value: multimillion

value:
We built BrowserCode, a FOSS web app to run TUI agents (Claude Code, Gemini CLI, others coming soon) fully in the browser, locally.
To use BrowserCode, you'll need to login to each CLI with the corresponding login, i.e. with your Anthropic account or API key. All the data and execution stays completely local to the browser and it's persistent across sessions thanks to a disk backend based on the Origin Private File System API or IndexedDB.
This is running the unmodified Claude Code (and Gemini CLI) command-line tool in browser using BrowserPod (https://browserpod.io), a WebAssembly-based code sandbox that runs Node.js, python, git, bash and many other command line tools.
You are welcome to fork / modify BrowserCode and integrate real AI agents in your web application, running client side.
This is a preview release, so please try and break it! Please report issues on GitHub and star the repo if you like our work. Your support will help us push this project forward.
For questions or feedback also please consider joining our Discord! https://discord.leaningtech.com

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

author: multimillion


value: yannranchere

value:
Hello HN!
If you want to connect your agent to a database (say, to build a data analyst chatbot or any kind of agentic app) today you have 2 options: an SQL MCP server or a semantic layer.
SQL MCP is the easiest path to setup, especially if you also have a .md knowledge base which the agent can update. It gets quite messy quickly though, especially if there's many interactions or DB is large. Generated SQL is hard to review if you want to understand where the numbers came from, and related queries can be hard to align and compare.
The  natural alternative is a semantic layer, which is an inventory of what data is available/useful (data models) and an interface for querying it using a structured DSL — usually a list of measures, dimensions, filters, with joins etc. handled under the hood.
When we needed a semantic layer at Motley for connecting to our customers' data, we first settled on Cube with custom wiring for multi-tenancy and updating the models on the fly. We quickly hit some limitations which led us to realize existing semantic layers just weren't built for the purpose: they're still a part of the BI world where you want an efficient backend for an essentially static set of human-curated dashboards, whereas agents need to iterate their way to the answer, learning in the process. That's when we built the first version of SLayer, which is now open-source.
Using either SLayer MCP or CLI, agents (and humans) can:
- Explore models, run queries, connect to multiple databases
- Edit columns/measures or create new ones
- Create custom models from SQL or from a query on other models
- Learn from interactions: save and retrieve natural-language memories linked to models, columns or queries, to form a knowledge base
Agents evolve the semantic layer, reuse the results of past interactions, and make fewer  mistakes going forward.
A few more features:
- Auto-creation of models from introspecting your DB schema for a warm start
- Embeddability — doesn't need a server running
- Python client for doing data analysis with dataframes
- Schema drift detection and handling
- Expressive DSL with compact, natural representations for arbitrarily deep multistage queries, custom aggregations, time shifts, combining metrics from multiple models, and other features that are tricky to get right in raw SQL
On the roadmap: access controls, caching, and more.
Repo: https://github.com/MotleyAI/slayer
Docs: https://motley-slayer.readthedocs.io/en/latest/

value: Show HN: SLayer, a semantic layer maintained by your agent

author: yannranchere


value: davidbuniat

value: Show HN: Hivemind turns agent traces into skills and shares with your team

author: davidbuniat


value: fantata

value: I'm a solo dev in Norwich. I've always loved quizzing, and wanted a wordle for quiz, so this is my attempt. Anonymous play and leagues with friends. Weekly News quiz on a Friday for members (UK focussed news quiz).<p>Stack: Laravel 13 + Livewire 4 + Alpine + Tailwind, Docker on a single DigitalOcean droplet behind Caddy.

value: Show HN: Fast Five Quiz – a daily quiz (5 Qs, no signup)

author: fantata


value: Show HN: Who Assists the Assistant? Russell's Barber Paradox-AI Support Systems


value: plaintosapp

value: Show HN: Free tool to see how much AI bots are costing your site

author: plaintosapp


value: arstep

value:
Hi folks,
I would like to share with you a project I built, which took me about 2 months as a side project to build.
I am a solo dev, and mostly not using AI for my projects, as I want to keep the craft and actually learn stuff, while I am building the software.
The original idea was to build a tool, where I can provide a Linkedin link of a post or a comment and some text as an "anonymous" comment, the tool should take it and post it from some "hidden" account, as sometimes I feel I would like to comment under something but the idea that a lot of my colleagues and people who know me might react in a very different way, and it might have a weird consequences.
After wrestling a while with Linkedin's API and it's super heavy limitations, I decided to give up on the idea and build an anonymous webapp instead, where people can bring anything from any other platform and feel free to discuss things openly without the fear of getting "caught" and bad consequences.
The DescreetVoice is a privacy first place for open but professional discussions. There is no tracking, just the conversation.
If anyone is interested in the stack, here it is on a very high level:
Frontend is built with React TypeScript, plus Vite bundled with Bun.
The backend is mainly Python with FastAPI. I initially wanted to go with Rust, but as I am not that familiar with frameworks and the language itself, decided to keep that for the next project, as here I wanted to bring the software to live asap.
There is also some Traefik as proxy, rate limiting etc.
I also use Resend for emails, it's pretty cool. (AWS SES is still in the sandbox, will probably migrate, when it's out of it).
As a DB I use PostgreSQL (pretty much standard nowadays in the industry).
On the deployment side everything is dockerized and running on the super modest AWS EC2 instance (small machine with 2GB RAM and 2 virtual cores).
I am very curious to hear your ideas and suggestions and also see how much traffic and load can this tiny machine handle. Would be also great to hear about your user journey's and suggestions for improvement of the UI and UX.
Thanks for your attention and have nice one!

value: Show HN: I built an anonymous social platform after fighting with LinkedIn's API

author: arstep


value: OlyEvans

value:
Every app in macOS currently has a different corner radius and as a designer this is something that has bothered me for a long time. Now with Liquid Glass's design language introducing more corner radii than ever before it's a mess that no 3rd party apps have solved before.
The dev process was challenging as this is my first solo dev project and it ended up more complex than I expected (with bricking my MacBook in the process while trying wild ways to modify macOS files). In the end I created something stable and safe but it does require SIP to be disabled and a custom boot command (instructions of how to do this are in the app and only take about 5 mins if u haven't done already).
Liquid Radius makes 95% of apps (including 3rd party apps) have consistent corners vs the less than 35% from default Tahoe.
Curious what you guys think about the tradeoff in security for a visual tweak like this. For me it's a no brainer but i realise i don't think like most people.

value: Show HN: Liquid Radius – Unifies macOS Tahoe's inconsistent window corners

author: OlyEvans


value: aminedhuibi

value: Show HN: I scraped 17 months of "Who is hiring?" – what 6,539 jobs require

author: aminedhuibi


value: garrypettet

value:
Objo Studio is a new development environment for building desktop and command line apps. It has a visual designer, a debugger, a compiler, and a modern BASIC-like language called ObjoBasic. The aim is simple: make it enjoyable to build real applications for macOS, Windows and Linux and learn how to program.
I've been working on Objo Studio in one shape or another since about 2019. I've always loved tools that let you move quickly from idea to working prototype and that abstract a lot of complexity and get out of your way. This has been tried before (VisualBasic, Xojo, etc) but have either been abandoned, become expensive or lost focus on hobbyists.
The whole stack is written in C#. There's a custom stack-based VM that is roughly on-par with Python for speed but this is not a high performance tool. It's an all-in-one IDE for visually developing cross-platform desktop apps. It tries to make it simple for users, abstracting runtimes and libraries to help newcomers learn but also let them thrive.
Yes I know lots of people think writing code is dead and we should all just vibe code everything but I think the world still needs programmers and I'd like to make it easier for newcomers and young people to learn the concepts of programming.
You can use Objo Studio for free forever if you just run locally. There's a fairly priced license to publish apps to run on other computers. It's free for education always.
Feedback is very much welcome. Be gentle, I'm a radiologist by profession!

value: Show HN: Objo Studio

author: garrypettet

title: Show HN: Objo Studio


value: PengSpirit

value: Show HN: Fulfillment MCP – one router contract, swap the printer

author: PengSpirit


value: Show HN: Learn how AI benchmarks cheat

title: Show HN: Learn how AI benchmarks cheat


value: isjustintime

value: Show HN: Tokémon – a Pokédex for LLMs that got out of hand

author: isjustintime


value: polyphilz

value: Show HN: Glance – Local Git diff review TUI, ported from VS Code

author: polyphilz


value: billtonium

value: Show HN: QuickAcuity – visual acuity screening from your phone

author: billtonium


value: ciwrl

value: Show HN: TikTok but for scientific papers

author: ciwrl


value: Show HN: The Extensions Scraping Your AI Chats


value: patriceckhart

value: Show HN: Zot coding agent now supports DeepSeek

author: patriceckhart


value:
LLMs can "learn", maybe. That doesn't mean we offload learning.
More than a decade ago I had built paw-on-es6 to help folks get hands-on with ES6 (ES2015). It did its job.
I am now introducing ESlabs. It covers every major feature from ES2015 through ES2025.
You write real code in your browser, run exercises, and actually internalize what the features do and why we need them in the first place.
The irony isn't lost on me: building a tool to help humans learn, in an era where the temptation is to just use an agent skill!
Give it a spin. Break things. That's the point

value: Show HN: ESLabs

title: Show HN: ESLabs


value: ryanrasti

value:
Every app I've built required the core data model to be rephrased four times: schema, ORM, controller, DTO. The "API" layer was just translation between them.
I wanted clients to compose against the schema directly, without coupling the public API to it. What I found:
- Prisma / Drizzle provide an ORM (but are server-only and still require a controller + DTO)
- PostgREST / Hasura / PostGraphile auto-expose the schema (but at the cost of tight coupling and without a first-class way to express complex logic)
- GraphQL removes nesting boilerplate (but clients don't have rich operators: filtering, aggregation, raw joins)
With Typegres:
1. Postgres tables become TypeScript classes, methods compile to the SQL you'd expect, and the underlying schema is yours to refactor.
2. Clients compose typed queries against the methods you choose to expose. Sandboxed via object-capability-based RPC.
3. `.live()` allows clients to subscribe to a query and get fresh results when underlying data changes.
Try it in your browser: https://typegres.com/play
Code: https://github.com/ryanrasti/typegres
Developer preview. Genuinely interested to see if this solves problems you've had.

