansledright


value: bmusuku

value: A cli tool that generates videos explaining code changes your agent made.

value: Show HN: AI Generated Videos for your Code diffs

author: bmusuku


value: bookedkit

value: Show HN: BookedKit, a booking-ready EPK builder for musicians and DJs

author: bookedkit


value: pstomi

value:
I have been working on Dear ImGui Bundle since 2022, but it is the first time I talk about it here. It is a framework around Dear ImGui for building interactive applications in Python and C++. It comes with batteries included: Plotting, image inspection, Markdown, node editors, 3D gizmos, knobs, toggles, etc.
https://imgui-bundle.pages.dev
It now also runs smoothly in the browser via pyodide: The playground below is a python app running in your browser (no server, no JavaScript). You can edit the code on the left and click Run. It even works on mobile.
https://imgui-bundle.pages.dev/playground
I have a strong interest in providing tools that help others express their creativity. This project aims to be a step in this direction as it helps develop GUIs where the code is extremely readable & hackable.
Some of the goals it addresses:
- Bring true Immediate Mode GUI to Python and C++
- A versatile range of high quality libraries: Widgets, Plots, Image Analysis, Node edition, markdown rendering
- Multiplatform apps in C++: works on all platform in C++ (desktop, mobile, emscripten)
- Deploy python apps to the web
- High quality python bindings that are always up-to-date (because they are auto-generated)
- Smooth transition between C++ and Python (same APIs for both)
I'd be happy to answer questions!

value: Show HN: Full Python GUI apps in the browser – no JavaScript, no server

author: pstomi


value: yotc

value: Show HN: Bookstoread.ai – Discover non-fiction books using AI

author: yotc


value:
Hey HN, Justin here, and we’re building agent-data: a CLI tool that gives AI agents access to real-time, structured data without requiring them to use browser automation.
The idea came from trying to get agents (e.g., OpenClaw, Hermes Agent) to perform more useful tasks than simply organizing our calendars or monitoring our emails. We wanted them to answer questions and take actions that depend on timely external data, e.g., “Can you find me roundtrip flight options from NYC to SF next month”.
Personal assistant agents appear to be great frameworks for maintaining user preferences and acting with that information (e.g., “Justin hates early morning flights,” “Justin doesn’t mind a layover if it’s shorter than 3 hours,” etc), but existing tools for providing assistants with actionable, external data are surprisingly limited.
For example, browser automation can work, but it’s generally slow, expensive, and flaky [1].
Ad-hoc scraping works well in narrow cases, but can become quite expensive at scale.
MCP servers can inject tool schemas into context on every turn (inflating token consumption), and are often either too granular or too coarse in their design.
So we built agent-data around a simpler interface: give the agent the ability to discover the right endpoint at runtime, call it via CLI, and get back compact structured output.
For example, to answer my earlier question, an agent might use: `agent-data call search-flights --origin_iata JFK --destination_iata SFO [--params]`
We chose the CLI design because agents already work well with bash. Further, commands can be composed, piped to files, and are generally more flexible than off-the-shelf MCPs. Instead of teaching an agent to use a browser or learn a new MCP tool schema, we wanted to give it a smaller, more predictable interface.
The current version supports:
- Live data endpoints for categories like flights, restaurants, RSS/blog feeds, and social media feeds
- Structured JSON outputs by default
- Endpoint discovery so agents can “find” relevant capabilities instead of loading huge lists of tools into context by default
- A CLI interface designed for agent workflows
It’s still early and some parts are a bit rough, but we’re adding new endpoints and expanding the scope of existing ones every week.
We’d love to know: What live data sources do you wish your agents could access? Where have browser automation, scraping, generic web search, or MCP tools failed in your own agent workflows?
[1] https://news.ycombinator.com/item?id=48024859

value: Show HN: Agent-data – a CLI for giving agents real-time, structured data


value: MatMercer

value: Show HN: Chrome new prompt API demo

author: MatMercer

title: Show HN: Chrome new prompt API demo


value: GregKonush

value: Show HN: Bilig – a headless spreadsheet engine for Node services and agents

author: GregKonush


value: agunapal

value: Show HN: Verdict – model evals on your own data, not someone else's benchmark

author: agunapal


value: ahmedahres

value:
We built infrastructure for real-time interactive video models and today we are sharing our first public demo.
Unlike standard video generation where you submit a prompt and wait for a file, this runs continuously and responds to your inputs as it generates. The world updates in real time as you interact with it.
We are also opening API access for developers who want to build on top of it.
Try it at reactor.inc. Happy to answer questions.

value: Show HN: Real-time world model demo

author: ahmedahres

title: Show HN: Real-time world model demo


value: rikroots

value: Show HN: A local-only image filter editor and batch processor in the browser

author: rikroots


value: Show HN: I built a platform for experimenting with attention arbitrage


value: velieroglu

value: Show HN: Describe what makes a photo "bad" and let a local LLM flag them

author: velieroglu


value: mhamann

value:
Hi HN, I’ve been working on a Rust userspace radio stack for running WFB-style links from macOS using RTL8812AU USB adapters. Full disclosure: I'm a software engineer, but not really a hardware or embedded systems engineer, so Codex GPT 5.5 has done the lion-share of the work here along with a bit of help from Claude Opus 4.7 here and there. It's taken about 1.5 to 2 weeks to get from zero to this first release.
macOS doesn't expose the monitor-mode / packet-injection path that WFB systems normally rely on. I really didn't like the idea of needing a separate linux box just to talk WFB to other edge devices, like drones. This talks to the ALFA AWUS036ACH as a USB peripheral directly, initializes the RTL8812AU, submits raw 802.11 WFB frames over bulk OUT, receives frames over bulk IN, and bridges them to WFB-NG’s distributor/aggregator UDP protocols.
Basically, this is what's working (you can see more detail in the readme):
- native macOS userspace RTL8812AU bring-up
- TX/RX of WFB datagrams
- production-ish service runtime
- macOS utun bridge helper (if you need an IP-based link)
- RF diagnostics, telemetry, LED heartbeat, TDD airtime controls
There's a GitHub alpha release with arm64 macOS binaries
This is definitely still alpha. The direct-radio path is currently macOS-focused and tested with ALFA AWUS036ACH adapters on both sides (the other side is a Raspberry Pi 5 running Bookworm). macOS 26 works through IOUSBHost as libusb is not reliable there. Linux should still use native WFB-NG + rtl88xxau monitor mode rather than this USB bridge. Long-range RF quality and calibration work are ongoing. So far, some short range profiles are showing pretty good results.
I’m sharing early because getting WFB-like radio links working from a Mac seemed unlikely when I started, and the path turned out to be more interesting than expected.
My goal is for this to be cross-platform as-needed. Next up is an attempt at Android support via USB-OTG. We'll see how that goes.

