value:
Hey HN!
I'm excited to share Musevise — a web app that helps you instantly identify and understand artworks from images.
- Why I built this
When I look at artworks, I often can’t recall the artist’s name or the title.
But without the right keywords, it’s difficult to search online.
I wanted to solve this problem and make it easier for anyone to explore and appreciate art without needing to remember exact terms.
- What Musevise does
Upload any artwork image or paste a URL
AI (Claude 3.5 Haiku) analyzes the image and identifies the artist, title, and visual elements
Automatically adds Wikipedia context for deeper understanding
Works with paintings, sculptures, and various art forms
- How it works
Musevise uses a vision-language model (VLM) to convert an image into descriptive text and retrieve related Wikipedia information.
One challenge was that Wikipedia entries often vary in how titles or artist names are written (punctuation, translations, aliases, etc.).
To handle this, I added a prompt-engineering layer that lets the LLM reformulate the Wikipedia search query dynamically — absorbing inconsistencies before hitting the API.
This approach significantly improved matching accuracy without building a custom search index.
Another technical challenge: sometimes the VLM fails to return output in the strict JSON format expected by the backend, causing parsing errors.
I’m refining prompts and adding fallbacks to make it more robust.
- What's next
Currently, Musevise automatically serves Japanese Wikipedia for Japanese browsers, and I’m working on expanding multilingual support.
Try it out and let me know your thoughts!
https://www.musevise.com

value: Show HN: Musevise – AI identifies artworks and enriches them with Wikipedia


value: tobihrbr

value: Show HN: Starbase – Browser-based MCP server testing with AI chat integration

author: tobihrbr


value: phboot

value: Show HN: SHA-2048 – a 2048-bit hash with AVX2 vectorization and runtime dispatch

author: phboot


value: offerrall

value:
I needed a tool to quickly prototype internal utilities for our company – PDF generators, data processors, file converters that non-technical colleagues could use.
func-to-web generates web UIs from Python function signatures with zero boilerplate:
```python
from func_to_web import run<p>def divide(a: int, b: int):
    return a / b<p>run(divide)  # Web UI at localhost:8000
```
For more complex needs, it supports advanced types:
```python
def process_data(
    scores: Annotated[
        list[Annotated[int, Field(ge=0, le=100)]],
        Field(min_length=3, max_length=10)
    ],  # 3-10 items, each 0-100
    files: list[ImageFile],           # Multiple file uploads
    email: Email,                     # Built-in validation
    notes: str | None = None          # Optional with toggle
):
    return FileResponse(pdf_data, "report.pdf")  # Auto-download<p>run(process_data)
```
Key features:
- *Advanced lists*: Dynamic add/remove with constraints on both list size and items
- *Optional fields*: `Type | None` creates toggle switches
- *File handling*: Upload/download with progress bars, supports GB+ files
- *Rich outputs*: Auto-displays PIL images, matplotlib plots, or downloadable files
- *Dynamic dropdowns*: Runtime-generated options from functions
- *Multiple functions*: Auto-generates index page
Not trying to replace full web frameworks, but for internal tools and quick utilities, this approach feels superior to writing HTML forms.
454 unit tests. Used daily for internal tools and rapid prototyping. Got 150 stars in the first week.
GitHub: https://github.com/offerrall/FuncToWeb
Sharing here in case others find it interesting too :)

value: Show HN: Func-to-web – Turn Python functions into web UIs with zero boilerplate

author: offerrall


value: WolfOliver

value: Show HN: MonsterWriter now supports collaborative LaTeX workspaces [video]

author: WolfOliver


value:
Hey HN — I hate social media but want to build in public and grow followers, so I built gitscribe: an open-source CLI that turns git history into posts, blogs, release notes, etc so I can focus on coding.<p>- Runs locally and can easily hooks into your Git workflow.
- Feeds on your commits and logs, and mimics any style of content (blogs, tweets, scripts, etc).
- Outputs content to a file and your clipboard for easy editing/sharing.<p>Link in the URL. Feedback, bugs, and PRs welcome.

value: Show HN: GitScribe – Because Indie Devs Hate Social Media


value:
HI HN, Sidekick sees and operates every website you use.
Use plain English and it navigates, clicks and types in your local browser
Demo video (40s): https://www.youtube.com/watch?v=8w-KNcFfQ1g
Try it free, for today all sign ups get 1 month of the paid Starter tier for free. There's also a Free tier
I'm Colby a bootstrapped solo-founder
I built Sidekick because I was drowning in repetitive workflows for my vacation rental management business, and I wanted my computer to do the clicking
VCs rejected me and the idea. But I don’t need their money. I need real people to try it and give honest feedback
I'll be hanging around all day, would love to get your feedback and answer questions about implementation, security or anything else!

value: Show HN: Turn Chrome into an Agent

title: Show HN: Turn Chrome into an Agent


value: UnicornSHARP

value: Show HN: I built a user-friendly Google Analytics alternative

author: UnicornSHARP


value: tcodeking

value:
Hey everyone,
I’ve been working on something called Guardrail Layer, an open-source system that sits between your databases and the tools (APIs, LLMs, automations) that query them.
It’s basically a data safety layer, it lets you connect to MySQL or Postgres, automatically redacts sensitive fields, and lets you run or even ask natural-language queries safely.
It’s built with Node.js, TypeScript, Prisma, Postgres, and Docker, and you can run it with a single docker compose up.
It lets you add metadata to help the AI understand your structure better. Also allows you to redact rows in your DB to keep them safe and secure from users and the AI itself.
GitHub: https://github.com/tyoung1996/guardrail-layer
It’s still early (alpha stage) but already functional, I’d love feedback from folks building with LLMs or connecting internal databases to AI tools.
Thanks!

value: Show HN: Guardrail Layer – self-hosted AI data layer for secure DB chat

author: tcodeking


value: AshBuk

value: Show HN: Spark Slider – Lightweight React Carousel (12KB, TypeScript)

author: AshBuk


value: KallDrexx

value:
Video of it in action here: https://youtu.be/3v0oKuXkYlA
This all started with a "simple" premise, can you use the .net runtime as a just-in-time compiler for any language. 2 months later and now I have a fully working code base that can compile most 6502 functions into MSIL and execute them on demand.
It achieves this by instantiating a memory bus with any memory mapped I/O devices you may have the need for, and which memory regions they map to. For the NES, this includes the CPU ram (and its mirrored regions), the PPU device, the cartridge space, etc...
Then the JIT compiler is told to run the function at a specific address. The JIT compiler then:
1. Traces out the function boundaries of the function using the passed in address as the entry point.
2. After all instructions and their ordering is determined, the instructions are disassembled.
3. The 6502 disassembled instructions are converted to one or more intermediary representation instructions
4. A JitCustomization process is run that allows different emulators/hardware setups to modify how the IR instructions are set up. This also allows for analysis and optimization passes.
5. The final set of IR instructions are passed one by one into a MSIL generation class, and the MSIL is written to the `ILGenerator`
6. This IL is then added into an assembly builder and compiled on the fly, providing a static .net method containing that function's code.
7. The JIT compiler then turns that function into an Executable method delegate and executes it
8. The function runs until a cancellation token gets a cancellation signal, or the function hits a return statement with a new address of a function to call.  The JIT compiler then repeats this process, but now with the function at the address returned.
This allows the above video, where NES games are running inside the .net runtime via MSIL. Since it is just-in-time compilation, in theory even arbitrary code execution exploits would be executable.  The main bugs visible in SMB are due to my inaccurate PPU emulation and not about the 6502 code itself.
# Why An Intermediary Representation?
Creating MSIL at runtime is pretty error prone and is hard to debug. If you have one simple mistake (such as passing a byte into a `ldc_i4` emit call) you get a generic "This is not a valid program" exception with no debugging.  So limiting how much MSIL I had to generate ended up pretty beneficial.
One significant benefit though is simplicity. The 6502 has 56 official instructions, each with some significant side effects. Creating MSIL for each of these with all the different memory addressing modes they could contain would spiral out.
However, it turns out you can create any 6502 instruction by composing about 12 smaller instructions together. This made it much simpler to write the MSIL for each IR instruction, and much easier test coverage to ensure they actually compile and work.
# Assembly Creation
There are code paths (disabled) that can actually create real dll files for each function generated.  In theory this means that if you run an application for a sufficient amount of time, you could collect all the dlls and piece them together for a MSIL precompiled build.
# NES Limitations
The NES emulator side isn't complete. It can run games as long as they are up to 32k ROMs with 16K character data. This is just because I didn't bother adding support for all the different bank/memory switchers that cartridges implement.
# What's Next?
Not sure.  I'm tempted to add some other 6502 emulations. Atari 2600 would work but may not be interesting. Using this to fully JIT the commodore 64 is something that is interesting, though I'm not totally sure how much of a rabbit hole emulating the video and other I/O devices would be.

