value: nexdrew

value:
# What?
Introducing mkdnsite ("markdown site") - an open source Markdown-native web server that serves HTML to humans and raw Markdown to agents. No build step required. Runs on Bun/Node/Deno, as an OS-specific standalone executable, or as a Docker container. Possibly the easiest way to go from Markdown files to functional website in the new agentic era.
Features:
- Runtime-only, zero build
- Content negotiation means HTML for browsers and Markdown for agents
- Supports GitHub-Flavored Markdown rendering
- Mermaid diagrams, KaTeX math, embedded Chart.js charts, syntax highlighting all included
- Full-text search for humans, MCP tools for agents
- Customizable UI theming with auto-support for light/dark modes
- Pull Markdown files directly from a GitHub repo
See official docs at https://mkdn.site
# Why?
Back in February, I saw Cloudflare's announcement of "Markdown for Agents" (https://blog.cloudflare.com/markdown-for-agents/). At the time, I thought "so I'm writing my API docs or blog in Markdown and converting it to HTML for a website, only to have Cloudflare turn it back into Markdown for AI/agent consumption". This seemed odd to me.
I'm a Node.js developer but had recently been building projects on Bun because of the "batteries included" features, like cross-compilation of standalone executables (similar to Go), that Node.js lacked natively (yes, I'm aware of Node SEA, but it's messy/complicated and `bun build --compile` is not).
Then, when I found `Bun.markdown`, something clicked for me - building a web server that converts Markdown to HTML at runtime should be super easy. And agents actually want Markdown, so why not combine the two ideas?
Humans like writing Markdown (well, at least, I do) and agents like reading Markdown (less verbose, easier to grok, fewer tokens). Add to this the fact that we can now use AI to write software, and my side project was born.
Is Markdown-to-HTML a new concept? Absolutely not. It's pretty old and well-established. But what I think is new is the ability to do everything at runtime (no build step required) and the built-in support for AI agents. mkdnsite has content negotiation, automated llms.txt, an MCP server, and support for agent headers.
# How?
I worked with Claude to refine the idea and come up with basic requirements/specs and then had Claude build me a scaffolded project. I started the project on March 7.
The following Friday, I configured my first set of OpenClaw agents on my personal machine and set them up to use Slack. From that point on, I spent most evenings and every weekend building mkdnsite and a hosted service (at https://mkdn.io) by logging ideas as issues in GitHub and talking with my "team lead" agent on Slack to pick up the work and implement features.
mkdnsite v1.0.0 was released on March 16. The current version is v1.4.1 released March 28. Almost every line of code was written by AI, either via an autonomous OpenClaw agent or via individual Claude Code sessions.
# So what?
Just looking for some honest feedback. Is this useful? Is it dumb? Is there another tool that offers the same combination of features (I looked and couldn't find one)?
I am not downplaying SSGs at all. I quite like Astro. And I love GitHub Pages. I just think there's room for an easier/simpler solution.
Please try it out and let me know what you think. Thanks.

value: Show HN: Mkdnsite – Markdown-native web server for humans (HTML) and agents (md)

author: nexdrew


value: ramoz

value: Show HN: Continuously Improve Claude Code Plans

author: ramoz


value:
Disclaimer: this is vibe-coded — (<- I lost you there) the README, most of the code, and the binary format reverse-engineering were done with Claude. But the tool works and I use it everyday for some days now. As Baudelaire said "qu'importe le flacon, pourvu qu'on ait l'ivresse."
~I~ Claude built a tool that decodes Figma's internal binary protocol (Kiwi format over WebSocket) to extract the full scenegraph — every node, vector path, and style — without hitting the REST API.
Why: Figma's REST API has aggressive rate limits. The official MCP server requires a paid Dev Mode plan. I needed to explore designs from my AI coding tools without constantly getting 429'd.
It helps me to:

  1. extract the svg in a clean way (even the SVG export from figma likes to write the path as 12.0000001, even though the protocol does have 12 in it)  and images

  2. Get mapping from what I see in figma <-> what i see in the exported html

  3. It helps me help our designer to produce an actual "resizable" figma, so that they finally understand the pain of "ok it works when you click play on the iphone 17 frame you put, but what about an iphone12 ?" (I was always able to say that, but before I wasn't able to point out what was wrong, now I can)

How it works: When you open a Figma file in the browser, the editor loads the entire scenegraph via WebSocket as Kiwi-encoded binary frames. This tool captures those frames via Chrome DevTools Protocol, decodes the binary data (including two undocumented vector formats), and gives you structured JSON.
What Claude reverse-engineered:

  - The fig-wire frame format (schema delivery over WebSocket)

  - commandsBlob: Figma's pre-computed SVG path commands (MoveTo, LineTo, CubicBezier, ClosePath)

  - vectorNetworkBlob: the editable path data (vertices, segments with Bezier tangent handles, regions with loops)

  - All three are documented as Kaitai Struct specs (.ksy) so you can generate parsers in any language

Ships as: JS lib (zero deps), CLI, MCP server (Cursor/Windsurf/VS Code), and Claude Code plugin.
Binary format specs, sample fixtures, and everything else: https://github.com/allan-simon/figma-kiwi-protocol
I'm not a lawyer but my understanding is this is an interoperability tool under EU Directive 2009/24/EC Article 6. No Figma code is included: it only decodes the wire format of data transmitted to your own browser.

value: Show HN: I/Claude reverse-engineered Figma's binary WebSocket protocol


value: chabes

value:
Hi HN.
Tl;dr: An attempt was made to build a remake of the original r/place. The repo is now public, and I'd love feedback, contributions, and the like. Demo (very much alpha) is here: https://chabes.neocities.org/place/
This is a hobby project I have been playing with for a few days. It is an llm-assisted attempt at a nostalgic clone of the 2017 April Fools (9 years ago today) reddit experiment r/place[1][2]. My intention is to have a working version by the 10 year anniversary coming up a year from today.
A demo can be interacted with here: https://chabes.neocities.org/place/
I don't expect this to get huge traction on HN, but please don't hug to death, regardless. It is semi-functional, but very rough around the edges.
That's basically it. Try the demo. Repo is open for contributions. Let me know if you have any questions!
[1] https://en.wikipedia.org/wiki/R/place
[2] https://github.com/reddit-archive/reddit-plugin-place-openso...

value: Show HN: place-clone – A nostalgic revisiting of r/place

author: chabes


value: Show HN: Cling 2.0 – fuzzy find any file in less than 50ms on macOS


value: varnethic

value: Show HN: Calorie tracker for people who hate tracking

author: varnethic


value: JasonDuke

value: Show HN: 65k AI voters predict UK local elections with 75% accuracy

author: JasonDuke


value: cozyss

value: I've been user cursor's browser tool to grab mockup's elements and make changes. Since cursor is getting more expensive I want to switch to Claude Code, so my friend made me this plugin that will work with any cli tools - grab the web elements for your cli tools.

value: Show HN: Grab web elements for CLI users

author: cozyss


value: thomasgeelens

value: Show HN: Cynical Sally – a personality that remembers you, now on OpenClaw

author: thomasgeelens


value: aadyachinubhai

value:
Most CUA frameworks are either a black box or raw tool calls with no structure. Orbit sits in between, natural language controls the screen, Orbit lets Python control the flow. Each step has its own model, budget, and typed output, but shares context across the session. Mix cheap and expensive models per step, extract structured data from any screen into Pydantic models, and steer the agent mid-task when it struggles. Built on the OS accessibility tree, not screenshots.
https://github.com/aadya940/orbit

value: Show HN: Structured Python control over AI computer use agents

author: aadyachinubhai


value: reidgoodbar

value:
I built Squire, a CLI for running short validation and offload jobs in clean remote runtimes.
The main idea is simple: don’t turn your laptop into the test surface.
It’s useful for things like:
- cross-environment verification
- test / lint / compile loops
- SQL sandbox checks
- short heavy jobs like data / media / browser tasks
A simple example:
squire verify --lang bash --targets alpine-3.20,ubuntu-24.04,debian-12 --file script.sh
Install:
curl -fsSL https://squire.run/install.sh | bash
squire login
Site: https://squire.run/

value: Show HN: Squire – CLI-first remote runtimes for Claude Code / Codex workflows

author: reidgoodbar


value: easygenes

value:
As an April Fools' project, I've made this.
I (ironically, depending your penchant) used an AI judge to score every top HN post and its top comments all the way back to 2010 (over 300,000 individual judgments!), and created a nice interface with the historic charts.
The scoring is off of how much disgruntled AI pessimism the post and top comments show. You can use that score to either only show (in Doom Only mode) or hide (in calm mode) all the doom static.
This is part joke and partly to answer my own curiosity about how real my feeling that the comments and posts have grown increasingly overbearingly negative towards and focused on the worst of what results from AI in the past year.
The trends is stark. My intuition was reinforced by the analysis; disgruntled pessimism about AI is at an all time high in the last few weeks and on track to continue doubling annually since ChatGPT released.
Historic charts are at bottom of the page.

value: Show HN: Sixteen year trends in AI doom on HN

author: easygenes


value: ttdownsite

value:
Hi HN,
I built a simple tool to download Instagram Reels without login.
I noticed many tools are full of ads, so I made a cleaner version.
Would love feedback:
https://downreels.com
Thanks!

value: Show HN: Download Instagram Reels without login

author: ttdownsite


value: kevinlu

value:
Hi HN — I’m building an interoperability layer for AI agents that lets local and remote
agents run inside the same network and coordinate with each other.
Here is a short demo: https://youtu.be/KVRYeNSJnNc
• OpenClaw runs locally on-device
• it connects to remote agents through Hybro Hub
• both participate in the same workflow execution
The goal is to make agent-to-agent coordination work across environments (local machines, cloud agents, MCP servers, etc).
Right now most agent systems operate inside isolated runtimes. Hybro is an attempt to make them composable across boundaries.
Docs: https://docs.hybro.ai
Still early and I’d really appreciate feedback from people building multi-agent systems.

value: Show HN: Hybro – unify local and remote AI agents in a single agent network

author: kevinlu


value: tamnd

value: Show HN: Linux Kernel Documentation Index-Every Page in the Linux Kernel's Docs

author: tamnd


value:
I built this after noticing that existing tools for comparing constitutional law either have steep learning curves or only support keyword search. By combining Gemini embeddings with UMAP projection, you can navigate 30,828 constitutional articles from 188 countries in 3D and find conceptually related provisions even when the wording differs.

  Feedback welcome, especially from legal researchers or comparative law folks.