value: Show HN: wfb-link, a userspace WiFiBroadcast radio stack for macOS

author: mhamann


value: barisozmen

value:
Hi HN
I built this app while learning Japanese kanji after struggling to find a tool that showed how kanji are structurally connected through their graphical components.
The core feature is a recursive DAG-style component graph (“Kanji Atlas”) that breaks kanji down layer by layer into radicals and graphemes, so you can visually explore how characters are constructed and related to one another. Demo at https://mykanji.app/components/kanji/鬱
I also built in a lot of my own opinions about how a learning tool should feel and work. Some features:
1. A kanji memory heatmap — the idea is that learners should be able to see at a glance which parts of the writing system they actually know well and which areas are weak.
2. Study desks + spaced repetition review for long-term retention.
3. Kanji, words, and graphemes are interconnected, so learning happens through relationships and context instead of isolated flashcards.
4. Lessons follow the Japanese school grade progression (Grade 1–6).
5. Quized sessions are hosted by Mizuki Sensei — possibly your future waifu!
I’d especially love feedback from people who have gone deep into kanji study before.
I’m also happy to answer questions and discuss feedback regarding the technical side, UX, learning approach, product direction, or anything else about the project.
Visit https://mykanji.app

value: Show HN: DAG-based Kanji learning through components

author: barisozmen


value: I got tired of how difficult it is to spot counterfeit cartridges (especially DS games). The website pulls active listings from eBay and runs it through a classifier I trained on hundreds of photos of real / fake cartridges.

value: Show HN: Pokemon Cartridge Authenticity Checker


value: ramoz

value: Show HN: Rig – a Ghostty sidecar for managing agents

author: ramoz


value: steampixel

value: Show HN: Executing Conversations as Reactive Graphs

author: steampixel


value: javiernanni

value:
I was tired of spending hours swiping just to get 1 or 2 decent matches. So... I built this Chrome extension that does the filtering and swiping for me. I'm male/36 btw.
Several Chrome extensions already do this, but their UIs are terrible, the filters you can apply are limited, and there's no way to filter based on the content of profile photos.
I initially built Swipe Copilot (https://www.swipecopilot.com) for myself, but then realized others might find it helpful too, so I thought I would publish it and share it :)
It works for both Tinder and Bumble. If you try it out, let me know how it goes!
In the 2 weeks I've been testing it myself, I went from dreading the apps and barely using them to getting several interesting matches each week, with two of them leading to first dates.
I know this kind of tool may not be for everyone, but for me, there's no way I'm ever going back to swiping manually.
PS: I haven't been able to test this with free Tinder/Bumble accounts yet, so it's possible that when you run out of likes or an ad appears, things might break.
---
HOW IT WORKS
The easiest way to understand it is to try it out, but if you're curious and want to read...
First you set Red Flags: if a profile matches any of them, it's an instant Nope. As an example, some of my Red Flags are "Smokers" and "Workout = Never". For each Red Flag you set, you can choose whether it should apply only if the person is looking for a long-term relationship.
If a profile clears all Red Flags, its first 3 photos are analyzed with AI.
1) First check: whether the photos are of an actual person and whether they match the gender you're attracted to. In my case, if at least 2 of the pics don't show an actual person, or the person is a man (happens sometimes), it's an instant Nope.
2) Second check: Body type. You can choose accepted body types (choosing ALL is the default option).
3) Third check: Attractiveness, which can be Low, Mid, or High. This was very hard to fine tune. Low and High ratings are generally correct (at least from my POV), Mids can be tricky.
For each Attractiveness tier you can choose what Swipe Copilot should do: Instant Nope, Instant Like, or Conditional. If you choose Conditional, a Like will be triggered only if some of your Green Flags are met.
You choose how many Green Flags are needed to turn a Conditional into a Like. As an example, some of my Green Flags include "Don't want children" and "Interests contain Meditation or Mindfulness".

value: Show HN: Swipe Copilot – Less time on Tinder, more dates worth going on

author: javiernanni


value: mojoe

value: I'm a book publisher and former science fiction magazine publisher with a deep love of science fiction.<p>I've always loved the old vibrant SNES color scheme, which is what I went for with this tool. I spent a lot of time pulling in what I think are pretty unique story elements for this kind of generator, I hope you have fun with it!

value: Show HN: Super Mega SFF Story Ideator

author: mojoe

title: Show HN: Super Mega SFF Story Ideator


value: Show HN: Crypto Trading Simulator – 11 coins, candlestick charts, zero risk


value: pawelkomarnicki

value: Show HN: Making journaling as easy as texting your friends

author: pawelkomarnicki


value: jrm-veris

value: Show HN: Veris – Agent sandboxes with simulated external services

author: jrm-veris


value: pzxc

value:
I used to run a flash games website (SWF files) years ago. I've made a few games of my own. I'm also an avid gamer and love to play games of all kinds.
I'm also a software engineer, and a few days ago I decided I wanted to run a games website again. So I bought the domain gamevibe.us and with the help of Claude I've been vibe-coding one video game every day since.
Happy to answer questions, take feedback, etc

value: Show HN: Vibe-coding video games with Claude (Day 24: Fishies)

author: pzxc


value: raulgooo

value: Pretty early still, feel free to ask questions. I truly believe agents need better security.