value: Show HN: JIT compilation of NES ROMs / 6502 programs to .NET MSIL

author: KallDrexx


value:
Personally, I think the JJ VCS (https://github.com/jj-vcs/jj) hit a point some time in this past year where I find it hard to find a great reason to continue using git. Over the years I've cobbled together aliases and bash functions to try to improve my git workflow, but after using jj, which works with ~any git repo and integrates great with Github repos, all of the workflow issues I ran into with git are not only solved, but improved in ways I couldn't manage with simple scripts.
One example is the op log, which lets you go to any point in your repo's time and provides simple undo and redo commands when you want to back out of a merge, didn't mean to rebase, etc.
Because I have a pretty strong conviction that JJ is at this point a cleaner and more powerful version of git, my hopes are that it continues to grow. With that, it seemed a proper full-featured GUI was missing for the VCS. There's some plugins that add some integration into VS Code, and there's one in the works to get Intellij support working, but many of the constructs JJ provides in my opinion necessitate a grounds-up build of a GUI around how JJ works.
Right now, [name-redacted] is an MVP in an open beta. I did my best to support all of the core functionality one would need, though there's many nice-to-haves that I am going to add, like native merge support, native splitting, etc. Most of this will be based on feedback from the Beta.
I'm really grateful for the great community JJ has built, alongside the HN community itself in the countless VCS-based posts I've read over the years, and am hoping for lots of input here during Beta under real usage - the goal is to be a full-featured desktop GUI for the VCS, similar to many of the great products that are out there for git.

value: Show HN: I created a cross-platform GUI for the JJ VCS (Git compatible)


value: vinhnx

value: Show HN: VT Code – Research preview semantic coding agent

author: vinhnx


value: Flamehaven

value:
Hi HN, I'm the author of this project.
Unstable Singularity Detector is an open-source implementation of a Physics-Informed Neural Network (PINN) system that detects blow-up singularities in PDEs — like those found in fluid dynamics.
It’s inspired by the methodology in a recent DeepMind paper, but fully independently built from scratch. The system predicts instability thresholds (lambda values), trains PINNs in multiple stages, and reaches machine-level residuals (10⁻¹³) using a high-precision Gauss–Newton optimizer.
This new v1.4.1 release adds:
- Multi-stage PINN orchestration with FSDP and Meta/K-FAC support
- Rank-1 Hessian + EMA for memory-efficient Gauss–Newton optimization
- Residual certificate generation (CI-ready)
- CLI bridge to external CFD solver output (e.g., `.npz` files)
- Docker/Gradio support for easier setup
No signups, no cloud dependencies — everything runs locally (CLI, Docker, or Gradio).
GitHub: https://github.com/Flamehaven/unstable-singularity-detector
Paper inspiration: https://arxiv.org/abs/2509.14185
Would love feedback from folks working on scientific computing, PDE solvers, numerical methods, or ML-based verification. I’m around for questions.

value: Show HN: Unstable Singularity Detector update 1.4.1

author: Flamehaven


value: olwal

value:
I've been interested in real-time Human-AI interaction for a while. This project is a prototype closed-loop drawing system, like "visual autocomplete" for drawings. The idea is that the user just draws along with the AI, without disrupting the flow through manual text prompting.
It works by AI continually observing and responding to live drawing on a canvas. A vision model (using Ollama) interprets what it sees, and that description drives real-time image generation (StreamDiffusion).
For real-time performance, this project is built in C++ and Python, leveraging the GPU for Spout-based texture sharing with minimal overhead.
Reusable components include:
- StreamDiffusionSpoutServer: lightweight Python server for real-time image generation with StreamDiffusion. Designed for interfacing with any Spout-compatible software and uses OSC for instructions.
- OllamaClient: minimal C++ library for interfacing with Ollama vision language models. Includes implementations for openFrameworks and Cinder.
The "visual autocomplete" concept has been explored in recent papers (e.g., arxiv.org/abs/2508.19254, arxiv.org/abs/2411.17673).
Hopefully, these open source components can help accelerate others experimenting and advancing this direction!

value: Show HN: Visual autocomplete for drawings (real-time Human-AI interaction)

author: olwal


value: Copilot AI Agent is a set of free tools that use artificial intelligence to support and assist developers in writing, understanding, and analyzing programming code.

value: Show HN: Copilot AI Agent

title: Show HN: Copilot AI Agent


value: abhishekbasu

value: I got tired of having to manage my sticky notes, and I'm not a huge fan of Google Keep. Stickyflo is how I prefer creating/editing/moving notes around. While this ain't a fancy AI app, it does the job (for me, and hopefully for you too!).

value: Show HN: Excalidraw for Sticky Notes

author: abhishekbasu

title: Show HN: Excalidraw for Sticky Notes


value:
Hey HN!
I built Wyapy to help small businesses understand their customers better and get actionable insights without much work.
Wyapy lets you collect feedback right after an interaction (for example, from a receipt, email, or QR code) and automatically summarizes what people love or what’s not working. It uses AI to surface recurring issues, highlight wins, and suggest what to focus on next.
The idea came from watching local restaurants and small stores struggle with feedback (they either got random Google reviews or nothing at all). With Wyapy, they can see clear insights like “Slow service mentioned 6× this week” or “People loved the new dish”, simple, actionable stuff.
It’s live now: https://www.wyapy.com
You can create a free project, share a feedback link, and see results right away.
You can also browse the demo projects I've created without login: https://dashboard.wyapy.com/demo
Or you can see an example of a survey here: https://feedback.wyapy.com/?id=4d05ab51-8079-4346-b843-69e8c...
Would love any feedback on how I can make this more useful!

value: Show HN: Wyapy – Capture customer feedback and uncover what to improve


value:
I just built Restring
 — a fast, modern toolbox for everyday dev tasks like formatting JSON, decoding JWTs, and converting strings.
I know there are plenty of similar tools out there, but I wanted something that felt instant and smart.
- Fast: Built with SvelteKit and plain HTML/CSS, with minimal dependencies and no UI bloat. The whole site is under 300 KB zipped and feels lightning quick.
- Smart: It tries to detect what you paste (like JSON, JWT, or Base64) and routes you to the right tool automatically.
Currently supports:
Base64, JSON, JWT, URL, Color, and DateTime.
I’ve used React, Vue, and Flutter before, but building this with SvelteKit was a joy — intuitive, minimal, and just works.
Would love feedback, especially on the auto-detection logic and ideas for other tools to add.

value: Show HN: Restring – a fast, smart web toolbox for JSON, JWT, Base64, and more


value: AlexandrBel

value: Show HN: Human replies that sell your product

author: AlexandrBel


value: dortal

value:
I got frustrated with recipe websites that force you through 3,000 words about someone's grandmother before showing the ingredients. So I built Cooky - an AI-powered recipe parser and organizer.
What it does:
- Paste any recipe URL or text → AI extracts structured recipe data
- Automatically detects timers in instructions ("bake for 25 minutes" → countdown button)
- Scale servings up/down with automatic ingredient recalculation
- Track your progress with checkable ingredients and steps
Tech stack:
- Frontend: Expo (React Native) with TypeScript for iOS/web
- Backend: Supabase (PostgreSQL with JSONB for flexible schema)
- AI: OpenAI GPT-4o-mini for parsing
- Deployed on Vercel
The interesting technical bit: I went with a "dumb scraper, smart parser" approach. Instead of trying to handle every recipe site's HTML structure, I just fetch the raw HTML and let GPT-4o-mini extract the recipe. It handles weird formats, handwritten recipes, even recipes pasted from emails surprisingly well.
Web app: https://cooky-app-ivory.vercel.app/
iOS version coming soon (currently in TestFlight)
Would love feedback on the UX and what features you'd want in a recipe app!

value: Show HN: Cooky – AI recipe parser that turns messy web recipes into clean JSON

author: dortal


value: spotus

value: Hi, I wanted to introduce you to the beta version of a project that uses AI to monitor websites. I’d be glad to receive your feedback.

