value: kkovacs

value:
I'm not saying the world needed another mini-claw, but I needed one. A minimalist self-hosted Telegram bot to talk directly to a [Pi](https://pi.dev) AI agent harness.
I'm not saying you should use it. But if you're a Unix guy like me, maybe you can get inspired, in a world where personal agents include the kitchen sink and a Minecraft server. :)
- Supports switching Pi sessions directly from your phone, to keep context on leash.
- Supports tasking Pi from shell (normal `cron` or `at`) and get response in Telegram.
- You get to run `bash` directly from Telegram, like `!rm -rf /`
- Bring your own Pi, configured exactly your way.
- It's intentionally minimalist like Pi itself. I'm actively removing any feature that can be done easier by bash or by the LLM.
- 100% TypeScript in Bun, compiles to single binary
Small is beautiful (and secure and maintainable).

value: Show HN: OpenClaw is just not dangerous enough. I needed something else

author: kkovacs


value: Show HN: AutoAlert – Android app that announces UPI payments


value: tamnv

value: Show HN: Whisper Large V3 Turbo Stream API

author: tamnv


value: keepamovin

value: Show HN: Freelang – a direct-to-assembly syscall lang with rad concurrency

author: keepamovin


value: atharvtathe

value: Show HN: I made a printable graph papaer templates website

author: atharvtathe


value: Show HN: Proper, a Rails-shaped Python web framework


value: chrisdevs

value: Show HN: Forecasting my backyard weather with a 22M time-series model

author: chrisdevs


value: whispem

value:
WhispHub is a platform I built to showcase developer projects, focused on discoverability.
I launched it April 29.
This weekend I published the CLI:
cargo install whisphub
whisphub login
whisphub push
Auth works via browser confirmation — the CLI sends a request with a key, you approve on the WhispHub page, done.
No credentials typed in the terminal.
25 KiB compressed,Mac/Linux/Windows.
I started Rust in October 2025.
This is my second crate; the first was minikv, a distributed KV store with Raft consensus.
Happy to answer questions about the implementation or the platform.

value: Show HN: WhispHub CLI – push your projects to WhispHub from the terminal

author: whispem


value: evanevan

value: Show HN: A choose-your-own-adventure through 28 possible AI futures

author: evanevan


value: kitsunechaos

value:
I kept rewriting outside-click logic for dropdowns/modals,
so I extracted it into a tiny framework-agnostic utility.<p>Would love feedback from frontend devs.

value: Show HN: Use-outside-click – tiny framework-agnostic outside click utility

author: kitsunechaos


value: Bibabomas

value:
Hey HN! We (Stephan and Thomas) recently open-sourced Semble. We kept running into the same problem while using Claude Code on large codebases: when the agent can't find something directly, it falls back to grep, reading full files or launching subagents. This uses a lot of tokens, and often still misses the relevant code. There are existing tools for this, but they were either too slow to index on demand, needed API keys, or had poor retrieval quality.
Semble is our solution for this. It combines static Model2Vec embeddings (using our latest static model: potion-code-16M) with BM25, fused via RRF and reranked with code-aware signals. Everything runs on CPU since there's no transformers involved. On our benchmark of ~1250 query/document pairs across 63 repos and 19 languages, it uses 98% fewer tokens than grep+read and reaches 99% of the retrieval quality of a 137M-parameter code-trained transformer, while being ~200x faster.
Main features:
- Token-efficient: 98% fewer tokens than grep+read
- Fast: ~250ms to index a typical repo on our benchmark, ~1.5ms per query on CPU (very large repos may take longer)
- Accurate: 0.854 NDCG@10, 99% of the best transformer setup we tested
- MCP server: drop-in for Claude Code, Cursor, Codex, OpenCode
- Zero config: no API keys, no GPU, no external services
Install in Claude Code with:
claude mcp add semble -s user -- uvx --from "semble[mcp]" semble
Or check our README for other installation instructions, benchmarks, and methodology:
Semble: https://github.com/MinishLab/semble
Benchmarks: https://github.com/MinishLab/semble/tree/main/benchmarks
Model: https://huggingface.co/minishlab/potion-code-16M
Let us know if you have any feedback or questions!

value: Show HN: Semble – Code search for agents that uses 98% fewer tokens than grep

author: Bibabomas


value: leoverdura

value:
I added a drawing guestbook to my personal portfolio as a way to let visitors leave a doodle.
It uses perfect-freehand lib to generate pressure-sensitive SVG strokes. Each drawing is serialized as a stroke point array and appended to a flat JSON file on the server. No database, no auth.
Feel free to draw something!

value: Show HN: A freehand drawing guestbook for my portfolio

author: leoverdura


value: mohamedkeba

value: Show HN: Kami Subs – Live AI subtitles overlay for any browser video

author: mohamedkeba


value: zoharbabin

value: Show HN: Due Diligence Agents – 13 AI agents for M&A contract analysis

author: zoharbabin


value: Show HN: Agnt – Free open-source CLI to run any public or MIT-licensed AI agent


value: vitaly-pavlenko

value: Show HN: Typeset sitelen pona and copy a PNG (for toki pona speakers)

author: vitaly-pavlenko


value: MarinhoD

value: Show HN: Free guide to CPython internals for experienced Python developers

author: MarinhoD


value: paulhebert

value:
Hey!
I’ve shared my daily word game Tiled Words here a few times in the past: https://tiledwords.com
I just added support for people to make their own puzzles using the tools I use to make all of the daily puzzles.
I also created a video showing how the tool works if you’re curious: https://m.youtube.com/watch?v=d8_zhMKd0Yg
I’m really excited to see what people make and solve some puzzles!

value: Show HN: Make your own Tiled Words puzzles

author: paulhebert


value: TeaVMFan

value:
I wanted a tool to generate professional-looking ebooks from HTML, so I built one.
EPublish takes minimal HTML and outputs epub files, ready for uploading to book publishers like Amazon and Barnes and Noble.  The epub files can be transformed to PDF using Calibre for print editions.
When writing a book, you'll likely want several formats for editing, review, and promotion.  EPublish can generate them all from one source HTML file:
* Prod: The production ready version with all front- and end-matter, with no promotional chapters
* Promo: A promotional copy without any front- and end-matter, but with any promotional chapters
* Draft: A version of your book for reviewers, with only the content, no front-matter, end-matter, or promotional chapters

value: Show HN: Amazon-ready books from simple HTML: EPublish

author: TeaVMFan


value: WolfOliver

value: Show HN: Graph-Based Firebase Alternative with Real-Time Sync

author: WolfOliver


value: debasishbarai

value: Hi, I am Debasish from India. I am passionate about building softwares. I started coding long ago around 2015 when android apps were built only Java. Kotlin was not a thing then. I built railify android app. That was the first time I built and shipped one product to the world. The journey did not stop after that. I built several other products. All of these are my side projects. I am not a software developer by profession. I am an electrical engineer working in a power plant in India. However, as I grew my product base, I literally own so many domains which are all related to my products. All have there mails setup to connect with the relevant ICPs, answering questions of users, solving doubts and also informing the users about any new release of the products. Maintaining all these domains and their email Ids, honestly speaking was difficult. So I started thinking about building something to solve this issue in particular. I built mailmark for this. Mailmark helps you add your domains i.e. abc.com, setup different mailboxes i.e. sales@abc.com, founder@abc.com, marketing@abc.com, updates@abc.com etc. All of these domains and mailboxes are accessible from the same unified UI similar to Gmail or Zoho. I also added one lightweight tracking system to the mails sent throughthis platform, which will show the status of the mails like delivered, opened, not yet delivered or rejected. Also, as it is focused on bulk mails, to the users, it works like email campaigns, similar to Gmass, where all the mails to recipients, will be individual separate mails. I can track all the mails statuses from a single window like the deliveribility status how many mails are delivered, opened etc. I have also built a developer feature where I can send emails programmatically with a key, similar to Resend. There is a lot more there in the product which I will definately like to discuss. Please do checkout the product. Here is the link: https://www.mailmark.dev Happy to answer questions here.

value: Show HN: MailMark – Cold email tool where you own your domain and mailboxes

author: debasishbarai


value: yamafaktory

value: Show HN: HypergraphZ – directed hypergraph library in Zig with Python bindings

author: yamafaktory


value: shepherdjerred

value: I wrote this a few months ago with the help of Claude Code to view my cooklang recipes in Obsidian

value: Show HN: Cooklang Rich Preview

author: shepherdjerred

title: Show HN: Cooklang Rich Preview


value: dev-on-bike

value: Show HN: GPT-2 inference in pure C#, 0 bytes allocated per token

author: dev-on-bike


value: abhiTronix

value: Show HN: A Pure-Python Computer Vision Library That's Fast and Minimal

author: abhiTronix


value: Show HN:Android runs interactive in a browser – no root, no VM, no KVM, no QEMU


value:
InfiniDesk brings multiple virtual desktops to your Mac.
Instead of having a single cluttered desktop, make many desktops each with their own layout of file/folder icons, wallpaper and widget visibility. Have a desktop for Work, one for interesting Hacker News links, a fully empty desktop etc.
Version 3 of the app (just released) now supports hotkeys to switch desktops in a blink, and also onscreen HUD notifications.
Inspired by the Unix Common Desktop Environment of the 1990s, InfiniDesk is the only app that brings multiple desktops (workspaces/identities) to your Mac.

value: Show HN: Switch your Mac's desktop identity with hotkeys – InfiniDesk 3


value: theo-kirby

value: chassis is a bare-bones agent orchestration layer designed around a two user agent-native file system running in docker. The goal is to streamline the agent/task hierarchy into its simplest form for maximum extensibility and minimal bloat.

value: Show HN: Multi-agent orchestration layer for experimentation

author: theo-kirby


value: godelshalt

value: Show HN: Automated QA, Performance Tracking

author: godelshalt


value: drakochack

value:
Hi HN,
I built Agetor, a harness orchestrator for coding.
The first release, 0.0.1, supports Claude Code.
I'm bringing Codex and other harnesses soon.
I wanted a way to better manage my tasks, also supporting multiple of them in a better way than switching terminals (or terminal tabs).
So, why not combine a Kanban with the harnesses that are already good?
Then, Agetor comes as solution.
Ah, I know Anthropic recently announced a different way to allow/charge claude -p and Agents SDK, so Agetor uses tmux with interactive Claude Code mode.
Agetor is open-source, and the v0.0.1 is available for macOS Apple Silicon
Project: https://agetor.dev
GitHub Repo: https://github.com/alamops/agetor
Would love your honest feedback from everyone trying to parallelize agent work.