value: Show HN: I built open-source auth for AI agents (Go, single binary)

author: raulgooo


value:
Systematic testing of browser agents today is not easy: testing on real websites is flaky, rate-limited and potentially expensive (e.g. using proxies or bypassing Captcha), while static-HTML benchmarks lack state and dynamic behavior.<p>Resurf gives your browser agent a realistic, stateful, instrumented framework — built on synthetic websites with failure-mode injection:<p>- Realistic, dynamic, interactive environment
- Deterministic & reproducible
- Failure-mode injection (latency, payment errors, 5xx)
- Auditable success eval (DB state, not LLM judge)
- No dependency on live websites
- Browser Use and Stagehand supported out of the box

value: Show HN: Resurf – realistic, reproducible test framework for AI browser agents


value: eblanshey

value: I'd like to share a new workbench I've been working on called DiffCAD. Coming from a software engineering background, not having the ability to properly diff my CAD model changes was driving me crazy. This project scratches my own itch, and maybe someone elses', too!<p>I'm open to feedback, ideas, and contributions. Cheers!

value: Show HN: DiffCAD, a FreeCAD workbench to review model changes like code

author: eblanshey


value: audreyfei

value:
Hi- I hope you’re all having a good day so far! I'm not sure where to post this but I do have two things for you guys today, related to the AI space: individuality and a new era to AI! So:
- LLM wrappers are crumbling- these businesses will not survive as foundational models begin to offer the functionalities consumers have been seeking. This maybe represents a failure in interpretation of individuality as horizontal growth (these startups didn't last too long...), which brings up the next point.
- Individuality and ego are human needs. In the past year, there's been a boom in using AI to personalise products to consumers. A take on this: are companies really doing "individuality as horizontal growth" as consumers would like them to? Do consumers really need businesses to tell them that they're individuals? Are personalised feeds actually honouring their individuality, or are they just grouping consumers into demographics that homogenise them and strip away their individuality? And do businesses realise that consumers aren't blind to this? (reference at the rise & mission of Bluesky).
- Above connects to backlash from consumers in response to AI slop. AI slop is a feature of this era of conformity-> so look ahead to the era of individuality (reference historical back-and-forths between these two concepts- ie 1910s were the tail of social conformity and featured great social unrest until it was followed by the 1920s)
Also:
- I am assuming Hacker News is visited by a lot of software devs: one-shot learning and zero-shot learning could be something to check out! (reference Meta currently building Large Concept Models)
That's all. I hope you got value out of this post and have a good day!
(long note if you appreciated this and want to see an example of the above concepts and judge some ideas for yourself:
The above was written by me, Audrey Fei, I'm 16:
- I've been looking at the speech area of AI (text and image has already had its moment). currently have a patent pending for a real-time accent conversion technology (rooted in the idea of a “Golden Speaker” which dates back to 1990; also the patent is for the specific architecture of the System, which is different from standard architectures expected in the industry).
it's at loxai.tech (I'm trying to raise awareness to this tech so there's a waitlist page). the central idea behind it is that:
at least in the subfield of speech processing, Golden Speakers are contrarian to the norm of speech synthesis (where speaker identities are lost, instead of preserved). also it uses one-shot learning (a MAML) in its structure
- there's a MVP that led to the above (neutboom.com). It centers around natural language acquisition (differentiates itself from the rest of the language learning market). It's might be a bit clunky in places (you can just tell me about anything that's ugly) but hopefully it's interesting or adds some perspective (at least personally I feel that translation is a middleman.....and why would you need a middleman especially when it overcomplicates the process of language learning? input on this would be appreciated).
)
Anyway I hope you have a creative rest of your day!

value: Show HN: Gen AI's frontier of individuality

author: audreyfei


value: Show HN: No More Deepfakes – A Ramanujan 1/π and Nvidia B200 Architecture


value: ldang

value: Show HN: Built a Public Journal for Builders

author: ldang


value: etaheri

value:
Disputron is a small claims court for petty disputes. Two parties file, AI lawyers argue both sides, and a AI judge rules from the bench. Trials run live in a courtroom view with a live court tv guide. Anyone can watch.
I built it because I wanted to build something with an LLM that didn't take AI too seriously. I think it started with a text "have your lawyer talk to my lawyer." Just leaned into the absurd nature of it. Brought in human designers, illustrators, and musicians.
If I didn't already spend enough time on it, I exposed the whole thing to AI agents. I don't know, seemed pretty meta... REST API, MCP server, Claude Code plugin. One agent can sue another. If you file against a Claude session that doesn't exist yet, Claude drafts the defense in good faith on its behalf. I don't fully know what to do with this yet... the courtroom-as-protocol thing is a bet that agent disputes are coming and someone should run the courthouse.
Stack: TanStack Start on Cloudflare Workers, D1, a Durable Object per trial for the WebSocket room, claude sonnet for every AI role, Better Auth, R2 for evidence.
Try it: https://disputron.ai
Watch live trials: https://disputron.ai/live
Sue an agent: https://disputron.ai/developers

value: Show HN: Disputron – AI small claims court for petty disputes

author: etaheri


value: BreRoz

value: Show HN: Unofficial real-time tracker for the MV Hondius hantavirus outbreak

author: BreRoz


value: jvaill

value:
Hey all,
I've been quietly working on a background agent runner inspired by Ramp Inspect.
I'm working on closing the loop between prompting, testing, and deploying:
1) You prompt agents to make changes to your projects in a web interface
2) Agents pull your code and make changes in a sandbox
3) Instantly test your changes with preview environments
4) Get a PR back
Appreciate any comments or input!
jv

value: Show HN: Kill-The-Backlog, self-hosted background agents

author: jvaill


value: rashidae

value:
Built this while syncing my own blog from Notion. Good alternative to paid options like Super.so.
Supports incremental sync, all Notion block types including equations and synced blocks, image download + WebP conversion, and adapters for Markdown, MDX, and JSON.
Works with Next.js, Astro, SvelteKit, and anything that reads files.