value: Show HN: Free AI Website Change Tracker and Smart Alerts

author: spotus


value: xinbenlv

value: Hey hacker friends, we are building a domain platform that is "modern". Offering modern features we think a domain platform should provide such as ownership with NFT (or if you dislike NFT as a term, cryptography and interoperability), AI for brand generation etc.<p>We love to get your feedback

value: Show HN: Namefi tokenize domain for trading, DeFi and future internet

author: xinbenlv


value: siggalucci

value: This is a Mac app that helps you manage conversations with LLMs via Ollama or any API. Allows you to set a hotkey to quickly query your LLMs after highlighting any text on your computer or selecting a file.

value: Show HN: ContextKey – Use a hotkey to query LLM using any text or file

author: siggalucci


value: vcast

value:
NY times has a popular rent vs buy calculator (https://www.nytimes.com/interactive/2024/upshot/buy-rent-cal...) However, it is gated by the paywall so I decided to vibecode my own using Replit.
Replit made it super easy for me as a non-developer to deploy the application. However I quickly learned that Replit is quite expensive during the iteration phase. A typical bug fix or design change would cost about 1min of work and $.50. This quickly added up to a bill of about $300 for the month. It took me too long to learn that Replit supports SSH to VS Code so I am now using the Claude extension from VS code for all the changes. I do still use Replit for hosting and deployment but I don't exceed what is included in the monthly cost ($25).
The site I built: https://housecalculators.com/rent-vs-buy-calculator

value: Show HN: I Spent $300 Learning That Replit Has SSH Support

author: vcast


value: uscnep-hn

value: ComfortView is a browser extension that improves readability by applying research-backed design choices: a soft, low-glare sepia background reduces eye strain; line spacing is increased by 1.5× for easier reading; line lengths are optimized to 50–75 characters to minimize eye fatigue; and clean, sans-serif fonts ensure clarity on screens. For more info : https://github.com/uscne/ComfortView

value: Show HN: ComfortView – Text-only reading view with research-backed design

author: uscnep-hn


value: Show HN: Launching Claude Skills Directory


value:
An ad-free, open source, self-hostable collection of 120+ networking utilities for devs, sysadmins and network engineers. Works offline, mobile-first and super lightweight. Can be customized with own branding, colors and tool selection.
Source is on GitHub at https://github.com/Lissy93/networking-toolbox

value: Show HN: Every single network-related tool you'll ever need, in one place


value: resill

value: WireGuard is a great VPN protocol. However, you may come across networks blocking VPN connections, sometimes including WireGuard. For such cases, try tunneling WireGuard over HTTPS, which is typically (far) less often blocked. Here's how to do so, using Wstunnel.

value: Show HN: Tunneling WireGuard over HTTPS Using Wstunnel

author: resill


value:
I'm a developer (not a 3D artist) who's been frustrated with current AI text-to-3D tools — most produce messy, monolithic meshes that are unusable without hours of cleanup.
So I built NativeBlend, a side project aimed at generating editable 3D assets that actually fit into a real workflow.
Key features:
- Semantic Part Segmentation: Outputs separate, meaningful components (e.g., wheels, doors), not just a single mesh blob.
- Native Blender Output: Generates clean, structured .blend files with proper hierarchies, editable PBR materials, and decent UVs — no FBX/GLB cleanup required.
The goal is to give devs a usable starting point for game assets without the usual AI slop. I have a working demo and would love feedback: Does this solve a real need, or am I just scratching my own itch?
Thanks for taking a look!

value: Show HN: NativeBlend – Text to fully editable 3D Models that don't suck


value: DaSettingsPNGN

value:
I would like to present a thermal management system I have been working on.  The idea was that I wanted to run a production Discord Bot on my S25+ rather than paying for a traditional server.  I ran into the Samsung throttle wall: at 42 degrees Celsius for battery temperature, Samsung will hard throttle your phone down to 50% performance until it regains a more moderate temperature.  This is by definition reactive, and can cause a spiral.  Lower performance increases the duration of my renders, this heats my phone even more, and it never recovers.  I propose a different method: predict thermal events before they happen, model the internal thermal properties of the different cores on your phone, and use Newton's Law of Cooling with thermal "banking" (having tasks wait to start for enough thermal overhead that it can successfully complete) and with using persistent learning to model how much thermal headroom you actually need for each action your bot takes.
The key is realizing that temperature is not a discrete event.  Using sensors to measure the temperature now does not tell you how it will increase or decrease in the near future.  Predictive intelligence is entirely possible when using thermal mass, knowledge of your hardware constraints, knowledge of your thermal effects from your bot, and preparing for thermal events BEFORE they happen, not when they do.  This keeps your phone under the thermal throttle limit perpetually, which translates to improved performance, battery life, hardware life, and user experience.
Implementation includes using public facing sys reads and Termux API to monitor core temperatures in real time (non-root), and using physics and past data from your actual bot use to predict thermal impacts and how you can prevent them before they even happen.
The main principle is modeling your phone as a interconnected system with fluid states, not discrete events that end up being locked into either throttling or not-throttling.
I am sharing this to discuss my model with engineers and physicists, to see if my thermal model can be improved at all, to see if my code can be improved at all, and to see if it would be of use to anyone else who would like to run a production server on a flagship phone without rooting it or melting it.  All feedback appreciated.  I'm available to help teach my software practice as well: I code through a physics lens.  Computers obey physics too, as much as they seem to not want to admit it.
GitHub: https://github.com/DaSettingsPNGN/S25_THERMAL-
Discord: @DaSettingsPNGN

value: Show HN: Predictive Thermal Management for a Production Phone Server

author: DaSettingsPNGN


value: lostqubit

value: My usual outlets for internet doom scrolling have felt a little stale lately, and I've been feeling a little nostalgic for the old internet, so I built sixth coast. It's the frontend for a webcrawler that looks for personal blogs and pulls RSS feeds out of them when they're present. The posts on the home page are from the last 24 hours, sorted by the inverse post frequency of the feeds they belong to. The results are a little quirky, but I've found it useful as a way to discover new, human-created corners of the internet.

value: Show HN: Sixth Coast -- RSS Blog Discovery Website

author: lostqubit


value: CoreLathe

value:
Single-header JSON field extractor for when you control both message format and receiver.
106 bytes on ARM Cortex-M4, no malloc, MIT licensed.

    #include "packet_atoms.h"
    char temp[16];
    jet("{\"temp\":22.5,\"hum\":65}", "temp", temp, sizeof(temp));
    // temp now holds "22.5"

Deliberate limitations:
- Fixed field order (uses strstr)
- No nested objects/arrays
- Strings include quotes
- You design the protocol
Size comparison (ARM ‑Os):
- cJSON: 3.2 kB + malloc
- JSMN: 800 B + token iteration
- This: 106 B
Tested on Cortex-M4 and x86-64. Header-only, copy-paste ready.

value: Show HN: 106-byte JSON field extractor for embedded (8× smaller than JSMN)

author: CoreLathe


value: ywv

value: Hi everyone, I built a product hunt specifically for University of Washington students. If this receives enough traction I might consider branching out to other universities. Could be a great way to launch your startup, get beta testers, source early founders, etc. LMK what y'all think.

value: Show HN: Product Hunt for UW Students

author: ywv

title: Show HN: Product Hunt for UW Students


value: harryyking

value:
With the advance of AI, everyone is building and creating solutions. It is actually amazing to see people in Africa engage this creative field and produce products that could help their ecosystem.
So I built a platform that will soon be the biggest directory of tech products made by people in Africa to solve African Problems.
I am taking this path because I understand we have very different problems and different cultures and things work differently especially in Africa.
What do you guys think? I want your feedback on everything.

value: Show HN: I built a Product Hunt alternative for African tech startups

author: harryyking


value: brettshep

value: Show HN: Refbox – Reference anything while you work

author: brettshep


value: jrandolf

value:
TL;DR: We built Workbench, a VM-based, ephemeral sandbox you (or your AI agents) can spin up, use, and tear down on demand—exposed over the Model Context Protocol (MCP) for code, filesystem, and terminal access. We’re opening a private beta for 25 users; everyone after will be waitlisted. When you join, you’ll get an email with a Discord invite for support and feedback. Issues/examples on GitHub.
Why we built it
Most useful agentic workflows end up writing code. Local tools are great but live on your machine and can be messy for security, reproducibility, and resource contention. We wanted the same “code+tools” experience—but cheap, temporary, and remote—so every run happens in an isolated clean room that auto-expires.
What it is
- Ephemeral VMs: clean, isolated environments for each run
- Full capabilities via MCP: code execution, filesystem, terminal
- Remote & disposable: spin up in seconds; auto-teardown shortly after
- Integrates with MCP-compatible clients (IDEs/assistants) using a simple URL + API key
Usage-based: pay for runtime only (no idle)
Quick start
1. Sign in with GitHub at workbench.brwse.ai.
2. Create an API key.
3. Use the MCP.