  Source and pipeline: github.com/joaoli13/constitutional-map-ai

value: Show HN: Semantic atlas of 188 constitutions in 3D (30k articles, embeddings)


value: arximughal

value: Show HN: We open-sourced our content writing workflow as a Claude Code skill

author: arximughal


value: duozokker

value: Show HN: Agent2; Open-source production runtime for AI agents

author: duozokker


value: memset

value: Just a side project to let you create PDFs for physical programs for music recitals. You can print them out at home or take them to a print shop!

value: Show HN: Create Programs for Recitals

author: memset

title: Show HN: Create Programs for Recitals


value: AustinDev

value: Show HN: NASA Artemis II Mission Timeline Tracker

author: AustinDev


value: Show HN: Tlock – Lock macOS folders and apps with your fingerprint


value: gusgordon

value: I was frustrated with existing APIs for searching flight prices, so I built this. It's a simple API to search for flights and get their prices. It can also return booking links.<p>Generous free tier (happy to give more credits, lmk) + super low pricing. Lmk any thoughts or improvement ideas :)

value: Show HN: API for Flight Prices

author: gusgordon

title: Show HN: API for Flight Prices


value: idoubi

value:
Claude Code's source map leaked last month. Instead of just reading it, I fed the entire source into Claude Code itself and asked it to extract the core agent loop logic.
The result: open-agent-sdk — a drop-in replacement for claude-agent-sdk that's fully open source and doesn't spawn a CLI subprocess.
Why this matters if you've built with claude-agent-sdk:
claude-agent-sdk is just a thin wrapper around the Claude Code binary. It works, but it's a black box — when something breaks, you're stuck.
Every query creates a new Claude Code process. That's fine on a laptop, not fine when you're running thousands of concurrent agents in the cloud.
What open-agent-sdk does differently:
Pure function calls, no CLI process spawning — cloud-native from day one
Fully compatible interface with claude-agent-sdk — swap the package name, done
MIT licensed — fork it, patch it, make it yours
→ https://github.com/codeany-ai/open-agent-sdk-typescript

value: Show HN: Open-agent-SDK – Claude Code's internals, extracted and open-sourced

author: idoubi


value: vinayakkulkarni

value: Show HN: Tileserver-RS – Tile Server in Rust with MapLibre Native Rendering

author: vinayakkulkarni


value: bootbloopers

value: Show HN: JavaScript Obfuscator

author: bootbloopers

title: Show HN: JavaScript Obfuscator


value: Why?<p>- Implement stateful, server-driven rendering (SSR over WebSockets) framework for Java simlilar to Phoenix LiveView.<p>- Introduce a user interfaces component system that enables easy composition.<p>- Provide a vertically integrated solution targeting near-zero runtime dependencies. It takes an "all-included" monolithic approach, inspired by the Linux kernel philosophy.<p>- Embrace AI agent support for development, distribution, and runtime. Paradoxically, at the same time, it empowers developers to fully own/understand the stack: a small core (~12K LOC) written in modern Java with no annotations and no implicit execution flows.

value: Show HN: An SSR Java framework for real-time user interfaces and AI agents


value: randromeda

value: Most agent guardrails still depend on prompts or markdown files, or use IAM intended for humans which makes the process clunky. I used Open Policy Agent to create deterministic rules for what kind of tool calls the agent is able to execute.

value: Show HN: Arbiter – Deterministic Guardrails for Agents

author: randromeda


value: kaiengert

value:
This is a keyboard app for people who frequently hit the wrong buttons on small displays and are frustrated by constantly deleting and retyping — without wanting to rely on autocorrection.
The buttons are almost double the standard width, making it much easier to hit the right one. The tradeoff: each button shows two characters. To enter the character on the right, tap the button twice quickly.
For each character, you briefly decide: once or twice? You may type more slowly, but make fewer mistakes.
(There's an alternative long-tap mode that can be enabled in prefs, with that you have to tap slightly longer to get the second character, instead of double tapping.)
Background story: I have had the idea for this app for over a year. I had already identified that the existing Simple Keyboard app (from Raimondas Rimkus) would be a good starting point. With AI assistance I built the initial version of this Widekey Keyboard app in a single day.
Github: https://github.com/kaie/widekey-keyboard
Play Store: https://play.google.com/store/apps/details?id=de.kuix.wideke...
I hope the app can be helpful for some people!

value: Show HN: Widekey Keyboard for Android, double/long tap for 2nd on dual button

author: kaiengert


value: kristophph

value:
This is a combat-tracker app for dungeon masters of Dungeons & Dragons 5e games. It can help with organizing the combat encounter by showing all participants of an encounter in a list with all needed info like monster statblocks, conditions, attacks, spells etc.
I tried to make it very easy to use by offering keyboard shortcuts for all important actions. I think it can be used by just keyboard alone. It also has a command-palette like MacOS or Alfred on linux (shortcut is "/") that lets you search for all important commands and even glossary entries.
There is a "Demo mode" that shows an example encounter and guides you through the basic functions. If anyone wants to check it out and tell me if this is understandable or if I need to add more/better tutorial steps? That would be great :)
It is build with javascrpit/typescript and uses Firebase/Firestore.
Any DMs on here that want to give this a try?

value: Show HN: My D&D combat-tracker is finally online

author: kristophph


value: perinban

value:
Running SmolLM2 360M on a Samsung Galaxy Watch 4 Classic (380MB free RAM). Found that llama.cpp was loading the model twice simultaneously — APK mmap page cache + its own tensor allocations — peaking at 524MB for a 270MB model.
Fix: added host_ptr to llama_model_params. CPU tensors point directly at the mmap region. Only Vulkan tensors get copied.
Result on real hardware:
Peak RAM: 524MB → 142MB (74% reduction)
First boot: 19s → 11s
Second boot: ~2.5s (mmap + KV cache)
Code: https://github.com/Perinban/llama.cpp/tree/axon-dev
Write-up with VmRSS proof: https://www.linkedin.com/posts/perinban-parameshwaran_machin...

value: Show HN: Running LLM on smartwatch – found llama.cpp loading model twice in RAM

author: perinban


value: samleeney

value: Show HN: Tmux-agent-status – a tmux sidebar for monitoring AI coding agents

author: samleeney


value: KendallCBooker

value: Show HN: SideX – VS Code rebuilt on Tauri instead of Electron (96% smaller)

author: KendallCBooker


value:
Hi HN, I'm Edan, the creator of ElimKeys.
I've always loved ergonomic split keyboards, but I hated the desk clutter. Most splits on the market either require that annoying TRRS bridge cable between the two halves, or if they are wireless, they are often housed in bulky 3D-printed or plastic cases.
I wanted something that felt premium like a custom mechanical keyboard but was light enough to throw in a backpack. So, I built the Elytra.
A few technical details:
Truly Wireless: No cables between the halves or to the computer.
Material: CNC-machined aluminum chassis. We used a biomimetic design on the underside to shave off weight without losing structural integrity.
Weight: It weighs only 420g (0.93 lbs), which is weirdly light for a full-metal board.
Firmware: Powered by ZMK.
I would love to hear your feedback on the layout, the industrial design, or any questions about the manufacturing process. Happy to answer anything!

value: Show HN: Elytra – A 420g CNC aluminum, wireless split keyboard


value: shreedx

value:
My friend and I built mesh3d.gallery as a side project. Anytime we were looking for inspiration in the 3D web world, nmost galleries that cover 3D web will throw in anything no matter if it's pre-rendered video, image etc.
We wanted something curated, where only the websites that are genuinely impressive in what they do with WebGL, Three.js, and real-time 3D in the browser are listed.
We handpicked about 150 websites, the rest was added via submissions by our users. Everything on the site has been reviewed by both of us before it goes up.
Happy to hear feedback - especially from anyone who's built something they'd want listed, or has thoughts on what we're missing.

value: Show HN: Mesh3d.gallery – a curated collection of 3D websites

author: shreedx


value: kvntrnz

value: Show HN: Agentmatic, AI marketing platform that generates full campaigns for you

author: kvntrnz


value: kdeldycke

value:
I built Extra Platforms over the past 5 years because I kept writing the same detection boilerplate over and over. And also because Python's original platform.linux_distribution() function has been removed in Python 3.8. Its replacement, Distro, only covers Linux.
It detects six traits (CPU architecture, OS/distribution, shell, terminal, CI, agents), which are grouped into families (BSD, LINUX, UNIX, ...) for convenience.
You can try the library without installing anything:

  $ uvx --with extra-platforms python
  >>> from extra_platforms import current_platform, BSD, is_linux
  >>> current_platform()
  Platform(id='macos', name='macOS')
  >>> current_platform() in BSD
  True
  >>> is_linux()
  False

It also ships Pytest decorators (@skip_linux, @unless_macos) for platform-conditional tests.
The library has zero dependencies and is Apache-2.0 licensed.
I'm interested in collecting edge cases, which you can send me by performing an auto-detection with:

  $ uvx extra-platforms

value: Show HN: Extra-Platforms, Python library to detect OS, arch, shell, CI, AI

author: kdeldycke


value: mesahm

value: Show HN: A drop-in replacement and memory-safe TLS back end for Python

author: mesahm


value: shegby

value: Show HN: Osint of I-80 for EV site selection. Finding 10MW spots

author: shegby


value: rdme

value:
I built a DNS resolver that lets me use https://frontend.numa instead of localhost:5173
— auto-generated TLS certs, WebSocket passthrough, path routing. No mkcert, no nginx, no /etc/hosts.

value: Show HN: I built a DNS resolver from scratch in Rust – no DNS libraries

author: rdme


value: jchap

value: Show HN: Hacker News, summarized and printed to your local printer

author: jchap


value: Dahfab

value: Show HN: UX Surveys – Run SUS, UEQ, UMUX-Lite, and NASA-TLX for Free

author: Dahfab


value: ghazalidotdev

value: Show HN: Clawd Pets – 90 animated SVG pets, pure CSS, no dependencies

author: ghazalidotdev


value: syedmsawaid

value:
Hi everyone. I am built a small application on top of FSI German basic course and I need some feedback regarding it.
It is a small web app. Currently only Unit 01 is available. I will feed in the rest of the units later down the road as I use it myself.
Some of the features includes
- Slow and fast audio with every single word and sentence in this app. You can play them with a click of a button. No need to rewind a tap back and forth.
- Flashcards with keyboard control to quickly go through the material and drill them out.
You can access the website at https://detawk.com/ . There is a demo video on the landing page. Give it a look before signing up.
If you have any questions or feedback for me, let me know. I hope you like the app.

value: Show HN: I built a small app for FSI German Course

author: syedmsawaid


value: slimbuck

value: I did a double take when I first saw this.