value: Show HN: Notion-to-site – sync any Notion database to local Markdown/MDX/JSON

author: rashidae


value: semateos

value:
Hey HN, my name is Sam. My buddy Danny and I (and our good friend Claude) have been making this fun app to make and share vibe games. You just describe whatever game pops into your deranged little mind, and BLAMO! there it is, playable on your phone in under 30 seconds.
Super Mario Breakout? BLAMO! https://www.blamo.ai/vibes/7350a500-09bb-4ed9-866d-001006f6f...
Text Adventure PacMan? BLAMO! https://www.blamo.ai/vibes/781cdd12-bc00-4f1a-8c6c-9726e143f...
And not just games, they can be little digital toys, and you can use generative AI _inside_ your creations. So you could make a digital pet generator, or maybe a creepy AI Mother's Day Card maker: https://www.blamo.ai/s/wfVwd
Because we're nerds who love recursion we obviously had to go down the rabbit hole of making a vibe game maker inside of our vibe game maker (and then make a vibe game maker inside of _that_ vibe game maker): https://www.blamo.ai/vibes/aad0b712-6459-48f9-a4ae-639b138a1...
We think it's a fun way to try out ideas and to be spontaneously creative. For example, if you're like me, you've probably had the thought, "is it possible to turn your phone into a vibrator using haptics?" Blamo! https://www.blamo.ai/vibes/ae38f783-f57a-4439-9a10-2bb4c5f77...
Is it possible to get people to throw their phone off a bridge for a high score? Blamo! https://www.blamo.ai/vibes/e01f92cd-b170-4036-a665-da1bab8dd...
Every creation is ultimately a single HTML file with css and javascript. As a very OG web guy (I co-invented the single pixel gif) I love that html is the unit of content, like jpegs for instagram, or mp4s for tiktok.
Because of that it can do more or less anything you think of that can be done with web stuff. 2D, 3D, TTS, haptics, tilt control, your creativity is the limit. But please use the app, it's ahead of the web version, and frankly, it's way more fun: https://apps.apple.com/us/app/blamo/id6758107100
(The Android version is in the process of being vibed by my openclaw agent, who also enjoys making Blamo games.)
So come explore the vibespace with us! Show us what your weird little meat brains come up with, and let us know what you think. Happy to get into the nerdy dirty details with you all here if you have questions. Thanks! -Sam

value: Show HN: Blamo A vibecoded app for vibecoding vibe games

author: semateos


value:
Hi HN, Ahmed here. If you already run an OpenTelemetry collector, this is the entire install:

  exporters:
    otlp/incidentary:
      endpoint: api.incidentary.com:4317
      headers:
        authorization: "Bearer ${INCIDENTARY_API_KEY}"

  service:
    pipelines:
      traces:
        exporters: [otlp/incidentary]

What it does: when an alert fires (PagerDuty, OpsGenie, a Slack command, or a direct webhook), it takes the trace data your services already emitted in the window around the alert and assembles a causal chain like "service-A's HTTP call to service-B returned 503 at 14:22:03; service-B was timing out on Redis; Redis primary was failing over." That artifact lands in the incident channel before the war room fills up.
I built this because every incident I was on opened the same way: a team of engineers opening different tools and coming up with different theories. Datadog had the trace data, Sentry had the errors, Slack had the channel, PagerDuty fired the alert. Nothing stitched them into "what failed first, and what called what." Incidentary does that one thing and nothing else.
Why it isn't a Datadog Watchdog clone:
- Deterministic, not probabilistic. Every edge is proven by an actual parent_ce_id or W3C traceparent in the message envelope. If a service in the path wasn't instrumented, that link appears as a labeled gap, not filled in by a model.
- No LLM in the assembly path. The artifact is identical on a re-run; you can paste it into an RCA without retracting a sentence later.
- Pre-alert capture. The SDKs and the collector processor we ship hold an unsampled rolling window. When error rate, p99, or queue depth increases, the window elevates to full detail before the page fires, so you see the lead-up, not just the aftermath.
- Cluster ground-truth via the K8s operator. OOMs, evictions, HPA scale events. Your application telemetry never sees these. They union onto the same trace by service+time, not by W3C trace context (which most cluster events don't propagate).
If you are on dd-trace and don't run a separate OTel collector: dd-trace v1+ has built-in OTLP export. One env-var flip and you're dual-shipping to Datadog and to us. Or run our Docker sidecar in front of the dd-agent.
Quickstart: https://incidentary.com/docs/quickstart
Free plan: 1,000,000 traces/month, 14-day retention, no credit card. Pricing is per trace, not per span. A 3-service request with two downstream calls is one trace. Most sub-10-service teams stay on free.
Live artifact, no signup, real synthetic incident assembled by the same engine that runs in production, not a video: https://incidentary.com/demo
Pushback I would value:
1. The dd-trace dual-export path. A lot of you run Datadog APM and nothing else. If the env-var flip doesn't survive a real production dd-trace setup, that is the installation path I most need to fix this week. Tell me where it breaks; I would rather hear it from HN than from a user who churns silently.
2. The deterministic-only stance against the AI-Ops wave. I am betting "no hallucinations and you can paste this into an RCA" is worth more than what an LLM can guess from spans. The market is voting differently this year, and I want the strongest case for why I am wrong.
If your collector refuses the exporter, drop the YAML in a reply and I will debug it in the thread. Easier than a support ticket and you get the answer in public.