value: Show HN: Workbench – ephemeral cloud sandboxes for agentic coding

author: jrandolf


value: rodgetech

value: Show HN: Omegle for Devs

author: rodgetech

title: Show HN: Omegle for Devs


value: helloanoop

value:
I built a small library over the weekend:  fast-json-format
In Bruno we have an issue where when displaying response, bigints get truncated as JSON stringify does not support bigints.
fast-json-format is a lightweight JSON formatter that pretty-prints without losing data or precision. It preserves BigInt, decimal formatting, and handles malformed input more gracefully.

value: Show HN: A Fast JSON Formatter

author: helloanoop

title: Show HN: A Fast JSON Formatter


value: altugnet

value:
Hello, I made this site to combat misinformation on the internet by allowing users to prove that their claim is valid by linking multiple sources and combining them in a single link<p>It's very early stage so I would love feedback on:
- What types of claims would be most useful to you?
- How can I make verification/sourcing more robust?
- Any features that would make this actually useful vs just interesting?  Thanks in advance, feel free to roast :)

value: Show HN: Online Sourcerer – The best answer to 'source?'

author: altugnet


value: tbabenko

value: Show HN: First platform in the world to rank robots

author: tbabenko


value: thefairdraw

value:
Wanted a picker that doesn’t rely on a server, token, or luck you can’t prove.
Inputs → seed → hash → choice. All client side.Logic seems tight, but extra eyes are better than mine.
Happy to hear if something’s off.

value: Show HN: TheFairDraw a verifiable, client side random picker

author: thefairdraw


value: I've built a Godot plugin that lets you publish and update your projects directly from the editor to TheGates. It gives you free hosting and native performance on Linux, Windows, and macOS — no setup or packaging needed.<p>it’s meant for indie devs who want to share builds quickly, gather feedback, or host small demos without exporting to multiple platforms or asking users to reinstall every time.

value: Show HN: One-click publishing for Godot games (Linux, Windows, macOS)


value:
I just open-sourced WatchDoggo, a lightweight service monitor built with Flask.
It checks multiple services (APIs, CRMs, etc.) from a single JSON config and shows uptime in a simple dashboard.
GitHub: https://github.com/zyra-engineering-ltda/watch-doggo
Built with  by Zyra Engineering. Feedback welcome!

value: Show HN: WatchDoggo – simple open-source service status monitor


value: jmrashedbd

value: Building a Production-Ready PHP REST API Framework

value: Show HN: A lightweight production-ready PHP REST API framework (Open Source)

author: jmrashedbd


value: maziweiss

value: I was frustrated with the options for S3 GUIs, so I built one myself. nicebucket is focused on great UX, performance through the use of Tauri and privacy. We do not track anything that you do and its code is completely open-source.

value: Show HN: An open-source S3 GUI for faster browsing and zero tracking

author: maziweiss


value: Show HN: Data-driven food rankings to make healthier dietary choices


value: surrTurr

value:
Hi HN!
Recently, I looked at my old Instagram Stories and thought: Wow, Stories feel much more immersive than normal photos in my Gallery! The catch: I always have to publish them.
*Zeitgeist* fixes that. It’s a story camera for yourself. No followers, no posting. Just private stories you can look back on.
*What it does*
* Shoot in the familiar story format (photo/video), then add text, GIFs, Memos and more.
* View your stories on a Grid / Map
* Everything stays on your device/iCloud. No account. No feed.
*That's it*
The app is completely free; in the future I may add some paid cosmetic IAPs but nothing major like ads or feature blockers.
If you want to try it out: https://apps.apple.com/de/app/zeitgeist-stories-for-you/id67...

value: Show HN: Zeitgeist – Stories for You

author: surrTurr

title: Show HN: Zeitgeist – Stories for You


value: imooc

value:
A few months ago, OpenAI open-sourced their incredible CLI coding tool Codex — a project we at AI Republic have loved and used heavily in our own development.
Today, we’re excited to share something more exciting: we’ve transformed Codex into a fully autonomous, privacy-preserving AI agent that runs right inside your browser.
This new in-browser agent can understand your natural-language commands and perform real tasks directly within the web pages you’re already using — no backend, no data leaving your device, just pure local intelligence.
Try it out and see the future of your work automation:https://github.com/The-AI-Republic/browserx
Here is demo: https://youtu.be/Aevz0Emz-b8

value: Show HN: We Turned Codex Into In-browser AI Agent!!

author: imooc


value: Just vibe coding a Calendly alternative for my personal use. Why? I've been paying $12/month for Calendly's meeting bookings and Google Calendar syncs. Time to hack my own.

value: Show HN: I Built a free Calendly alternative in 24 hours


value: Check it out!

value: Show HN: Distributed Storage System to 8x LLM Inference, GPU Training Efficiency

story_text: Check it out!


value: dorianniemiec

value:
Hello! I got quite some feedback on a web server I'm building, so I'm rewriting the server to be faster and easier to use.
I (and maybe some other contributors?) have optimized the web server performance, especially for static file serving and reverse proxying (the last use case I optimized for very recently).
I also picked a different configuration format and specification, what I believe is easier to write.
Automatic TLS is also enabled by default out of the box, you don't need to even enable it manually, like it was in the original server I was building.
Yesterday, I released the first release candidate of my web server's rewrite. I'm so excited for this. I have even seen some serving websites with the rewritten web server, even if the rewrite was in beta.
Any feedback is welcome!

value: Show HN: I'm rewriting a web server written in Rust for speed and ease of use

author: dorianniemiec


value: tiempie

value:
I made a self-hosted API for crud-ing json data (initially for simple storage use cases). However, I started using to mock APIs, where I have scripts that create/edit random jsons and I make them available as API endpoints through this application.
The API is based on your JSON structure. So the example below is for CRUD-ing [key1][key2] in file.json. The value (which can be anything) is then added to the body of the request. Moreover, there are helper functions for appending and incrementing values.

  DELETE/PUT/GET: /api/file/key1/key2/...

value: Show HN: Mocking APIs by just posting jsons to endpoints

author: tiempie


value: harperhuang

value:
Hi HN,
I just launched UltraFaceSwap (https://ultrafaceswap.com), an AI face swapping tool that handles photos, GIFs, and videos with single or multiple face swaps.
*What makes it different:*
- *Multi-person swapping*: Swap multiple faces in one image/video (most tools only do one)
- *Multi-face GIF support*: First tool I've seen that handles multi-person face swapping in animated GIFs
- *Video quality*: Maintains temporal consistency (no flickering between frames)
- *Comprehensive format support*: Works seamlessly across photos, GIFs, and videos
*Why I built it:*
A friend needed a face swap tool for their project, so I tried every option on the market. They all had limitations:
- Only single face swaps
- Poor video quality with flickering
- No proper GIF support, especially for multiple faces
- Clunky UX requiring multiple steps
So I built what I wished existed.
*Pricing model:*
- Free trial to test it out
- Daily free credits (casual users might never pay)
- Pay-as-you-go for volume (no subscription)
*Tech challenges I solved:*
- Face tracking across video frames
- Handling occlusions (when faces turn away)
- Multi-face detection and assignment in animated GIFs
- GIF color palette preservation while swapping multiple faces
*Current limitations:*
- Processing videos takes time (30s video = ~3-5 min processing)
- Works best with clear, well-lit faces
- Very fast motion can still cause artifacts
I'm a solo developer and spent 2 months getting the quality right. Would love feedback from HN:
- What use cases would you have for this?
- Is multi-face swapping something you've needed?
- Any concerns about the technology?
Try it out – I think you'll find the quality noticeably better than alternatives.

value: Show HN: UltraFaceSwap – Multi-face swap for photos, GIFs, and videos

author: harperhuang


value: shnksi

value: Show HN: I made a tool to help teachers build exams, lessons, etc. in minutes

author: shnksi


value: pariharAshwin

value:
I built FocusStream because I was frustrated with how hard it is to stay focused when trying to learn from YouTube.
You go there to watch one tutorial and twenty minutes later, you're deep into random recommendations that have nothing to do with what you came for.
FocusStream solves that. It strips away the noise and lets you use YouTube intentionally:
- You enter a topic you want to learn.
- It fetches only relevant educational videos.
- No autoplay, no sidebar recommendations, no algorithmic rabbit holes.
The goal is simple: help people actually learn from YouTube without getting pulled away by distractions.
It's free, minimal, and runs directly in the browser.
Try it: https://focusstream.media
 For those who prefer to watch a video, here's the demo:
https://drive.google.com/file/d/1fCvOJ6kRs9jn7O_hIGgP6wBuq4f...
Would love your feedback, especially from anyone who's struggled to stay focused while learning online.