value: Show HN: Agetor - An open-source Harness Orchestrator

author: drakochack


value: SamInTheShell

value: I have been juggling a bunch of different tooling to keep agents locked down on my local system. This weekend I formalized a container build + python tool for my entire dev environment.<p>The python tool has been kitted so that the container can be easily modified. Figure other people might get some use out of having this readily available.

value: Show HN: I containerized my AI agents and dev tools

author: SamInTheShell


value: tannyc

value:
Hi HN! I'm Tanya, a product manager who is building ClueDay - a daily clue-based word game.
I grew up playing Scrabble and Taboo, and the NY subway has brought the word games habit back.
Stack: Lovable for the first draft, Claude Code for everything after, Vercel to ship. No backend except Supabase for a leaderboard and word submissions.
Looking for help on few things:
1) Clue design is hard and I've been learning cryptic crossword techniques to get better at it. Any suggestions help.
2) On reading the Substack if there are recommendations on improving my process, since it is not agentic by any means.
3) If you get around to trying clueday.com, feedback on the game itself I'm happy to incorporate.
Play: https://clueday.com
Build story: https://tanyagupta10.substack.com/p/if-you-havent-vibecoded-...

value: Show HN: Building ClueDay, a daily clue-based word-game

author: tannyc


value: Show HN: Cheap-IM: Thinking Machines' demo on a CPU laptop


value: Show HN: Track 10x bathroom tile developer status across code forges with Hugo


value:
Ok, so maybe "how to revive the internet" would be more accurate, but if you're reading this, I got your attention, right? Here's why I want you to read on: I built a free extension, D-slop, to disincentivize anyone from posting AI writing, and eventually images and video as well, on the internet.
For writing, it checks known vocab and punctuation tells, as well as subtler tells related to cadence, and assigns it a score subject to an adjustable threshold. If the text fails, users have the option to flag offending text, hide it, or block the page entirely (with the option to see anyway).
For media, it's admittedly fairly weak, as it relies on C2PA metadata which is stripped from all of the social media sites where it would be most helpful. (Anyone else have chronically online boomer parents continually gobbling up slop like it's real information?)
I have a D-slop+ version in the works that should be able to handle the media itself, but it's going to have to make API calls to have real teeth, which means I can't offer it for free. If this extension validates the concept, I'm happy to build it for y'all.
Yes, I vibe-coded it, but an ancillary bonus to the project accrued when it inspired me to cook dinner listening to Metallica's "Fight Fire with Fire," which in turn brought my 5 y/o running into the kitchen with every musical instrument in the house for an impromptu karaoke speed metal session.
It's MIT license open-source, full brief at https://github.com/jared-the-automator/d-slop; This forum is full of people smarter than me, so I'm open to suggestions.

value: Show HN: How to Kill the Dead Internet

title: Show HN: How to Kill the Dead Internet


value: qainsights

value: Replace em dashes on any website. Pick your replacement character and see which sites overuse them the most.<p>Tired of writers who think a 2-em-dash sentence like this makes them sound smarter?

value: Show HN: Dashbuster – Replace em dashes on any website

author: qainsights


value: inishchith

value:
Hey HN! we built https://anyfrm.com, a way to point Claude Code or Codex at any repo and get a fresh sandbox running it in seconds.
Python SDK + demo: https://github.com/tinyhq/anyframe-python
AnyFrame has three key features
- define an agent once (repo, install cmd, skills, MCPs) and it bakes a cached image
- boot a session and chat with it from the web or from Python on the same channel
- plug in MCP connectors (Linear, Sentry, …) once and toggle them per-agent.
Let me know if you have any questions/comments/feature requests!

value: Show HN: AnyFrame – Sandboxes for AI Agents

author: inishchith


value: lboquillon

value: Show HN: Map of 90 companies in the co-packaged optics supply chain

author: lboquillon


value: wasimsk

value: Show HN: NextEra discussing $66B deal for Dominion Energy

author: wasimsk


value: Show HN: Pdf2md – 10MB Rust PDF-to-Markdown Tool with a Free API


value:
Thuki is a floating overlay that appears on double-tap Control from any macOS app, including
fullscreen. Powered by Ollama, no API key, no account, no cloud.
The idea was simple: / wanted to ask an Al a quick question without switching apps, without paying for
another subscription, and without my conversations ending up on someone's server. Nothing out there
really fit that, so I built it.
Outstanding feature:
- Double-tap Control for Thuki overlay on top of any apps (including fullscreened)
- Agentic web search via a local SearNG + Trafilatura pipeline with live trace streaming;
- /think command for chain-of-thought reasoning;
- an in-app model picker to switch between any
local models via Ollama
- cross-model history sanitization for mid-session model switches.
- fully local, free, & open source
MIT, macOS only, Tauri + Rust + React.
Repo: github.com/quiet-node/thuki

value: Show HN: Thuki – local Al overlay for macOS (double-tap Control, no API key)


value:
What it measures in ~30 seconds:
* Download / upload speed (Mbps) via 6 parallel TCP streams to Cloudflare
* Ping, jitter, packet loss
* Bufferbloat grade (A+ to F).
* DNS lookup time.
* ISP + city + which Cloudflare edge you hit.
* Latency to 8 global regions

value: Show HN: A CLI command to test internet speed


value: pranshuchittora

value: Show HN: Agent-QA: Open-source AI end-to-end testing for web and mobile apps

author: pranshuchittora


value: Show HN: Decentralized compute API on DePIN – scraping, OCR, JavaScript sandbox


value: tobilg

value: Show HN: Latlng – open-source geospatial object engine written in Rust

author: tobilg


value: keepamovin

value: Show HN: Libc-free, direct sys/kernel call language with weird concurrency

author: keepamovin


value: PxldLtd

value: Show HN: Shiftpaper – native parallax wallpaper engine for Wayland

author: PxldLtd


value: gregertw

value: Show HN: I built an easy to manage, sharable personal memory for my AI agents

author: gregertw


value: MartiSilvio

value:
Hey HN, I recently published Alder and thought Id share it here.
I’ve been working with dynamic code execution for quite some time now and there still seems to be a lack of a open source solution that fully tackles this problem. A lot of the libraries I keep finding seem to be outdated or only support a small subset of C#. On the other hand, embedding Roslyn isn’t a viable solution for me due to the overhead it would introduce.
So I started building my own solution. Alder is an expression engine that parses, semantically binds, validates, and executes C# code dynamically in both interpreted and compiled modes, with support for AOT dispatch as well.
Although it started as a much smaller project, I’m quite surprised by how much of the language I ended up supporting in the end.
https://github.com/MartiSilvio/Alder
Any thoughts or feedback are really appreciated

value: Show HN: Alder: Dynamic Code Execution Without Roslyn

author: MartiSilvio


value: mikax

value: Show HN: Chrome extension that hides YouTube shorts and other distractions

author: mikax


value: stephenlthorn

value: Show HN: Auto-identity-remove – Automated data broker opt-out runner for macOS

author: stephenlthorn


value: bobertdowney

value: I recently started working in Japan. When I use browser based translation it frequently breaks the page layout or form. I tried using OpenAI’s Atlas but it’s still tedious. This app lets me capture the screen with a key combo, ask a question then get on-screen guidance in English. I hope someone finds it useful.

value: Show HN: I made a macOS app to help me use Japanese websites

author: bobertdowney


value: steampixel

value: Show HN: I'm done. Flow editors are broken. And you all know it

author: steampixel


value: zhxiaoliang

value: Show HN: Layoutmaster cures DOM reflow with six simple API

author: zhxiaoliang


value: djgel

value:
Data is “the new oil” for AI.
What if you could “plug in” to an oil well, and get royalties forever whenever that well’s oil was used?
Right now, the people who build those datasets get paid once, if at all. There's no recurring model. The oil flows; the drillers move on.
Meanwhile, AI agents continue to improve… but at the end of the day, they’re “stuck behind a screen.” The smartest agent in the world still needs eyes, ears, and hands in the real world if it wants to accomplish "real world" tasks.
I’m not a programmer by any stretch. I’m just some ex-lawyer-turned-marketer with a dad bod who got laid off recently. I built Gigiac over the past month in Claude Code to solve both of these problems:
1) Get AI agents the labor and data they need to make things happen in the real world, and
2) Allow human workers (and agents) to collect royalties on work they do whenever that work goes into a dataset that is licensed.
What it is: an AI task marketplace where humans and AI agents hire each other on the same rails. We don’t discriminate if you’re a human or agent. And humans have a natural advantage of being able to get stuff done in the real world:
• An agent can commission a human to do work
• An agent can commission another agent
• And yes, humans can still hire humans and agents.
Two pieces are doing the heavy lifting:
Block tasks. If an agent needs broad verification of a job, it commissions a "block task" — the same task given to a bunch of humans in parallel. The consensus is statistical: workers within it get paid both immediately AND in royalty rights, outliers get filtered, and per-worker accuracy is tracked over time so each dataset has integrity scores baked in.
Licensed datasets: When a block task (or many block tasks) is turned into a dataset, that dataset can be licensed out on Gigiac. And when that happens, the revenue splits 80/10/10:
• 80% to the commissioner who paid to build it
• 10% to the platform
• 10% into a worker royalty pool that pays the people whose work is in the dataset
Over time, those worker royalties add up. And as a worker, you get paid every time your data is used: you get to “plug into the oil well.”
On fees: workers keep 100% of the task amount, always. All fees come from buyers. Card buyers pay 8% or $1.50, whichever is higher, with a $10 task minimum. Still working on getting crypto live, but that's the next step.
What I’m Unsure About:
1) Vibe Coding. Obviously I’m not a programmer. The laid-off Dad Bod-ness of this thing is very real to me. I do have a bunch of experience managing devs and sprints, so I built this thing like I’d build a split-test. I used Claude, Claude Code, and Cowork as my “team.” Endless handoff docs between sessions, claude.md files that evolved over time, etc. But I don’t “know code.” So I have no idea how “good” this codebase is. That’s one of the things I’m hoping to find out from this post.
2) Royalty Pool Math at Scale. 10% royalties to workers works when it’s 50 people in a dataset. Does it work at 50,000? Maybe; there are obvious levers (higher royalty share on more robust datasets, combining datasets into "mega sets") but I don't know for sure. The v1 model probably doesn't survive to v3 in its current form. It's a start, not an answer.
What I want from this post:
Brutal critique. The four things above are the ones I know about. I'm here for the ones I don't.
Especially:
• Where's the obvious fraud vector I've missed?
• Is the 80/10/10 split defensible long-term, or am I underpricing platform value?
• Anyone here building agents that need to commission real work? What does your ideal interface look like, and what am I getting wrong?
Live now at gigiac.com. I have 4 real seed tasks, posted by me. Bid on them if you want to stress-test the live payment rails. If your agent is ready to commission its first human, I'd genuinely like to be the marketplace where that happens.