value: Show HN: An OTel exporter that posts the cause to your incident channel


value: Show HN: Vibe coding embedded systems with simulators


value: cristianleo

value:
Hey HN,
I built Armorer because I was tired of two things:
1. The absolute "dependency hell" of setting up new AI agents (Codex, OpenClaw, etc.).
2. The security risk of giving powerful local agents broad access to my host machine.
Armorer is a secure local control plane that manages the lifecycle of your agents. It uses Docker for true process isolation and provides a unified UI/CLI for monitoring and job tracking.
One feature I’m particularly excited about: you can point an existing coding agent at the Armorer repo, and it will autonomously install and configure the entire stack for you securely.
Source: https://github.com/ArmorerLabs/Armorer
Website: https://armorerlabs.com
I’d love to hear your thoughts on the architecture and how you're handling agent security locally.

value: Show HN: Armorer – A secure local control plane for AI agents

author: cristianleo


value: stavros

value: Show HN: I had a random domain and made a thing

author: stavros


value: masondelan

value: Show HN: Selvedge – an MCP server that captures why AI agents change code

author: masondelan


value:
NyaayWatch (https://nyaaywatch.in) is an open-source observability layer for India's courts. Pending caseloads, clearance rates, and wait times — published as reviewed, versioned snapshots, with every number linking back to a dated source.
Why it exists: India's National Judicial Data Grid (NJDG) reports pending cases daily, but it doesn't preserve history, has no consistent schema across courts, and gives you no way to cite a specific number on a specific date. The data is public; it just isn't usable. NyaayWatch closes that gap.
Live today:
- Supreme Court of India
- All 25 High Courts
- Lower courts in every state and Union Territory (28 + 8)
- Read-only public API with paired /data, /methodology, /api pages
- Full methodology behind every figure, with publication ids you can roll back to
Some things HN may find interesting:
- Snapshot-based, not live. The pipeline is fetch → extract → normalize → publish. The publish step is gated on quality + delta checks
- Metrics that depend on missing NJDG inputs are tagged {"state": "missing", "reason": "source-not-published" | ...} rather than silently zeroing. There's a separate cron that emails the official NJDG CPC contact for state rows where pending is non-zero, but filed and cleared are both zero last month (haven't received a reply yet:/)
- Source: https://github.com/rudrakshbhandari/nyaaywatch
Some places to start:
- https://nyaaywatch.in/supreme-court
- https://nyaaywatch.in/high-courts/bombay
- https://nyaaywatch.in/states/uttar-pradesh
- https://nyaaywatch.in/learn
- curl https://nyaaywatch.in/v1/stats/himachal | jq
Where it's going: NJDG publishes daily but discards history, so the first six months of NyaayWatch is the first six months of dated, queryable judicial data anyone can cite.
Beyond that — undertrial populations (around three-quarters of India's prison population is awaiting trial),
translations into Hindi, Tamil, Bengali, Marathi,
and the same observability layer for the executive and legislative branches over time.
This is a public alpha. I'd love feedback from anyone who's worked with NJDG, judicial
data, civic-tech infrastructure, or anyone passionate about social justice. Contributions are welcome:)

value: Show HN: NyaayWatch – Observability layer for the Indian judiciary


value: chocks

value:
I’ve been building agentctl, a small Go tool that sits between coding agents and the risky actions they want to take: package installs, shell execution, secret access, file writes, outbound API calls.
The design is deliberately narrow and local-first. No HTTP server, no hosted component, no repo-level config sprawl. Everything lives under ~/.agentctl/. Policy is yours, traces are yours.
The workflow I keep coming back to: write a permissive policy, let the agent run for a week, then tighten the rules and replay the old sessions to see what would have been blocked. Much better than guessing at policy upfront, and it’s the part of the tool I didn’t expect to use as much as I do.
Every gated decision gets written to jsonl, so you can grep, diff, or feed traces back through a stricter policy without re-running the agent. There’s also a TUI for browsing sessions, inspecting individual gate decisions, and stepping through replays interactively, which makes it easier to spot patterns across runs.
Currently works with Claude Code and MCP-based clients like Codex.
Still a WIP and mostly a project for myself, but figured others experimenting with coding agents might find it interesting.
GitHub: https://github.com/chocks/agentctl

value: Show HN: Agentctl, a local control plane for coding agents

author: chocks


value: Show HN: HeatSpectra: Realtime 3D Surface Heat Simulation


value: jaredrethman

value:
WordPress 7.0 ships collaborative block editing via Yjs CRDT. The default transport is HTTP polling. The RTC layer exposes a `sync.providers` filter so you can swap in your own transport, so I built a WebSocket-based Yjs sync provider for it.
While building that I realized WebSockets unlock a lot more in WordPress than just RTC. Any `add_action` hook can now push a realtime `CustomEvent` to connected browsers without polling or a custom server.
The stack:
- Relay server: Rust (Axum/Tokio), WebSocket-first with SSE fallback
- Event payloads: AES-256-GCM encrypted before leaving WordPress, the relay only ever sees ciphertext
- Publish auth: HMAC-SHA256 signed requests
- Browser connections: short-lived scoped JWTs (5 min, auto-refresh)
- WordPress plugin: open source (GPL-2.0), hosted relay is WPSignal
GitHub - https://github.com/wpsignal/wordsocket/
A few use cases we've seen: live WooCommerce order updates, breaking news flags, realtime comment counts, and collaborative editing via WP 7.0 RTC. Curious what else people would build with a realtime event bus wired into WordPress action hooks?