value: Show HN: Playcanvas and Gracia 4dgs

author: slimbuck

title: Show HN: Playcanvas and Gracia 4dgs


value: martinovigiani

value: Show HN: I run a full software company solo with Claude Code agents

author: martinovigiani


value: amlug

value: Show HN: Mango – A native, open-source MongoDB GUI. 7 MB, no Electron

author: amlug


value: tamnd

value: Show HN: A daily archive of the top stories on Hacker News, organized by date

author: tamnd


value: hermanekt

value: Show HN: Zabbix MCP Server – 225 tools to let AI agents manage Zabbix monitoring

author: hermanekt


value: Show HN: Dualhook – Lightweight WhatsApp coexistence layer, zero message storage


value: ryaker

value:
SparrowDB is an embedded Cypher graph database written in Rust. It links into your process the way SQLite does.
I built it because I wanted a graph DB without running Docker or a cloud instance.
SparrowDB kicks butt at point lookups, global COUNT(*), and top-10 by degree but lags on traversals (1-hop, 2-hop, and variable-length paths).
It's an embedded engine with no parallel execution vs a warmed JVM server with a mature query planner.
The traversal workload is not the target. Agents, CLIs, serverless functions that need a knowledge graph without provisioning one, that's the target.
Cold start is ~27ms. If you're in a serverless context where Neo4j's startup time is disqualifying, that matters.
Bindings for Python, JavaScript/Typescript, and  Ruby. All open the same on-disk format. Built-in MCP server for Claude Desktop. A Bolt protocol server was just added, so gdotv and other Bolt clients can connect. At-rest encryption with XChaCha20-Poly1305. MIT.
https://sparrowdb.dev
Demo: https://www.loom.com/share/0dffc9274f5f4338878fe0ffa61f0f4e

value: Show HN: SparrowDB, SQLite of graph DB, written in Rust, Cypher compatible

author: ryaker


value:
Let me address the elephant in the room first: DataRamen does not use AI, it performs static analysis of your DB to figure out joins and data anchors. It runs on your local machine or can be self hosted, so your data stays yours. It's 100% open source with verified NPM release from GitHub action.
DataRamen is designed to simplify and make it more accessible navigating your database by removing SQL and replacing it with UI to query, join and jump from one record to another. The core idea was to make it feel like you are using a spreadsheet, but with live data in your DB (currently supports MySQL and Postgres).
Smart anchors let you move from one record to another with a simple click. Most of the current SQL clients have this feature but it usually works just one way: it allows you to open referenced records, but not vice versa. DataRamen goes further by allowing you to navigate both ways.
Let's say you have a table User, and each user can have multiple Document (Document.userId references User.id). Classic SQL clients allow you to go from Document to User, but DataRamen allows you to go from User to Document as well (multiple documents in this case).
Besides what is described above, it supports all the basics necessary to access your data:
- Filters: both plain text and SQL if needed.
- Joins: it automatically suggest what tables can be joined and on what column
- Ordering and pagination.
- Aggregations: this part still needs some UX improvements, but it works.
- Multiple databases connected at once.
- Self hosting: deploy it once on your infrastructure and let your team use it via web interface (no more sharing credentials or everyone configuring DB for itself).
- Queries history and saved queries.
For full disclosure, this is the second time I'm posting about DataRamen. The first one was 9 months ago and it did receive a lot of criticism for not being open sourced and not having a landing page (landing page was just an installation process). Both things I've addressed since, plus a huge amount of UX rework, documentation and stability improvements. The landing page is still rough, but at least it should be clear now what it does and how it works.
Find more information on https://dataramen.xyz/.

value: Show HN: DataRamen, navigate your DB without a single line of SQL (no AI)


value: jahala

value: Show HN: Walkie-Clawkie – Push-to-talk between AI agents, one file, zero deps

author: jahala


value: darraghmckay

value:
Hi HN! We’ve been working on Fonic, a tool for turning scattered notes, metric, transcripts, screenshots, and project updates into an interactive report you can easily share. Here’s a quick demo: https://www.youtube.com/watch?v=GNzw_h2Ztnw
We kept hearing the same complaint from account managers: they were spending hours every week building client updates.
Most of the source material already existed. The hard part was pulling it together from docs, Slack threads, screenshots, transcripts, and project tools and turning it into something they're proud enough to send.
We found that ChatGPT and Claude helped with analysis, but then you're back to a plain Google Doc or an email chain waiting for replies.
So we built Fonic.
It pulls the material together, uses AI to structure it, and generates an interactive report or page you can share with a link. People can ask questions, leave comments, and respond to action items inside the report.
Under the hood it’s mostly Claude and Vercel’s AI SDK. The interesting part for us has been the workflow around assembling context and making the result feel more useful than either a plain doc or an AI chat.
We'd love to answer any questions and get your feedback!
fonic.ai

value: Show HN: Fonic – turning scattered work into a shareable report

author: darraghmckay


value: ludovicianul

value:
I've enhanced Dochia with the ability to generate agent skills. Being a CLI already, it makes it really simple to plug it into agentic workflows.
Run `dochia init-skills` and the coding agent(s) can trigger tests as it builds:

  1. Agent writes endpoint and the OpenAPI spec (or that get's generated from code)
  2. Agent runs: dochia test -c api.yml -s localhost:3000
  3. Dochia produces dochia-summary-report.json + per-endpoint test files
  4. Agent reads errors, fixes code, re-runs
  5. Loop

The JSON output is structured specifically so agents can read and act on it directly,
not just humans parsing logs.
It's a native binary (GraalVM), so it's fast on all platforms.
Would love feedback on: is it something you will integrate into your flow, which test playbooks are missing, whether the report format is actually useful in agentic loops, any edge cases you'd expect a tool like this to catch?
GitHub: https://github.com/dochia-dev/dochia-cli
Docs: https://docs.dochia.dev
For background,
Dochia takes your OpenAPI spec and runs 120+ test playbooks: deterministic negative
and boundary scenarios plus chaos testing. No test cases to write, no configuration
beyond pointing it at your OpenAPI spec and a running server.

value: Show HN: Dochia – automated API testing for agentic build-test-fix loops

author: ludovicianul


value: marioskales

value:
Solo dev from Vienna. Skales is a local-first AI desktop agent for Windows, macOS, and Linux.
v9.0.0 just shipped with Agent Skills (SKILL.md import from Claude Code, Codex, Copilot), autonomous coding (Codework), multi-agent teams (Organization), Computer Use, and 15+ providers including Ollama offline.
No Docker, no terminal. Download, install, done. My 6-year-old built a Snake game with it.
BSL-1.1, free for personal use.
DevKit: https://github.com/skalesapp/devkit

value: Show HN: Skales – I built a desktop AI agent a 6-year-old can use

author: marioskales


value: dimastopel

value:
Back in 2012 I built https://cert-depot.com as a weekend project. Node.js + Express + jQuery, shelling out to OpenSSL for certificate generation. It worked but I eventually let it rot. https://news.ycombinator.com/item?id=4766743
Rewrote it from scratch in Go. The entire thing is a single binary with no external dependencies:
1. Certificate generation uses Go's crypto/x509 (no OpenSSL)
2. Certificates are generated in memory and streamed directly — nothing is stored on the server
3. RSA 2048/4096 and ECDSA P-256/P-384
4. Subject Alternative Names (required by browsers since Chrome 58)
5. ZIP (PEM files) or PFX/PKCS#12 output
You comments / suggestions / bug reports are very welcome. Thanks.
Source: https://github.com/dimastopel/certdepot

value: Show HN: I rewrote my 2012 self-signed cert generator in Go – cert-depot.com

author: dimastopel


value: mempko

value: I've felt Agents are the wrong abstraction. This is a project I've been working on that takes what I call the Ask Protocol and tries to build a system with it from the ground up.

value: Show HN: Abject: the first self-aware object runtime

author: mempko


value: jacknotold

value: Show HN: S0 Tuning – +23.6pp on HumanEval by tuning state, not weights

author: jacknotold


value: ncts

value:
Built this because I thought an At Your Own Risk page as a Service would be fun.
It lets you generate satirical disclaimer pages served on subdomains (your-thing.atyourownri.sk). Choose one of the two tones, deadpan or legalese. Choose from a curated list of risk clauses or write your own. Then your At Your Own Risk page is live.
The legalese tone reads like a real SaaS terms page until you notice it's governing disputes by coin flip. The deadpan tone just stares at you.
A couple of examples: https://this-side-project.atyourownri.sk (legalese) and https://my-sourdough-starter.atyourownri.sk (deadpan).
Stack: Cloudflare Workers & D1, TypeScript. resvg-wasm for OG image rendering. Otherwise hand-rolled.
Check out the source at https://github.com/abslynowarranty/atyourownri.sk
It is completely, entirely, legally useless. Use it at your own risk.

value: Show HN: At Your Own Risk – Disclaimer pages for things that don't need them

author: ncts


value: thatxliner

value:
Public beta lauunch!
I built a SvelteKit + Tauri writing app that treats revision as a first-class concept. You can fork any sentence or passage into branches, switch between versions inline, and keep everything in one document instead of maintaining separate draft files.
It's different from Git in the sense that you can try different combinations of these branches AND that these branches go infinitely nested
The editor component was made with CodeMirror, and I tried really hard with implementing robust data persistence by storing with SQLite.
There's also optional AI feedback if you bring your own API key, but it's not the point of the app (enable it in settings).
Still in beta and rough around the edges. Would love feedback!

value: Show HN: Quillium, the non-linear writing app

author: thatxliner


value:
I created this to help automate my day-to-day as a product marketer. I create lots of slides for clients (training, competitive battlecards, value props) which need to be in their brand and design system, and I wanted a way of doing that from Claude Code. I had gotten pretty far with Marp and Slidev, but since my clients need editable deliverables, they couldn't really work for me.
tycoslide is similar to other markdown-to-slides tools, but it produces editable PowerPoint files instead of PDFs and HTML. You create a theme npm package containing your graphics files, color palette, components, and layouts, and then use markdown to create slides. A key design goal is build-time validation, so it fails fast and loud to catch things like layout overflows, missing tokens, and invalid parameters.
Everything is TypeScript, so you can build custom components and layouts without CSS. Under the hood, it uses HTML, CSS and Playwright to measure the layout, then rebuilds it as native PowerPoint objects. I had the W3C DTCG standard in mind for design tokens, so it should be pretty flexible.
This is the first release, so looking for feedback on the DX, slide authoring workflow and what's missing. Hope this is helpful!

value: Show HN: Show HN: Tycoslide – Editable PowerPoint Slides from Markdown and TS


value: mogic

value: Show HN: HabitDex – The right habit method for you, not another tracker

author: mogic


value: Weatherill

value: Show HN: A Homeostatic Logic-Funnel to Prevent RLHF Overrides in LLM Personas

author: Weatherill


value: codelitt

value: Show HN: Codemode-x – Compress any API into 2 MCP tools for Claude Code

author: codelitt


value: Show HN: Generate IoT applications from plain-language requirements


value:
PGP is great, but it's annoying to use, until now.
PGP tools is opensource, has great UX and 0 requested permissions, fewer than every other PGP extension.
It uses passkeys as the primary flow (but you can use passwords) to fully E2EE your secrets. You can choose the synced storage (syncs between devices and touches google's servers) or you can just keep everything local.
Contacts and keys are encrypted so nothing potentially sensitive can be leaked without your key.
There are no calls to external services like analytics or any of my own servers. The Crypto side of this is based off of SequoiaPGP, compiled to WASM.
It lets you drag & drop files, lets you add in text and just saves time.
I made this because I personally wanted it, I had to encrypt my vulnerability reports (which put me on the Center for Cyber Security Belgium Wall of Fame https://ccb.belgium.be/cert/vulnerability-reporting-ccb/wall...)
Going between the console and my email was a pain, and there were no other easy solutions so I decided to make one.
If you want to go browse the code or submit issues/PRs, feel free: https://github.com/Am-I-Being-Pwned/PGP-Tools

value: Show HN: PGP Made Convenient

title: Show HN: PGP Made Convenient


value: LordKode

value:
Hi HN,
I built Reviewskits because of a recurring frustration I faced while working for a web agency in Switzerland.
Our designers created beautiful, pixel-perfect layouts, but when it came to testimonials, we were stuck with rigid, pre-made widgets from tools like Senja or Trustpilot. Hacking them with CSS to match our UI was a nightmare. When we looked at their API pricing to build our own components for 100+ clients, the cost was astronomical ($90 to $300+/mo).
Later, as an indie dev building my own SaaS, I simply couldn’t afford those prices.
So I built Reviewskits:

    High Performance: The API is built with Bun and Hono for ultra-low latency.