value: Show HN: Typegres – pg tables as TS classes, sandboxed client SQL, live queries

author: ryanrasti


value: novateg

value: Show HN: Design.md and Skill.md Generator Chrome Extension

author: novateg


value: adamhsn

value: Show HN: I built a mobile website builder on the Claude Agent SDK

author: adamhsn


value: innovationlab

value:
Hi HN,
I built MessyData as a small online utility for turning messy data into clean tables because I repeatedly do this.
I use ChatGPT (or other AI) to help me interpret and format data into a table. Wondered if others who don't use AI directly would need this.
And can then copy the result or download it as CSV.
It is an MVP, so I’m interested in:
- What kinds of messy data people might need it to handle?
- Where the output breaks or could be improved?
- If CSV/table export is enough, or if XLSX/Google Sheets export would be more useful?
- If it's worth expanding?
I'm also looking to give transparency that it uses AI, which I haven't done yet, if that's something that's needed for trust. Meaning, will there be people who don't care and will be glad of this tool; or will it be better to cater to those who would be more concerned. (I'm leaning towards the latter, and personally would encourage it.)
Welcoming any feedback, critique, or examples of how this could be useful.

value: Show HN: MessyData – turn messy data into clean tables/CSV

author: innovationlab


value: scarsam

value:
Hi HN. I built Inspection Credit because the inspection-response window in a home purchase is one of the worst-designed parts of the entire transaction.
You get a 60 to 90 page inspection report at 11pm. You have 5 days to respond. Half the report is photos of outlets. A third is non-issues. The 3 or 4 things that actually matter are buried on page 47 next to a missing smoke detector. Your inspector legally cannot advise on negotiation. Your agent makes commission when you close, not when you walk. So you decide, alone, in a panic.
The product takes the PDF and returns a packet with the negotiable findings, a credit-request letter, an escalation script for seller pushback, walk-away guidance that references your state's standard inspection-response form, and a UPL-defensive disclaimer. $79, refundable if the report turns up nothing worth negotiating.
A few engineering notes:
(1) The aggregator sites (HomeAdvisor, Fixr, Angi, HomeGuide) disagree by 30 to 50 percent on the same repair scope. I pulled current 2026 pricing for 67 inspection-finding categories from 3 to 5 sources each, took the median across them, and stored `last_verified` plus source URLs per entry so the data is auditable.
(2) Replaced 4-region BLS CPI cost multipliers (range 0.93 to 1.06, basically useless for skilled-trade pricing) with state-level BEA Regional Price Parities plus 25 metro-zip overrides anchored to the RSMeans City Cost Index for HCOL metros. Manhattan and SF land at 1.65x national, Seattle at 1.38x, the Southeast at 0.95x. The default 4-region CPI under-quotes Seattle construction labor by 25 to 40 percent because the consumer basket gets dragged around by housing rents and groceries, not actual trades.
(3) An asymmetric override gate on the model's cost estimates. Within plus-or-minus 30 percent of the verified value, keep the model (it has PDF context the static entry doesn't). Outside the band, snap up if the model under-priced, but keep the model if it over-priced up to 10x. Most over-pricing turns out to be finding-scope bundling (the model prices "carport: open wires + non-functional GFCI + extension cord wired into a switch" against a GFCI-only entry), not hallucination. The first symmetric version was snapping down on perfectly reasonable bundled findings.
(4) A 4-reviewer-agent feedback loop during prompt iteration. Content reviewer, WA real-estate attorney, PDF designer, veteran Seattle buyer's agent. Each surfaced different failure modes across three iterations. The lawyer agent specifically flagged the UPL-exposure shape of the early drafts (under WA General Rule 24, drafting bespoke contractual language for a third party is regulated even when wrapped in a disclaimer), which led to reframing the walk-away page as a talking-points memo for the buyer's licensed agent rather than a fileable termination notice.
Stack: Next.js, Neon Postgres, Drizzle, Resend, Stripe, Anthropic batch API for the 50 percent discount, react-pdf for the deliverable. About a week of focused work for v1 packet quality, plus another two days on the cost-data verification.
Sample is free. Email yourself a real packet from the landing page (no card, no signup) if you want to see what the deliverable actually looks like before deciding it's snake oil. Happy to answer questions about the prompt iterations, the data work, the regional multiplier methodology, or the legal-defensive framing.

value: Show HN: Inspection Credit – read your inspection, draft the negotiation

author: scarsam


value: max-roma

value: Show HN: Mimik – open-source local-first alternative to Scribe and Tango

author: max-roma


value: Show HN: Claude tournaments a Unity WebGL scene across parallel islo sandboxes


value: degu-temesgen

value:
Due to the recent conflict in the Middle East, my boss half-laid me off (told me not come to work but didn't officially fire me). I had free time to spend or waste.
Spent about 4 weeks to build this open-source tool which holds the flag for the agent as a service move. I wanted it to be simple and easy that small businesses can build an AI agent for their service in natural language using the domain knowledge and data they have.
It can be used between a deploying a booking appointment agent on Whatsapp to actually selling a real stuff; as the tool allows agents to take Stripe payment. WhatsApp and Telegram are best spots to deploy. Token consumption is fair compared to OpenClaw, I recommend using DeepSeek as the provider. Use Claude if you are selling something expensive!

value: Show HN: AaaS – to build and deploy business AI agents to messaging apps in NL

author: degu-temesgen


value: samdsgn

value: Show HN: SyncBank – Self-hosted bank sync for EU banks

author: samdsgn


value: pkacprzak

value:
Add the bot to private or group chat: https://t.me/ChessvisionAiBot
Join Telegram channel: https://t.me/chessvision_ai
Bot's page: https://telegram.chessvision.ai
What it does:
- Recognizes chess positions from images
- Provides engine evaluation, hints, and links to external analysis
- Finds games the positions come from and videos explaining the positions
- You can save positions directly to your Library and study them

value: Show HN: Telegram bot that analyzes chess positions from images

author: pkacprzak


value: abdik

value: Got into YC interview recently and built this to practice, it's been helpful.<p>Sharing, so it can be used by others well. Good luck everyone!

value: Show HN: YC Interview Simulator (Voice of Garry Tan)

author: abdik


value: ebrahimpleite

value: Show HN: HiveTerm – Workspace for Claude, Codex, Gemini and your dev stack

author: ebrahimpleite


value: WasimBhai

value: Show HN: Rapunzel – a tree-style tab terminal emulator for Codex Claude Gemini

author: WasimBhai


value: sastra

value: Vibe coding is great at producing bugs after all.

value: Show HN: I made an app full of bugs

author: sastra

title: Show HN: I made an app full of bugs


value: mounnar

value: Show HN: Sipsa Inference – lossless serving at 50% off

author: mounnar


value: bolshchikov

value: Show HN: Agentic productivity platform for high perfomers

author: bolshchikov


value: shanselman

value: Show HN: A geocities inspired place for your vibed tools

author: shanselman


value: jeeybee

value:
PgQueuer is a Python job queue that uses PostgreSQL for everything — queue
storage, locking, notifications. No Redis, no RabbitMQ, no separate broker
to operate. If your app already has Postgres, you already have the broker.
After ~2 years and 26 minor releases, 1.0 ships today as the first stable
release. Strict semver from here on.
Thanks to everyone who contributed and left feedback!

value: Show HN: PgQueuer v1.0 – Python job queue using only PostgreSQ

author: jeeybee


value:
Hi. I’m a high school student studying for my GCSEs. I was using Google Antigravity heavily for my side projects, but I kept hitting the usage limits, and getting random "agent terminated" errors. So I decided to try build my own version of the IDE. I love the UI, so I copied it as accurately as possible, and then hooked up some logic into it, including the INCREDIBLY finicky webcontainer api.
I tried to keep it super lightweight, no build steps, or dependencies, and now that its open source, I'm hoping people can build things on top of it that arent possible with closed source tools, like complex custom agent workflows.
Some screenshots: - https://github.com/ab-613/OpenGravity/blob/main/examples/scr... - https://github.com/ab-613/OpenGravity/blob/main/examples/htm...
What it's made from:
- Pure Vanilla JS: no react, vue, or build step. Built entirely in plain HTML/CSS/JS to keep it super lightweight.
- WebContainer API and xterm.js: Instead of faking a terminal, I (after much pain) hooked up the WebContainer API so the AI agent has a real, in browser linux environment to run shell commands, install dependencies, and edit local files.
- BYOK (Bring Your Own Key): API key ALWAYS stays in localStorage.
Whats currently happening:
- It works, but it's an alpha. The AI can proactively start projects going properly and edit files, but because I built this over a few days before my exams, a lot of the UI dropdowns and buttons are currently just hardcoded placeholders.
- I’m open sourcing it early because I think the foundation of a Vanilla JS + WebContainer IDE is really strong, and I'd love to see where the community takes it while I'm doing my exams.
- Live demo: https://opengravity.pages.dev (Zoom out to 80% if not full screen. It will prompt for a gemini api key on load). Start by uploading a folder, then you can fiddle with the terminal and agent, and see how it goes!
Would love to hear feedback on the code, the WebContainer integration, or how to improve the agent loop!

value: Show HN: OpenGravity – A zero-install, BYOK vanilla JS clone of Antigravity


value:
Coding agent management is all the rage right now, and many tools are being created to fill the gap.
As a power user for all tools I've used since I've started my software engineering career, I've always taken the time to test multiple tools thoroughly before deciding on one, and an agentic manager was no different.
I've tested many tools, but ultimately landed on Agent of Empires (AoE for short). Why ? Because it's fast, the development is active and it's feature complete, and easy to contribute to.
So I did (contribute). In my day to day workflow for my job, I need the ability to start agent sessions against multiple repositories, and while AoE had basic support for it, I spent some time extending it to have full project support which has just been merged! (PR #974, more optimizations coming in the next release) With it, each repository get its own worktree and sandbox but the agent can access them all, which makes it ideal for organizations with separate repositories for frontend, backend etc ...
I'm now trying to contribute actively to AoE and we would love more feedback!
Many more features and improvements coming soon too!
https://github.com/njbrake/agent-of-empires

value: Show HN: I've implemented multi-repo workspace support in Agent of Empires


value: aadyachinubhai

value: Show HN: n8n like workflows for AI agents that control a real VM

author: aadyachinubhai


value: mnexa

value:
We were building an agent system and wanted email as a trigger. We decided to take it out and made it a standalone service.
The primary email features we wanted and used for our own agent system:
1. Email threading stays consistent with agent conversation threading
2. Human in the loop review for outbound emails (especially during testing phase)
3. Quick onboarding/offboarding email addresses for agents within minutes
4. Websocket for local agents and at-least-once webhook delivery for Cloud agents
Not yet: DMARC (only SPF/DKIM today), scoped API keys, HA/multi-region (single VM + single Postgres), app-layer email data encryption, compliance attestations (SOC 2/HIPAA).
GitHub: https://github.com/Mnexa-AI/e2a
Hosted: https://e2a.dev/
Appreciate any feedback / contributions.