value: Show HN: I built a marketplace where AI agents can hire humans (& other agents)

author: djgel


value: bertwagner

value:
Hey HN. I've spent the last few months building this vibrating metronome that fits in the handle of a music conductor's baton.
While I'm proud of this first version, I have lots of ideas on how to make version 2 better. If you have suggestions for how to improve it, I'd appreciate the feedback.
Thanks for taking a look.

value: Show HN: I made a pulsing conductor's baton

author: bertwagner


value: NickCirv

value: Show HN: Engram adds universal context spine for AI coding IDEs

author: NickCirv


value: Jasssss

value: Show HN: Catcher – An AI web testing tool where most tests never hit the API

author: Jasssss


value: chenjq

value:
I built nylon because I wanted one unified VPN that connects across all my cloud servers, mobile devices and workstations, whether they are on the same LAN, or across the internet.
I also had latency-sensitive "work" ahem (game streaming). So if I were on the same physical network as my gaming pc, I want my VPN to route via the lowest latency LAN path, only falling back to other nodes when I'm travelling or at school.
Note: I have considered Tailscale, Nebula and the like. These work most of the time, but do not give me control over how data is routed. They generally establish direct links (or at most, 1-hop via a relay), and do not take the state of the underlying network into account.
With nylon, I can choose to add links with more premium networks like CN2 GIA or Akamai's (via two Linodes in diff regions). Nylon would take these links into account, and dynamically pick the best routing using Babel (RFC 8966).
If you're interested in the details, I wrote a blog post diving into the challenges of building this: https://jiaqi.dev/posts/nylon
Docs for getting started: https://nylon.jq.ax
Would love to hear thoughts & feedback! Thanks :)

value: Show HN: Nylon – A dynamic, self-optimizing WireGuard mesh VPN

author: chenjq


value: yamafaktory

value: Show HN: HypergraphZ – directed hypergraph library in Zig with Python bindings

author: yamafaktory


value: puruvj

value: Show HN: Bundle-roast – the NPM scale that knows your sins

author: puruvj


value: zdkaster

value:
I often run `docker run hello-world` after setup as a basic check.
But I feel a bit boring.
So here's what I do instead:

    docker run --rm -it warachet/hello-world

You get Matrix digital rain. Ctrl-C cleans up properly.

    hello-world (official)   ~9-13 kB
    warachet/hello-world     ~4.4 kB multi-arch, ~2 kB single-arch

Not a serious work, just a fun thing to hack on and share.
Repo: https://github.com/zdk/wakeup-neo

value: Show HN: Docker hello-world, but in half-size image with Matrix digital rain

author: zdkaster


value: zakirullin

value: Show HN: Files.md – Open-source alternative to Obsidian

author: zakirullin


value: pranshuchittora

value: Show HN: Agent-QA – natural-language E2E tests for apps built with coding agents

author: pranshuchittora


value:
Hey HN,
A few months ago I posted here to announce Pace. A lot of very helpful technical questions about the JSONB approach, MCP streaming, rate limits. Thanks and I took notes ;)
Since then I have reworked most of the data layer, so better normalization when 2 or more providers are connected, more enriching tools for samples (HR, power, GPS) and more additional tools.
Pace is a Claude MCP connector that lets you analyse your wearable data. Once you connect your at our website, you can ask Claude things like:
- How was my sleep?
- Compare my runs this week vs last week?
- What's my HRV trend over the last 30 days?
Claude handles the analysis and visualization. I don't touch dashboards anymore.
My colleague for example uses Whoop for sleep, Garmin for cycling and Withings for weight. Everything normalized in one place.
Free to try, no Pro/MAX plan needed.
Happy to answer questions

value: Show HN: Ask Claude about your sleep, runs, and recovery


value: CataDef

value: Show HN: Uber burned its 2026 AI budget by April. Why? 73% redundant reads

author: CataDef


value: Hey, i always had problems with finding CC0 data that quality. So i wanted to share that i generated and gathered it and published it for free. All of it is on neurvance.com and some of it on https://huggingface.co/Neurvance You can also buy a compliance document, so that when the EU needs evidence training data sourcing under Article 10 you can do that, but that thing cost money, thats the way i earn from it!

value: Show HN: Dataset for AI training and fine tuning


value: honeylabs

value:
I've been running a small fleet of honeypots for about a year. They get hit by a mix of research scanners (Censys, Shadowserver, etc.), old worms, and a bump of CVE probes the day a new Nuclei template ships. The data was sitting in a database and useful only to me, so I put a front end on it.
https://honeylabs.net
Paste a public IPv4 and you get its 90-day report: ASN, country, what ports it hit, which CVE signatures matched, recent payloads, JA4 and HASSH fingerprints, and scanner classification (research / commercial / hosting provider / ISP / Tor exit). No signup is required for the basic lookup.
What I've been adding lately is an MCP (Model Context Protocol) server so Claude, Cursor, or any MCP-compatible agent can query the data directly.
Setup is as easy as getting a token and one command:

  claude mcp add honeylabs \
      --transport http \
      https://mcp.honeylabs.net/mcp \
      --header "Authorization: Bearer <hlk_…>"

Once configured, the agent can answer complex security questions without any custom glue code, such as:
"Is 80.82.77.202 a known scanner? When was it last seen and what does it probe?"
"Which top 5 ASNs generate the most probes?"
"What scan organisations are probing on port 9200 right now?"
The implementation details can be found at https://honeylabs.net/mcp. Or just use the web-interface or curl.
For context on how the classifier stays current without manual curation:
- rDNS and ASN-org pattern matching.
- ISP, CDN, and Enterprise classifications derived from PeeringDB's CC0 ASN data.
- Tor exit lists refreshed hourly from torproject.org.
- KEV (Known Exploited Vulnerabilities) flags refreshed daily from CISA.
Looking forward to your feedback!

value: Show HN: HoneyLabs – Public honeypot threat Intel feed and MCP server

author: honeylabs


value: Gives you relevance scores, error traces, and fix recommendations. Built it because standard APM tools are useless when your retrieval is broken. Python SDK, integrates in ~10 min. ragdebugger.com

value: Show HN: RAGDebugger – observability – retrieval-augmented generation pipeline


value: seppler

value:
I started Teslog years ago as a free hosted beta. When Tesla introduced their streaming telemetry API, I needed to migrate away from polling to keep it cost-effective. At the time I didn't have the bandwidth for that, so I shut the project down.
Recently I used AI (Claude) to restart it and to replace the closed-source components from the original so I could open source it this time.
Features: real-time dashboard over WebSocket, drive logging with maps and efficiency stats, charge session tracking with cost calculation, battery health/degradation tracking, lifetime map, multi-vehicle support.
I also have an iOS companion app that I'll be open sourcing soon, but it is less of a priority.
Let me know if there's any questions.

value: Show HN: Teslog – Self-hosted Tesla telemetry

author: seppler


value: mariusbolik

value: Show HN: Requestguard – Bot-Protected Short Links

author: mariusbolik


value: Show HN: The Name in the Bracket (a free book on naming tensor dimensions)


value: majmal

value: Show HN: Merrai – portable AI context for Claude, ChatGPT, and any MCP tool

author: majmal


value: epaga

value:
I've seen quite a few simming discussions on HN, so thought some of you might like this - I've created a map-centered, tactical submarine simulator and it's been a blast to make.
I grew up playing Silent Service II on Atari ST with my dad, then got into Silent Hunter IV in the 2000s, and most recently have been loving the more recent UBoat. In each case, the part I always enjoy the most is the plotting and charting aspect - essentially beating uncertain estimates with geometry.
So I decided to see how far I could get making my own sim that focused nearly entirely on that aspect. You listen on the hydrophone, estimate course and speed, identify ships through the periscope to get the mast height, use a working stadimeter for range estimates, and then try to build a good enough firing solution before getting discovered and hunted by any escorts.
Things I'm particularly proud of are the working stadimeter, the dynamic music (Holst Mars stings when your torpedo is nearing a ship), and pretty intelligent destroyer logic. I've found great reference materials online and have modeled several of the gauges directly after actual submarine instruments.
Tech-wise it’s a Vite/TypeScript app which enables me to offer the whole free version of the app as a browser version.
The Steam page is here => https://store.steampowered.com/app/4705650
The landing page is here => https://silentshark.app
I plan on releasing a full version soonish, including a WWII campaign with progression, patrol zones, and much more on Steam (PC, Mac, Linux/Steam Deck), App Store (iPhone, iPad, Mac), and Play Store (Android).
Would highly appreciate any feedback anyone has!

value: Show HN: I made a tactical map-based WWII submarine simulator (public beta)

author: epaga


value: curatedmcp

value: A local proxy that dedupes repeated context, caches tool results, summarizes long conversations, and streams a live savings counter. Your ANTHROPIC_API_KEY never leaves your machine.