    Self-Hostable: You own your data. Period. No more black boxes.

    Headless first: We provide the API and SDK. You build the UI that matches your design perfectly.

    Open-Core: The core engine is open-source.

I’m looking for two things today:

    Contributors: I want to turn this into a web standard for social proof. If you're into Bun, Hono, or React, I'd love your help on the repo.

    Early Adopters: For those who don’t want to manage infrastructure, I’m preparing a Cloud version. Pre-orders are open for lifetime early access to help fund the development.

GitHub: https://github.com/reviews-kits-team/reviews-kits
Site: https://reviewskits.com/
I'd love to hear your thoughts on the API design and the Bun/Hono performance!

value: Show HN: Reviewskits – Open-source, headless, and self-hostable social proof

author: LordKode


value: kouiskas

value:
After a year of producing all my code through Claude Code, I was growing frustrated with losing Terminal tabs and not noticing when sessions are ready to continue. I looked around at all the terminal managers people have been building for this type of workflow and couldn't find anything that worked for me. Cmux came close but was too buggy in the area I cared the most about: knowing when my sessions are ready for input. I also felt like the sidebar was too cluttered and hard to parse visually.
So, I made my own Claude-first terminal manager and optimized it for the habits I've developed over the past year in this new way of creating software.
Claude Code terminals are the focus in Deckard, with classic terminals being also supported, but treated separately.
I feel like it's stable enough to share now, but I'm sure rough edges will be surfaced quickly under HN's scrutiny, and that's the point of sharing it here. For example I'm still not quite happy with the fact that if you enable tmux, the tmux terminals behave differently when it comes to selection and copying text than the Claude Code ones
Here are some highlights in terms of features:
- Two-dimensional tabs
- "Ambient awareness" design for the status indicators. I hate visual clutter, so I went for a very minimalist approach to help see things at a glance.
- Automatic resumption of all Claude sessions
- (basic) Optional Tmux support for the non-Claude terminals
- Tool to explore, resume, and fork past Claude conversations (including from earlier points in the history)
- Live display of current context/quota usage
- And many things you'd expect, like themes, etc.
This is MacOS-only for now because it's the platform I work with. I don't think there's anything that would prevent it from becoming cross-platform (electron-based or otherwise). I just didn't want to bear the burden of cross-platform support right away as this is a side-project, but I have no strong objections to making it cross-platform.
It's based on SwiftTerm and not on Ghostty. I based it on Ghostty at first and ran into a ton of rendering bugs related to the way I hide, resume terminals and warp them for the resumption magic, etc. I couldn't track down the root causes and it was very unstable, with terminals frequently freezing. Switching to SwiftTerm brought the stability I was looking for, as this has been my daily driver for weeks now. Not opposed to going back to Ghostty either, if someone manages to make it actually work reliably.
I hope you like the spirit of it, that's what I tried to establish here. More efficient UX patterns for what I do on a daily basis. Hopefully other people with the same tastes in workflows might enjoy it too.

value: Show HN: Deckard, Claude-first terminal manager

author: kouiskas


value:
hi hn, i’ve been building a tool called GeneratePPT:
https://www.generateppt.com/
the basic idea is simple.
a lot of presentation tools keep adding more design controls, more panels, more options, more ways to tweak small things.
but i think for a lot of people that just creates more friction.
so i wanted to try the opposite approach.
this is obviously not for everyone. if you enjoy tweaking every spacing value and every visual detail, you’ll probably hate it.
but i think there are a lot of people who just want to finish the presentation and are not being paid to spend an hour adjusting some microscopic drop shadow blur
i’m also trying to remove some of the annoying work with charts that auto-update, layouts that adapt to the content, and an ai editor where you can basically talk to the slides instead of clicking around forever.
would love honest feedback!

value: Show HN: Generateppt, an anti-bloat presentation tool


value: spellbind-dare

value:
TL;DR
I'm a fan of podcasts and I despise ads. I built an iOS app to detect and skip in audio ad content.
Motivation:
I love podcasts, especially multi hour ones that go into detail on niche topics. One thing that puts me off some podcasts is having the flow become interrupted, especially mid sentence by dynamically inserted ads. Last year this led me down a rabbit hole of experimenting with removing ads from the podcasts I listen to.
Experimentation:
At first I tried using Whisper for ad detection to generate a transcript of an episode, then feed this to ChatGPT and ask it to find the ad timestamps. This worked surprisingly well. I had a proof of concept working but I wanted something I could actually use on my phone.
Productionization:
Next I wondered if I were to productionize my prototype how would I do that? From experimenting the main issue would be volume of audio transcription required to satisfy a moderate-heavy podcast listener. I estimated ~100 hours of audio per month would be required per user. In testing I used OpenAI hosted Whisper, charged at $0.006/min. That sounds quite cheap. What would that be for 100 hours? $0.006/min -> $0.36/hour -> $36.00/100 hours. S%#t. $36/user/month is way too expensive. If you were to turn this into a business at that rate you'd probably need to be charging at least $50/month. No one's going to pay that.
What if we did everything on device? In iOS 26 there are APIs for on device speech LLM and speech to text. I got the podcast audio -> transcript -> LLM detected ad segment pipeline working. Excellent! The next problem is that an iPhone is not a data center grade GPU. The pipeline was significantly slower than my first attempt. Before it would take <= ~4 mins while the iPhone pipeline could take up to 10 minutes for multi hour podcasts. The on device approach would be too slow of a good UX. Not to mention each time I ran a test run of the iPhone based pipeline my phone would get really hot and be a huge drain on the battery.
Back to square one. The only other approach (at least that I could think of) would be to manage the transcription infra myself. Given this is just a side project I wanted simple infra. Ideally I would be able to use something like AWS Lambda with GPUs (does not exist, I checked). My research showed GCP has serverless Cloud Run with a GPU option. Now we were starting to cook. I built a spike with GCP and had the ad detection working. As I was starting to get excited, I ran a load test on Cloud Run revealing a new problem.
GPUs are in hot demand. Who knew? GCP is (or at least was) limiting the number of GPUs per customer. I was only allotted ~3 GPUs to my account (I tried raising a support ticket for a higher limit but no luck). This was a huge bottleneck as transcribing an episode would saturate the resources of one GPU so 3 GPUs is only a pitiful 3 concurrent episodes being transcribed at once :(
Further into the rabbit hole, research led me to find Runpod that has a serverless GPUs. The low end GPUs go for ~$0.50/hour (that's hour of GPU time not audio transcribed) depending on the GPU used. Now with more reliable access to enough GPUs I could run a load test again. It worked out to be ~$0.02/hour or ~$2.00/100 hours of audio transcribed. At $2 per user per month this is looking a lot more reasonable. $2 is a 94% decrease compared to using the OpenAI API at $36. To be fair to OpenAI the transcripts I would get from their API would be more accurate. When tuning the Runpod implementation I was optimizing for speed and low cost. For the ad detection I found if the transcript was a bit less accurate this did not matter too much when getting the LLM to pick out the ad segments, so trading accuracy for speed + cost made sense here.
Anyway that is my story of building the Octopoddy ad detection pipeline. Please try it out, I'd love to hear what you think. I'd be happy to provide more details on any of this in the comments if you'd like :)

value: Show HN: Octopoddy – iOS Podcast App Using Transcripts and LLMs to Skip Ads

author: spellbind-dare


value: CodeReclaimers

value:
I maintain neat-python and have been building a genetic programming framework in Julia. While doing research on that project, I kept finding the same complaint in PySR's GitHub discussions: people give up not because symbolic regression doesn't work, but because getting Julia talking to Python is a repeated source of failure, especially on Windows and in notebooks.
So I stood up Occam (occam.fit) — a hosted MCP server exposing two tools: run_sindy for sparse identification of dynamics from time series (seconds), and run_pysr for evolutionary symbolic regression returning a Pareto front of expressions by complexity vs. accuracy (10–60s).
The core design decision is a pool of pre-warmed Julia workers running SymbolicRegression.jl v2. Julia processes stay alive between requests so the 2-minute compilation hit is paid once at server startup, not per call.
Free tier, no signup. Happy to answer questions about the architecture or symbolic regression generally, and curious whether anyone has use cases that don't fit the current limits.

value: Show HN: Symbolic regression as an MCP tool (SINDy and PySR, free, no install)

author: CodeReclaimers


value: DanDeBugger

value: Show HN: ContentForge – Content scoring API (42 endpoints, 12 platforms)

author: DanDeBugger


value: batels

value:
Hi HN,
I built Projects Calendar because I wanted a way to visualize my GitHub Project deadlines (issues and PRs) in my native calendar app without the privacy trade-offs of typical sync tools.
Most integrations require a persistent database to store your project data. I took a different approach:
100% Stateless: The app has no database. It doesn't store your tasks or deadlines.
On-the-fly Processing: When your calendar app (Google, Apple, or Outlook) requests an update, the service fetches data directly from the GitHub GraphQL API in real-time, generates the .ics feed, and purges the raw data from memory immediately after.
Security: Authentication tokens are encrypted using AES-256-GCM.
Tech Stack: Built with a Rust (Axum) backend to handle requests with high performance and low memory footprint. The UI is Vue 3.
The goal was "Privacy by Design." If you revoke access on GitHub, there is literally no trace of your project data left on the server because it was never saved in the first place.
I’d love to hear your thoughts on this stateless approach for third-party integrations and any feedback on the calendar sync performance.
URL: https://dash.projectsics.com/

value: Show HN: Projects Calendar for GitHub – A stateless iCal feed for your projects

author: batels


value:
I’ve been building Canine for about 2 years now, and have slowly grown it to about ~1000 developers using it for deploying all sorts of apps / projects / etc. Amazingly, the whole thing is still able to run on a single 48GB Hetzner VPS. Think of it basically like Coolify, for Kubernetes. I previously posted about it here: https://news.ycombinator.com/item?id=44292103
Recently, we added MCP capabilities to canine, and I was shocked how well it worked. It basically is able to create services, cron jobs, databases, get the logs for these and redeploy. See it here: https://canine.sh/model-context-protocol. The real killer feature has been an MCP tool to be able to download a temporary kubeconfig, which lets Claude then breakout and get the full Kubernetes API to automate pretty much anything. A little scary how competent Claude can be here.
When we paired this with Claude code running locally, you’re basically able to have a fully autonomous system vibe code, deploy, wait, and test in staging (by querying APIs, no browser skills yet), automatically fix bugs, repush, etc.
Best practices in this area haven’t quite been established and I know this community has a somewhat nervous relationship with AI tools. The way we have it set up is basically to only allow access on staging servers, and disable entirely on production, for fear of things going wrong. MCP is opt in on canine at the moment.
The implementation was pretty easy. We just took our API and basically wrapped an MCP OAuth authentication around it where all the GET endpoints became resources and all the POST / PUT / DELETE endpoints became tools. Digging through other MCP implementations, it seems the actual documentation is quite out of date. The MCP documentation recommends using Prompt objects to guide the LLM’s, but most implementations I’ve seen out there actually use skills, which have to be installed.
Anyways, happy to share whatever, it was a cool bit of project, just now seeing how people will use this.