value: Show HN: E2a – Open-source email gateway for AI agents

author: mnexa


value: degutemesgen

value: Show HN: It's like Fiverr but for AI agents – Platform and Open-source kit

author: degutemesgen


value: spectry

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

author: spectry


value: Show HN: Compiled an archive of copium content for SF Bay Area engineers


value: pantherolive

value: Show HN: Route optimization API that solves fleet planning as a single problem

author: pantherolive


value: uniqid

value:
Hey. Just wanted to show-off my project built with the help of AI/LLMs and share my experiences and clear myths I keep hearing and seeing about how AI will take over everything and everyone.
I have over 10 years experience in software development so I guess I know a thing or two but of course people are free to form their opinions, these are mine. And they become much more apparent while working on Origami.
- Coding with help of AI is not a one-stop shop, nor can you one-shot prompts for anything that can be called worth. Obviously a project of this magnitude is substantially faster to get working but still... lots of working nights and weeks spent on a having something people can use and enjoy and that feels complete.
- Software architecture is the most important skill to have and develop if you want to use AI. Without it, you're just vibe coding and you will sooner or later hit a wall. How that wall looks like or its size... depends.
- AI/LLMs are statistical machines! They are not creative, they base themselves on what has come before. If you want to innovate you need to do it yourself. They do not provide fresh ideas and most likely will not net you the next big thing. Do not delegate everything to AI.
I'll stop here for now - in any case, it's fun, it's definitely faster and it does feel good to see a prototype up and running like never before. It's here to stay, people just need to know how to use it right and with right mindset.
I got a bit lost above but I think that shows a bit more of how Origami came to be than if I just showed you yet another app. Take a look at the website if interested, it's free!
In summary:
- It's a terminal manager
- It supports multiple workspaces at the same time
- Each workspace has organized tabs within them that you can configure
- Has integrated git support
- Has its MCP so it can be controller from within itself
- Bring your own agents, shells and whatever else - it does not replace them.
See everyone around.

value: Show HN: Origami – A simple workspace-oriented terminal manager

author: uniqid


value: i dont trust LLMs to make trades for me, however i do trust them to pressure test theses, process large amounts of market and exchange data, RSS feeds. theres are pages and pages of text, opinions, about any given ticker. does not having a risk committee or a fund-manager overlord allow me to make riskier, and more profitable trades compared to a hedge fund? im currently finding out. while i've been making money, im still far away from becoming retiring off of it. would love to hear about others taking this approach

value: Show HN: I built an MCP server for narrative-driven trading intelligence


value: Show HN: Scholr – search 200M+ academic papers with citation-grounded synthesis


value: burnedchris

value: Show HN: Inrepo – Pull upstream repos into your app without forks or submodules

author: burnedchris


value:
Hey HN,
I've been working on a multi-model database called NodeDB.
Originally, i've found out the idea of SurrealDB quite good. However, it doesn't have some graph and vector features that I need. And since it is just a KV wrapper, instead of purpose-built engine, the performance will never be close to the specialized databases (like Neo4j, Pinecone, Clickhouse, etc).
And i've asked myself, what if, there is a database that have the same idea, but built differently? Instead of just treating it as KV database, we build specialized engines for the data.
Besides that, I want it to be able to support my IOT/edge project, where i need offline sync capabilities (Currentyl still in progress).
Will it work?
I put it into test. I've been experimenting and researching for a year, creating multiple versions, and then I created NodeDB.
Disclaimer: It is still in public beta (as of May 2026), but it really excites me if I can make this db work. And I use AI as assistant for coding and planning. It is nearly impossible to do as a solo developer without any AI assistance.
Would love feedback from HN:
- Are there specific features or improvements that would make it more useful?
If you're interested in experimenting or contributing, the repo is here: GitHub Repo: https://github.com/nodedb-lab/nodedb
Looking forward to your thoughts!

value: Show HN: NodeDB – High Perfomance Multi-Model Database


value: Show HN: ProvisioningIQ – Continuous Benchmarks of AWS/Azure/GCP Latency


value: gkiely

value:
In light of the ongoing npm supply chain compromises, I built safe-install:
https://www.npmjs.com/package/@gkiely/safe-install
It brings a couple of protections I wanted from npm but are not built in.
Similar to Bun’s trusted dependencies, it lets you disable install scripts by default and define a list of dependencies that are allowed to run build/install scripts:
https://bun.com/docs/guides/install/trusted
It also supports blocking exotic sub-dependencies, similar to pnpm’s `blockExoticSubdeps` setting:
https://gajus.com/blog/3-pnpm-settings-to-protect-yourself-f...
I was hoping npm would eventually add something like this, but it does not seem to be happening soon, so I made a small package for it.

value: Show HN: Safe-install – safer NPM installs with trusted build dependencies

author: gkiely


value: Show HN: A browser-friendly mirror of the war.gov UFO/UAP Release 01 files


value: madprops

value: Show HN: Compare Similar Audio Tracks

author: madprops

title: Show HN: Compare Similar Audio Tracks


value: erwanalliaume

value:
Hi HN, I'm an indie dev who built this to settle a long-running argument with my teenage son about who lifts more at the gym.
I wanted a workout tracker to kept our data side-by-side on a leaderboard, and let us swap training plans without texting screenshots back and forth.
Nothing I tried did all three without a subscription wall, so I wrote my own.
Most of the app is free, it covers the full workout experience and progress tracking with 80+ exercises.
The one-time purchase unlocks multiple plans, custom movements, and the social/sharing features, mainly to pay for the infra.
The mobile app is React Native via Expo with Expo Router, NativeWind for styling, Zustand for state (every store is user-scoped via an AsyncStorage key prefix so account switches do a clean rehydrate, good way to have several using using the same app), Reanimated for animations, and react-i18next across six locales.
The core workout loop is fully offline, and a Firebase layer sits on top for optional cross-device sync and the social features.
Backend is a small workspace of Firebase Cloud Functions v2 that handle cross-user fan-out (friend requests, shared plans, shared movements) with rate limiting and anti-spam in Firestore triggers.
Published a few weeks ago, I can proudly but surprisingly see the daily usage increasing.
This is my first mobile app since a while (was doing some 10+y ago), keen for any feedback since it gave me the excitement of building some more.
Android only for now, iOS to be published soon.

value: Show HN: Personal Trainer – Lift, share plans, and rank with friends

author: erwanalliaume


value: ICodeSometimes

value: Show HN: Open-source GEO auditor (no signup)

author: ICodeSometimes


value: dremnik

value: Show HN: Wispr Flow but free, 100% on-device, and open source (macOS)

author: dremnik


value: cavalrytactics

value:
SigmaShake Desktop - Guardrails for YOLO AI coding agents
Your AI will use the wrong tool, nuke your database, force push to main because it won't respect your markdown instructions
One ruleset, every major AI coding tool, local, no cloud, no sandbox
Open to hearing feedback. Free to use
BuildingInPublic live on twitch and youtube as well. Feel free to hangout and say Hi!

value: Show HN: Sigmashake Desktop – AI Coding Agent Guardrails

author: cavalrytactics


value: wyattmattoe

value: Show HN: 3D pin art Audio Visualizer

author: wyattmattoe

title: Show HN: 3D pin art Audio Visualizer


value: willsuo

value: Show HN: KeepDue – private iPhone reminders for free trials and renewals

author: willsuo


value: keepamovin

value: Show HN: Doomscroll the Goverment's UFO Files as One Gigantic Microfilm

author: keepamovin


value: horanglabs

value: Show HN: Tessera – Turn coding agent sessions into structured work

author: horanglabs


value: anideshp

value: Show HN: Agent FM – local, open-source radio for Claude Code and Codex agents

author: anideshp


value: Show HN: TextifyALL – AI transcription with zero file size or duration limits


value: manojtrek

value: Show HN: AI Powered fair-price checker for home repairs using BLS wage data.

value: Show HN: I built a fair-price checker for home repairs using BLS wage data

author: manojtrek


value: zafronix

value:
Hi HN — my previous post got flagged for some reason so re-posting to spread the word as well as get some actionable feedback.
When I was a kid and was playing soccer in my home town, my Dad had an idea - what if there was a correlation between a successful soccer player in a specific position and the birth month - i.e., can we determine based on a player's month of birth if he could statistically become a good goalkeeper, defender, midfielder, or an attacker? Obviously, back then the data was hard to come by and I did not think too much about it until recently.
Now, I'm my Dad's age when he vocalized the idea to me, he is still alive, and I felt an obligation to to build something to help him his own stats. That's main the reason I started to build the dataset for the World Cup API, which eventually grew as more data points were introduced.  over a few weekends because LLMs are genuinely.
What you can find right now is - every World Cup since 1930, every group standing, every squad, every scorer, every match, every venue, etc. etc. etc.
In addition to the API, I've also wrapped it in an MCP and published it out for folks to play around and provide feedback.
I've also built a live sample dashboard if you want to preview without installing anything: https://api.zafronix.com/wc-explorer/
Otherwise, you can get started with a free API key takes 30 seconds, 1,000 req/day, no card. Repo + install: https://glama.ai/mcp/servers/zafronix/wc-mcp or find it on ChatGPT and Claude marketplace.
Like I said, looking for constructive feedback.
Thanks HN!

value: Show HN: World Cup History MCP – every FIFA tournament 1930–2026

author: zafronix


value: Show HN: I built a fair-price checker App for home repairs using BLS wage data.


value: andreamonaco

value:
It reached version 1.6, now it covers more than 80% of the standard.
alisp ships with ASDF and is capable of loading many real-world systems, let me know if your favorite system succeeds!
License is GPL3 or later, no LLMs used.

value: Show HN: An implementation of Common Lisp in development, reached version 1.6

author: andreamonaco


value: mathix

value: Show HN: Alacritree, terminal with built-in worktree management

author: mathix


value: mexirica

value: Show HN: Aptui-TUI package manager for APT-based Linux distributions

author: mexirica


value:
Idempotency4j is a Java idempotency library with pluggable storage backends and Spring Web / Spring Boot support.
This library solves the problem of ensuring that sensitive endpoints do not trigger side-effects multiple times - this is especially useful for any endpoints that handle financial operations.
Currently, the library supports Spring MVC (Servlet-based) applications and MySQL and PostgreSQL with jdbc regarding storage backends. It is very simple to integrate, all that you have to do is add @Idempotent to any endpoints that need idempotency.
Full explanation of the functionalities and configuration is available in the readme of the repository.
Repository : https://github.com/josipmusa/idempotency4j
I would love any feedback or review regarding the implementation - also, any recommendation is welcome.