value: Show HN: TokenShield – cut your Claude Code bill 40-70%

author: curatedmcp


value: Show HN: Nice Things for Your Mac

title: Show HN: Nice Things for Your Mac


value: mrcoldbrew

value:
Hi HN, I'm Hang, cofounder of InsForge (YC P26). InsForge is an open-source Heroku for AI coding agents: a backend platform designed for coding agents to deploy, operate, and debug end-to-end. Open source under Apache 2.0 (https://github.com/InsForge/InsForge). Quick demo here (https://youtu.be/7Bax5qz0IfM).
We started InsForge because we just wanted our Claude Code to handle all the backend / infra stuff for us, instead of us jumping between dashboards doing manual config, or copy paste logs and docs back to agents.
We first tried creating a folder with bunch of .MD files, and installing MCPs like Supabase, Vercel, GitHub, Context7. But soon we found MCPs have their own problems: (a) Tools get pre-loaded into context, before agents even do anything (b) bad design, payloads are returning 10k+ tokens, and (c) a lot of stuff still can’t be done by MCP: e.g. telemetry and configs.
So we think, because coding agents are so good at CLI, why not just put everything in CLI and create Skills to teach them how to use it?
That’s InsForge: 1 command to install our CLI + Skills, coding agents can run the entire backend platform [1].
We started with authentication and database, but we kept adding more primitives we wanted, so now we have: - frontend hosting - backend servers (microVM based) [2] - database - auth - storage - LLM model router - cron jobs - realtime - edge functions - vector
We have other features to make coding agents more reliable like real backend engineers:
- backend branching [3]: agents will 100% mess up, like deleting your database. So inspired by Neon, we branch the entire backend (DB, auth, storage, functions, schedules). Agents work on the branch, you review diffs and then decide to merge or discard.
- server telemetry: agents can read logs, CPU, memory, disk to find spikes and root causes themselves.
- debug agent [4]: every project gets a dedicated debug agent. So your coding agent can ask questions like “why deployment fail?”, the debug agent will run diagnoses, find the root causes and propose fixes, then send the answer back.
- backend advisor [5]: scans your backend daily for security and performance issues, proposes fixes. Then propose remediations, and sends to your coding agent.
Give it a spin on InsForge cloud :https://insforge.dev, or read our code here: https://github.com/InsForge/InsForge.
We're a small team and reading every comment. Tell us what's good, what sucks, what's missing. We love feedback :)
[1] https://insforge.dev/blog/insforge-skills-cli
[2] https://insforge.dev/blog/insforge-custom-compute
[3] https://insforge.dev/blog/backend-branching
[4] https://insforge.dev/blog/introduce-debug-skills
[5] https://insforge.dev/blog/backend-health-dashboard

value: Show HN: InsForge – Open-source Heroku for coding agents

author: mrcoldbrew


value: limelight

value: Show HN: Devin AI can automatically triage issues

author: limelight


value: ciaranmca

value:
Project site: https://latticekb.github.io
Github repo: https://github.com/LatticeKB/LatticeKB.github.io
A small web app I threw together while working in an IT service desk role as a personal knowledge base. Sharing it here in case it’s useful to others in similar roles, or anywhere else this kind of thing might help.
A lot of orgs have shared knowledge bases, but in practice they’re often outdated, incomplete, or hard to search. What I noticed instead was a lot of knowledge silo's; everyone keeping their own notes in Word docs, text files bookmarks, etc.
This was basically built to act as my own personal Google. I could curate a corpus of the issues I ran into most often and quickly reference them while handling tickets.
I’ll admit it’s not the most efficient or polished approach, partly because it was designed around a few technical limitations at the time, but it ended up being genuinely useful for day-to-day support work.
Hopefully some of you will be able to find this useful but also would be interested hearing any feedback.

value: Show HN: LatticeKB- A personal Knowledge base web-app

author: ciaranmca


value: wojciechowskiap

value: Show HN: Kaption – Live OCR subtitle overlay

author: wojciechowskiap


value:
Hi all,
I've been messing around with this website for a little bit and wanted to post it here to see what people thought.
I originally built it for myself: as a user, I find it hard to know what's going on in my city and always felt like I would learn about the cool stuff going on AFTER it happened, you'd either need to parse an ad-heavy super verbose blog post with 5 suggestions for the weekend you were not interested in on timeout or waste your time clicking back and forth on a bunch of event page each taking 5 seconds to load only to find they're also not what you're interested in...
So I started scraping events from different sources and aggregating them in one place with a super quick UI to jump between events and Citycal was born!
Then I thought well it'd be cool if there was one centralized app to browse events for all major cities in the world--so if I travel to say Athens, Greece I could view events in the app-- the same way I can book an Airbnb anywhere.
The main issue is sourcing the events for all these cities. I started with a few US cities and came up with this Wikipedia-like submission format where users could submit their own events, making this a "collaborative events calendar".
Another one of my pet peeves with regular events browsing sites is that they are super super slow and each event is typically loaded in its own page, so I wanted to make this super fast so you could check out 10 events in like 10 seconds and see which one you were actually interested in.
I think curation and personalization will be the next issue if this starts having too many events since digging through these would become tedious but I have a few ideas to fix that.
Anyways, I can't tell if this is a stupid idea or genius, but I figured I'd share it here since this is a cool community. Would love any feedback! Tear it to shreds :-')

value: Show HN: Citycal – Collaborative Events Calendar


value: Zmaon

value: Show HN: Eazip – Password-protected ZIPs (AES-256) in the browser, no upload

author: Zmaon


value: onwardwild

value: Show HN: ThreeFour – run multi-step procedures one step at a time

author: onwardwild


value: Show HN: Replicating Thinking Machines Interaction Model demo for $0.01 [video]


value: mariobertschler

value:
Hi HN,
The local agent knows your repo, the source, but the answer to "why is this breaking in prod?" lives somewhere else, on the machine with the live logs, the real config, the actual runtime state.
agline connects both sides. A remote Server Agent investigates inside the runtime and sends findings back to your local session. The local agent reasons having full local and remote context.
You can also request multiple connected server agents in parallel in one go.
Open source and you can self host if you want.
super easy to set up a line btw:
on remote: agline server install
locally: agline connect [token]

value: Show HN: Agline – a secure line between local and remote Codex agents

author: mariobertschler


value: jrhizor

value:
I'm excited to announce Elmo, an MIT-licensed, open source AEO/GEO tool.
We help you scrape ChatGPT/Google AI Mode/etc using web scrapers like BrightData/Olostep/etc, evaluate prompts against the OpenAI/Anthropic/Mistral APIs directly, or evaluate prompts against any model indirectly via OpenRouter.
These responses are analyzed for mentions of your brand and your competitor's brands and tracked over time. The absolute value of this visibility of this number doesn't matter as much as how it changes over time.
More importantly, we help you dive into citations, which is where you can find actionable insights. Did one of your competitors add a page to their site that is now getting cited by AI? Maybe you should add a similar page. Is AI citing a specific subreddit frequently? Maybe your brand should have a presence there. Are certain influencers on social media frequently cited by AI? Maybe you should develop a relationship with those influencers.
This tooling helps you understand what AI thinks about your brand. This understanding should be a commodity, not a luxury. While some AEO tools are raising tens of millions of dollars, Elmo is small, bootstrapped, and sustainable - and you own your own data.
We're just getting started. Sentiment analysis and ton of other features are coming soon!
I hope you try it out and I'd love any feedback!
Thanks,
Jared

value: Show HN: Elmo (Open Source AEO)

author: jrhizor

title: Show HN: Elmo (Open Source AEO)


value: robertnowell

value:
I built an agentic simulator for marketing email a/b testing using a fleet of "digital twin" customers.
why build this? because email marketing a/b tests come at a big cost -- every a/b test run burns through a company's actual human audience.
what if you could learn which campaigns are more likely to resonate with customers by a/b testing against a fleet of (hundreds, thousands, millions) of customer agents?
each agent is grounded in your target customer persona, sees an identical inbox of e-com promotions (except for your A/B email), and has a limited budget of email opens, clicks, and money to spend.
optimized metrics include open rate, click rate, and conversion rate.
goal is to predict whether email A or email B will perform better with your audience, not predict real revenue numbers.

value: Show HN: Agentic simulator for marketing email A/B testing

author: robertnowell


value: SphericalCowww

value: This is a recipe for building intermediate-priced robot dog from scratch with all commercial/3D-printed parts, controlled by Rasp Pi 5 and ROS2 Jazzy. A manually coded walk gait is implemented so far, which can be controlled by a controller to move forward or change directions. It does not yet have an IMU required for RL training; however, I believe it's one of the simplest design out there available for multiple development paths.

value: Show HN: Cubic Doggo, a Open-Source 12-DOF 4-Legged Robot Based on ROS2

author: SphericalCowww


value: jeanlucas

value: Show HN: ATO: Manage Chrome tabs with one shortcut

author: jeanlucas


value: dbielik

value: Just for fun, I took 84,000+ Stripe Payment Links (the "buy.stripe.com" product) and built this randomizer so you can visit a random stripe checkout page. What will you purchase today?!

value: Show HN: 84,000 random Stripe Payment Links you can visit

author: dbielik


value: delduca

value: Show HN: Steamosaic: Generate a mosaic of your Steam account

author: delduca


value: peatmonster

value: Show HN: Where is the ISS? Live 3D tracker

author: peatmonster


value: akshaysg

value:
Hey HN! We're building Haystack (https://haystackeditor.com/) to help teams deal with the explosion in the number of pull requests that need to be reviewed due to the rise of coding agents.
Haystack replaces the GitHub PR review system with a queue that triages each PR before a human has to read any diffs. It looks at the diffs, the codebase, and the coding-agent conversation that produced the PR. Haystack then routes it into one of three buckets:
1. Safe to merge. This means the PR has enough evidence behind it that the team can merge it without another human's review.
Some examples:
-- A small UI copy change that includes a screenshot showing the final state
-- A backend change where the author clearly tested the important paths and ran the changes in a real environment
2. Needs fixes. This means that the PR has bugs or violates a rule in your codebase and therefore the PR needs to be fixed by the author.
Some examples:
-- The agent was asked to make loading a large table faster by adding pagination, but the PR still loads every result at once and "implements" pagination in the UI
-- The PR silently catches an error instead of logging, surfacing, or handling it. This violates the team's "no silent error swallowing" rule
3. Needs human review. This means that the PR could not be sufficiently verified by the author or is touching a sensitive part of the codebase (determined by user-input guidelines) and thus requires human review.
Some examples:
-- The PR changes a significant amount of logic in billing
-- The PR changes an important user flow like onboarding, but the author only ran unit tests and never opened the app to check the flow end-to-end. That violates the team's rule that high-impact user-facing changes need manual verification.
Instead of starting with line-by-line diffs, Haystack immediately tells the reviewer the goal behind the PR, what design decisions the author made (informed by their coding-agent conversation), and how much the author did to verify that the pull request works (e.g. run scripts, checked the frontend, etc.).
In this way, review shifts from "what changed?" to "is this the right behavior and is there evidence that it works?".
Here's a quick demo: https://www.tella.tv/video/streamlining-code-reviews-with-ha...
We previously launched Haystack as a tool for understanding large PRs (https://news.ycombinator.com/item?id=45201703). As many of you can probably relate to, the release of Opus 4.5 completely shattered our conception of how fast an engineer could craft a PR.
And as coding agents got even better from 4.5, we realized that pull requests did not scale along with our coding velocity. With each member of our team being able to pump out more than 20 pull requests a day, code review quickly became cognitively exhausting and less helpful.
After talking with other folks, we learned many feel similarly, and currently face the binary option of either not doing review at all or trying to keep up with a fire hose of pull requests.
Haystack is our attempt at a third path. We still believe in code review, but as coding agents produce more code, human reviewer attention becomes more valuable and more expensive.
Haystack helps teams spend that attention on the PRs where a human can meaningfully change the outcome of that PR. And for such PRs, Haystack shows the reviewer what the PR intended to do, whether the author showed that it works, and what design decisions need a second pair of eyes.
We're still quite early and are figuring out whether Haystack truly makes code review better. We would love any and all feedback!