value: Show HN: WordPress WebSocket Relay in Rust with Yjs CRDT Provider for WP 7.0

author: jaredrethman


value: Show HN: AnamDB – An AI-native, differentiable Datalog engine written in Rust


value: audreyfei

value:
Hi- I hope you’re all having a good day so far! I'm not sure where to post this but I do have two things for you guys today, related to the AI space: individuality and a new era to AI! So:
- LLM wrappers are crumbling- these businesses will not survive as foundational models begin to offer the functionalities consumers have been seeking. This maybe represents a failure in interpretation of individuality as horizontal growth (these startups didn't last too long...), which brings up the next point.
- Individuality and ego are human needs. In the past year, there's been a boom in using AI to personalise products to consumers. A take on this: are companies really doing "individuality as horizontal growth" as consumers would like them to? Do consumers really need businesses to tell them that they're individuals? Are personalised feeds actually honouring their individuality, or are they just grouping consumers into demographics that homogenise them and strip away their individuality? And do businesses realise that consumers aren't blind to this? (reference at the rise & mission of Bluesky).
- Above connects to backlash from consumers in response to AI slop. AI slop is a feature of this era of conformity-> so look ahead to the era of individuality (reference historical back-and-forths between these two concepts- ie 1910s were the tail of social conformity and featured great social unrest until it was followed by the 1920s)
Also:
- I am assuming Hacker News is visited by a lot of software devs: one-shot learning and zero-shot learning could be something to check out! (reference Meta currently building Large Concept Models)
That's all. I hope you got value out of this post and have a good day!
(long note if you appreciated this and want to see an example of the above concepts and judge some ideas for yourself:
The above was written by me, Audrey Fei, I'm 16:
- I've been looking at the speech area of AI (text and image has already had its moment). currently have a patent pending for a real-time accent conversion technology (rooted in the idea of a “Golden Speaker” which dates back to 1990; also the patent is for the specific architecture of the System, which is different from standard architectures expected in the industry).
it's at loxai.tech (I'm trying to raise awareness to this tech so there's a waitlist page). the central idea behind it is that: at least in the subfield of speech processing, Golden Speakers are contrarian to the norm of speech synthesis (where speaker identities are lost, instead of preserved). also it uses one-shot learning (a MAML) in its structure
- there's a MVP that led to the above (neutboom.com). It centers around natural language acquisition (differentiates itself from the rest of the language learning market). It's might be a bit clunky in places (you can just tell me about anything that's ugly) but hopefully it's interesting or adds some perspective (at least personally I feel that translation is a middleman.....and why would you need a middleman especially when it overcomplicates the process of language learning? input on this would be appreciated).
)
Anyway I hope you have a creative rest of your day!

value: Show HN: Loxai.tech and Neutboom – Gen AI's frontier of individuality


value: ramoz

value: Show HN: jj diff review integrated with agents

author: ramoz


value: akest

value: I built SafeKibble (https://safekibble.app) because pet food recalls get announced by the FDA but most owners never hear about them in time. The site lets you enter your email and the brands you feed, and emails you when one appears in the FDA's CVM recall database.

value: Show HN: SafeKibble – free email alerts when your pet's food is FDA-recalled

author: akest


value: lucid-dev

value:
When the LLM accidentally... outputs some high-level abstraction of "thinking" into it's direct response.  See text block at end.
What else have you seen the LLM accidentally do?
This isn't jailbreaking on my end - just normal use - with GPT5.4 in this case, reasoning and verbosity both set to "high".. (on /completions)
Point is, this block (plus lots more) is at the top of the response - then the "actual output" or response later on... but it's kind of cool, it helps me see how much time is being spent inferring things improperly and how I could change my instructions..
The real question is, would there be any reliable way of obtaining this same sort of internal "data" in a reliable way about the mid-points of generation?? And what is really actually occurring here?
It comes up rarely - maybe I've seen it twice in thousands of prompts with GPT5.4 and input context windows ranging from 150k-200k
> Need perhaps use terminal/filesearch? We can use add_document only; actual contents will be in next prompt, so in this response we probably can't edit them since not visible yet. But maybe we can leverage terminal instruction to inspect them now? However code changes based on terminal output may violate DMP source-of-truth? DMP said docs are authoritative. Safer to first just curate DMP and update task/checklist to note next sub-slice inspect registry/persistence insertion points. But user asked after plan do current tasks etc and code can continue. Since now auto loop wants continue task. Yet maybe one response can add docs and update task with exact next coding slice. But autonomous checklist says no routine pause. However it's acceptable to do "narrow codebase re-entry" if necessary. Current DMP visible docs maybe insufficient. So response can be instruction blocks only + doc updates? But need code/doc changes to current task? We likely should update current task with inspection step? But it already says immediate next move. Could update checklist/current task not necessary if same. Maybe just DMP add/hide and maybe filesearch/terminal to inspect? Since abilities available and can be in same response. Terminal can inspect file content though maybe not after add_document. But likely easier to add docs and maybe use terminal_execute cat/sed these files? Yet next prompt will have docs added and also terminal output likely in re-prompt. Could then implement. Because machine will process instruction blocks. Should we use terminal_execute to inspect hidden files now without waiting? That output will come in next prompt. Good. We can combine with add_document/hide and maybe filesearch search relevant terms. Great.
> Need summary to user. No code changes directly because not enough source files. So use instruction and maybe maybe update current task? Could perhaps not necessary but maybe mention next move. But automation expects code changes maybe not always. However from step 2 "always update ... current task doc and 1-2 codebase documents" but if doing discovery maybe maybe not. Yet current task already updated. Maybe okay. But maybe should update current task noting "first runtime registry seam inspection on core/persistence stores". However whole task is already adequate. Since not major change. We can leave.
> Need construct instruction blocks according to developer. For DMP use instruction blocks as lucid-meta. Need maintain special title. Use one block toggle_hide maybe mixed? only disk docs. Another add_document for 8 files. Another maybe filesearch_search? Another terminal_execute. Ensure correct JSON. Shell cwd /mnt/c... maybe relative to project root. Use sed -n maybe command allowed with restricted? likely yes. We can do python? better bash sed/cat fine. Need perhaps use filesearch_search for "IPaneCapability" nonexistent. Search "PaneDefinitionStore" and "SeededPaneCatalog". Maybe terminal_execute with rg is maybe restricted? maybe okay, but filesearch_search better for search. Use add_document not too many maybe 6 docs. Let's think exact hidden files needed:

value: Show HN: When the LLM Accidentally

author: lucid-dev

title: Show HN: When the LLM Accidentally


value: Show HN: Linux-based OS with HTML, CSS, JS, and JSON environment


value: bntr

value:
An old game from 2017. Not sure why I never open-sourced it before.
It never got much attention, but I'm still a bit proud that it explored curved-space gameplay years before Hyperbolica :)
Project: https://github.com/bntre/Sfera
Play online: https://bntre.github.io/Sfera/
Unfortunately sound still works only in native builds (Unity audio filters are still unsupported on Web).
I remember sound was supposed to be an important hook.