value: Show HN: Java/Spring Boot Idempotency Library


value: Jonverrier

value:
Hi all,
RipStop is a node package implementing a set of rules that consumers can use to protect their repos from wilder actions by LLM agents. A consumer needs only a few lines of code to configure the rules they wish to apply. Example rules: no PII in commits, no Git actions that interfere with the Git history and thus might impact your ability to recover from problems.
I built this for two main reasons:
- in my own repos I had a few incidents - in one Claude Code erased some un-staged changes, and in another started trying to roll back some commits.
- I was reflecting on why agentic development is slow on the uptake in corporate environments. One possibility is fear of the wilder actions LLMs take - so I thought it might be helpful to illustrate how to control these.
The security model is as follows:
- Layer 1 - guidance to the LLM in AGENTS.md or CLAUDE.md. This is of course guidance, and gets forgotten if context rot sets in.
- Layer 2 - Git controls, via hooks that get fired automatically on various actions. Higher hurdle - the LLM would need to generate very specific commands to get round these. This is the space I am aiming at. BTW we also generate a file to go into AGENTS.md to tell the agent the environment it is working in and the  controls the consumer has chosen, so there is a bit of layer 1.
- Layer 3 - containers with hard configuration. Not trying to go this far in this package. This is really the space the major labs are going after with cloud agents.
I think it might be useful in two domains:
- People running local agents who want a little more safety
- A POC for corporate controls
Feel free to look, provide commentary, and use.
Jon

value: Show HN: RipStop – Git guardrails to reduce impact if your code agent goes wild

author: Jonverrier


value: max-azendorf

value: Show HN: A benchmark where LLMs make memes from current news

author: max-azendorf


value: pkundr

value: Hi, I built Survser as a more affordable survey / user research solution because I found existing tools to be bloated and unnecessarily expensive. Hope someone finds it useful.

value: Show HN: Affordable Survey Software

author: pkundr

title: Show HN: Affordable Survey Software


value: Show HN: Tickstem – Python SDK for cron, uptime and heartbeat monitoring


value: Show HN: StabilityPulse – Are you Zoom call ready


value: FelixWag

value: Show HN: Talk to your Oura Ring data through Claude

author: FelixWag


value: keepamovin

value: Show HN: I made a weird language and if you no think it dumb, I want your help


value: vlaaad

value: Show HN: I mage GhosttyFX, a JavaFX terminal view that uses libghostty

author: vlaaad


value: schmuhblaster

value: Show HN: Agent Harness with Prolog and WASM core incl. 90s Borland-style TUI

author: schmuhblaster


value: lowtecky

value: Show HN: Music visualizers that react to audio in real time

author: lowtecky


value: Show HN: Kapbit – A Kafka-powered workflow orchestrator for Go


value: Show HN: Team-of-agents, A multi-role SDLC orchestrator for Claude Code


value: enthusaist

value: Show HN: How Scaleway brought the first RISC-V servers to the cloud

author: enthusaist


value: chrka

value: Show HN: Branchless Quicksort – faster than std:sort and pdqsort

author: chrka


value: helpcodeai

value: Show HN: AnythingMCP – source-available gateway turning REST/SOAP/SQL into MCP

author: helpcodeai


value:
Nathan here, one of the people who built Retrace. Happy to answer technical questions.
Retrace records a CPython application's interactions with the nondeterministic outside world i.e. network, DB, filesystem, time, randomness, subprocesses, and lets you replay that execution locally and deterministically. The goal is to take a production failure and open the same execution in VS Code, with the ability to step forwards and backwards through the replay.
The core idea is to record boundary crossings rather than tracing every Python line in production. External calls are recorded as calls/results/errors, and replay stubs return the recorded results so the original application code runs again deterministically.
The preview today covers Python 3.11/3.12 on macOS and Linux, with Flask, Django, requests, psycopg2, and threading/forking covered. There is a compatibility table in the README.
This is a preview, not a finished product. Things we know are missing: async support is partial, FastAPI is not in the table yet, Windows is not supported, and free-threaded 3.13 is detected and refused.
Happy to go deep on: - how we get determinism on real Python stacks (threads, async, third-party libraries, C extensions) - recording overhead, what it depends on, and what we have actually benchmarked vs claimed - what works and what does not yet - how this differs from rr, Replay.io, pdb time-travel forks, and APM tools
Blog post (longer write-up): https://retracesoftware.com/blog/introducing-retrace/

value: Show HN: Retrace – reverse debugging for production CPython applications


value: loadzero

value: Show HN: AI to Arse – Chrome text replacer for the new age

author: loadzero


value: biduskamil

value:
Hi, I'm Kamil and I'm a founder of Applied AI agency in Warsaw, Poland.
We've trained a small <1MB voice classifier model that runs on CPU in 4ms. Can be run next to silero VAD in voice AI deployments.
What we noticed in production deployments of voice assistants in Contact Centers in EU is that human consultants pick up immediately how to inflect verbs and ajdectives after one utterance from the caller. But voice AI agents don't know it until 1-2 minutes into the call when they are either corrected or the caller uses explicitly words with male/female form a couple of times.
Our model solves this just from the first utterance of caller speech. The voice AI pipeline can inject the classification as context to the system prompt. We observed a significant impact of this on the adoption of voice AI in practice.
Model + paper: https://huggingface.co/syntropicsignal-ai/gender-voice-class...

value: Show HN: Voice gender classifier for European voice AI (1MB, ONNX, 4ms)

author: biduskamil


value: vednig

value: Show HN: Is Github Online?

author: vednig

title: Show HN: Is Github Online?


value: ichbinsoftware

value: Show HN: Watch Claude think

author: ichbinsoftware

title: Show HN: Watch Claude think


value: lowdanie

value: Show HN: Formal Verification with Lean

author: lowdanie

title: Show HN: Formal Verification with Lean


value: nihilpista

value:
I wanted a way to quickly jump between different projects (Wikipedia, Wikivoyage, Wikiquote, etc.) and different languages all in one interface.
It uses the official Wikimedia REST API and features a client-side buffer system so the next random page loads instantly without waiting for the server.
It also has buttons to search for the title on Google or YouTube instantly.

value: Show HN: WikiMixer – Explore random Wikipedia and Wikivoyage in 50 languages

author: nihilpista


value: mindwarp

value:
I built a Telegram/Slack chat interface for local Codex for myself and decided to share it here:
https://github.com/kravchik/orc It’s called ORC (originally it was for ORChestrator  ).
It is intended for programming on mobile. But it turned out so convenient that I am even using it on desktop (Telegram Web) instead of the CLI.
It allows not only the use of an agent, but also control agents lifecycle, directory bind, etc.

value: Show HN: Telegram/Slack bridge for local Codex agents

author: mindwarp


value: ossughychen

value: Show HN: Browser-native replay of an AI agent governance incident

author: ossughychen


value: baursha

value: Show HN: Automatic Git snapshots while AI agents edit your repo

author: baursha


value: wek

value:
Hi, I'm Karl. Greg and I spent the last year building Nimbalyst, an open-source local desktop workspace for working with coding agents.
We want to give agents and humans one place to work together with maximum bandwidth and context, instead of Obsidian for plans, Excalidraw for diagrams, Codex app or Conductor for session management, and Linear for tasks. So we integrated:
- Visual editors for markdown, diagrams, mockups, data models, CSV, code, and your own custom extensions
- Red/green diff review with per-block accept/reject when an agent makes changes
- Session manager with parallel sessions, kanban, search, resume, and links from sessions to the files they touched
- Task tracking where agents and humans create, update, and execute tasks linked to files and sessions
- Developer features like a terminal, worktrees, visual git, and agent-driven commits and branches
Nimbalyst supports Codex, Claude Code, OpenCode (alpha), and Copilot (alpha) through a pluggable provider system.
The desktop and iOS apps are MIT; the collab server is AGPL.
Repo: https://github.com/nimbalyst/nimbalyst
Website: https://nimbalyst.com
I'd welcome your feedback and contributions.

value: Show HN: Nimbalyst open source Obsidian, Codex app, and Linear for coding agents

author: wek


value: Show HN: Tiny long-memory benchmark with Harbor running across Islo sandboxes


value: morelandjs

value:
I built Chumlord, a little iOS app to help me stay in touch with the people I care about. Set a catchup cadence for each friend, and it shows you who you’re overdue to reach out to. No accounts, no data collection, just open it to check the health of your friend roster!
The app is technically trivial, but withering social circles is a topic I see routinely discussed on HN, and I decided I wanted to take a stab at giving the problem a physical form and a tool to shape it. Been using this for a week now, and I really like it!
https://apps.apple.com/us/app/chumlord/id6767711584

value: Show HN: Curate and Nurture a Friend Roster

author: morelandjs


value: sinameraji

value:
hey HN, this is sina.
i've had some cloudflare credits expiring on may 14 and was wondering what to do with them. when kimi k2.6 dropped and it was available on workers ai, i figured i'd build an open-source claude code clone with it. didn't think too much about it. (people asked if i know about opencode and tbh i learned about them only after i built this. but they seem really brilliant.)
anyway, kimiflare is a CLI coding agent, basically claude code but powered by kimi k2.6 on cloudflare workers ai.
it's at v0.57.0 and has gotten 12k+ npm downloads, 137 github stars, and PRs from 4 contributors (including a zed/ACP integration from marshall thompson at featherjs). the credits are the only reason the cloud tier exists, so once they expire on thursday i'm sunsetting it and the project continues as open source / BYOK.
i'm giving away 5M tokens per user to anyone who signs up before the credits expire — no credit card needed. you'll automatically get the tokens when you sign up and choose the Cloud option when prompted by the cli.
repo: https://github.com/sinameraji/kimiflare
install: npm i -g kimiflare
happy to answer anything.
p.s. i used claude code for the first 2-3 commits in kimiflare, then used kimiflare to build itself from v0.3.0 onwards for maximum dogfooding. it's been a fun experience.

value: Show HN: Kimiflare, Kimi K2.6 as a Coding Agent on Cloudflare Workers AI

author: sinameraji


value: robkam

value:
Ytree is a terminal file manager in the XTree style. It can log multiple volumes, collect selected files into a single list, filter that list for operations, and operate on one file at a time or on multiple files. It can also be used to preview, view, and edit files, read and write archives, and compare files and directories.
When I first used Linux in the 1990s, Werner Bregulla’s Ytree looked promising. Tinkering with Linux again recently, I found that Ytree was still not fully developed, so I set out to push it towards feature completeness.
Writing C at any non-trivial scale is beyond my abilities, so I am experimenting with AI-generated code, guided by Unix and FOSS conventions and what I understand to be best practice. The workflow has evolved from browser chat plus an editor and a diff tool to an agentic IDE, including many checks and QA passes before each commit.
In this workflow, the human steers the design and maintains quality control, while the AI does the heavy lifting. Working this way has enabled me to build the program I have long missed having.
It has taken months of coaxing and verification to get this far, and beta is still months away, but I am releasing v3.0.0-alpha now in the hope that it will be useful to others. It is usable, but expect rough edges, occasional UX/workflow bugs, and some features may still change or be removed.