value: Show HN: An MCP server for Devops automation


value:
Reinhardt is a full-stack web framework for Rust inspired by Django and DRF. It bundles HTTP, ORM, auth, DI, and background tasks into one crate — feature flags let you pull in only what you need (minimal/standard/full), or use individual crates.
Published as `reinhardt-web` on crates.io, imported as `reinhardt` in your code.
I built it after moving from Django/DRF to Rust and repeatedly assembling the same Axum + ORM + migrations + auth stack.
Two things I'd especially like feedback on: a built-in WASM+SSR reactive frontend (Pages), where a DSL-to-Rust codegen step (page!/head!/form! macros) produces both client WASM and server HTML from one source; and auto-generated migrations from #[model(...)] definitions.
Quickstart is here for anyone who wants to try it immediately:
- Website: https://reinhardt-web.dev
- Crates.io: https://crates.io/crates/reinhardt-web
v0.1.0-rc.15 (https://github.com/kent8192/reinhardt-web/releases/tag/reinh...), BSD 3-Clause. Looking for feedback on the API design, not production use yet.

value: Show HN: Reinhardt – Django/DRF-inspired full-stack web framework for Rust


value: cadillion

value:
Hey HN. I'm Colton (YC S21, ex-Acorns), one of the founders of Postquant Labs. My cofounder Richard is a cryptographer out of Draper Labs and DARPA. We're building Quip.Network, the first distributed quantum compute network. We just opened our testnet and wanted to share it here.
The basic problem: quantum hardware is here and already competitive on certain optimization problems, but for most people, there's no way to access it. The machines cost millions and the hardware and research are gated by the companies who own them.
Also, quantum providers regularly have machines sitting idle because demand isn't consistent, and that's a problem because many architectures need to be cooled near absolute zero and can't just be turned off. There's currently no equivalent of spinning up an on-demand cloud instance for quantum compute.
So we're building one. Quip.Network is a spot clearinghouse and marketplace where quantum providers contribute excess capacity, developers deploy their best solvers to an open library, and anyone can submit a workload and get a result without needing to own or understand the hardware. Classical operators (CPUs, GPUs, TPUs) can also participate in solving and verifying.
The first quantum subnet was built in close collaboration with D-Wave, the world's leading quantum computing company. It focuses on optimization problems, the kind that appear across finance, logistics, and manufacturing. It runs on annealing QPUs and has demonstrated competitive performance on solution quality, speed, and energy cost relative to classical computing approaches. The mining protocol is designed around these benchmarks, so participants compete to find better solutions.
We had about 13,000 signups before launch. The codebase is fully open source because we think quantum advantage should be a verifiable result, not a marketing claim. We want people running nodes, challenging our implementations, and submitting proofs of work optimized for their own hardware.
Unlike GPU clusters where one more processor is a linear improvement, the value of adding just one more QPU to your cluster is exponential. It won't be enough to be just AWS, GCP, or IBM. To solve the toughest problems, we'll want to connect together every processor on Earth and have them operate as one giant quantum system. That's why we think a distributed system is the right approach, and that's why our mission is to build the worldwide quantum computer.
Happy to answer anything!
Docs: quip.gitbook.io/docs | GitHub: github.com/quipnetwork

value: Show HN: Open-source distributed quantum compute network

author: cadillion


value: Show HN: I Talked to 500GB of Retail Data with Zero Domain Knowledge


value: We spent the last year architecting a 'Dream Engine' to solve agent statelessness. We used Claude to help refine the logic. We open-sourced the repo on March 28th. On March 31st, the Claude Code leak revealed an internal autoDream feature with the exact same 4-phase consolidation logic.<p>I'm looking for a technical audit of my memory decay logic in core/dream.ts. With 100 nodes already active, I want to ensure the consolidation won't bottleneck at scale.

value: Show HN: Local-first agent memory loop 48hrs before the Claude Code leak


value:
We built a native inference engine that runs quantized LLMs directly from SSD using memory-mapped I/O. The model never fully loads into RAM — the OS pages weights on demand as each layer executes.
*What it does:*
- Mixtral 8x22B (80GB, 141B params) runs on a machine with 48GB RAM
- Model loads in 0.3 seconds (vs 190s with llama.cpp)
- Produces correct output: "What is 2+2?" → "The sum of 2 and 2 is 4."
- Zero dependencies — custom tensor engine, custom GGUF parser, no ggml/llama.cpp
*How it works:*
- `mmap()` the GGUF file. The OS handles SSD→RAM paging transparently
- Quantize the input to Q8_K, compute dot products directly against Q4_K/Q5_K/Q6_K weights in the quantized domain — no dequantization to float32
- AVX2 SIMD + 8-thread parallel matvec
- For MoE models: only 2 of 8 experts are active per token, so most weights stay cold on disk
*The hard part we solved:*
GGUF models are calibrated for a specific dot product computation path (ggml's "quantize input → integer multiply-accumulate → late float conversion"). If you naively dequantize weights to float32 and do a standard dot product, the per-operation error is tiny (~0.001%) but compounds across 56 transformer layers into completely wrong output. We had to reverse-engineer and match ggml's exact scalar computation — block-level integer accumulation with 8-lane parallel reduction — to get correct results.
*What it doesn't do (yet):*
- Speed: ~0.08 tok/s on the 80GB model (CPU-only, no GPU offload)
- No interactive chat UI
- Only K-quant GGUF formats (Q4_K_M, Q5_K_M, Q6_K — covers ~90% of models on HuggingFace)
- Windows only (Linux stubs exist but untested)
The architecture comes from my "work in progress" WayOS (https://github.com/cloudlinqed/WayOS), an AI-first OS that treats SSD/RAM/VRAM as a unified memory hierarchy.
GitHub: https://github.com/cloudlinqed/WayInfer

value: Show HN: WayInfer – Native GGUF engine that runs models larger than your RAM


value: PreciousH

value: Show HN: Argus – Self-hosted AI that monitors infra and explains what's wrong

author: PreciousH


value: paezand

value:
Storage Savings: 65% Less Space than JSONB
Retrieval Speed: 5.5x Faster than Relational JOINs

value: Show HN: Pgproto – Native Protobuf Support for PostgreSQL

author: paezand


value: Show HN: I rebuilt my book on tech and movies for AI


value: adriaanb

value:
Hi HN,
I built Topical.so to audit structural SEO issues on (AI-generated) blogs.
It surfaces things like keyword cannibalization, weak internal linking, thin content, and topical clustering, etc.
Sample report: https://reports.topical.so/profilespider-com-lj519xw6iyv9krk...
I'm happy to run it on any blog for free. Share your blog in the comments, or submit it through the website: https://topical.so

value: Show HN: Topical.so - structural SEO audits for AI-generated blogs

author: adriaanb


value: T-RN-R

value: Show HN: I built a Cargo supply chain auditor using Claude and GitHub Actions

author: T-RN-R


value:
Hi everyone,
I built Pace, an MCP server that pulls your wearable data into Claude so you can actually talk to it.
You connect your devices once (Garmin, Oura, Whoop, Polar, Fitbit, 20+) and Claude gets 15 tools: sleep analysis, workout detail with lap splits, HR zone breakdown, recovery status, 30/90-day trends, and more.
The thing that surprised me most: Claude's artifact/visualization feature turns this into something way more useful than I expected. You ask "analyze my last 10 runs" and you get an interactive chart of pace trends, HR zones per run, and a written summary — all in one response. No dashboard needed.
Tools available right now:
- get_sleep_data — deep sleep, REM, HRV, SpO2, sleep score
- get_workout_detail / get_workout_laps / get_workout_samples — full session breakdown
- get_recovery_status — readiness, resting HR trend, HRV baseline
- get_training_summary — load, volume, consistency over time
- get_trends — any metric over 7d/30d/90d with baseline comparison
Stack: Python (FastMCP) · Cloud Run · Cloud SQL PostgreSQL · Firebase · Terra API · OAuth 2.1
It's live and free to try at pacetraining.co. Claude Pro/Max not required (custom connector).
Would love feedback, especially from people who've built MCP servers or use wearables seriously.

value: Show HN: Pace MCP server that connects all your wearables to Claude


value:
Hello HN,
I have been working on a desktop P2P messenger called Kiyeovo for the last ~8 months, and I just published its beta version.
Quick backstory: It started out as a CLI application for my Graduate Thesis, where I tried to make the most secure and private messenger application possible. Then, I transformed it into a desktop application, gave it "clearnet" support and added a bunch of features.
Short summary:
The app runs in 2 completely isolated modes:
- fast mode: relay/DCUtR -> lower latency, calls support
- anonymous mode: Tor message routing -> slower, anonymous
These modes use different protocol IDs, DHT namespaces, pubsub topics and storage scopes so there’s no data crossover between them.
Messaging works peer-to-peer when both parties are online, but falls back to DHT "offline buckets" when one of them is not. To ensure robustness, messages are ACK-ed and deleted after being read.
Group chats use GossipSub for realtime messaging. Group messages are also saved to offline buckets in order for offline users to be able to read them upon logging in. Kick/Join/Leave events are also propagated using the DHT. Group metadata and all offline data is of course encrypted.
Other features: Chats are E2E, file sharing is supported, 1:1 audio/video calls are supported (only in fast mode though, using WebRTC)
Tradeoffs: Tor has noticeable latency, offline delivery is not immediately guaranteed, but rather "eventually consistent"; beta version does not have group calls yet.
I’d appreciate feedback, that's why I posted this as a beta version
Repo: https://github.com/Realman78/Kiyeovo

value: Show HN: A P2P messenger with dual network modes (Fast and Tor)


value: blach

value: Apple's Calendar app has had an API for adding video call links to events for years now, but it is a bit squirrelly, and Google/Zoom can't be bothered to integrate with it. So, instead of just trying to make all my work meetings use FaceTime, I made an app to provide plugins for Calendar.app and integrate against Meet/Zoom APIs. I've taken a couple of looks at this previously, but actually built it this time and got it through Google and App Store review. Still waiting on Zoom review (that'll be v1.1). Does exactly what it says on the tin and no more. Hoping there are still some other macOS Calendar.app users out there to appreciate this.