value: Show HN: FocusStream – Learn from YouTube Without the Distractions

author: pariharAshwin


value: aschapmann

value:
Hey HN,
I'm a solopreneur and I ship apps like a madman: 7 projects in the last year.
I always felt like I was doing marketing, a tweet here, a LinkedIn post there.. but when I looked back, I couldn’t remember what I’d actually done.
So I built Marketing Memory for 2 reasons:
1. To make marketing visible and consistent, like tracking commits but for growth
2. To understand which actions actually drive traffic and impact
It connects your marketing activity logs with Google Analytics so you can finally see your effort and results in one place.
I hope this helps other makers who struggle to stay consistent with marketing. Would love your feedback pls
Axel

value: Show HN: A tool to track your marketing consistency

author: aschapmann


value: antonellof

value:
Built a multi-agent research system with OpenAI Agents SDK where specialized AI agents collaborate autonomously:
Master Orchestrator → Data Analyst → Statistician → Report Writer
Each agent has specific expertise. The orchestrator delegates tasks. All agents can execute code securely to solve problems.
Example workflow: "Analyze e-commerce data"
- Data Analyst: writes Python to load/clean data, spots trends
- Statistician: performs significance tests, calculates growth rates
- Report Writer: synthesizes findings into executive summary
This demonstrates OpenAI Agents SDK's handoff system + autonomous code execution working together. One of 6 examples including a stock analyst with ML predictions, interactive coding assistant, and data viz pipelines.
GitHub: https://github.com/Cognitora/Integration-Example-OpenAI-Agen...

value: Show HN: Multi-Agent AI with OpenAI Agents SDK (Analysts → Statisticians)

author: antonellof


value: control-h

value: We are looking for pilots to test it out; setting up will take only a few minutes. General feedback also appreciated.

value: Show HN: A user feedback system with no dashboards

author: control-h


value: yardole

value:
Hello, i wanted to share this tool where you can use simple English prompts (more like conditions) to monitor anything in real-time like a cctv just using a camera like your old phone/tablet or computer with a webcam.
You can also receive alerts through telegram and email.
It is in beta now, and everything is free.
It would be tremendously appreciated if you can try it out and give some feedback. /\

value: Show HN: You can turn any phone or device into an AI CCTV at home using VLM

author: yardole


value: BohdanPetryshyn

value:
Hey HN,
I’m building Lenzy AI - probably the first product analytics platform for AI agents.
From my research:
Companies building AI agents have thousands or even millions of conversations. In these, users express what they need, use, love, or hate. Often long before they reach out to support (or churn).
Some teams try to read chats manually, some build in-house pipelines to analyze them, others completely miss out on this data.
The idea:
Lenzy continuously analyzes conversations users have with your AI agents to:
1. Discover missing features (e.g. "Fetch info from a URL" mentioned 42 times this week)
2. Spot churn signals (e.g., “Bob’s requests were fulfilled in 35% of chats. Frustration is high”)
3. Detect chats that require human review.
4. Track user satisfaction and task completion rates.
5. Surface any custom insight (e.g., “Top topics with support?”, “Most used features?”)
Existing solutions:
I reviewed about 10 analytical tools like Langfuse, Helicone, and Braintrust. They all seem to focus on evaluating individual LLM calls, not full conversations. Some are starting to move toward multi-turn evals, which suggests demand but they look constrained by data models built around single-call evaluations. For example, in Langfuse you’d need the entire conversation in one LLM call to analyze it (N+1 evaluations).
Where I’m at:
It’s been three weeks since the idea’s inception. I’ve interviewed 12 founders shipping AI agents and developed the product concept.
Now, I’m resisting the urge to build until I find the right design partners to build this with.
If you’ve shipped an AI agent with 100+ daily conversations and aren’t analyzing them yet, consider becoming a Lenzy design partner at https://lenzy.ai. You set the price. I build for your needs. Premium support forever.
Would love your feedback! What am I missing? Should I make it open source?

value: Show HN: Lenzy AI – Turn AI agent conversations into actionable insights

author: BohdanPetryshyn


value: cpickett

value: xcache.io lets you instantly create private Redis caches, each with a unique ID, with no signup required. You pay per use using USDC via the x402 protocol, no subscriptions or accounts needed. It’s ideal for developers and agents needing quick, isolated caching for experiments or workflows.

value: Show HN: Xcache.io – fast, instant, permissionless Redis cache

author: cpickett


value: juros

value:
I've been researching the bot & proxies space for years. I slowly incubated a service to protect public forms, contents and APIs. It recenty reached a few million daily requests and I now dare to bring it to light.
Truesign detects bots, proxies/vpns and fake emails, through a single request from the browser, without challenges or user interaction. It can block the request based on rules you choose, or grant a token with encrypted information about the visitor for you to decide.
I created a few pages to showcase how it works:
- https:/demo.truesign.ai/protected-form : a form you can't post if you're a bot, a human behind a vpn, or input a fake/disposable email
- https:/demo.truesign.ai/protected-content : a page you can't access if you're a bot or a human behind a vpn
- https:/demo.truesign.ai/protected-content-no-js : like above but there's no Javascript analysis of the browser, it only catches trivial bots like a python script or curl. For those that need to serve their content to javascript-less cients.
I'd love if you hackers could attempt to troll the above using bots or VPNs. I'll share the results in 24h.
Some interesting points about Truesign:
- your contents are protected by simple HTTP redirections, no need to place your whole infra behind a MITM (== Cloudflare)
- attack detection: allow bots and anonymizers until their traffic exceeds a suspicious threshold
- granular rules (i.e. block bots, flag fake emails) that can be switched in real time
- admin dashboard to inspect and analyze your traffic
There's a free plan to play around. Also I offer discounts to free/public services.
Super interested in your feedback!

value: Show HN: Bot, proxy and fake email detection without captchas

author: juros


value: Xlexander

value: Show HN: Let Customer Finding-Conversion-Retention be all our problem not yours

author: Xlexander


value: protontypes

value: Show HN: Good First Lines – Get Started with Transmission Line Mapping

author: protontypes


value: ali-dev

value: Show HN: Formcn: modern shadcn form builder

author: ali-dev


value: mabolivar

value:
Correct link is here → https://somniaplanner.com/en/barcelona/2026.
I built SomniaPlanner, a web app that maximizes your time off by aligning PTO with city-level public holidays and weekends.
What’s different:
(1) you can mark block (must-work) and prefer (must-take) days as hard constraints—the optimizer must satisfy them.
(2) A linear calendar view for planning fans.
Why: this was a first step toward a parental-leave planner for Spain; PTO planning lets me validate the constraint UX and solver.
How: a client-side dynamic programming algorithm enumerates feasible ranges and scores them by days-off/PTO, with a small balance term to trade off one long streak versus several shorter breaks. Runs fully in the browser (<20ms); no backend. Optimization engine written in TypeScript.
Try it:
San Francisco 2026 - https://somniaplanner.com/en/san-francisco/2026
Barcelona 2026 - https://somniaplanner.com/en/barcelona/2026
Bogota 2026 - https://somniaplanner.com/en/bogota/2026
Browse all cities: https://somniaplanner.com/en
Feedback:
– What drawbacks do you see from running client-side only?
– Are the block/prefer interactions intuitive and explanations clear?
– Any ideas for extending this app (e.g. parental-leave planner or Travel-aware planning — budget + flights/hotels)?

value: Show HN: City-aware PTO optimizer with block/prefer day constraints

author: mabolivar


value: zackho

value: NewsletterStack is a curated directory of tools and platforms powering today’s most successful newsletters. Discover what creators actually use to send, grow, and monetize their audience. Compare pricing across email platforms, explore tech stacks behind leading publications, and find resources to help you build a sustainable newsletter business.