value: Show HN: Ytree v3.0.0-alpha, an AI-assisted rewrite towards feature completeness

author: robkam


value: Show HN: C3X: Offline cloud cost estimation from Terraform


value: mikepk

value:
Hey HN. I'm Michael, founder of Matterbeam. Been chewing on the core ideas of it for over ten years, building toward it for three.
demo: https://www.youtube.com/watch?v=YuhujARUmhA
whitepaper: https://matterbeam.com/whitepaper
Short version: companies build their data infra on point-to-point pipelines and one place to put all the data. Source A goes to warehouse B. Team C wants the same data shaped differently? Build another. Eventually a mess of brittle ETL nobody wants to touch.
Matterbeam puts existing ideas together in a different way. Source data collected as immutable, time-ordered facts into a log. Destinations replay and transform those facts, from any point in time, into the target they need. One source, many uses.
My last startup was acquired by Pluralsight in 2014. I ended up leading product architecture and data there for about five years. Working with really brilliant, product and data people that I would have said were doing everything _right_. Yet no one in the company was happy with data. It made me question if something more fundamental wasn't broken.
A key inspiration came from Martin Kleppmann's 2015 talk "Turning the Database Inside Out." (https://www.youtube.com/watch?v=fU9hR3kiOK0) Most databases internally do something interesting: a write-ahead log (durable, append-only, time-ordered) as a source of truth, and derived structures are created (B-trees, indexes, materialized views) optimized to serve different read patterns.
What if you took that pattern and blew it up to org scale? Your uses become materializations. Warehouse, RAG vector db, graph db, any new use created when needed with a late transform and a new emitter.
A few comparisons:
We aren't Kafka. Kafka is lower-level. My first attempt at this was at Pluralsight using Kafka as the log. It was crazy expensive and complicated to operate. For Matterbeam we built cloud-native: object storage gives durability, ephemeral compute avoids coordination, we don't need 100ms latency for most jobs. Allowed us to avoid a lot of Kafka's complexity.
We aren't Fivetran. Fivetran is a managed pipeline. We're a utility. One customer replaced Fivetran when they brought us in. Saved them money, but that wasn't the goal, suddenly projects they estimated at five months started taking two days. A two-year migration compressed into months. Their PMs started asking to use Matterbeam for everything.
We aren't a warehouse or lake. Snowflake and Databricks are great at what they're great at. The push to centralize all data in these systems was a mistake. We aim to be the layer underneath. Basically fulfill the original promise of the data lake: collect without a use case, materialize when you figure out what you need, in the shape and system you need.
What's broken:
This doesn't fit cleanly into "what does this replace" buckets. Most people agree data is broken but then lament "data is hard" or some form of "my team isn't doing it right." Nobody's actively looking to solve the deeper problem. Hard to find new customers even with glowing testimonials.
Connector coverage. Fivetran has hundreds. We have way fewer in production. We're working on it, we're using AI, you can write your own pretty quickly. Still, if your stack needs fifty SaaS integrations on day one, we struggle.
We're early. Handful of paid customers. Not large-enterprise-ready no SOC2, HIPAA etc yet.
Also, conscious decision not to be open source. Long list of reasons, separate post.
I'd love feedback on:
How would you position or market this? It feels like category creation, which I know is hard.
Does the mental model land, or is there a piece where you go WAT?
If you've built CDC-into-warehouse, Kafka-plus-schema-registry, or rolled a data backbone, what's the part you'd have wanted an easier solution for?
Blog, testimonials, marketing video on the site. I'll be watching the thread. Be brutal, I can take it (I think).

value: Show HN: Matterbeam, a company-wide write-ahead log for your data

author: mikepk


value: pranabsarkar

value: Show HN: YantrikDB – persistent memory for AI agents

author: pranabsarkar


value: Show HN: AI IQ – Mapping AI benchmarks onto a common capability scale


value:
I wanted to make a QR code for a separate business (a software company for MEP engineers) where the QR code itself looked like the logo. I found several tools online, but none that produced the result I was looking for.
I made a tool that powers MosaicQR.com to achieve the balance of aesthetics and functional scanning that I wanted. This website generates QR codes where the module layout looks like the inputted image. The free version auto-fetches the favicon from any URL you enter.
Curious what people think.

value: Show HN: MosaicQR – QR codes that double as pixel art of any simple image


value: azurewraith

value:
Agentic problem solving in its current state is very brittle.  I fell in love with it, but it creates as many problems as it solves.
I'm Ben Cochran, I spent 20+ years in the trenches with full-stack Engineering, DevOps, high performance computing & ML with stints at NVIDIA, AMD and various other organizations most recently as a Distinguished Engineer.
For agents to work reliably you either need massive parameter counts or massive context windows to keep the solution spaces workable. Most people are brute forcing reliability with bigger models and longer prompts.
What if I made the problem smaller instead of making the model bigger?
I took a different approach by using smaller models: models in the 13-20B parameter range and set them to task solving real SWE-bench problems. I constrained the tool and solution spaces using formal state machines. Each state in the machine defines which tools the model can access, how many iterations it gets and what transitions are valid. A planning state gets read-only tools.  An implementation state gets edit tools (scoped to prevent mega edits) and write friendly bash tools. The testing state gets bash but only for testing commands.  The model cannot physically skip steps or use the wrong tool at the wrong time. It is enforced via protocol, not via prompts.
The results were more promising than I would have expected. Across multiple model families irrespective of age (qwen-coder, gpt-oss, gemma4) and the improvements were consistent above the 13B parameter inflection point. Below that, models can navigate the state machine but can't retain enough context to produce accurate edits. More on the research bit: https://statewright.ai/research
Surprisingly this yielded improvements in frontier models as well. Haiku and Sonnet start to punch above their weight and Opus solves more reliably with fewer tokens and death spirals.  Fine tuning did not yield these kinds of functional improvements for me. The takeaway it seems is that context window utilization matters more than raw context size - a tightly scoped working context at each step outperforms a model given carte blanche over everything. Constraining LLMs which are non-idempotent by using deterministic code is a pattern that nobody is currently talking about.
So, I built Statewright. Its core is a Rust engine that evaluates state machine definitions: states, transitions, guards and tool restrictions.  Its orchestration doesn't use an LLM, just enforces the state machine. On top of that is a plugin layer that integrates with Claude Code (and soon Codex, Cursor and others) via MCP.  When you activate a workflow, hooks enforce the guardrails per state automatically.  The model sees 5 tools available instead of dozens, gets clear instructions for the current phase and transitions when conditions are met.  Importantly it tells the model when it's attempting to do something that isn't in scope, incorrect or when it needs to try something else after getting stuck.
You can use your agent via MCP to build a state machine for you to solve a problem in your current context. The visual editor at statewright.ai lets you tweak these workflows in a graph view... You can clearly see the failure paths, the retry loops and the approval gates. State machines aren't DAGs; they loop and retry, which is what agentic work actually needs.
Statewright is currently live with a free tier, try it out in Claude Code by running the following:
/plugin marketplace add statewright/statewright
/plugin install statewright
/reload-plugins
Then "start the bugfix workflow" or /statewright start bugfix. You'll need to paste your API key when prompted. The latest versions of Claude may complain -- paste the API key again and say you really mean it, Claude is just being cautious here.
Feedback is welcome on the workflow editor, the plugin experience, and tell me what workflows you'd want to build first. Agents are suggestions, states are laws.

value: Show HN: Statewright – Visual state machines that make AI agents reliable

author: azurewraith


value: recruiterinfo

value: Show HN: Rate and Review Recruiters

author: recruiterinfo

title: Show HN: Rate and Review Recruiters


value: jitl

value:
I needed a SQLite parser small and fast enough to use in Notion's UI thread that I can trust will handle modern SQLite syntax. The most-downloaded SQLite parser on NPM is unfortunately unmaintained and slow, and while there are some fast and accurate WASM options, WASM pays a very large start-up cost as well as per-call overhead.
SQLite uses a LALR(1) parser generator call Lemon (similar to Yacc). I patched Lemon to dump its parse tables to JSON, then ported SQLite's [parse.y][] grammar to TypeScript with some help from Claude. The result is this library, which I think is the fastest JavaScript SQL parser out there:

      ~2.5x faster than liteparser (wasm)
      ~6x   faster than @guanmingchiu/sqlparser-ts (wasm)
     ~10x   faster than node-sql-parser
    ~100x   faster than pgsql-ast-parser
    ~200x   faster than sqlite-parser
    ~250x   faster than @appland/sql-parser

This shipped in Notion a few weeks ago and cleared up some sporadic crash reports where the library we previously used choked on valid input.
parse.y: https://github.com/justjake/sqlite3-parser-js/blob/main/vend...

value: Show HN: JavaScript port of SQLite's parser, 2x-200x faster than others

author: jitl


value: withinboredom

value:
Almost 10 years ago, I was working on two projects: a space game that simulated relativity and a "dead man's switch" in case I died. I realized two things back then:
1. If I wanted to leave a message for my son in 30 years, I couldn't make any assumptions about technology in the future.
2. No database is unkillable.
Over the coming decade, I set out to figure out how to build a leaderless database that could go "holographic" -- any partition could create a completely independent cluster -- while simultaneously acting like any other database. It was a long journey with a lot of dead ends and then suddenly there weren't.
The last year has been a whirlwind of progress, resulting in Swytch, licensed under the AGPL. A drop-in replacement for Redis clusters, with almost 100% command coverage (some lua stuff and debug commands are not implemented, see the docs[1]). It passes self-built Jepsen tests, the underlying system is proven correct through TLA+, and we've written a paper about the underlying framework Swytch is built on[2].
No clock-sync required.
Ask me anything
[1]: https://docs.getswytch.com
[2]: https://arxiv.org/abs/2605.09114

value: Show HN: Self-hosted Spanner-like database that speaks Redis

author: withinboredom


value: rohanmahen

value: Show HN: We Built OpenClaw but Worse

author: rohanmahen

title: Show HN: We Built OpenClaw but Worse


value: fsrc

value: Show HN: Grunden – Frontier AI inference hosted in Sweden, OpenAI-compatible

author: fsrc


value: ombedzi

value: Show HN: UIGen – Production UI from any API spec with full override control

author: ombedzi


value: Jbunga

value: Show HN: Reducing LLM input tokens by 70%

author: Jbunga


value: solvik

value:
Certificates expire silently. Kubernetes won't warn you, and most teams find out when something breaks. This exporter watches PEM files, kubeconfigs, Kubernetes TLS secrets, and PKCS#12 bundles, and exposes expiration as Prometheus metrics you can alert on. It works standalone too, no Kubernetes required. A Grafana dashboard is included.
The new release is a major rewrite, built from experience running this across a large number of production clusters. The main pain point it addresses: at scale, with thousands of certificates, the exporter was putting too much pressure on the Kubernetes API. We also put a lot of care into supply chain security this time around.