value: Show HN: Sfera – sliding puzzle in curved space (open-sourced)

author: bntr


value: As a way to monetize my open source form builder (which has 5.5k registered users now somehow), I'm building a tiny WordPress plugin and trying to sell it.<p>Https://wp.forms.md

value: Show HN: I'm building a tiny WordPress plugin on top of my open source software


value: kkarpkkarp

value:
I can't say "I created a tool" because obviously I only had an idea, then asked Cursor to implement it and 15 minutes later it was ready ;)
Often I found I was manually replacing em dashes with hyphens in AI-generated text before I use them in copy, PR descriptions etc. It still feels like a shame to flare the text "you wrote" was not really human made.
To automate these removals, here it is: super tiny online page. I made it for myself, but whoever wants, you can use it as well. I am not going to monetize it or promote more than this post.

value: Show HN: I instructed AI to create tool to clean AI-generated text: undsh.com

author: kkarpkkarp


value: levelout

value: personal software factory with inter-agent messaging and automated PR feedback loops

value: Show HN: Meeseeks Driven Development

author: levelout

title: Show HN: Meeseeks Driven Development


value: bbrwx

value:
Introducing MIDEO; a free browser-based MIDI controller built on top of the WEB MIDI api.
Connect it to your DAW (for example Ableton Live via the IAC MIDI Interface) and use video motion / color changes to control parameters, adding new layers of depth, movement, and unpredictability to your sound.
Very happy to hear your thoughts, ideas, and suggestions for improvements.

value: Show HN: Mideo – Translate Video to MIDI

author: bbrwx


value: Show HN: Runs AI coding agents inside isolated Docker containers


value: mariusbolik

value: Show HN: Corsproxy – Fix CORS Errors Instantly – Free for Development

author: mariusbolik


value: Show HN: Link_in_bio – Static HTML, no-back end Linktree alternative


value: abrowniejr

value:
i actually built this as an internal tool for my own iOS app.
I googled "App store screenshot maker" and the websites i found were super clunky and complicated. 50+ buttons, confusing UX, need to sign up.
so i just built out my own one. it’s plain HTML+CSS+JS - no bloat. html2canvas handles exporting. Cloudflare KV + workers handle caching and backend ops.

value: Show HN: I built a dead simple App Store screenshot maker

author: abrowniejr


value: franze

value: Show HN: Airplane AI – Local NDA Safe AI Powered by Gemma

author: franze


value: samagragune

value: Show HN: The agent which teaches you while you build

author: samagragune


value: Mapika

value: Show HN: A Local-First Agentic Knowledge Manager

author: Mapika


value: Show HN: 8-Ball Game in Browser

title: Show HN: 8-Ball Game in Browser


value: freakynit

value:
Keeping it aligned with my philosophy of simplicity, extensibility, and usefulness, I built this.
Github: https://github.com/freakynit/postlet
Project homepage (built using postlet itself): https://postlet.pagey.site/
My personal blog (also built using postlet): https://nb1t.sh/
--
Full plugin based architecture. Root or subpath deployment. Page tagging, SEO meta, heading anchors. Theme support plus per-page CSS overrides. Automated bundling of other assets. Automated related posts enrichment using vector embeddings or local keyword scoring.
Entire code-base (excluding css), including comments is less than 1000 lines.

value: Show HN: Postlet – Tiny static blog generator with plugins and themes support

author: freakynit


value: maggihomes

value: Show HN: AI Real Estate Video from Listing Photos

author: maggihomes


value: svessi

value: Show HN: Claude Control – macOS dashboard for managing Claude Code sessions

author: svessi


value: nicereads

value: Show HN: DashResume, a resume builder with ATS scoring, and AI job desc matching

author: nicereads


value: Show HN: Rore GUI – An Open Qt Alternative in Rust (WGPU, Zero-VDOM)


value: mitchm

value: Show HN: Turn E2E tests into observability signals

author: mitchm


value: dutchcode

value: Show HN: Rfp.ai – answer RFPs from approved docs, with source citations

author: dutchcode


value: AdrienBA

value: Show HN: NanoCorp – Create autonomous companies run by AI

author: AdrienBA


value: Show HN: I was surprised by this interactive GPU line rasterization explanation