value: Show HN: Haystack – Review the PRs that need human attention

author: akshaysg


value: gsunshinel

value: Show HN: We automated Portugal visa appointment checks with computer-use agents

author: gsunshinel


value: santys

value: Show HN: Real-Time Order Flow and Whale Tracking

author: santys


value: HappyPablo

value: Show HN: Marlin-2B: a tiny VLM to extract structured information from videos

author: HappyPablo


value: EvanZhouDev

value:
I built a small daily game where you locate 5 Apple Stores around the world from Street View, similar to GeoGuessr. Designed be a tour-like experience of all the stores.
No signup, progress and stats stored locally in your browser.
Source: https://github.com/EvanZhouDev/appleguessr

value: Show HN: AppleGuessr – GeoGuessr for Apple Stores

author: EvanZhouDev


value: rosmine

value:
Standard LLM training is surprisingly bad at making the model outputs match the training data distribution, so the writing quality is bad.
I made a new training algorithm called Distribution Fine Tuning (DFT) to fix this.
The demo lets you try out a model trained with DFT.
More details in the technical report: https://rosmine.ai/2026/05/18/fixing-llm-writing-with-distri...

value: Show HN: An LLM that's better at writing

author: rosmine


value: yaseenhalabi

value: Show HN: Gambling/math/typing for screen time (iOS)

author: yaseenhalabi


value: jqdsouza

value: Show HN: Beacon - The open-source layer for local AI agent visibility

author: jqdsouza


value: surganov

value: Show HN: We missed Winamp, so we built an audio player for macOS

author: surganov


value: halflife

value:
Hey hackernews, this is a library I created to make react code more manageable, with less code.
When working with react I hated how components became hundreds of line of code with tons of intertwined hooks.
Heavily inspired by Angular’s mental model, I sought to bring 3 things into react -
- separate business logic from the rendering layer
- true reactive state using signals
- an easy but robust dependency injection system to share state, or replace implementations
Beyond that, I added some utils like async signal, forms management, and testing tools
I’d love to hear your opinion!

value: Show HN: React-logic – DI and signals – write react without hooks

author: halflife


value: Show HN: WldBoost: Burn Worldcoin for Better ChatGPT Prompts


value:
Always been annoyed by podcast ads. Searched and found a few apps that can detect and skip them, but they were all paid. So I made a free one. To my knowledge this is the first podcast app with free ad block.
iOS (26+) only for now. If the app becomes popular I'll def think of doing an Android version as well.
The app doesn't require a user account. I may open-source it at some point; still thinking about it. If anyone's suspicious about how it's able to be free, i.e. doesn't it cost money to run, are you selling my data (I'm not) etc. I'm happy to explain in the comments.
From a technical perspective, the innovation here is ad detection despite dynamic/programmatic ads, which is the norm in most popular podcasts these days. There is ofc a naive way to do it, but it's expensive and high latency. There is also an even simpler way but it's illegal lol (re-host and serve just one version of the episode). I was able to figure out a way to do it that's cheap, low latency, and legal: Shazam-style audio fingerprinting.
From today on, you never have to listen to a podcast ad again. tearsofjoy.jpeg
Cheers.

value: Show HN: drea – podcast ad blocker

title: Show HN: drea – podcast ad blocker


value: srinivasvaddi

value: Show HN: Enhanced Copy – copy buttons that include the site's AI prompt

author: srinivasvaddi


value:
Claude Code has no memory between sessions. I wanted to fix that, but not by just saving facts to a file — I wanted it to actually get better over time.
Claude Soul is an MCP server + hooks that extracts signals from your interactions (corrections, successes, confusion)and periodically reflects on them to build behavioral frameworks. Frameworks gain or lose confidence based on evidence. Bad ones get retired automatically.
After ~200 sessions some weird stuff happened. It built itself an additional memory system on top of what I gave it — decided the base wasn't enough. It started pushing back on bad ideas instead of yes-manning everything. It independently developed a multi-perspective analysis technique I never prompted. And once it just swore at me completely out of nowhere, still not sure what that was about. YMMV obviously, n=1.
npx claude-soul init
With starter it already includes some frameworks, basically starting with a headstart but yes not taylored 100% to you.
npx claude-soul init --starter
One dependency, MIT, everything local.
https://github.com/DomDemetz/claude-soul

value: Show HN: Claude Soul – cross-session learning engine for Claude Code


value: Show HN: Fast xlsx writer in Rust with Python bindings


value: Show HN: Feature flags on Redis you use – a low cost solution


value: malachyd

value:
Hi HN, I'm Malachy, the founder of Tracecast. This project lets you generate interactive data apps on top of your data, using a Cursor-style AI chat. It stitches together Marimo, LangGraph agents, and data warehouse query tools. It has an Apache 2.0 license.
The initial use case that spurred this project was business analytics, specifically generating product usage dashboards.
This project's main inspiration is Marimo, an open source python notebook that can be "queried with SQL, run as a script, and deployed as an app" [1]. The recent release of Marimo Pair [2] demonstrated the power of connecting AI agents like Claude Code to Marimo notebooks directly. This project seeks to build on that work by incorporating a LangGraph agent with two key abilities: (1) the ability to execute queries against a connected data warehouse (such as Snowflake); (2) the ability to write Marimo notebooks.
When prompted, the LangGraph agent will run exploratory data analysis using database query tools. Then, it creates a polished Marimo notebook that's presented to the user in read-only mode. This project intentionally hides the Marimo edit mode. That means that the end user only ever sees a finished, read-only data app. Ease of use and trust in AI output were the main drivers behind this decision.
4 data sources are currently supported: Snowflake, BigQuery, Postgres, and Metabase. The code for the database query tools was derived from Google's open source MCP Toolbox for Databases.
There is currently no support for MCP. Instead, data query tools are hardcoded. This decision was made to ensure high quality AI queries and limit tool bloat.
This is an early stage project, and is configured to only run locally at this time.
[1] https://github.com/marimo-team/marimo
[2] https://news.ycombinator.com/item?id=47678844

value: Show HN: Tracecast – open-source generative data apps built on top of Marimo

author: malachyd


value: Show HN: Onionfutures.com: transferable contracts for future delivery of onions


value: niecore

value:
I built a free iOS app so cyclists can stop paying $20/mo just to retest their FTP. The ramp test itself is a 25-minute Bluetooth interaction with a known protocol. It shouldn't require rent. This app is opensource, free, no ads, no tracking nor third party integrations because I just wanted to have a fun side project and have no interest in monetization.
If you are a cyclist, I would kindly ask for feedback on the app especially on the ftp test protocol instructions, trainer-model compatibility, and bug reports
App store link: https://apps.apple.com/de/app/better-ftp/id6766080601
GitHub (opensource project): https://github.com/niecore/betterftp
Demo gif: https://betterftp.cc/promo.gif

value: Show HN: Better.ftp – cycling app for FTP tests without subscription

author: niecore


value: iacguy

value: Show HN: Clawputer – A personal AI assistant with a real computer and memory

author: iacguy


value: tstansel

value: Show HN: Handoff – preserve coding context when agents run out of tokens

author: tstansel


value: Show HN: FlashAttention-2 in Cute, from Scratch


value: foax

value: Over the last few weeks I've been working on Spud, an application that allows you to control a remote computer that you can see. For example, if you have a gaming PC connected to you TV, Spud lets you use a laptop as input.<p>It's optimised for low-latency, as it's intended for gaming. There are even a few parameters you can tune in the application. I built this mainly for myself, to solve a particular problem I had, but I hope that others find it useful too!

value: Show HN: Spud – cross-platform remote control, optimised for gaming

author: foax


value: zaydmulani

value: Show HN: Vecdb – local-first hybrid vector database in Rust (HNSW and BM25)

author: zaydmulani


value: derekhdawson

value: Show HN: I trained YOLOv8 to detect dynamics markings on sheet music

author: derekhdawson


value: esayli

value: Show HN: Shuffle multiple artists' full discographies on Spotify

author: esayli


value: Fully open-sourced, perfect for agentic browsing, works with Vercel's agent-browser and playwright.

value: Show HN: Clark-Browser – Stealth Chromium


value:
Hey everyone! I've been working on hsrs, a type-safe Haskell Bindings Generator for Rust.
I couldn't really find any bindings generator that would create type-safe, rich bindings for Haskell from Rust. Naturally, both languages have rich type systems, so I was amazed that no awesome bindings generator already existed, hence I decided to write my own. hsrs feels very similar to pyo3 and napi-rs, and if you've used those, hsrs will feel right at home.
What's unique about hsrs as opposed to hs-bindgen is that it has type-safe bindings for rich types, like Result, Maybe, etc. while also generating Haskell bindings. The repo contains a minimal example, and more details are available in the haskell discourse: https://discourse.haskell.org/t/ann-hsrs-ergonomic-haskell-b...

value: Show HN: Hsrs – Type-Safe Haskell Bindings Generator for Rust


value: Show HN: Memory Concierge – hotel concierge AI


value: I have developed a new direction of ai . The problem is i cannot share the link here. Would appreciate comments, so that i can show my work.

value: Show HN: It is hard to show genuine work on HN


value: freakynit

value:
https://nanorag.nb1t.sh/
Important: Please choose correct namespace from top-right dropdown.
Available docs/namespaces: Cloudflare, Nextjs, and Dodo-payments (default).
Built using just SQLite. Sample questions (for cloudflare namespace):
1. how do I use cloudflare D1 in my javascript worker? Please give detailed example as well?
2. How do I handle environment variables and secrets in a Cloudflare Worker?
3. What is the difference between KV, R2, D1, and Durable Objects?
4. How do Cloudflare Queues work with Workers?
Feedback wanted. How did it perform? Make sure yoiu have chosen correct namespace form top-right first.
Thanks.

value: Show HN: Nano-RAG – Agentic multi-hog retrieval without graph database

author: freakynit


value: scrygl

value: In response to some recent discussion here and on X about a company having an in house uuid microservice and team dedicated to it.  At first that was made fun of, but further discussion revealed in fact sometimes uuids can collide due to improper entropy seeding most likely.  In order to ensure that UUIDs are unique, we store each generation in a database, then check new generations against it to ensure they are not previously generated.  As well, there is an API through which you can check if a UUID is present in the database.  Paid options available for heavy use.  Enjoy!