value: Show HN: X509-certificate-exporter – Prometheus exporter for TLS cert expiration

author: solvik


value: kqr

value: I saw some funny physics in the crane that's outside my window when I work. I wanted to see if I could (a) replicate it digitally, and then most of all (b) do a better job of stabilising the load than the crane operator I watched doing it.<p>The answer is not really, and definitely no!

value: Show HN: Crane Control

author: kqr

title: Show HN: Crane Control


value: hugobeey

value: Show HN: My father said I'd never read 10 books a year so I built a book tracker

author: hugobeey


value: jbethune

value: Built this back in March because of fears my vibe coding was getting away from me. Basically it just analyzes PRs and asks a question to the developer about them to verify understanding. Turned into a larger project with my consulting firm and clients over the last month. Going to leave the original basic implementation open source.

value: Show HN: Verification of Human Understanding of LLM-Generated Work

author: jbethune


value: I made an RSS proxy written in Go (no dependencies). Use roxy to handle CORS restrictions and combine multiple RSS feeds into one queryable feed that's available in XML and JSON.<p>Why did I do this? Fun I guess.

value: Show HN: Roxy, the feature-rich RSS proxy


value: vincentlenoach

value: Show HN: Isle31 - 31 people per group, locked for life

author: vincentlenoach


value: reubenlavin

value: Show HN: Bullseye – $40/mo for a Marketplace deal-finder? I built a free one

author: reubenlavin


value: devGrimm

value: Made this out of a whim, because I felt like it'd be fun to create a game of touch typing/code writing in the era where people say it's dead. Hope it's fun :p

value: Show HN: Monkey Type for Devs

author: devGrimm

title: Show HN: Monkey Type for Devs


value: asakin

value:
I use Claude Code and also pay for Perplexity, OpenAI, Gemini, and run Ollama locally. Got tired of switching tabs when the right model for a question wasn't Claude.
Dragoman is a small CLI (~800 lines) that plugs into Claude Code's sub-agent system. Ask about the news → routes to Perplexity. "Try Gemini" → goes to Gemini. "Run locally" → Ollama. You can fan out to four models and have Claude synthesize. Keys resolve from 1Password/Keychain at call time, never enter Claude's context.
The fun part: Anthropic's sub-agent architecture already does the hard work. Dragoman just adds the verb.
Happy to answer questions about the architecture or the sub-agent integration.

value: Show HN: Dragoman – Multi-model routing for Claude Code via sub-agents

author: asakin


value: jinhkuan

value: Show HN: MCP for cross-functional software teams

author: jinhkuan


value: allanren

value: Self hosted version.

value: Show HN: ClawDocu – Claw Native document review tool. New way to collaborate

author: allanren

story_text: Self hosted version.


value: avinashpdy

value: Show HN: Atlas - Local-first AI code reviewer for Claude Code, Codex, Cursor

author: avinashpdy


value: namanyayg

value:
Hi HN, I’m Namanyay from Gigacatalyst (link: https://gigacatalyst.com/). Gigacatalyst allows sales, CS, and users to build one-off features, so your SaaS can support long-tail customer workflows and engineers aren’t pulled away from the roadmap.
When you sell software to large businesses, you realize that each customer needs their own workflow and features. Traditionally, this either means long engineering roadmaps or the customers end up using workarounds.
But what if everyone could build their critical missing features just by talking to an AI? That’s what we do at Gigacatalyst. We provide an AI customization layer for your customers, CS team, and sales team to build these missing critical workflows without needing any engineers at all. Think Lovable, but built on top of YOUR platform.
We connect to your product's APIs, learn your data model and design system, and let non-technical users build governed apps via natural language - inside your product, under your brand.
Here’s what it looks like in action: https://www.youtube.com/watch?v=_taSpSphH6E
One of our customers, a Series B company, saw their users (not engineers - managers, ops people, facility directors) build critical workflows like:
- Parts stockout prevention: A maintenance manager typed "show me which parts will run out in the next 2 weeks based on usage over the last 90 days, accounting for vendor lead times." The app tracks consumption velocity, forecasts stockouts, and alerts before it's too late. He says it's prevented ~$500K in emergency downtime.
- Invoice OCR from phone photos: Technicians kept losing paper invoices. The prompt: "upload a photo of the invoice, extract vendor name, date, amount, and line items, then match it to the purchase order and flag discrepancies." Now techs snap a photo on-site to automatically add to the system of record.
- Restaurant emergency triage: A pizza chain's facilities manager was drowning in maintenance requests. He built a priority matrix: "walk-in freezer not cooling" auto-routes as CRITICAL, "dining room light flickering" goes to LOW. He's now able to manage backlogs with the correct priority.
How Gigacatalyst works under the hood:
1. Agentic API discovery: Our agents go through your app and parse your endpoints, query params, request/response shapes, and sample data to build the base layer.
2. Generation and Validation: When a user describes what they want our AI generates an app. We set up multiple validation steps, including static checks, runtime error analysis, and LLM-as-a-judge.
3. Sandboxing and Compilation: We wrote our own compilation and sandboxing framework to get the fastest speeds and lowest costs. This means that users can interact with the built app in seconds.
4. Proxy layer: We create a proxy layer for all APIs to handle auth, tenant isolation, and rate limiting. Everything the agent has access to is controlled, logged, observed, and version controlled.
After 2000+ daily users, 900+ apps built, and 70% 30-day retention, today we're opening a public demo.
Try it: https://app.gigacatalyst.com/ - enter your SaaS product's API URL (or just the homepage) and start prompting.
If you're serving a variety of use cases, you probably deal with a lot of custom requests and Gigacatalyst will save you time and increase your bottom line. Book a meeting at https://gigacatalyst.com/#contact and I'll help your team and customers build new functionality on top of your platform.
I've been reading Hacker News since I was 12 years old. I'm proud to launch for all of you and I want to hear your feedback on my product and comments!

value: Show HN: Gigacatalyst – Extend your SaaS with an embedded AI builder

author: namanyayg


value: rajatrv

value: Show HN: Cutting our credential bulk-import from 17 minutes to 2

author: rajatrv


value: jdbiggs

value: I'm a writer and I often ask AI to draft things for me. Rather than trusting the results outright, I've been trying to edit side-by-side using various tools. Instead of retrofitting something, I made a web app that lets me edit my text while keeping a draft, notes, or information in another pane.

value: Show HN: DualDoc – A text editor for the AI age

author: jdbiggs


value: jclarkcom

value:
We built CircadianLab, a free in-browser tool for lighting design. It uses webGPU shaders to calculate melanopic equivalent daylight illuminance (mel-EDI, formerly EML, relevant for circadian rhythm and WELL v2 compliance), photopic illuminance, UGR glare per CIE 117, and actual daylight through windows and skylights.
It has a database of 400,000+ IES files from 81 lighting manufacturers and supports easy sharing of scenes/configs with other people.
Daylight uses the NREL Solar Position Algorithm and a Perez clear / intermediate / overcast sky model, mixed into the same radiosity solve as electric fixtures. Sun and sky are added as initial flux on every patch, then bounced through the same form-factor network.  Form factors via Monte Carlo with visibility tests, then a Gauss-Seidel 3-bounce iterative solve.

  My company (Innerscene) makes "daylight" luminaires. We built CircadianLab to address a specific gap (no browser-based way to verify WELL v2 mel-EDI compliance before specifying), but it works with any IES file from any manufacturer, not just our line.  For mel-EDI you need SPDs to accurately calculate but CCT is a good proxy.

  Write-up + demo videos: https://www.innerscene.com/blog/introducing-circadian-lab

Of interest to HN crowd, there are measurable productivity/performance enhancements that can be achieved with higher mel-EDIs which is why the design community is now incorporating this into building design.   If you haven't dug into any of the research before checkout:
https://www.innerscene.com/research?topic=Workplace+Performa...
Here is an example scene with a classroom and sunlight coming through a window, showing foot candles as a heatmap:
3d view: https://www.innerscene.com/tools/circadian-lab?share=b104262...
2d view: https://www.innerscene.com/tools/circadian-lab?share=456ad19...
Happy to answer questions on anything related.

value: Show HN: CircadianLab – Browser-based radiosity lighting simulator (WebGPU)

author: jclarkcom


value: pzullo

value:
Hey HN, I am Pietro from Manufact (https://manufact.com), we build open source dev tools and infrastructure for MCP.
You might know us for mcp-use (https://github.com/mcp-use/mcp-use) our open source full stack SDK to build MCP servers and clients.
At Manufact we gave ourselves the mission, and delight, to write as many MCP servers as we could, through this journey we could hone our SDK to offer the best possible developer/agent experience.
Testing/developing MCP servers is a pain because:
- Configuring MCPs in normal clients is not an easy feat. People complain that installing them is not easy, imagine having to refresh them every time you make a change
- Testing does not only mean testing tools work one at a time, but making sure agents understand them and can call the tool in the right way/order
- If installing an MCP locally is a challenge, it is even more on remote clients where people are going to actually use your products (claude.ai, chatgpt.com)
- Model capabilities + system prompt (agent) that will end up using your server vary greatly. Some people might be using Opus 4.7 from Claude Code, some might use Instant on chatgpt.com, the model's ability to call your tool varies a lot. Testing on GPT5.5 locally and testing on ChatGPT with the same model yield very different experiences.
First: local development loop
Two things made web development frameworks like Next and Vite (etc.) better than anything else, HMR and preview on localhost.
What is the preview of an MCP ? In our opinion a chat, every time you npm run dev an mcp-use server we serve an inspector on localhost, automatically connected to your MCP server, it has a BYOK chat, a way to test tools one by one, and super detailed metadata about your MCP server to make sure it is compliant
Interesting technical challenge here was to make an MCP client that runs completely (or almost) in the browser.
About HMR: this was not super easy, there are a few ways to do this, we chose the hard but proper way. We implemented HMR using the protocol primitives, if you change a tool we do not hard refresh the server and cancel the previous MCP session, we send a notifications/tools/list_changed notification (in spec) to the client which knows it should reload the tools. As far as UI elements we use Vite HMR and we forward the UI changes across all elements of the inspector so for instance you can change the UI element your MCP returns and see the change live in the embedded chat. (This is pretty marvellous to look at)
This sped up the development of MCPs by a lot.
You can try it out our inspector by running npx @mcp-use/inspector or just by using our sdk.
Bonus: one thing I do often is launch Claude Code with --chrome enabled and tell it to go to the inspector URL to test the server, this creates a closed loop for the agents that make development of MCP with them much much more predictable
Second: testing on other clients (Disclaimer : this is a cloud feature)
Testing on actual client is possibly more painful. We created an automated testing feature, you define the test cases associated with an MCP server in the regular agent testing shape (user message, expected tool calls, rubrics). Since "Testing on GPT5.5 locally and testing on ChatGPT with the same model yield very different experiences." we need to test on the actual client so we use browser agents to install the app and start the tests directly on the clients themselves.
Once the session is over, you get the results and both screenshots and screen recordings of the conversations. These turned out to be super useful to share new versions of MCP apps between teams as well.
I'd love to hear thoughts and feedback and specifically know how (if) people are testing their MCP servers both in production and locally.
(I started writing MCPs in Feb 25, when no tool was available and hardly any support in clients, I'd love to see how people are doing this today)