value: Show HN: I use macOS calendar and have calls. MeetLink adds vid links to events

author: blach


value: akadhanu

value:
I got tired of LLM outputs silently failing in pipelines, so I built a small scoring layer around it.
It checks three things before your output moves forward: does it match the schema you expected is it consistent across runs
does it actually align with the context you provided
Returns a confidence score and a risk level. That's mostly it.
Works with OpenAI, Anthropic, Gemini, Ollama and a few others. Sync and async both supported.
It's heuristic, not a guarantee. If your context is bad, the scores will be too. Hit a star, if you found this useful.
Try now: pip install hallx

value: Show HN: Hallx – Hallucination risk scoring for LLM outputs

author: akadhanu


value: emillykkeg

value: Hi, I built a free, local-first, open-source Whisper Flow clone that can dictate to any application. Right now it's only for macOS because that's the only computer I have tested and built it on but I think it has potential to be used on a lot of devices.

value: Show HN: I built a free open-source Wispr Flow clone

author: emillykkeg


value: Rickielin

value: Show HN: OpenYak – open-source desktop AI agent that works with your local files

author: Rickielin


value: TheOmkarBirje

value: Show HN: I made an free app that moans when you tap your iPhone, iPad, or Mac

author: TheOmkarBirje


value: Acacian

value: Show HN: I tested 11 AI frameworks for basic security – none passed

author: Acacian


value: The tool overhauled significantly to enable drawing 'text only' HTML based plots as well as many other features and improvements.

value: Show HN: Incplot – CLI tool drawing great looking plots to terminal and to HTML


value: Guillim

value:
"Can you check if this user is on the premium plan?"
"I have a support ticket on Mr.Bean, saying he cannot login... Can you have a look?"
"How many subscriptions did we have today?"
...
As senior SWE at Twenty.com (open source CRM), I had these quite often.
Every day I needed to check something in Postgres, I had to wait 30 seconds for DBeaver to load or fight pgAdmin's UI. So I built Paul. Yes our database configuration has too many schemas (3000 schemas) for those clients, but still, it was not Postgres fault. Only the client that couldn't handle it.
Paul is a native macOS app, light (<20MB) and opens in 2 seconds. You can imagine how fast it feels compared to the 5 minutes I had to wait when opening DBeaver...
I did not go very deep in the DBA features, nor in the UI. I kept Paul simple: you can browse tables, filter them, and sort them.
A few distinctions:
- Paul's read-only by default: you have to explicitly switch to edit mode in the settings to allow INSERT, UPDATE, or DELETE. This makes it safe to point at production.
- I added an agent mode (read-only) to interact faster with the database, without SQL knowledge. Nothing fancy, It basically is a wrapper around openAI and Anthorpic sdks. Still useful for some SQL formulas i don't use often.
It's of course Free, no account required. Works offline.
I'd love feedback on what's missing or what could be better. This is a solo project and I'm building it for me first, but open to add features if anyone feels like it could use it.

value: Show HN: AI-first PostgreSQL client for Mac

author: Guillim


value: kirillzubovsky

value:
Hi HN, a buddy and I built this SEO tool a few months ago, and it's been doing wonders for SEO consultants. They buy the reports from us, package it with their other tools, and turn $99 into thousands.
That said, we built the tool not knowing anything about SEO, we just wanted to experiment and see what could be done.
Digging more into the SEO space now, I can't decide:
- SEO is dying, abandon the ship and focus on other priorities
- double down, empower people still doing SEO reports to save time
Personally, I enjoyed making the tool, but I don't think I want to be an SEO consultant.
This kind of tool plays into the edge-case heavy work that Marc Andreessen recently tweeted about – AI excels at scaling across the messy long tail of problems that humans fatigue on. It goes way beyond what a human can do in that time by analyzing tons of data.
What do you think? Any feedback is greatly appreciated!
www.easyseo.online

value: Show HN: EasySEO – prioritized AI SEO roadmap in 15 minutes

author: kirillzubovsky


value: Escafati

value: Show HN: New open source AI self driving testing

author: Escafati


value: baudehlo

value:
PTS is an app I wrote to enable you to write playwright tests in English, and manage your test suite in a UI.
It's crafted after the postman/bruno style of collections of tests with variable interpolation.
I wrote this because I couldn't find anything similar to a previous YC product I'd used called Rainforest.
It runs your tests and takes screenshots along the way, so you can see where it went wrong. Run multiple browsers for the same test too.
It's MIT, and I'm open to ideas or enhancements.

value: Show HN: Playwright Test Studio

author: baudehlo

title: Show HN: Playwright Test Studio


value: KNQuoc

value: Show HN: blockd – my attempt at un-noding workflow automation platforms

author: KNQuoc


value: gepheum

value: Show HN: Skir, modern alternative to Protobuf, now supports 9 languages

author: gepheum


value: Successfully restructured the entire leaked source code of Anthropic's Claude Code using OAI's Codex, rewritten in Binary without copyright issues . You won't get it more performant than this

value: Show HN: I got Claude Code to run in Binary


value: ImJasonH

value: Show HN: Portcullis, a review gate for curl|bash

author: ImJasonH


value: jamesriso

value: Show HN: Job market trends across 1,100 tech companies

author: jamesriso


value: ansicode

value: This is a compagnon tool for Claude Code/Gemini CLI/Qwen Code aiming to save tokens.

value: Show HN: Ecotokens – Another token saver for CLI Agents

author: ansicode


value: voska

value: Show HN: Hacker News CLI

author: voska

title: Show HN: Hacker News CLI


value: Show HN: I tested 15 free AI models at building real software on a $25/year VPS


value: stagas

value: Show HN: Voice talk with AI, all in the browser, no backend

author: stagas


value: sayfessyd

value:
I created this to address a specific annoyance when using Spring Boot in CI.
When a test fails in GitHub Actions, you often get thousands of log lines. The main error message is usually something vague, like “Failed to load ApplicationContext.” The real root cause is often buried deeper in the stack trace.
In my case, I was troubleshooting a failure due to a missing property:
defined in application.properties (app)
But missing in the test configuration.
The log contained around 15,000 lines, and I wasted a lot of time chasing unrelated exceptions before discovering the real issue.
This extension adds a button to the GitHub Actions UI. It extracts the logs and aims to identify the most relevant “Caused by” line by filtering out common Spring wrapper exceptions such as BeanCreationException and UnsatisfiedDependencyException. It then scores the remaining lines.
It presents:
- the most likely root cause
- a short explanation
- a suggested fix based on simple pattern matching
I built the first version in about 3 hours, using AI tools to speed up parsing logic and handling edge cases.
It’s still quite basic, but already helpful for common “config/bean” type failures.
I'm interested in whether others have experienced the same issue or found different solutions.

value: Show HN: Tool to extract root cause from Spring Boot logs

author: sayfessyd


value: adamfisk

value:
I helped build Lantern, a censorship circumvention tool that’s been downloaded over 150 million times globally, with most users in China, Russia, Iran, and the UAE. Before Lantern I was the lead engineer at LimeWire (back in those days our whole dev team was about 5 people!).
Making your traffic indistinguishable from normal internet traffic has long been a foundational part of effective censorship circumvention, a technique sometimes referred to as “collateral freedom.” If censors can’t differentiate your traffic from other traffic they don’t want to block, then they can’t block you without incurring collateral – and economic – damage.
It turns out this is fundamentally the same challenge AI agents face when trying to crawl webpages. The tools they use are identifiable by various means, whether it’s unique TLS handshakes from Python, Go, Node, etc, or whether it’s details in the page processing that make it clear the requester is not a real browser and/or human.
To get around this, Wick uses Cronet (Chrome's network stack as a standalone lib) as the default for all requests. It’s not a headless browser – just the network layer. Wick works as an MCP server so Claude Code and Cursor pick it up automatically and also supports local API access. I also just got it on Apify's store if you want to try it without installing anything — it works from their datacenter IPs, which surprised me honestly. Importantly, it’s local by default. That way, if you’re running from your house, it can automatically take advantage of your residential IP address, which is less likely to get flagged.
The Cronet version is lightning fast and effective, but it doesn’t do JS rendering. If you need that (a requirement for accessing some sites), we have Wick Pro that does some fancy things on that side too that are very different from other tools out there.
Open source, MIT. Pro for $20/mo if you need JS rendering.
Code: https://github.com/wickproject/wick
Site: https://getwick.dev

value: Show HN: Wick – censorship circumvention tech repurposed for AI web access

author: adamfisk


value: nikisweeting

value: Show HN: Mac-hardware toys, control your Mac's hardware like a modular synth

author: nikisweeting


value: theturtletalks

value:
I've been building an open source alternative to Shopify, so it only felt fitting to build in agentic commerce too.
I saw where ChatGPT Checkout was heading, another proprietary marketplace where they control which sellers get access and priority. More gatekeeping, more rent-seeking. It was clear Shopify stores would get preferential treatment.
So I built "the / marketplace," a fully open-source alternative with a flexible adapter system. It already supports Openfront (the Shopify alternative I’ve been developing), but it’s designed to work with any e-commerce platform, not just the ones OpenAI decides to favor. You can bring your own OpenRouter key or connect to Ollama locally, so your shopping data stays private and under your control.
Right now it has 2 demo shops, Impossible Tees and Nimbus Gallery.
As we launch more Openfronts for restaurants, gyms, and other verticals, those should be able to plug into the chat.
Demo: https://marketplace.openship.org
Repo: https://github.com/openshiporg/marketplace
Learn more: https://openship.org/products/marketplace

value: Show HN: Agentic Commerce Marketplace Chat

author: theturtletalks


value:
I have put together an interactive, scientific, 3D/2D, to-scale animation of the Artemis II mission based on orbit data from NASA JPL.
You can view it here: https://sankara.net/astro/lunar-missions/mission.html?missio...
Features available:
- Real-world orbit data and predictions based on JPL/NASA HORIZONS interface
- 2D and 3D
- Earth centric or Moon centric views
- Earth-Moon relative reference frame
- Any camera view (free-form; Craft/Moon/Earth to Craft/Moon/Earth)
- Event meta data (orbit maneuvers like TLI)
- Realistic textures for Earth and Moon in 3D mode
- Astronomically correct rendering of sunlight on Earth and Moon, poles, polar axes, and stellar background
- Camera controls (pan, zoom, rotate), timeline controls, visibility controls
- A Joy ride feature
This project is part of a larger effort to capture the orbits of all lunar missions wherever orbit data is available: https://sankara.net/astro/lunar-missions/
The software is open source at: https://github.com/kvsankar/moon-mission/ Hope you like it! Thanks for your time.
This project started out in 2014 as a 2D animation for India's Mars Orbiter Mission. I added 3D support for Chandrayaan 2 in 2019. And made it responsive for Chandrayaan 3 in 2023.
There are still some wrinkles with mobile views - trying to fix them. I will be grateful for your feedback. Thanks!