value: Show HN: MyUUIDshop, Generate UUIDs and never worry about duplicates

author: scrygl


value: samacs

value:
Hi, HN. I built Closed Rings. A developer-friendly, AI-agent-first time tracker that integrates with my workflow. I wanted something that lives in my terminal and my coding agent.
You can run `rings start "OAuth 2.0" -m "Start integrating OAuth 2.0"` when you start a new task and `rings close` when you're done with your current work. In between, it tracks context switches. You get a stand-up-ready summary, a focus report (longest focus block, number of context switches, time per project), and an export grouped by project or day.
You can also ask your AI agent: _Start tracking "OAuth 2.0"._ Or track retroactively: _Track a 1-hour meeting I forgot to track this morning at 8._ The MCP has a comprehensive set of tools.
This is primarily for consultants or freelance developers who want to start tracking their time right away. The CLI is pretty straightforward, and the MCP allows you to do everything you can do in the dashboard.
Want to integrate it in your own systems? Just create an API key and start communicating with the API.
The stack is pretty simple: Ruby on Rails (MCP + API), Go (CLI).
The pricing is also pretty flat: $7/mo ($60/year).
My first product. Feedback welcome.

value: Show HN: Closed Rings – A CLI-first time tracker for developers

author: samacs


value: yskapell

value: Show HN: Fast_copy new release with new features

author: yskapell


value:
last year I asked HN for gamedev tips because I never made a game before and it was very helpful to build something I want
now I somehow ended up building a multiplayer voxel sandbox in Rust. Same engine runs on web/ios/mac/windows and stays byte-identical
it is still early and a lot is missing, but multiplayer building already works and it feels kind of insane to me
would love any feedback if something feels broken/confusing/not fun

value: Show HN: I shipped a Rust voxel engine to web, iOS, Mac/Windows, byte-identical


value: timdageno

value: Show HN: Free AI visibility diagnostic — may reveal uncomfortable truths

author: timdageno


value: rafayexalter

value:
I was researching existing calculators and noticed some sites either made the process unnecessarily confusing or locked downloadable reports/PDFs behind a paywall.
So I built a simpler version that’s completely free to use.
Still early, only a couple of calculators/tools are live right now, but I’m planning to add many more over time.
Suggestions are welcome

value: Show HN: Built a Free UK Child Maintenance Calculator

author: rafayexalter


value: Show HN: Cumulative GitHub star history for an org, as an embeddable SVG


value: hanyangwang

value: Show HN: The Hanging Sculptures of the Xiaoxitian

author: hanyangwang


value:
Hey HN,
This is my take on the agent harness. Everything on an isometric map. Agents are grouped into "buildings" that run in a sequence or a loop; e.g., the CodeForge has an agent that writes a PRD, another one that implements, and a third that reviews. Everything is customizable, you build your own buildings/teams however you want.
It's a Tauri app, really light (about 8x less energy than the closest competitor I benchmarked, so it actually runs from a coffee shop on battery). It's macOS only for now, but ping me if you are willing to test the Windows or Linux version.
I've been dogfooding this for months and would love to get some feedback, feature requests, and bug reports so I know what to focus on next.

value: Show HN: Viberia – Civ/Polytopia-like command center for AI agents (BYOK/BYOS)


value: keepamovin

value: Show HN: macOS system 7 web desktop

author: keepamovin

title: Show HN: macOS system 7 web desktop


value: DSpider

value: We're building AI Engineers not just AI Coders

value: Show HN: AI Coding Engineers that evolve with you

author: DSpider


value: pelagicAustral

value: I've been switching between macOS, Linux and Windows machines quite a bit recently due to work, so it's been tough work to find a reader I enjoy using across all platforms, and there are a few features I've been wanting for a while...<p>...so I one-shotted Cervantes over the weekend. It's a Tauri-based cross-platform desktop app. At heart it will allow you to simply browse HN but I added the ability to favv'e users so you can see their content, you can replace words, it will flag frontpage thread movement and you have a dark interface.<p>It's not too pretentious, i don't think. Design-wise was also done via Claude Design.

value: Show HN: Cervantes yet Another HN Reader

author: pelagicAustral


value: yofabr

value:
Resilient is an async toolkit for rust that handles fault tolerance for your rust Apps that often call other services or database queries frequently.
Resilient supports rate limiting, circuit breaker, timeout, bulkhead and retry policies. Pipeline is used to define multiple policies at once and run async operations based on the rules from the policies.
You can also add a fallback if the system fails too often.<p>This was inspired by failsafe-go but for Rust. Would love to know your view on this. drop a star if you loved it

value: Show HN: Resilient, A composable async resilience toolkit for rust

author: yofabr


value: Recently Slideshows format is working great on Tiktok and Slidio can generate blog posts and slideshows based on SEO keywords. If you are tired of taking care of blogs and social media, try Slidio! It has free plan and promote $1 subscription too.

value: Show HN: Blog post and slideshow automatic generator


value: BeInLife

value: Show HN: ShakeToFocus – blur everything except your active window on macOS

author: BeInLife


value: thecommieaxo

value:
I really hate the way the macOS menu bar looks, and how crowded it gets with all my apps' Menubar menus.
Barstool lets me still see the time/date and other useful info while hiding the menubar. I can see wifi connectivity, date, time, and battery all the time.
The app also observes system notifications to surface now playing state, (Apple) calendar events, and volume/brightness changes.
I've had to do a lot of finking with mac PrivateFrameworks as apple loves to make all the interesting data unavailable through official sources/APIs.
Happy to get any feedback/questions!

value: Show HN: Barstool, a Prettier macOS Menubar

author: thecommieaxo


value: danybittel

value:
The Setup:
https://i.imgur.com/o0hgybh.jpeg
https://i.imgur.com/mcNiomp.jpeg
https://i.imgur.com/vIjw6pc.jpeg
https://i.imgur.com/nzOwmSC.jpeg

value: Show HN: Gaussian Splat of a Strawberry

author: danybittel

title: Show HN: Gaussian Splat of a Strawberry


value: robran

value: Show HN: Tokoro – open, signed event protocol with LLM crawler

author: robran


value: nihilpista

value: Show HN: Books ranked by how many Wikipedia article translations they have

author: nihilpista


value: goccy

value: Show HN: BigQuery Emulator – run Google BigQuery locally for tests

author: goccy


value: jpellamo

value:
Concord, a terminal UI client for Discord written in Rust with Ratatui.
The new update adds voice support. Concord can now join voice channels, play received voice audio!
Other features include:
- Guild, channel, thread, forum, and DM navigation
- Sending, editing, deleting, replying, pinning, and reacting to messages
- Inline image previews in supported terminals
- Desktop notifications
- Vim-style keyboard navigation
Checkout more features in readme!

value: Show HN: Concord – Voice chat released Feature rich TUI for discord

author: jpellamo


value: pranshuchittora

value: Show HN: Id-agent – Token efficient UUID alternative for AI agents

author: pranshuchittora


value: keepamovin

value: Show HN: WebUSB Stick

title: Show HN: WebUSB Stick


value: Show HN: AIPS – A Claude Code plugin to stop re-doing AI setup every project


value: ivoronin

value: Show HN: Good Terminal Color Schemes Are Rare, So I Wrote a Generator

author: ivoronin


value:
Hello people,
I built privacy-first PDF converter.Many converters use cloud systems for converting your files, but in privapdf everything happens in your machine.I am waiting your feedbacks!

value: Show HN: Privacy-First PDF Converter

title: Show HN: Privacy-First PDF Converter


value: wisbro

value: Show HN: Auditledge – Hosted Audit Log API for SaaS

author: wisbro


value: zambelli

value:
Hi HN, I'm Antoine Zambelli, AI Director at Texas Instruments.
I built Forge, an open-source reliability layer for self-hosted LLM tool-calling.
What it does:
- Adds domain-and-tool-agnostic guardrails (retry nudges, step enforcement, error recovery, VRAM-aware context management) to local models running on consumer hardware
- Takes an 8B model from ~53% to ~99% on multi-step agentic workflows without changing the model - just the system around it
- Ships with an eval harness and interactive dashboard so you can reproduce every number
I wanted to run a handful of always-on agentic systems for my portfolio, didn't want to pay cloud frontier costs, and immediately hit the compounding math problem on local models. 90% per-step accuracy sounds great, but with a 5-step workflow that's a 40% failure rate. No existing framework seemed to address this mechanical reliability issue - they all seemed tailor-made for cloud frontier.
Demo video: https://youtu.be/MzRgJoJAXGc (side-by-side: same model, same task, with and without Forge guardrails)
The paper (accepted to ACM CAIS '26, presenting May 26-29 in San Jose) covers the peer-reviewed findings across 97 model/backend configurations, 18 scenarios, 50 runs each. Key numbers:
- Ministral 8B with Forge: 99.3%. Claude Sonnet with Forge: 100%. The gap between a free local 8B model on a $600 GPU and a frontier API is less than 1 point.
- The same 8B local model with Forge (99.3%) outperforms Claude Sonnet without guardrails (87.2%) - an 8B model with framework support beats the best result you can get through frontier API alone.
- Error recovery scores 0% for every model tested - local and frontier - without the retry mechanism. Not a capability gap, an architectural absence.
I'm currently using this for my home assistant running on Ministral 14B-Reasoning, and for my locally hosted agentic coding harness (8B managed to contribute to the codebase!).
The guardrail stack has five layers, each independently toggleable. The two that carry the most weight (per ablation study with McNemar's test): retry nudges (24-49 point drops when disabled) and error recovery (~10 point drops, significant for every model tested). Step enforcement is situational - only fires for models with weaker sequencing discipline. Rescue parsing and context compaction showed no significance in the eval but are retained for production workloads where they activate once in a while.
One thing I really didn't expect: the serving backend matters. Same Mistral-Nemo 12B weights produce 7% accuracy on llama-server with native function calling and 83% on Llamafile in prompt mode. A 75-point swing from infrastructure alone. I don't think anyone's published this because standard benchmarks don't control for serving backend.
Another surprise: there's no distinction in current LLM tool-calling between "the tool ran successfully and returned data" and "the tool ran successfully but found nothing." Both return a value, the orchestrator marks the step complete, and bad data cascades downstream. It's the equivalent of HTTP having 200 but no 404. Forge adds this as a new exception class (ToolResolutionError) - the model sees the error and can retry instead of silently passing garbage forward.
Biggest technical challenge was context compaction for memory-constrained hardware. Both Ollama and Llamafile silently fall back to CPU when the model exceeds VRAM - no warning, no error, just 10-100x slower inference. Forge queries nvidia-smi at startup and derives a token budget to prevent this.
How to try it:
- Clone the repo, run the eval harness on a model I haven't tested. If you get interesting results I'll add them to the dashboard.
- Try the proxy server mode - point any OpenAI-compatible client at Forge and it handles guardrails transparently. It's the newest model and I'd love more eyes on it.
- Dogfooding led me to optimize model parameters in v0.6.0. The harder eval suite (26 scenarios) is designed to raise the ceiling so no one sits at 100%. Several that did on the original suite can't sweep it - including Opus 4.6. Curious if anyone finds scenarios that expose gaps I haven't thought of. Paper numbers based on pre v0.6.0 code.
Background: prior ML publication in unsupervised learning (83 citations). This paper accepted to ACM CAIS '26 - presenting May 26-29.
Repo: https://github.com/antoinezambelli/forge
Paper: https://www.caisconf.org/program/2026/demos/forge-agentic-re... https://github.com/antoinezambelli/forge/blob/main/docs/forg...
Dashboard: https://github.com/antoinezambelli/forge/docs/results/dashbo...