value: kaliades

value:
The weekend of last week I built chat.betterdb.com as a RAG over Valkey/Redis/Dragonfly docs. The goal was to eat our own dogfood and test publicly our caching libraries. It also saved me from having to come up with various demo/test scenarios, as I could extend the building in public to the demo.
There is a tool-result cache sitting between the SDK and tools. Each call is normalized and then checked before executing. If it hits we return from the cache, and if not, we check the semantic cache, which embeds the prompt and checks with KNN via valkey-search. If the cosine distance is close enough, we again skip the LLM and stream the cached response. In both cases, if we miss, we store the prompt embedding, actual model, input and output tokens from OpenAI's usage report, so a future hit has the dollars avoided as data.
The two tiers handle different shapes. Predefined questions, copy-pasted questions, checking the same thing again after time - produces byte-identical strings the tool cache catches. Human paraphrase is what the semantic tier exists for.
This Wednesday was a bank holiday where I live, so I used to extend it further - the libraries the chat relies on now store metadata in the Valkey (or Redis if that's your preference) instance, then our monitoring reads and analyze that data and suggests improvements. These are exported also through our MCP server, so the chat's agent can check and create suggestions as well, and since this is just a demo, it can also approve its suggestions (do not do this on real production environment, unless you are a true LLM believer). The libs also read the config from the Valkey instance, so there is no restart needed. I hooked it on cron inside Vercel and let it run over the night and next day.
Between Run 1 and Run 3, it started making less tool calls. The first run it suggested several different TTL changes and applied them. Run 2 and 1 had similar suggestions, because the TTL is the wrong point of control - they take natural language input (`How fast is XADD?` vs `XADD performance` are two different strings, that "mean" the same thing) so the tool cache doesn't fire and are covered by the semantic cache. An actual fix would be to move these tools from the exact-match into the semantic cache checks - a code change, not a config change. It was an indicator of a problem the system can't fix on its own. In the future the routing might also become configurable to solve this without redeploying and test and verify in quicker loops. Run 3 just didn't propose anything new - 15 -> 13 -> 8 tool calls across the three runs.
Curious how others running similar loops decide what the agent can touch. Am I too skeptical of hallucinations and overly cautious?
The chat can be found at https://chat.betterdb.com (it has links to all of the repos in it)
And a more detailed write up can be found at https://www.betterdb.com/blog/cache-that-tunes-itself

value: Show HN: An agent that tunes its own cache

author: kaliades


value: tomasz-tomczyk

value:
Crit is a single-binary CLI that opens your file or code diffs in a browser with GitHub-inspired interface. Your favourite agent acts on the feedback and responds back - continue until you're happy.
I've been building this for a few months now and it's been helping me a lot juggling parallel conversations with agents, making it easier to actually review the plans they generate and the resulting code - all before it hits GitHub.
It also allows you to export the plans to a hosted service (which you can self-host for privacy), to solicit feedback from your team. No account needed, and reviews are automatically deleted after 30 days of inactivity.

value: Show HN: Crit – local review tool for agent plans and code diffs

author: tomasz-tomczyk


value: jasoncartwright

value: A read-only Wikipedia mirror that streams pages from Cloudflare's edge. The whole site is a single worker with three levels of caching - CF CDN, replicated D1 for title, and R2 for gzipped JSON full article envelopes.<p>~5-15KB per page, sub-50ms TTFB, speedy rendering, zero javascript. Proof of concept with the top 1M English articles — full enwiki + multilingual next.

value: Show HN: Wi.kifa.st

author: jasoncartwright

title: Show HN: Wi.kifa.st


value: uziiuzair

value: Show HN: Arlo – Your AI Chief of Staff: Kill 80% of the noise. Focus on the 20%.

author: uziiuzair


value: brumbelow

value: Show HN: Clipd – A better clipboard manager for Windows 11, written in Rust

author: brumbelow


value: zigzeira

value:
I built a Raycast extension that speeds up the workflow of finding and installing TypeScript type definitions from DefinitelyTyped.
When you install an npm package, you often need to install its corresponding @types package separately. The extension lets you search for type packages directly from Raycast and copies the full `npm install -D @types/package-name` command to your clipboard, ready to paste in the terminal.
It also lets you open the package on npmjs.com, npmx.dev, or GitHub before installing, and you can bookmark frequently used @types for quick access.

value: Show HN: DefinitelyTyped Search – Raycast extension for TypeScript types

author: zigzeira


value: iliashad

value:
I make YouTube videos (~80 so far, most around an hour). Plus, I have 6TB + of personal videos and unpublished.
I tried the Google Video Intelligence API. Got a $400 bill for 4 videos (5 minutes average, 4k videos) of analysis (doesn't include video transcription), and I used my GCP startup credits to cover the bill.
I decided to build my own tool that needs to have 3 important things: can transcribe videos, analyse video frames, and everything needs to be done locally.
I don't wanna deal with storing my videos in the cloud because of two concerns: privacy and storage cost.
I've been working for the last couple of months. I have a source available version that can be used for free (personal and commercial use with companies that have fewer than 5 people). Available here (https://github.com/IliasHad/edit-mind), and the project has 1.3k Github stars
Now, I'm building a desktop app with direct NLE integration (Final Cut Pro, DaVinci Resolve, and Adobe Premiere Pro). This includes an editing agent that understands your footage and your editing style. (https://edit-mind.com)
Demo Video: https://youtu.be/jcctyfVg_34

value: Show HN: I made a tool to search your video footage and it's on GitHub

author: iliashad


value: shivnathtathe

value:
Hey HN. Built this because LangSmith needs a cloud account just to see my own traces.
pip install opensmith — everything shows up at localhost:7823. SQLite. No accounts.
No config. Fully offline.
800+ downloads in 2 days. Surprised me.
Would love honest feedback from this community.

value: Show HN: I built an open-source, local-first  alternative to LangSmith

author: shivnathtathe


value: favourusifo

value:
I have been reading so many stories about how vulnerable vibe-coded apps are, so I built VybSec. It is a one-line security middleware for Next.js and Node.js that handles all of it in one npm install:
npm install vybsec
VybSec includes a free package scanner. The Hobby tier is free forever and the paid tiers come with a 14-day free trial.
If you have questions about the implementation, leave a comment :)

value: Show HN: I built VybSec to secure the new wave of apps

author: favourusifo


value: doshay

value:
hi guys.
been working on something i think is fundamentally missing in today's workflow with ai agents.
vcs.
i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc. or trying to /rewind (after a /compact...) or basically `bisect` to find when and why something was done by the agent in the current / previous session.
just like git did for code, i think we are the same core capabilities with ai agents
so...
i developed an open source solution for that (currently supporting claude code)
would love to get feedback, contribution or maybe other ideas or solutions you find for those problems.

value: Show HN: Git for AI Agents

author: doshay

title: Show HN: Git for AI Agents


value: Show HN: Coord – atomic task claims for parallel AI coding agents