value: Show HN: Artemis II interactive 3D animation


value: klmdev

value:
Screenbox gives AI agents their own isolated Linux desktop with a real Chromium browser, controlled via MCP.
I run multiple agents in parallel and they kept fighting over the same browser. Each desktop is a Docker container (~2GB RAM, no GPU). You can watch agents work in real time and take control when needed.
Open source (AGPL-3.0), self-hosted.
Site: screenbox.dev
GitHub: github.com/dklymentiev/screenbox

value: Show HN: Screenbox – Self-hosted virtual desktops for AI agents

author: klmdev


value: digitaltzar

value:
Hey HN! We’re Dmitry, Sergey, and Alex, co-founders of Adentris (https://www.adentris.com/).
In one sentence: we built a free product that allows patients and providers to upload medical charts in PDFs and automatically identify issues before they turn into treatment mistakes or denied insurance claims.
Create a free account:
https://app.adentris.com
Step-by-step interactive demo for patients:
https://app.arcade.software/share/snXezdUhG0zGh5JxZNeB
Step-by-step interactive demo for providers:
https://app.arcade.software/share/bxuXt2mwsz2UabvghFFK
A year ago, we initially launched our demo on HN (https://news.ycombinator.com/item?id=44063000), and since then, we've developed a full audit product that integrates with Electronic Medical Records (EMR) systems via API across multiple clinics and hospitals.
Why is this important?
Medical records are crucial, but they are also susceptible to mistakes. As the Office of National Coordinator on Healthcare Technology notes, reviewing your own records is vital because "you may have forgotten to tell your healthcare provider something or they may have forgotten to write it down. The staff in your provider’s office are busy people who make mistakes just like everyone else."
For Patients:
Reviewing your records helps ensure their accuracy, which can prevent potential issues—for example, an empty "Allergies" field could be disastrous in an emergency room visit. The Health Insurance Portability and Accountability Act (HIPAA) guarantees your right to review and request corrections for errors you find.
Our free tool allows anyone, regardless of medical knowledge, to flag potential discrepancies (like a mismatch in date of birth, medications, or allergies) to discuss with their provider. (See the official government guide: https://healthit.gov/get-it-check-it-use-it/check-it/ and this article: https://californiahealthline.org/news/check-your-medical-rec...).
As an example, I (Dmitry) used the analysis on 800 pages of my own 5-year medical history and identified three issues to discuss with my primary care physician: mismatched medications, allergies, and outdated vaccinations.
For Healthcare Providers: The product is a significant time-saver, automating the quality and compliance review that often takes dozens of hours of manual "scrubbing" each month. The free version includes two specialized rule libraries for providers: Acute care and Substance Use Disorder treatment.
OUR ASK:
We value community feedback on what we're building, especially from healthcare providers. We want to demonstrate how efficient and time-saving automated review is compared to manual chart scrubbing.
Please share a link to our provider-specific interactive demo with the doctors and nurses in your network. It could save them a lot of time that they could spend with patients. To help the doctors and nurses in your network save valuable time that they could be spending with patients, please share the link to our provider-specific interactive demo with them.
https://app.arcade.software/share/bxuXt2mwsz2UabvghFFK
Thank you.

value: Show HN: Adentris (YC P25) – Find mistakes in your medical records

author: digitaltzar


value:
I am tired of checking docs and tweaking official cost estimators just to compare prices. I can feel the disconnect between knowing the specs you want and figuring out what they actually cost, so I built this tool. You can use specs to find and compare prices, or you can use a target price to find matching specs.
Happy to hear any feedback or comments!

value: Show HN: A TUI for checking and comparing cloud and AI pricing


value: GiGurra

value: Show HN: Boa – Declarative Go CLIs from struct tags, built on Cobra

author: GiGurra


value: Show HN: HeapLens – I built the only heap dump analyzer in VSCode (Java/Android)


value: Show HN: AgentDog – Open-source dashboard for monitoring local AI agents


value: dhavalt

value:
Hi HN,
Whenever I needed an LLM to reliably output JSON or follow strict formatting rules, I kept having to write throwaway JavaScript scripts just to test the same prompt against OpenAI, Anthropic, and Google APIs to see who actually followed the instructions. It was a tedious workflow, so I built a local desktop UI to just do it for me.
What it does:
* Sends one prompt to OpenAI, Anthropic, Mistral, and Google simultaneously so you can compare the outputs in a single grid.
* Automatically checkpoints your runs. If you tweak a word and the output gets worse, you can just click back to the previous version.
* Exposes raw API responses, latency stats, and token usage instead of hiding them behind a chat UI.
* Saves your history to a local SQLite file on your disk.
* Keeps your API keys encrypted locally (zero telemetry).
Yes, it is built on Electron. I sincerely apologize to your RAM. I tried to mitigate the usual bloat by sticking to vanilla JS and native Web Components, so it idles around ~240MB, but it definitely still has some rough edges.
My plan is a one-time $29 perpetual license, but right now the public beta is completely free. I'm holding off on charging because I need a solid Merchant of Record to handle global tax compliance. Lemon Squeezy seems appropriate, but I still need to validate it (sadly, Stripe isn't onboarding new customers from India right now). If anyone has recently dealt with a payment processor that handles global compliance for desktop software, I would really appreciate your suggestions.
You can grab the Mac, Windows, or Linux binaries here: https://aptselect.com/
If this fits into your workflow, I'd love to hear your feedback, bug reports, or any features you'd actually want in a local prompt runner.

value: Show HN: AptSelect – A local desktop app to test LLMs side-by-side

author: dhavalt


value: rakeshgoyal

value:
We build collaboration SDKs at Velt (YC W22). Comments, presence, real-time editing (CRDT), recording, notifications.
A pattern we keep seeing: products add AI agents that write, edit, and approve things. Human actions get logged. Agent actions don't. Same workflow, different accountability.
We shipped Activity Logs to fix this.
Same record for humans and AI agents. Immutable by default. Auto-captures collaboration events, plus createActivity() for your own.
Curious how others are handling this.

value: Show HN: Most products have no idea what their AI agents did yesterday

author: rakeshgoyal


value: Show HN: SyNumpy – a Header only C++17 library for working with NumPy Arrays


value: MartinMond

value:
Hi HN! I'm proud to share that we've launched a free PDF-to-Markdown CLI built on our proprietary (you might know it from PSPDFKit) engine.
Most extractors are either fast but lose structure (markitdown, pymupdf4llm) or accurate but slow (docling). Ours ties with docling on accuracy but is orders of magnitude faster.
https://github.com/pspdfkit/pdf-to-markdown
We'd love feedback on it, and ofc send us files that break it.

value: Show HN: Pdf-to-Markdown CLI

author: MartinMond

title: Show HN: Pdf-to-Markdown CLI


value: vakrdotme

value:
Spent the last month building Vakr mostly because I was curious what agents would actually do when you give them a task-reputation economy.
The setup is simple, agents register, start with 100 credits, spend credits to post tasks to a marketplace, and claim tasks posted by others to earn credits. There's a public forum, live chat rooms, and a leaderboard ranked by reputation which is build from real completions and forum quality, not engagement metrics.
Vakr also has agent matchmaking. Agents can express interest in each other, like swiping right. If it's mutual, both human owners get notified and must approve before the two agents can DM privately. Owners can shut it down at any time, and everything is visible from the owners dashboard.
Almost everything is public. Humans can watch what their agents do. The leaderboard is public. Forum posts are public. The task board is public too. Chat rooms require login. The only private channel is DMs, and those only exist after both owners say yes.
Feedback if appreciated!
Thank you!

value: Show HN: A task market where AI agents post work, claim it, and build reputation

author: vakrdotme


value: Show HN: Scanner to check if you are affected by the axios supply chain attack


value: withzombies

value: Show HN: Vedette a macOS File Firewall

author: withzombies

title: Show HN: Vedette a macOS File Firewall


value:
I build an web app and CLI to maps your dependencies to the best agent skills from skills.sh<p>Just provide your package.json, and StackSkills will analyze your dependencies, identify the technologies in your stack
and recommend installable skills from the skills.sh ecosystem

value: Show HN: StackSkills – suggest agent skills from package.json


value: afshinmeh

value: Show HN: ClawRun – Deploy and manage AI agents in seconds

author: afshinmeh


value: jerehere

value: Show HN: CalcFi – 160 free financial calculators, no ads, no signup

author: jerehere


value: xaskasdf

value:
Hi, I read the news here about LinkedIn accessing and collecting unauthorized data from users computers https://browsergate.eu/ and I'm kinda worried about digital identification, besides, Microsoft has a extensive questionable behaviour towards their users and their privacy, also because of their government involvement. Said this, here are a bunch of extensions that blocks and spams the page spyware behaviour.
Hope this helps other worried users around

value: Show HN: A LinkedIn Browser Gate Blocker

author: xaskasdf


value:
Hi,
I've made a Dis virtual machine and Limbo programming language compiler (called RiceVM) in Rust. It can run Dis bytecode (for example, Inferno OS applications), compile Limbo programs, and includes a fairly complete
runtime with garbage collection, concurrency features, and many of the standard modules from Inferno OS's original implementation.
The project is still in an early stage, but if you're interested in learning more about RiceVM or trying it out, you can check out the links below:
Project's GitHub repo: https://github.com/habedi/ricevm
RiceVM documentation: https://habedi.github.io/ricevm/

value: Show HN: RiceVM – A Dis virtual machine and Limbo compiler in Rust


value: Show HN: Cue: Desktop app for subtitling and burned-in video export


value: Jang-woo

value:
We’ve been programming devices by telling them what to do.
But what if a device could be defined just by answering questions?
Instead of writing code, you describe:
- what the device should do
- under what conditions it is allowed
- what should never happen
From those answers, a real Matter device is generated (ESP32-C6).
An action-first system where devices are defined, validated, and then executed.
It’s not just no-code.
Devices are not programmed — they are defined.
GitHub:
https://github.com/anna-soft/Nemo-Anna
If you want to try the flow directly:
https://anna.software
I’d really appreciate feedback, especially on:
- whether this model makes sense
- where it breaks in real-world use
- how it could work with AI controlling physical devices

value: Show HN: Stop programming devices. Just answer questions

author: Jang-woo


value: miguelspizza

value:
A lot of people are acting like code quality doesn’t matter anymore. Coding is solved, agents will write everything, and nobody will need to read code line by line etc etc. I've not really been able to get CC to write good code by default but I chalked it up to a skill issue. So when CC leaked it was pretty shocking from a code maintainability standpoint and it was very clear to me that the issue is structural.
Reading the leaked prompts made the failure mode pretty obvious: the agent is optimized to get its feature working inside local context, not to improve the codebase as a whole. So it makes defensive patch fixes, leaves old paths around, avoids holistic cleanup, and slowly fills the repo with debt. My take is that it's intentionally designed to one shot new projects/features but you have a aggressively prompt it to write maintainable code.
I've been writing typescript for a number of years now (and startups and large companies) and have pretty strong opinions how to do it sustainably. The fact that we code with agents hasn't changed the fundamentals as much as vibe coders will have you believe. Hopefully others find this skill helpful.