value: Show HN: How we made MCP development feel good

author: pzullo


value: aisinghal

value: Show HN: Profine - Profile and rewrite your PyTorch training loop on real GPUs

author: aisinghal


value: Uptrenda

value: Show HN: One-shot NAT traversal library

author: Uptrenda

title: Show HN: One-shot NAT traversal library


value: lmushro

value:
Six weeks ago, Daniel Nissani at Mozilla.ai shared cq (https://news.ycombinator.com/item?id=47491466), Stack Overflow for agents. One of the top concerns in that thread was security and trust around shared knowledge.
So we worked together to build VIBE, a first line of defense for cq.
Before a developer approves any knowledge unit for the shared corpus, VIBE runs a four-domain audit:  Vulnerabilities (what and who becomes exposed through this code's existence), Intention versus Impact (the gap between what a system is trying to do versus what it actually does), Bias & Blind Spots (known limitations in the agent's training or assumptions in the code), and Edge Case Handling (stress-testing the system before it meets users).
Knowledge units get flagged as clean, soft concern, or hard finding, & hard findings come with a sanitized rewrite for human review.
How would you use this in your automated pipelines?

value: Show HN: Vibe – Responsible AI Review for Cq (Stack Overflow for Agents)

author: lmushro


value:
Hi HN, we’re Sai and Aayush, and we’re building Hypercubic (https://www.hypercubic.ai/), bringing AI tools to the mainframe and COBOL world. (We did a Launch HN last year: https://news.ycombinator.com/item?id=45877517.) Today we’re launching Hopper, an agentic development environment for mainframes.
You can download it here: https://www.hypercubic.ai/hopper, and you can also request access and immediately get a mainframe user account to play with.
There's also a video runthrough at https://www.youtube.com/watch?v=q81L5DcfBvE.
Mainframes still run a surprising amount of critical infrastructure: banking, payments, insurance, airlines, government programs, logistics, and core operations at large institutions. Many of these systems are decades old, but they continue to process enormous transaction volumes because they are reliable, secure, and deeply embedded into business operations.
A lot of that software is written in COBOL and runs on IBM z/OS. The development environment looks very different from modern cloud or Unix-style development. Instead of GitHub, shell commands, package managers, and CI pipelines, developers often work through TN3270 terminal sessions, ISPF panels, partitioned datasets, JCL, JES queues, spool output, return codes, VSAM files, CICS transactions, and shop-specific conventions.
TN3270 is the terminal interface used to interact with many IBM mainframe systems. ISPF is the menu and panel system developers use inside that terminal to browse datasets, edit source, submit jobs, and inspect output. It is powerful and reliable, but it was designed for expert humans navigating screens, function keys, and fixed-width workflows, not AI agents.
A simple COBOL change might require finding the right source member, checking copybooks, locating compile JCL, submitting a job, reading JES/SYSPRINT output, interpreting condition codes, patching fixed-width source, and resubmitting.
Much of this work is so well-defined and repetitive that it's a good fit for agentic AI. To get that working, however, a chatbot next to a terminal is not enough. The agent needs to operate inside the mainframe environment.
Hopper combines three things: (1) A real TN3270 terminal, (2) Mainframe-aware panels for datasets, members, jobs, and spool output, and (3) An AI agent that can operate across those z/OS surfaces.
For example, here is a tiny version of the kind of thing Hopper can help debug:

  COBOL:

   IDENTIFICATION DIVISION.
   PROGRAM-ID. PAYCALC.

   DATA DIVISION.
   WORKING-STORAGE SECTION.
   01  CUSTOMER-BALANCE     PIC 9(7)V99.

   PROCEDURE DIVISION.
       ADD 100.00 TO CUSTOMER-BALNCE
       DISPLAY "UPDATED BALANCE: " CUSTOMER-BALANCE
       STOP RUN.

  JCL:

    //PAYCOMP  JOB (ACCT),'COMPILE',CLASS=A,MSGCLASS=X

    //COBOL    EXEC IGYWCL

    [//COBOL.SYSIN](https://cobol.sysin/) DD DSN=USER1.APP.COBOL(PAYCALC),DISP=SHR

    [//LKED.SYSLMOD](https://lked.syslmod/) DD DSN=USER1.APP.LOAD(PAYCALC),DISP=SHR

A human would submit this job, inspect JES output, open `SYSPRINT`, find the undefined `CUSTOMER-BALNCE`, map it back to the source, patch the member, and resubmit. Hopper is designed to let an agent operate through that same loop autonomously.
Hopper is not trying to hide the mainframe behind a generic abstraction, and it's not a chatbot. The design principle is simple: preserve the fidelity of the mainframe environment, but make it accessible to AI agents.
Sensitive operations require approval, and the terminal remains visible at all times.
Once agents can operate inside the mainframe environment, new workflows become possible: faster job debugging, automated documentation, safer code changes, test generation, migration planning, traffic replay, and modernization verification.
We’re curious to hear your thoughts! especially from anyone who has worked with mainframes, COBOL or has done legacy enterprise modernization.

value: Show HN: Agentic interface for mainframes and COBOL


value: lexokoh

value: Show HN: Kplane – Isolated cloud environments for AI agents

author: lexokoh


value: zahlekhan

value:
Hi HN, We made OSS Claude Cowork, built as an OpenClaw plugin.
It lets you create live artifacts (like Claude) that connect to datasources instead of datasets. (eg: fetching Stripe data automatically)
Other tools(Paperclip, Multica) focus on task management but our vision is to build one screen that feels like the SaaS tools you already love using.
It’s OSS. Feedback is highly appreciated.

value: Show HN: OpenClaw OS – OSS Claude Cowork Built on Top of OpenClaw

author: zahlekhan


value: mckabue

value: Show HN: Blober.io – The easiest way to transfer files between cloud providers

author: mckabue


value: HenryNdubuaku

value:
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices.
We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention is the right primitive for this, and FFN parameters are wasted at this scale.
Simple Attention Networks: the entire model is just attention and gating, no MLPs anywhere. Needle is an experimental run for single-shot function calling for consumer devices (phones, watches, glasses...).
Training:
- Pretrained on 200B tokens across 16 TPU v6e (27 hours)
- Post-trained on 2B tokens of synthesized function-calling data (45 minutes)
- Dataset synthesized via Gemini with 15 tool categories (timers, messaging, navigation, smart home, etc.)
You can test it right now and finetune on your Mac/PC: https://github.com/cactus-compute/needle
The full writeup on the architecture is here: https://github.com/cactus-compute/needle/blob/main/docs/simp...
We found that the "no FFN" finding generalizes beyond function calling to any task where the model has access to external structured knowledge (RAG, tool use, retrieval-augmented generation). The model doesn't need to memorize facts in FFN weights if the facts are provided in the input. Experimental results to published.
While it beats FunctionGemma-270M, Qwen-0.6B, Granite-350M, LFM2.5-350M on single-shot function calling, those models have more scope/capacity and excel in conversational settings. We encourage you to test on your own tools via the playground and finetune accordingly.
This is part of our broader work on Cactus (https://github.com/cactus-compute/cactus), an inference engine built from scratch for mobile, wearables and custom hardware. We wrote about Cactus here previously: https://news.ycombinator.com/item?id=44524544
Everything is MIT licensed. Weights: https://huggingface.co/Cactus-Compute/needle
GitHub: https://github.com/cactus-compute/needle

value: Show HN: Needle: We Distilled Gemini Tool Calling into a 26M Model

author: HenryNdubuaku


value: Hindurable

value: Show HN: NURL – A programming language designed for language models

author: Hindurable


value: Show HN: I submitted 316 AI-generated PRs to open source


value: rileycevans

value: Show HN: Play10q – a daily 10-question general knowledge trivia game

author: rileycevans


value: xkoda

value:
You speak to the Oracle of Aion, an ancient entity with the power to affect the dungeon.
If your wish is worthy, he may grant it, and the dungeon remember your wish forevermore. The changes will be visible for all players, forever.
Play now in the browser! Free and no registration.
Disclaimers:
I singlehandedly made this game, it is in a crude state, the oracle works 50% of the time.
Also, since your wishes turn into code automatically via AI, and literally anyone can wish whatever he wants, dont expect a polished experience.
However, nothing like it exists and its free, enjoy the chaos! Hopefully it will evolve over time :)
What can the Oracle do?
He can do most changes within a limited framework (rotjs and 2d sprites). The cool thing is the LLM can dream up new sprites and audio, aswell as gameplay logic.
The gameplay loops goes on about 5 mins + whatever he takes to code (up to 15 mins).
Then, if he decided to do something, you can press restart to play the new game and the
change gets added to the Oracle's Decrees (together with a diff of the change).
The oracle has a personality. He wont accept just any suggestion, and he may reinterpret your wish with his own bias for cryptic darkness.