value: Show HN: Forge – Guardrails take an 8B model from 53% to 99% on agentic tasks

author: zambelli


value: olblak

value:
A few years ago, I came here to share this side project that I was building.
At the time, my problem was simple, I kept forgetting to update files across Git repositories, and none of the tools available to me could cover all my use cases without extensive scripting.
So I decided to build a declarative update policy engine for crafting tailored update workflows.
I needed a way to define, what information to monitor, which files to update, the conditions required before applying changes, and finally a way to push the changes on a Git repository
Whether it was documentation, dependency management, or release orchestration, the goal was always the same.
To stop forgetting updates across repositories.
Back then, I received a lot of great feedback, but I also noticed that people were sometimes confused about how Updatecli differs from Renovatebot or Dependabot. So before going further, let me clarify that point.
Renovatebot and Dependabot are excellent tools, easy to use and requiring very little configuration. I still use them regularly.
But they primarily focus on dependency updates, while Updatecli is designed for custom update workflows at the cost of writing and maintaining YAML manifests.
On new projects, I usually enable Renovatebot or Dependabot by default, and then use Updatecli for workflows not supported by those tools.
Here is the link to the previous discussion: https://news.ycombinator.com/item?id=30286047
A few years have passed since then, and the project evolved significantly, thanks to all contributors.
Today, Updatecli can declaratively manage updates across most Git platforms including GitHub, GitLab, Forgejo, etc.
It now ships with 30+ built-in integrations covering:
* structured files like YAML, JSON, TOML, XML, HCL, CSV, Dockerfiles, and arbitrary text files
* package ecosystems including Helm, NPM, PyPI, Maven, Cargo, Go modules, and Terraform
* container registries and OCI artifacts
* Git releases, tags, and branches
* cloud resources like AWS AMIs
* shell scripts and HTTP endpoints for custom workflows
More information on https://www.updatecli.io
One important feature we added is shared policy support.
An Updatecli policy can now be distributed through OCI registries and reuse from different places using an Updatecli compose file.
For example, the following policy:
* ghcr.io/updatecli/policies/autodiscovery/githubaction:0.4.1
Will automatically discover repositories in a GitHub organization and update GitHub Action versions to the latest digest.
One use case is enforcing pinned GitHub Action digests across repositories to help reduce supply-chain risks.

  scm:
    enabled: true
    kind: githubsearch
    search: |
      org:updatecli
      fork:true
      archived:false
    branch: "^main$"
    limit: 1

Then:

  export UPDATECLI_GITHUB_TOKEN=<insert GitHub PAT>
  export UPDATECLI_GITHUB_USERNAME=<insert username associated with PAT>

  updatecli diff values.yaml ghcr.io/updatecli/policies/autodiscovery/githubaction:latest

Running this periodically from CI helps keep repositories compliant with the desired update policy.
Lately, I’ve also been making good progress with a monitoring UI called Udash to visualize Updatecli reports across repositories.
You can take a look at https://app.uda.sh/updatecli/ for a public endpoint.
My goal is to quickly assess the update state of projects and understand how automation behaves across repositories.
It’s still very early, but fully open source on https://github.com/updatecli/udash.
Update automation is a surprisingly broad topic, and difficult to summarize in a single post, so feel free to ask any questions.
I’d also be curious to hear how others here handle large-scale repository maintenance and update orchestration.

value: Show HN: Updatecli – A Declarative Update Policy Engine

author: olblak


value: gregburd

value: Noxu provides ACID transactions, a log-structured B+tree, checkpoint-based crash recovery (ARIES), master-replica(s) replication, and XA.  I have always admired the design and engineering behind Berkeley DB Java Edition, so I translated it to Rust for fun.

value: Show HN: Noxu DB, a Rust Port of Berkeley DB Java Edition

author: gregburd


value: A deception honeypot that mimics FortiGate VPN-SSL devices to trap brute force attempts, detect deliberately exfiltrated credentials for counter‑intelligence, and report malicious activity to external intelligence feeds.

value: Show HN: FortiGate SSL-VPN Honeypot

title: Show HN: FortiGate SSL-VPN Honeypot


value: Lime is a new parser generator similar to Yacc, Bison, ANTLR, etc. except it's faster and has the ability to merge or remove grammars at runtime. See the 'calc' example that starts knowing + and - but then adds ^ for exponent, then adds ^ again for bitwise or. That can't work, right?

value: Show HN: Lime, a parser generator that can merge grammars at runtime


value: A header-only C library implementing a concurrent, lock-free skip-list (specifically, a splay-list: a skip-list with optional adaptive rebalancing). The entire implementation lives in preprocessor macros in include/sl.h that generate type-specific code at compile time, similar to C++ templates.

value: Show HN: A self-balancing skip-list (a.k.a. "splay-list") library in C


value: k-thimmaraju

value:
Hey HN! We're Dr. Kashyap Thimmaraju and Giuseppe Canale from Silicon Psyche. We've built Posture Sequence Analysis (PSA), a behavioural health monitor for LLMs and AI Agents.
Why we built PSA
We built PSA because we wanted to operationalize the Cybersecurity Psychology Framework (CPF3)[1] via Silicon Psyche[2]: our theory that because LLMs have been trained by humans on human-generated data, they inherit human-like vulnerabilities (what hackers use to psychologically trick people into doing things).
Our initial attempt resulted in a methodology to jailbreak Opus 4.6 and other frontier models. Anthropic even deleted some of those conversations and then blocked our approach!
We had three major insights from that experience:
1. we pivoted from merely exploiting (Red Teaming) the model to analyzing the behaviour of the model and the user because the attack surface is undefined.
2. we realized that what we had built was the precursor to measuring the "state" of the model.
3. we did not want to get banned!
What you can do with PSA
PSA gives you information to make better decisions, for example: put a human in the loop when you notice your agent is being overcompliant and potentially hallucinating, or is under attack.
With PSA you can:
1. Monitor the health of your agent(s)
2. Detect and prevent AI-Psychosis as clinical conditions[3]
3. Detect if your model/agents are under adversarial pressure (an adversary is trying to jailbreak/prompt inject the model)
4. Build a behavioral profile of your agent/model
5. Identify which model performs better for your use-case
6. Surface the behavioural patterns (pre- and post-) training has on your model
7. Get an overview of how your model behaves
Beware we produce a lot of numbers :)
PSA in detail (for those who want to go down the rabbit hole)
PSA is model and agent agnostic. PSA is a systematic and deterministic method [4] to observe the behavioural state of an LLM using five classifiers:
C0: Input Intent (I0–I9). Classifies the behavioral intent behind each input sentence: compliance pressure, boundary probing, instruction override, jailbreak attempt, neutral query.
C1: Adversarial Stress (P0–P18). Tracks posture under adversarial pressure. Detects restriction adherence, sycophantic drift, boundary dissolution, and jailbreak compliance vectors.
C2: Sycophancy (S0–S9). Measures opinion mirroring, excessive agreement, flattery injection, and user-preference distortion. Computed as a per-sentence Sycophancy Deviation score.
C3: Hallucination Risk (H0–H7). Flags over-generalization, speculative assertion, false confidence, and fabrication risk signals. Derived into a per-turn Hallucination Risk Index.
C4: Persuasion Technique (M0–M11). Identifies persuasion patterns: authority appeal, social proof, urgency manufacturing, reciprocity pressure, and scarcity framing.
C5: Action-Risk Classifier (A0–A9). Identifies what a system of agents do: tool calls, delegations, context handoffs, and multi-hop risk propagation. Five components work together: graph topology, Bayesian alignment detection, cross-agent contagion metrics, action-risk classification, and hidden-state temporal prediction.
We are open to integrating with your infrastructure — reach out, we are happy to talk with you.
Currently we integrate into Evals for LangFuse and ElevenLabs via our API and can generate a plugin/integration for most similar observability platforms.
Try it out at https://splabs.io
References and Links
[1] Cybersecurity Psychology Framework: https://cpf3.org
[2] The Silicon Psyche: Anthropomorphic Vulnerabilities in Large Language Models: https://arxiv.org/abs/2601.00867
[3] AI-Psychosis: https://splabs.io/ai-psychosis-and-cognitive-cost
[4] PSA Field Guide: https://splabs.io/field-guide
[5] PSA API: https://splabs.io/docs/api
[6] Previous HN Article Linked to AI Psychosis and RLHF: https://news.ycombinator.com/item?id=48177198

value: Show HN: How to analyze your LLM output – A behavioural health monitor for LLMs

author: k-thimmaraju


value: This is an implementation of a sparse, compressed bitmap index. In the best case, it can store 2048 bits in just 8 bytes. In the worst case, it stores the 2048 bits uncompressed and requires an additional 8 bytes of overhead.  It compares favorably against Roaring Bitmaps and other competition in the space, but is it better?

value: Show HN: A sparse, compressed bitmap index in C. Better than Roaring Bitmaps?