value: Show HN: NewsletterStack – Discover the tools behind successful newsletters

author: zackho


value: moudah

value:
Hey HN
After years in the startup world, listening to hundreds of pitches, I saw a pattern over and over:
- A stagnant market is a slow death.
- A saturated market is a brutal, cash-burning fight.
- A growing, overlooked market is a massive, unfair advantage.
I got obsessed with finding that third option. So, I built Markethunt.
It’s a simple database of market reports designed to uncover those high-growth niches. Think less "AI disruption" and more "Automated Fare Collection Systems" - real industries with real money, just not always in the headlines.
Each report gives you the growth projections, key drivers, and a few concrete startup ideas to get you started.
I've made it free to check out 7 rotating reports. No credit card, no nonsense, just see if it's useful for you.
I'd love your feedback: is this genuinely useful, or am I just scratching my own itch?
The site is built with Next.js and Supabase. The link is here: https://www.markethunt.io/
I'll be around all day to answer questions. Thanks for looking.

value: Show HN: Markethunt – I built a database to find growing, overlooked markets

author: moudah


value: hauxir

value: Show HN: MacOS Live Screensaver – A screensaver that plays live video streams

author: hauxir


value: manicmanias

value:
I built Databomz to fix a recurring problem in my AI workflow — scattered prompts, lost versions, and no simple way to reuse or share them with teammates.
Databomz includes:
- A Chrome Extension to capture prompts instantly from any LLM (ChatGPT, Claude, Gemini, etc.)
- Paste prompts directly from the extension into your chats or save them in one click
- A WebApp with workspaces with tags, folders, and version history
- Search to instantly find prompts by keyword or tag
- Sharing controls for individuals and teams
- A Public Prompt Library for discovery and inspiration
There’s a Forever Free version that already covers a lot of features — it’s meant to be genuinely useful for solo users, not just a demo.
Website: https://www.databomz.com
Would love feedback from anyone managing multiple AI prompts or collaborating across tools. What’s the hardest part of keeping your prompts organized?

value: Show HN: Databomz: Organize and Share AI Prompts via Chrome Extension and WebApp

author: manicmanias


value:
I've been working on this for a while and figured there were a lot of avid readers on here.
TBR Deal Finder is a desktop app to track and centralize pricing across digital book retailers. It integrates with Kindle, Audible, Chirp, and Libro.fm, plus book discovery platforms like Goodreads and StoryGraph. It tracks prices over time and shows you where to find the best deal.
It also handles Whispersync pricing—where you can add a Kindle Unlimited ebook to unlock deep discounts on the Audible version.
Built with Python and Flet. Happy to answer questions!

value: Show HN: TBR Deal Finder – Track and compare deals on audiobooks and ebooks


value: snide

value:
Hey all. I've spent the bulk of 2025 fiddling with Table Slayer, a virtual table top specific to in person play with a television. Although there are plenty of options for playing games like Dungeons and Dragons online, there wasn't much tailored to running a game with friends at a table.
The source is open[0], and my stack is currently SQLite, Sveltekit, and Fly. I use Cloudflare for my media, and workers that handle the Partykit real-time syncing (which additionally uses YJS for conflict resolution and syncing).
I have a few dozen paying users at this point, but mostly this is a labor of love that scratches a specific itch I've had myself. Right now I'm working on touch screen controls to support some large-format touchscreens I'm trying to source.
[0]: https://github.com/Siege-Perilous/tableslayer

value: Show HN: I built a virtual tabletop for in person RPG games

author: snide


value: nicohayes

value: Show HN: I built an AI music generator

author: nicohayes

title: Show HN: I built an AI music generator


value: jpzk

value: Show HN: Habit Tracking with API/TUI and MCP

author: jpzk


value: Show HN: Kite – Copy Files from Git Repos (No, That's It)


value: amironi

value:
I built ContextGuard after discovering that 43% of MCP servers have critical security vulnerabilities. MCP (Model Context Protocol) is the new standard that lets Claude Clients(Desktop, Windsurf, Cursor, etc.) access external tools and data sources - think of it as a plugin system for AI assistants.
The problem: When you give those clients access to your filesystem, databases, or APIs through MCP servers, you're opening up serious attack vectors. Prompt injection, data leakage, and path traversal attacks are all possible. Most developers building MCP servers don't have security expertise, and there wasn't an easy way to add protection.
What ContextGuard does:
- Wraps your MCP server as a transparent security proxy
- Detects 8+ prompt injection patterns in real-time
- Scans for sensitive data (API keys, passwords, SSNs) in responses
- Prevents path traversal attacks
- Rate limiting to prevent abuse
- Comprehensive JSON logging for auditing
- <1% performance overhead
Technical approach:
- TypeScript-based stdio proxy
- Pattern matching + heuristics for threat detection
- Works with any MCP server using stdio transport
- Zero code changes needed - just wrap your existing server
- All detection happens synchronously in the request/response flow
The README includes a testing section where you can see the same attacks succeed on an unprotected server vs being blocked with ContextGuard enabled. It's pretty eye-opening to see how easy these attacks are.
Why open source:
Security tools need transparency. I want the community to audit the detection patterns, contribute new ones, and help identify blind spots. Plus, MCP is still early days - we need to establish security best practices together.
Roadmap:
Currently working on SSE/HTTP transport support, a web dashboard for monitoring, and a custom rule engine. Planning to offer Pro features for enterprises (team management, priority support, advanced analytics) while keeping the core security features free and open source forever.
I'd love feedback on:
1. What other attack patterns should I prioritize detecting?
2. Is the web dashboard a must-have or nice-to-have?
3. Any blind spots in the current detection logic?
4. Should I focus more on detection accuracy or performance?
The project is on GitHub with full docs and examples: https://github.com/amironi/contextguard
You can try it right now:
npm install -g contextguard
contextguard --server "node your-mcp-server.js"
Happy to answer any questions!

value: Show HN: ContextGuard – Open-source security monitoring for MCP servers

author: amironi


value: sanyam-khurana

value:
After a decade of shipping Django to production, I got tired of solving the same setup problems on every new project.
Environment-first settings. Sensible auth defaults. Structured logging. CI from day zero. Pre-commit hooks. Docker. Security hardening. Every project meant two days of boilerplate before writing business logic.
So I built Django Keel: a production-ready Django starter that eliminates the yak-shaving.
GitHub: https://github.com/CuriousLearner/django-keel
*What you get*:
- 12-factor config with environment-based secrets
- Production-hardened security defaults
- Pre-wired linting, formatting, testing, pre-commit hooks
- CI workflow ready to go
- Clear project structure that scales
- Documentation with real trade-offs explained
*Background*:
I maintained a popular cookiecutter template for years. Django Keel is what that should've been from the start—battle-tested patterns without the accumulated cruft.
*Who it's for*:
Teams and solo builders shipping Django to production who want a strong baseline without tech debt.
Feedback welcome on what works, what doesn't, and what's missing. Issues and PRs appreciated.

value: Show HN: Django Keel – 10 Years of Django Best Practices in One Template

author: sanyam-khurana


value: vladoh

value: I built this web app to experiment with the Gemini Computer Use model and learn more about its capabilities. I'm using it for some automation tasks, and it works quite well in some cases while failing in others, but it is quite good overall even if a bit lazy :)

value: Show HN: Web interface for the Gemini 2.5 Computer Use model

author: vladoh


value: liad

value: Show HN: Agent Spending Controls – Enforce spending limits without custody

author: liad


value: andersmyrmel

value: Show HN: Vard – Zod-inspired prompt injection detection for TypeScript

author: andersmyrmel


value: abacussh

value: Apicat is the ultimate offline Postman alternative that stores your .http files locally. It’s Git-friendly, open-source, and highly compatible with Postman. Test APIs offline with this powerful free offline API client designed for developers who need a reliable local API testing tool.

value: Show HN: Apicat – A Lightweight Offline Postman Alternative

author: abacussh


value: justanotherunit

value:
Hey Hacker news!
I was in the need of a website that can let me convert images to native icons (linux, mac and windows) easily for an application I am building. Since vibe coding is a thing and this was a perfect fit for something that not need to be maintained, but has a useful purpose, I used the magic of LLM and vibed with them.
I want to share it with all you guys if you are in the need of this. It is statically hosted in github pages, all running on the client using web assembly to convert the images.

value: Show HN: Free web assembly icon converter

author: justanotherunit


value: Your AI-powered train travel assistant for the Netherlands.

value: Show HN: RailGPT, train travel assistant


value:
Managing multiple GitHub accounts (work/personal) is a pain – switching git configs, SSH keys, and GitHub CLI auth manually.
I built ghswap to automate this. One command (`ghswap work`) and everything switches. It also supports directory-based auto-switching and handles SSH key generation.
Install: npm install -g ghswap
Repo: https://github.com/shubhamV123/ghswap
Would love feedback from the community!