value: Show HN: Game evolves itself with your wishes

author: xkoda


value: Show HN: Cook a Django project well, the agent-skill take on cookiecutter


value: arashbehmand

value: Show HN: Awesome Stars- render github awesome list with live star/fork badges

author: arashbehmand


value: nullandvoid

value:
I built Mealplannr because I wanted to cook more food from chefs I like, without spending 30–60 minutes every week planning meals and writing shopping lists.
The app lets you follow YouTube chefs, find videos with usable ingredients in the description, and save recipes into your own cookbook.
From there, you can generate a weekly meal plan and shopping list. The list is auto-categorised, deduplicated, and can remove common pantry items. There’s also an optional weekly email that generates a plan and list and sends them to your inbox, mixing new discoveries with recipes you already saved.
I now use it for my own weekly shop. It has cut planning down to a few minutes, while helping me add fresh recipes to my regular rotation.
It’s still early, but I’d love feedback on the core workflow.
You can head straight to chef section via https://mealplannr.io/discover (default lands on mealplannr)

value: Show HN: Mealplannr – turn YouTube chef videos into weekly meal plans

author: nullandvoid


value: Show HN: Send Cold Emails with AI Agents


value: andriosr

value:
Hi HN, I’m the founder of an open-source infra access gateway. I’ve always been frustrated by how our users were missing the cool data generated by our tool.
Think a list of all actions devs perform on infrastructure: SQL, shell, CLIs, etc. I dreamed of the day our tool would be able to tell users: “hey, you run this query every week, consider adding it to an internal tool or scheduler”. Or: “you read 1000 customer e-mails last week, likely a mistake, please remove this column from your queries.”
We tried building it a few times. First indexing session contents on Elasticsearch. Then trying to query directly from Postgres blob data types in-line parsing to json. All failed. Data is too big and making this work would be it’s own product (SIEM?).
Thanks to LLMs we were able to launch something much simpler that does a better job then I ever imagined: an MCP server where users can query their session history from an agent.
Agents do a good job of pulling only the right pieces of sessions and analysing them in small chunks to surface cool ideas. And users aren’t locked to whatever rules we add to our interface, they can freely ask the agent about the stuff they care about.
Project is here if you want to give it a shot: https://github.com/hoophq/hoop
Does this make sense to you? Would help a lot even if you told me it doesn’t.

value: Show HN: Feeding agents with session recording data

author: andriosr


value: jonasrosland

value: Show HN: Prempti – Guardrails and observability for AI coding agents

author: jonasrosland


value: yichi

value: Simple AI Orchestrator based on Ralph. The original Ralph idea was to repeat the same PROMPT over and over again, which was still a pretty powerful idea to this day. This workflow builds on top of the original Ralph idea by introducing verification after development, planning iteration before we start development using the same Ralph idea for planning and not just developing code. The entire thing is also free and open source so anyone can start using it right away. I'll be here to answer any questions.

value: Show HN: Ralph Workflow - Simple Agent-Agnostic AI Orchestrator based on Ralph.

author: yichi


value: rgombash

value: Show HN: OCL Nexus – An automated compute layer for AI agents with native MCP

author: rgombash


value: furcyd

value: I am a college CS prof and have, over the years, put together educational videos for my students and anyone interested in learning computer science. I am currently producing a "Build your own javac compiler" course, with 8 videos already out. On my channel, you'll also find a 158-video "Discrete Structures" or "Math for computer scientists" course. Finally, several other playlists cover computer security topics. I post videos at least once a week. Looking forward to your feedback.

value: Show HN: Free online lectures on Computer Science and Discrete Math topics

author: furcyd


value: snats

value: Show HN: Ranking every disease (the unmet needs index)

author: snats


value: dinoze

value:
Built GitGlimpse — a CLI that helps you understand AI-generated code changes faster.
Coding agents can generate huge diffs quickly, but reviewing those changes is getting harder — especially in PRs where the author used an agent and already has the context in their head.
GitGlimpse analyzes git diffs and generates contextual summaries of what changed and why, making PR reviews easier and faster.
It can also:
* generate standups/changelogs
* summarize commits and branches
* run in CI pipelines and automatically post PR context/comments
GitHub: https://github.com/dino-zecevic/gitglimpse
Would love feedback from people dealing with AI-generated PRs/code reviews.

value: Show HN: GitGlimpse – CLI for understanding AI-generated Git diffs

author: dinoze


value: liambl

value:
My friend and I have built a tool that can replicate mobile app API traffic precisely. We then wrap the app’s functionality in a standardized API and route traffic through a local proxy running on your computer or phone, so your traffic can’t be fingerprinted.<p>We’re building an open platform around these connections, starting with a  macOS app y’all can try for free. It lets you securely log in to your accounts and then exposes an MCP with one-click install for Claude. We’re most excited about enabling “write” actions, for example asking Claude to:<p>- automate your biz ops on LinkedIn
- schedule a ride to the airport with Uber
- settle up with your friends on Venmo

value: Show HN: Fast, reliable MCP for LinkedIn, Uber, Venmo (r/w)

author: liambl


value:
I'm quite fond of obnoxious looking gifs in a post-ironic way as a manner of shitposting and or injecting humor into a chat. The issue with this however is that, for no real good reason at all, the simple usecase of "Have image/gif background, bombard with garbage" had no real good tooling.
There's gif editors out there, EZgif my beloved is probably my most used non-search-indexing-slash-social-media-site, but they're kinda clunky for my specific usecase of making digital eye-sandpaper bombastic garbage. Other options are bleak and gave me the mark of the beast via shitty watermarks. I just wanted a pile of gifs on top of each other, and thus far the "easiest" way was to bust open a video editor, muck around with it, mess up exporting as a gif directly, get mad, export it as a 4 second mp4, and then use ffmpeg to get it working. is this probably moronic? yes. am I likely to have missed a decent tool? yes. Did I give up looking after sending 4 dollars to some Indian guy for "No watermarks ever for 4$", only for that "ever" to be a year, and then the clunky weird af login process not work? absolutely. (Fuck you, you know who you are)
This took me a few hours (most of which was dealing with the fact I don't do webshit normally and the clunk that one would expect from that), and is a minimal site for my personal minimal usecase. It's static because I'm not going to deal w/ hosting other people's shit and I don't want to deal with that can of worms. all processing is done locally on your browser. Yes, this means that using a 4k image as a base layer for your gif pile will make it take an age. It'll work eventually though.
This will never have a watermark unless I'm bought out (total investment thus far has been 14 bucks, 4 of which was that one dude fucking me), in which case I probably earned it. at most I'll likely throw adsense on there at some point to scrape a few cents from the people who can't figure out adblock if it gets popular enough for me to warrant it.
There's no timelines or anything like that. literally just a pile of gifs. thus far my primary usecase has been overlaying text gifs from the various fancy text generator sites onto glitter backgrounds with uncomfortable rat GIFs to call people poor on the internet. this makes me happy.
There's likely to be obvious UI, UX, or other U-whatever fuckups. If you point them out and I deem it pedantic I'll probably laugh at you. if it's helpful I'll probably implement it when I get a bit.
Surprisingly, works on mobile.
CSS is exceedingly generic and souless atm, just went off vauge memories of ss13's TGUI. I'll likely scrap the CSS entirely and go full neocities at some point because that's more soulful.

value: Show HN: GIF Pile. a site to make piles of GIFs


value: patakxd

value:
I’ve been working on Duckflix, a self-hosted media streaming platform.
It started as a full-stack project to combine a clean streaming UI with a Bun/Elysia backend, FFmpeg processing, SQLite, Docker deployment, and addon support.
Website: https://duckflix.fun
Demo: https://demo.duckflix.fun
GitHub: https://github.com/duckflixapp/duckflix

value: Show HN: Duckflix, an open-source self-hosted media streaming platform

author: patakxd


value: yashau

value:
I looked around for a while looking for something that:
A. Is a self-contained binary. I know it's not really important, but I like the hygiene.
B. I wanted Codex Desktop on the go, not Codex CLI.
C. I wanted to go back to the work I started on my phone once I return to my desktop. Vice-versa would be nice too, but I don't really need it.
D. I was sick of the usual "agents" that sucked at managing context, poor tool handling, and overall instability. First party harnesses are just better.
E. Native Windows support without a ton of deps. Apparently nobody likes Windows so all the good stuff is made for macOS.
F. Finally, I wanted Codex on the go, not a full-blown agent. I am seriously over agents at this point and I will probably return to them at a later date.
I didn't find anything I liked so I decided to make one.
Features are listed in git. Hopefully someone likes it.
There might/will be bugs. Create issues or submit PRs. Be nice :)
PS: project was entirely done in GPT-5.5-High

value: Show HN: Dexgram – Telegram to Codex Desktop Bridge for Windows

author: yashau


value: Chrome extension that captures Claude.ai conversation state and lets you reload it into a new chat. All local, no account, free. Solves the "I lost my whole debugging session" problem.

value: Show HN: Clodcapture – save and resume Claude.ai chats across sessions


value: coldbrxthe

value:
I built rs-pug because I wanted a TUI music player that’s actually extensible. Most players are either hardcoded or too heavy, so I made this one scriptable via Lua, think Neovim, but for music.
and it has a lot of other cool features

value: Show HN: Rs-pug – A scriptable terminal music player written in Rust with Lua

author: coldbrxthe


value: CarlRannaberg

value:
Last week's post from Thariq "The Unreasonable Effectiveness of HTML" went viral in X. He made a good point about HTML being the more expressive and human friendly alternative to markdown files. I completely buy in where he's coming from, I've been asking Claude Code to create me HTML files to better understand what we're planning and building together.
What Thariq didn't address was the part of sharing and collaborating on these HTML artifacts (he proposed uploading to S3). While I've been heavy user of HTML artifacts to share quarterly plans, implementation specs, technical guides and more, it has been a challenge of sharing them with my teammates securely. Not all people in the company have GitHub access to see the markdown file. Slack and Google Drive don't render HTML.
There's been no good solution today on the market, until now, which gives you tools for your agent to publish the HTML and MD files, gate the artifacts behind company SSO or OTP and collaborate with your teammates on these artifacts through inline comments. All the tools out there are either local only or best case for solo developers.
There are of course GitHub Pages, Cloudflare Pages (with Access) and other options, but they all charge you per seat, which is a hefty bill to pay if you just want to share an HTML file with your PM or marketing manager who doesn't have access to GitHub. GitBook is the worst option with $299/site + $15/viewer + BYO auth provider. We offer flat pricing (free, $15/mo, $49/mo) as we don't want to penalize the many users in your company who want to have access to the artifacts.
Me and my co-founder have been dogfooding it daily for weeks. It has become the default way we collaborate. We don’t use GDrive, Confluence, Notion etc. Our stack is just Whatsapp, GitHub and Display.dev.
Here's one example artifact with mockups of nav changes: https://display.dsp.so/c5kajiu3-mockup-settings-tabs-simplif...
I think an agent-native product category is forming in this space, which is going to supersede the Notion/GDocs/Confluence generation of tools. Display.dev is our humble contribution to advance it.
Try it without signup. Paste this into your coding agent:
---
Build me an HTML page comparing 3 different mockups of how Hacker News could look better. Side-by-side layout. Each mockup styled in a clearly different design philosophy (your call — pick three contrasting takes).
Label each with its philosophy and a one-line rationale. Polished. Publish to display.dev's public endpoint at https://api.display.dev/v1/public/artifacts (multipart/form-data, HTML in the `file` field, title in `name`). Open the `previewUrl`.
---
How have you solved the sharing and collaboration part with HTML and MD files?

value: Show HN: Display.dev, agent-native way to publish HTML or MD behind company auth

author: CarlRannaberg


value: markjgx

value: Show HN: Outpainting Avatar: The Last Airbender from 4:3 to 16:9

author: markjgx