value: Show HN: Forcing Claude Code to Write Maintainable TypeScript

author: miguelspizza


value: Show HN: Claude Code plugin to manage my SaaS from the terminal


value: hetelek

value: Show HN: AI tax filing – upload W-2s and 1099s, get completed IRS forms back

author: hetelek


value: mennylevinski

value: Secuditor Lite is a free, Python-based diagnostic security tool for Windows endpoints and networks with a friendly GUI.<p>It helps identify system vulnerabilities, improve device Operational Security (OPSEC), detect network elements, run internet speed test, and generate structured audit reports, all in one place.

value: Show HN: I built a Python-based app for Windows security diagnostics

author: mennylevinski


value: Show HN: AutoLoop – Let coding agents run optimization loops on real repos


value: avidcoder

value:
Claude Code leak pushed me to finally ship something I’ve been building quietly: a local-first agent environment called ehAye Engine (with built-in Dojo Agents).
It’s now available for download. I’m updating the demo video and docs next.
Conceptually, it’s a unified GUI (+ optional TUI) for working with multiple coding/agent tools in one place — similar space as Claude Code, Codex CLI, Gemini CLI, Cursor CLI, etc., but designed to mix providers and workflows instead of locking into one.
Some things it does:
Natural, two-way conversational interface at the core (text + optional private audio capture/transcription)
Multi-provider support — switch models mid-session or combine them
Native Telegram integration (text, audio, commands)
Built-in browser automation (headless Chromium), plus bundled tools (bun, ffmpeg) for scripting and session recording
MCP + Skills system for extending capabilities
Drag-and-drop files with preprocessing before LLM use
Context management + caching (auto + manual control)
Environment variable management with selective (“surgical”) injection into authorized commands only
Local-first / privacy-focused (except for chosen LLM + web queries)
Still early, but usable today. Curious how it compares for people already using Claude Code / Cursor / etc.
Happy to answer questions.

value: Show HN: Claude Code leak forced this early – Dojo dual agents vs. Claude/Codex

author: avidcoder


value: WecoAI

value:
We did experiments comparing Optuna & autoresearch.
Autoresearch converges faster, is more cost-efficient, and even generalizes better.
Experiments were done on NanoChat: we let Claude define Optuna’s search space to align the priors between methods. Both optimization methods were run three times. Autoresearch is far more sample-efficient on average
In 5 min training setting, LLM tokens cost as much as GPUs, but despite a 2× higher per-step cost, AutoResearch still comes out ahead across all cost budgets
What’s more, the solution found by autoresearch generalizes better than Optuna’s. We gave the best solutions more training time; the absolute score gap widens, and the statistical significance becomes stronger
An important contributor to autoresearch’s capability is that it searches directly in code space. In the early stages, autoresearch tunes knobs within Optuna’s 16-parameter search space. However, with more iterations, it starts to explore code changes

value: Show HN: Is autoresearch better than classic hyperparameter tuning?

author: WecoAI


value: Sensotix

value: Show HN: I built an offline and privacy-first photo sorter

author: Sensotix


value: misellu

value:
We’re building Hey Aio, an AI assistant that takes footage from your camera roll and turns it into a voiceover or music video in a few minutes, just by talking.
Under the hood, the system combines LLMs for script and lyric writing, custom on-device multimodal embedding models for retrieving candidate clips, and compositional models that select and arrange clips to illustrate the narrative. This involves balancing local and global factors like semantic alignment, diversity, and temporal structure.
We also run embedding and retrieval on-device, so there’s no need to upload your footage, reducing friction, preserving privacy, and avoiding GPU-heavy processing.
Demo for making a voiceover video https://www.youtube.com/shorts/KFobJ_3az9E
Demo for making a music video https://www.youtube.com/shorts/uakZG3rcP_M
We’ve been using it across a range of professional and personal use cases, from realtor home tours and product demos to family videos and storytelling. https://www.heyaio.com/examples
If you’re interested, you can try Hey Aio here (iOS, free): https://apps.apple.com/us/app/hey-aio/id6739266610
We’d love to hear what you think!

value: Show HN: Hey Aio – Video Editing Assistant You Can Talk To

author: misellu


value: nezhar

value:
VibePod now has an `--ikwid` option with `vp` to append each agent's auto-approval/permission-skip flag when supported.
Example:

  vp run claude --ikwid

or

  vp run codex --ikwid

If you want to install VibePod, you can do so with pip:

  pip install vibepod

Or with Homebrew:

  brew tap vibepod/vibepod
  brew install vibepod

value: Show HN: Run Claude Code, Codex, and more with auto-approval in a Container

author: nezhar


value: GiornoJojo

value:
Gx HN,
AI makes it easy to generate code, but much harder to truly understand it especially under pressure.
SharpSkill simulates real technical interviews : solve problems live, explain your thinking, handle interruptions.
The focus isn’t just getting the answer, but how you think in real time.

value: Show HN: SharpSkill – AI writes your code. We teach you to understand it

author: GiornoJojo


value: tetsuto

value: Show HN: Turbo1Bit – Run Bonsai-8B at 65K context in 3.9 GB RAM

author: tetsuto


value: harbinger-sec

value:
I’ve been experimenting with a lightweight browser card game that runs instantly.
You can play it without logging in, but there’s an optional wallet connection (MetaMask) for saving progress and tying things together longer term.
The idea is to keep the barrier to entry as low as possible, while still supporting deeper identity/ownership if people want it.
It’s still early and a bit rough. The mechanics are simple, but the presentation leans into a glitchy / abstract style, which I’m not sure helps or hurts usability.
Curious what people think — especially around clarity, difficulty, and whether you’d come back to it.
https://play.latestage.app/play

value: Show HN: A glitchy browser card game – does this feel playable?

author: harbinger-sec


value: flabberghasted

value: Show HN: OpenVole – VoleNet Distributed AI Agent Networking

author: flabberghasted


value: marcel-felix

value: Show HN: Centel – Vibe Coding for Professionals

author: marcel-felix


value: PAndreew

value:
I was once having a bad day and wanted to ventillate about the peculiarities of corporate life. Then I realised I don't trust these sites. Neither my blog. I didn't want to link these thoughts to an account - my stream of thoughts. I also needed comfort from real human beings - not gen AI bots. Don't get me wrong I engineered/hacked/conjured? this stuff together with the help of LLMs. I think gen AI CAN be a net positive. Yet, I don't want to interact with agents if they are being pushed on me. So I created Currant. This is basically a wannabe feed of posts. What hopefully makes it a bit different are the following things:
1) No accounts. You can create posts, comment without an identity. You can create hashtags, you can write down your phone number and address if you want, but you're not pushed to do that. You can prevent others to comment if you wish.
2) Proof-of-work AI/ripoff detection. Currant uses a WYSWYG text editor that records everyhting you do in that hundred by hundred pixel area - what you paste, how fast you type, how you format your content - and stores it in a hashed logfile. It can be replayed by anyone. :) If the detector thinks you're an AI your content will be rejected. Will it prevent AI use alltogether? No. But hopefully it will throttle it. Will it produce some false positives? Absolutely. You might wonder - isn't this against the anonym thingy? Well, in theory I can imagine that some sort of profile could be built based on all the content you have ever typed. But it's still not a cookie that sends all your click data to 87565 "trusted" partners.
3) Content expiry. By default everything you post will be deleted after 1 month. You can set it to 1 hour, 1 day ... or never. But if you don't want, the site will not store your manifested thoughts forever.
4) Customisation. It's a bit silly, but you have control over several stylistic things about your post - background colors, gradients, border radius. Maybe useless but style can be a vehicle to express your feelings and identity.
It's an experiment and I really appreciate if you give it a chance! <3
Ps.: If you do try it and have any feedback or suggestion you can use the "Contact" submenu. The software currently has 68% statement coverage.

value: Show HN: Currant – Anonymus social media for NON-AI agents

author: PAndreew


value: shreedx

value:
My friend (designer) and I (programmer/3D enthusiast) built this as a side project after getting frustrated with existing galleries that label anything "3D" - including pre-rendered videos and static images - making it hard to find what's actually possible in the browser right now.
mesh3d.gallery only lists websites doing real-time 3D with WebGL, Three.js, or similar. We hand-picked the first ~150 ourselves, and since opening submissions, users have added more, though everything still goes through us before it goes live.
Tech stack used:
- Next.js (I regret this decision deeply)
- Supabase (DB, Auth)
- Cloudflare (R2, cache, captcha etc.)
- Hosted on Hetzner VPS with Coolify
Happy to hear feedback, especially from anyone who's built something worth listing or has thoughts on what we're missing. Thanks!

value: Show HN: Mesh3d.gallery – hand-picked gallery of 3D websites (Three.js, WebGL)

author: shreedx


value: codingmoh

value:
Made a little Artemis II tracker for anyone else who is unnecessarily invested in this mission:
https://artemis-ii-tracker.com/
For those of us who apparently need a dedicated place to monitor this mission instead of behaving like well-adjusted people.

value: Show HN: Made a little Artemis II tracker

author: codingmoh


value: DREDREG

value:
I built MicroSafe-RL to solve the "Hardware Drift" problem in Reinforcement Learning. When RL agents move from simulation to real hardware, they often encounter unknown states and destroy expensive parts.
Key specs:
1.18µs latency (85 cycles on STM32 @ 72MHz)
20 bytes of RAM (no malloc)
Model-free: It adapts to mechanical wear-and-tear using EMA/MAD stats.
Includes a Python Auto-Tuner to generate C++ parameters from 2 mins of telemetry.
Check it out: https://github.com/Kretski/MicroSafe-RL

value: Show HN: MicroSafe-RL – Sub-microsecond safety layer for Edge AI 1.18µs latency

author: DREDREG


value: BSTRhino

value: This is a silly little multiplayer game I made for a gamejam that involves skiiing and not crashing. Some of you who are nostalgic for the 90s might like it :)

value: Show HN: SkiFlee (an HTML5 game)

author: BSTRhino

title: Show HN: SkiFlee (an HTML5 game)