value: Show HN: Ghswap – CLI tool for managing multiple GitHub accounts


value: FinnLennard

value: I was surprised to learn that open source model providers never get feedback/reports from their actual end-users. Once you publish your OS model, you only get feedback from technical users who find the HF community tab or manage to email you directly. I wanted an easy way to tell the model provider mid conversation that their model sucks & why.<p>I've been working on ModelSignature, a system that embeds a feedback URL (a “Model Signature”), directly into model weights using LoRA fine-tuning. Users can ask the chatbot "where can I report issues?" and the model responds with its ModelSignature page for bug reports and feedback. Providers get a detailed feedback/reports overview. Takes about 30 minutes on a T4 GPU. Since it's embedded in the weights, it persists wherever the model gets deployed.

value: Show HN: ModelSignature – Get end-user feedback for your OS AI models

author: FinnLennard


value: Show HN: Prompt Optimizer – Free AI prompt optimization tool


value:
I built Toffu after getting frustrated juggling 20+ marketing tools.
Instead of logging into Google Ads, opening GA4, checking Meta dashboards, and writing reports, you just chat:
"What's my ROAS this week?"
"Pause underperforming ads"
"Create a competitor analysis"
"Increase budget on winning campaigns"
The AI executes everything – not just recommendations.
Connects to: Google Ads, GA4, Meta Ads, LinkedIn, Reddit, Search Console, Webflow, HubSpot, and more.
SOC2 certified for enterprise use.
Free tier available. Happy to answer questions or hear feedback.

value: Show HN: Toffu – AI marketing agent that executes campaigns through chat


value: ericcurtin

value:
Hey Hacker News,
We're the maintainers of docker/model-runner and wanted to share some major updates we're excited about.
Link: https://github.com/docker/model-runner
We are revitalizing the community:
https://www.docker.com/blog/revitalizing-model-runner-commun...
At its core, model-runner is a simple, backend-agnostic tool for downloading and running local large language models. Think of it as a consistent interface to interact with different model backends. One of our main backends is llama.cpp, and we make it a point to contribute any improvements we make back upstream to their project. It also allows people to transport models via OCI registries like Docker Hub. Docker Hub hosts our curated local AI model collection, packaged as OCI Artifacts and ready to run. You can easily download, share, and upload models on Docker Hub, making it a central hub for both containerized applications and the next wave of generative AI.
We've been working hard on a few things recently:
- Vulkan and AMD Support: We've just merged support for Vulkan, which opens up local inference to a much wider range of GPUs, especially from AMD.
- Contributor Experience: We refactored the project into a monorepo. The main goal was to make the architecture clearer and dramatically lower the barrier for new contributors to get involved and understand the codebase.
- It's Fully Open Source: We know that a project from Docker might raise questions about its openness. To be clear, this is a 100% open-source, Apache 2.0 licensed project. We want to build a community around it and welcome all contributions, from documentation fixes to new model backends.
- DGX Spark day-0 support, we've got it!
Our goal is to grow the community. We'll be here all day to answer any questions you have. We'd love for you to check it out, give us a star if you like it, and let us know what you think.
Thanks!

value: Show HN: Docker/Model-Runner – Join Us in Revitalizing the DMR Community

author: ericcurtin


value: Make time make sense. Create and share beautiful interactive timelines from plain text. Also available as an Obsidian plugin.<p>Developers can render Chronos timelines in their apps with chronos-timeline-md library on NPM

value: Show HN: Interactive timelines from Markdown – Chronos Timeline


value:
Hey HN,
We built MailAI - personal AI agents that run 24/7 in secure sandboxes to automate email workflows. MailAI is CASA-verified for enterprise security.
The Problem:
Every "AI email tool" just gives suggestions. We wanted agents that ACTUALLY DO THE WORK.
Technical Innovation:
- Agents run in isolated, secure sandboxes
- MailAI is CASA-verified for enterprise security
- Complete isolation (your data never leaks)
- 24/7 execution (not just suggestions)
What It Does:
- Auto-responds to customers using your knowledge base
- Tracks invoices and sends payment reminders
- Coordinates meetings (checks your calendar)
- Handles custom workflows in plain English
Real Example:
"Every morning at 9am, summarize all unread emails marked important"
"Track all invoices and remind clients 3 days before due date"
"Auto-respond to customer support emails using our FAQ docs"
Why Sandboxes Matter:
Unlike other tools that run on shared infrastructure, our sandboxes provide complete isolation. Your agent can only access what you explicitly grant - nothing more. This prevents data leaks, unauthorized access, and cross-contamination between users.
Try It:
7-day free trial: https://mailai.live
We'd Love Feedback On:
1. Security concerns (we're paranoid about this)
2. Use cases we're missing
3. Technical implementation questions
Built by two founders and one founding member who were drowning in emails. Happy to answer any questions!

value: Show HN: MailAI – Personal AI agents in secure sandboxes for email automation


value: RichHickson

value:
Hi HN,
I built a small macOS utility called HostFileApp that lets you manage your /etc/hosts file with a simple visual interface — no Terminal required.
I’ve always found editing the hosts file manually a bit risky and inconvenient (especially when switching between dev and production environments), so I wanted something that felt native to macOS and handled the details safely.
What it does:
 • Add, edit, or disable host entries visually
 • Automatically back up before every save
 • Validate hostnames and IPs
 • Flush the DNS cache instantly
 • Optional lightweight local DNS server with wildcard domain support (*.example.com)
It’s built with Swift and SwiftUI, signed and notarised by Apple, and runs natively on Apple Silicon.
There’s a small licensing component for updates and continued development, but you can try everything freely for a week — no email required.
I’d really appreciate feedback from other Mac devs or sysadmins:
 • Is there anything missing that would make this more useful?
 • How do you handle local domain mapping in your workflow today?
You can download and run it here: https://hostfileapp.com
Thanks,
Rich

value: Show HN: HostFileApp – Edit your Mac's hosts file without using the Terminal

author: RichHickson


value: sanderbell

value:
How it works:
Copy a YouTube link → open app → it auto-detects from clipboard, pulls metadata + transcript, and generates a structured summary (key points + narrative) in seconds. No inputs, no pasting, no prompting. Supports 60+ languages for summaries, the video's language doesn't matter.
Why I built:
I had an endless queue of educational videos but no time to sit through rambling or clickbait. ChatGPT flow = copy → open → paste → prompt → pray it formats correctly. Existing summarizers felt feature-bloated or unreliable. I wanted something super minimalist: “clipboard → value” on repeat.
Decisions:
Stack — React Native 0.81 (New Arch) + TypeScript
Clipboard trick
— Monitors clipboard on app start/resume — no manual paste
Caching
— Stores transcripts + summaries in AsyncStorage with metadata
— fast image library prevents repetitive refetching
APIs
— YouTube metadata
— Third-party transcript provider (exploring Whisper)
— OpenAI for summarization
Output
— Structured prompts → consistent format across 60+ languages
— Easter egg: philosophical analysis for songs/poems
Time-saved calculation
— Uses actual video length (30% of cases)
— Fallback = estimated from average speech speed
Main headache:
Grandfathering legacy users without breaking App Review was harder than I expected. The first version was paid upfront ($14.99 or leave). Got some sales in the first two weeks, then traffic died. After some internal fighting, I switched to free-to-try with IAP. By then I already had thousands of users I’d promised free access forever, plus a dozen who actually paid. I wanted to keep my word and never show them a paywall.
RevenueCat’s originalAppVersion looked perfect… until I actually used it.. Turns out it’s not the marketing version (1.0, 2.3), but the build number (the variable name originalAppVersion is so misleading…). And Apple Review/TestFlight always report it as 1.0, so reviewers looked like legacy users and never saw the paywall (5 rejections). Everything worked for me, totally broken for them.
My mistake: I auto-entitled anyone with 1.0. First hacky fix: show a review-only paywall. Proper fix: if originalAppVersion === "1.0" (I never had such a build number anyways), treat as non-legacy. Days of digging and testing across devices/envs… finally approved.
Current state:
3800+ users and 12 sales within 2 weeks post-launch, 4.9-star rating globally. Now multi-tier subscription after 3 free summaries due to ongoing costs and long-term value.
Limitations/Challenges:
— iOS only for now. Android clipboard monitoring is restricted—would need a different UX.
— Some countries need VPN due to API restrictions; I notify users on app start.
— Dependency on third-party transcript API (evaluating OpenAI-based solution).
— YouTube's testing AI conversational tools, but it's very truncated, sandboxed only for some users and unlikely to roll out widely as it cuts ad their revenue from watching.
Happy to answer questions about implementation or share code snippets if helpful.