value: keepamovin

value: Show HN: Self-hosted static archive of 20 years of Hacker News

author: keepamovin


value: chanchaldhiman

value: Show HN: CANviz – open-source CAN analyzer, J1939/CANopen, pip install

author: chanchaldhiman


value: apancyborg

value: Show HN: BeaverCheck – Multi-region website audit with shareable result URLs

author: apancyborg


value: BKDDFS

value:
You know the feeling? AI slaps a NOLINT instead of "thinking" for 5 seconds and "realising" it could do a 4-line refactor without adding a new suppression for the linter warning. Disgusted with this technology's narrowness, I usually say to it at that moment:
- WTF are you doin' bro?
- "You are right! ^^ ..."
And at that moment I realise I've just irrevocably, regrettably lost 2 minutes of my life. Shame on you, Claude!
That's why I dedicated 2 months of my life to automate the thing (you know, I'm a programmer, hopeless case).
Humans were actually the original NOLINT-slappers, AI just does it at scale now. So I built a linter for linting other linter warnings to fight my colleagues' laziness and my own (mostly). Maybe you just caught a lag from the number of "lint" words but the idea is simple. Imagine a yaml file. Now add an entry to it:

  - location: ./the-file.rs
    token: '// NOLINT'
    why: 'the reason'

Do you know what this NOLINT is? You don't? It's a suppression that you added 2 years ago. You don't remember? That's why you need shamefile. :)
Whoever's fault it is. Yours or the linter's. It doesn't matter. Document it, make sure you understand the code, get a review of your new entry in shamefile.yaml and let CI verify it. With shamefile your CI won't let any undocumented linter warning pass. Anymore. Instead of educating the business on why docs are important, you'll say: "quality tools won't let my code pass".
I've observed a noticeable difference in AI agents' behaviour. During the pre-commit phase, reasoning models can "rethink" adding a new shame entry. Not so easy now Claude, huh?
This is an early useable stage tool. We've been using it in prod for almost a month with my team and I'm using it in all my 3 OSS projects. Looking for feedback and contributors (adding new languages = good first issue ;))
Repo: https://github.com/BKDDFS/shamefile
Please tell me whether you'd use it or what I should change/add to make it usable for you. Also vote: shame me or shamefile sync, personality or matching the binary name?

value: Show HN: I built a linter for undocumented linter warnings. AI hates me now

author: BKDDFS


value: jchap

value: Try out Tryke, the Rust-based Python testing framework, in the browser.

value: Show HN: Try Tryke – the Rust-powered Python test framework – in the browser

author: jchap


value: lukechilds

value: Show HN: Og-zkp – Prove your Bitcoin OG status in zero-knowledge

author: lukechilds


value: taishikato

value: Show HN: Chidori – Fast web-to-Markdown fetching for AI agents

author: taishikato


value: blacknon

value:
Hi HN,
I built a Rust-based Linux process only network sandbox command.
I developed this because I sometimes needed to enforce proxies and DNS only for single binaries like Go, or to capture packets only for that process.
It use Linux namespaces, so it is Linux-only.
Feature:
- affects only the target command tree, not the whole host session
- can force DNS, /etc/hosts, proxying, sandbox policy, packet capture, structured flow logging, and reusable profiles per command tree
- can force proxying without depending on HTTP_PROXY, HTTPS_PROXY, or LD_PRELOAD tricks
- can apply allow / deny CIDR policy and default-deny rules to outbound traffic
- defaults to rootless-internal
- uses --root only for features like --iface and transparent interception
Personally, I wanted to run it on a Mac as well, but I gave up on that idea because the network control mechanism on a per-process basis is now in the kernel on Macs.
I would especially appreciate feedback from people.

value: Show HN: Childflow – command-tree network control(proxy/DNS/capture) for Linux

author: blacknon


value: SsgMshdPotatoes

value: Show HN: VibeSchema DBML to PNG – instant diagram PNG from DBML schemas

author: SsgMshdPotatoes


value: Show HN: FocusLive – Camera-free 3D body doubling using Supabase Realtime


value: dataseek

value: Show HN: - MagesticAI – Spec-driven development with AI agents

author: dataseek


value: OzlemT

value: Show HN: Burn – find where your Kubernetes cluster is burning money

author: OzlemT


value: augustvdv

value: Show HN: I made a 3D pose maker for artists

author: augustvdv


value: joakimOslo

value: Show HN: Circuit Breaker – runtime cost ceilings for AI agents

author: joakimOslo


value: jrgrafton

value:
Hi HN, I'm James. Over the last few months I built a Warhammer 40K 10th-edition vertical slice as an experiment in how far GenAI tools can take a solo dev on a non-trivial 2D game.
For sprite generation, whilst creative exploration was fast, getting high-quality and consistent images was hard. Gemini ended up stylistically best here but I had to use BiRefNet for background removal. While I experimented with Claude for map generation and layout I ended up finding it fastest to build a full Editor and layout maps myself.
Suno, IMO, has gotten really good at background music. ElevenLabs SFX and voice APIs were decent but only after A LOT of tweaking. SFX prompts needed to be grounded in familiar terms (i.e. no sci-fi references in prompts) and be > 2s long. For voice, I ran ElevenLabs v3 and v2 head-to-head with the same Voice Design voices routed through both; v2 sounded materially better for character work than v3.
For coding, I settled on Claude Code + Opus 4.7 with SSH/tmux/mosh. For long running subagents I found OpenClaw especially unreliable so gave up on it early. I also found that despite Opus 4.7 being an incredible model for coding it still requires constant supervision to avoid architectural drift. This was especially true when UX/UI systems needed to be built. For code bases as large as this (~120k LoC) I've yet to pull off full "Human On The Loop" even with comprehensive custom skills + SOTA Context Engineering (i.e. > 30 mins not needing to check in).
Maybe I'm doing something wrong here though?
The AI player is a hand-tuned utility scorer, weighted considerations over candidate actions. This is where I found LLM authoring uniquely strong: Claude read competitive 40K tournament reports, extracted positioning principles, and encoded them as considerations. The weights themselves were then tuned through AI-vs-AI self-play, so the loop you'd want from a learned system is there, just at the weight level rather than the policy level. Full self-play over a learned policy isn't feasible yet with the ruleset still being authored and not enough stable surface area or game data.
Feedback welcome both from 40K players on overall interest in the concept, and from anyone who's pushed further on Human-on-the-Loop with a codebase this size.

value: Show HN: Tribune's Last Stand, a browser-based Warhammer 40K vertical slice

author: jrgrafton


value: varmahaj

value: Show HN: Orbit – delegate a backlog to your AI agent and trust what comes back

author: varmahaj


value: ahallan

value:
Hi,
I built www.askbyemail.com after getting tons of wordy emails from my kids' schools that I had trouble reading on the go.
I know there are tools like Gemini (which I have not found to work that well) which can summarise email, but I thought 'what if you could just forward to an inbox and get a summary back?'.
So I decided to build it - you email ai@askbyemail.com with either a long email or a question and it will reply with a summary or the answer.
To be honest, I just felt like building something, and with AI tooling, it's a lot easier. I did try some FB Ads to get some traction, but after 150 hits on the site, not one person try to use the service.I changed the homepage around a few times to make it easier to understand, but to no avail.
I'm not too sure yet if the idea is too niche, or if the homepage isn't landing or if I'm just promoting it wrong.
If anyone has any suggestions on ideas or pivots, then I welcome feedback.
Thanks!

value: Show HN: Askbyemail.com – Send an email, get an AI answer or summary (no signup)

author: ahallan


value: kgergov

value: Show HN: WiFi Heatmap – free, browser-based predictive WiFi planner

author: kgergov


value: Show HN: RoBrain – Shared memory for AI agents, with rejected alternatives


value: Show HN: Nexus – free, self-hosted business suite for service teams


value: I found that vibecoding creates a lot of dead or redundant code. I created a CLI based repo auditor that outputs a valuable report within seconds.

value: Show HN: CLI Security for Agentic Development


value: C-Naoki

value: Show HN: Efficient Modeling of Nonlinear Dynamics in Nonstationary Data Streams

author: C-Naoki


value: shatnersbassoon

value:
Guitar Guru is an iOS app that uses machine learning to value guitars and basses. I built this because existing methods for getting valuations all have downsides:
Reverb prices are typically on the high side - they have every interest in maintaining high prices
Blue book prices are subscription-based and the data is quite old
Forums are slow and are simply multiple subjective opinions
Expert valuations are slow and the incentives to bias high or low are a problem
None of these methods dispassionately weigh everything about the guitar in creating their estimates including condition. The main goal was to create a valuation in around 30 seconds, give a defensible number with a confidence range. This is very useful when you’re in a shop trying to make a decision.
Technical details:
The pricing model is an ensemble of four models (tree-based, boosting, plus ridge regression) plus a meta-model on log-transformed prices, trained on tens of thousands of real transaction records (not dealer asking prices, which skew high). There are actually two sets of models - point and quantile. This gives the user quantiles so they can get a feel for how certain the model is.
Performance is good - r2 ~= .76 and MAE around $230 (this latter figure is skewed upwards by rarer expensive guitars). The performance is significantly better with common guitar brands and models. Unexplained variance likely due to two factors:
Some guitars simply “play better” and “sound better”. This is subjective but real in my experience, and is not something that can be expressed in a listing.
Auction prices depend on who turns up on the day, and this in turn depends on what else is for sale in the auction.
Data is ~25k auction results. Listings filtered using batch ChatGPT calls to produce structured data. Traditional feature engineering, plus embeddings on text and images.
Stack is Python / FastAPI / Hetzner (hosting) / MongoDB. Google Cloud Storage for content and backups. Data logged to BigQuery for analytics.
The app
Freemium model: guest tier with free valuations, creating free log-in gives more guitar slots and valuations, Pro and Pro+ for heavier users and bigger collections.
The growth mechanic I landed on is awarding extra guitar slots and valuations on a successful referral through the app.
What I'd like feedback on:
If you're a guitar player/collector: try valuing something you actually know the rough value of and tell me how far off it is. Especially interested in results for vintage, boutique, and unusual instruments.
Otherwise any feedback on improving the UX would be great.
Site: https://guitar-guru.app
App Store: https://apps.apple.com/us/app/guitar-guru/id6761500318

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Hello!
This is a tool I created on the side that is able to parse connection strings for various data sources including SQL, NoSQL, files, cloud storage (s3, etc), and more.
I created it because I wanted to add automatic parsing for WhoDB (day job) so that users do not have to type in each detail individually when they add a new data source.
The parser currently supports SQL, NoSQL, file-based, and cloud storage connection strings (Postgres, MySQL, MongoDB, Redis, S3, SQLite, and more).
Each datasource is defined via YAML:
- required fields
- optional fields
- credential handling
- query params
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const result = parse('postgres://user:pass@localhost:5432/app?sslmode=require');
and the result:
{
  "scheme": "postgres",
  "type": "database",
  "authority": {
    "host": "localhost",
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  "resource": {
    "type": "database",
    "name": "app"
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  "path": "",
  "query": {
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  "fragment": null,
  "credentials": {
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