value: Show HN: I built a 3-tap YouTube summarizer for iOS

author: sanderbell


value: uchibeke

value:
Hey HN,
I pitched an investor for 30 minutes before realizing they'd already passed on a similar company in their portfolio.
That moment broke me. I'd wasted both our time because I didn't do basic research.
So I built Briefing AI: Paste any calendar invite and Get an Intelligence-style dossier on attendees in 30 seconds.
THE WORKFLOW:
You have a meeting in 10 minutes. You know nothing about the attendees.
Before:

  • Open LinkedIn, search "Sarah Chen Sequoia"
  • Skim profile, open 5 tabs
  • Google her recent activity
  • Try to remember talking points
  • Show up flustered
  • Total time: 15-20 minutes (if you even do it)

After:

  • Paste calendar invite into Briefing AI
  • Get: Executive summary, attendee backgrounds, company context, talking points, red flags
  • Walk in prepared
  • Total time: 30 seconds

THE TECH:

  • Next.js 15 + Cloudflare Pages (serverless)
  • Brave Search API (real company/attendee data, not just AI hallucinations)
  • GPT-4 (parsing + generation)
  • Device fingerprinting (1 free briefing, then $49 LTD or $19/month)

Launched Friday. Made 2 sales. Learning fast.
"BUT CAN'T I JUST USE CHATGPT?"
Yes. But:

  • ChatGPT = 8-10 prompts, 10 minutes ("extract attendees" → "who is Sarah?" → "what should I ask?")
  • Briefing AI = 1 paste, 30 seconds
  • ChatGPT = conversation disappears
  • Briefing AI = saved dashboard, searchable history

I'm not competing with ChatGPT. I'm making one specific workflow 10x faster.
WHAT I LEARNED (2 sales in 3 days):
The problem is real (everyone wings meetings), but I have zero distribution. 80 website visits, 2.5% conversion. Product works. Distribution doesn't.
So I'm asking HN:

  • Is this genuinely useful, or am I solving a fake problem?
  • Would you pay $49 lifetime for this?
  • What's the #1 feature I'm missing?

Try it free (no card required): getbriefing.io
I'm here all day to answer questions and iterate based on your feedback.
PS: If you've ever Googled someone 5 minutes before a Zoom call, this is for you.

value: Show HN: Pitched a VC for 30min before realizing they invested in a competitor

author: uchibeke


value: gbxk

value:
I've built this to make it easy to host your own infra for lightweight VMs at large scale.
Intended for exec of AI-generated code, for CICD runners, or for off-chain AI DApps. Mainly to avoid Docker-in-Docker dangers and mess.
Super easy to use with CLI / Python SDK, friendly to AI engs who usually don't like to mess with VM orchestration and networking too much.
Defense-in-depth philosophy.
Would love to get feedback (and contributors: clear & exciting roadmap!), thx

value: Show HN: Katakate – Dozens of VMs per node for safe code exec

author: gbxk


value: kapkapkap

value:
14 years ago, I launched my original version of TicketData via a Show HN. While the public site didn't get traction, the data proved valuable to those in the ticketing industry, and it became a B2B data product that's kept me busy ever since. I'm now relaunching the front-end site as a totally free and public tool for anyone to make smarter decisions when buying tickets for live events.
The re-launched site shows live resale price charts (using data from sites like StubHub, Vivid Seats, SeatGeek, etc) that update as often as every few minutes. You can see price history for the cheapest tickets ("Get In Price"), or for pre-defined zones (like Floor seats), or you can set up your own custom zone across any sections or rows (for example "Floor Center, Rows 1-10"). You can also set alerts for when prices go above or below whatever threshold you set.
Many of the larger events also include a forecast of where prices will go next. Those are based on years of historical data combined with the live data and other inputs (like sales data and a whole bunch of other variables…opponent, day of week, venue capacity, etc) passed through a model built in XGBoost. I'm slowly rolling out the forecast feature to more events as the models get refined and I'm confident in the accuracy for different event types/genres.
In addition to all the data for upcoming events, there are currently about 2.5 years of historical data live on the site. If there is sustained interest, I'll work on getting data all the way back to 2011 loaded in.
Here are a few examples:
[Upcoming Event] Paul McCartney next week:
https://www.ticketdata.com/events/12435572
[Past Event] Kansas City Chiefs vs. Las Vegas Raiders (Monday Night)
https://www.ticketdata.com/events/1174976
All 8 of Oasis's North American concerts this summer:
https://www.ticketdata.com/events/compare?ids=1006457%2C1006...
Or to see your cheapest local shows happening this weekend, click the "Local" + "This Weekend" filters on the homepage: https://www.ticketdata.com/
Feedback appreciated!

value: Show HN: I built TicketData – Ticket price trends and data for Sports & Concerts

author: kapkapkap


value: asenzz

value:
Tempus is a project aimed at high accuracy modeling of time series data or regression problems. It implements an improved kernel regression algorithm based on the support vector machine theory by professors Vapnik, Chervonenkis and Lerner but with several improvements such are nested kernels, multilayered weights, massive parallelization and systemic parameter tuning.
Tempus provides several signal decomposition methods and automated feature engineering. This new implementation of SVM allows for using of any statistical model, even itself, as a kernel function. This is done by calculating the ideal kernel matrix which is used as a reference for measuring the kernel function fitness. So far LightGBM, Torch, Path, RBF and Global alignment kernels have been implemented.
Tempus achieves significantly higher accuracy than other competing models even on the most complex data.

value: Show HN: Tempus is a high accuracy time-series analysis project

author: asenzz


value: aaronSong

value:
Clink lets you use the coding agents you already pay for (Claude Code, Codex CLI, Gemini CLI, Z.ai GLM) to build → live-preview → ship apps in an isolated container.
No token purchases, no extra cost for coding. Just link your existing Claude/OpenAI/Gemini account and start building and deploying instantly.
Why we built this:
Claude Code is our go-to for coding, but it lacked preview + deploy capabilities. We didn't want to pay Lovable again just for that.
Different agents excel at different tasks - Claude Code for versatility, Codex for complex work, GLM for speed. We needed one platform to leverage them all.
CLI agents offer more freedom than traditional web builders. We wanted to unlock their full potential with proper dev tooling.
What it does:
- Prompt → Build → Live → Deploy - The fastest path from idea to live website. Deploy for free.
- BYO Subscription - Use your existing plans efficiently (Claude Code $20 = 10x Lovable $25 usage, GLM $3 = 3x Claude Code $20)
DEV Mode (Beta):
- Multi-stack support - Build with Node, Python, Go, Rust and deploy containers to public URLs instantly
- Repo imports - Upgrade and deploy your existing projects across any stack
Links:
- Clink: https://clink.new
- OSS origin (Claudable, ~2.8k): https://github.com/opactorai/Claudable
We'd love any feedback, bug reports, or stack requests - we iterate fast and read every comment.

value: Show HN: Clink – Bring your own CLI Agents, Ship instantly

author: aaronSong


value: ryandvm

value:
My very small team has built an Android live wallpaper that displays the current NEXRAD weather radar data as your Android phone’s live wallpaper.
The app automatically selects the nearest radar site using coarse location permissions, or you can manually choose a location. Everything is size optimized and only updates when the wallpaper is being viewed to minimize battery footprint.
Interesting technical bits:

  - Using the US National Weather Service public radar feed (via public S3 bucket)
  - Custom radar volume data decoder written in Go and running as AWS Lambdas (triggered by S3 bucket events)
  - Custom rendering API
  - Kotlin Android app is <10 MB (no cross-platform bloat)

Available on Google Play:
https://play.google.com/store/apps/details?id=app.radarlove....
Happy to answer questions about the radar data processing pipeline, infrastructure, or the live wallpaper implementation. Also open to interesting opportunities for collaboration...

value: Show HN: Live weather radar wallpaper for Android

author: ryandvm


value: jspizziri

value:
I spent the last 1yr+ building an audiobook streaming service that focuses on timeless classic works in the public domain.
One thing I'm especially proud of is the restoration I did on the "War of the Worlds" 1938 Radio broadcast. I'm really happy with how it turned out. I've made it temporarily free (no login required or anything untoward) to listen to [1] in case anyone is curious. You should compare it with the original [2] and let me know what you think. I find the actual broadcast super engaging and enjoyable.
I've done everything from building the app to the audio engineering. A lot of learning involved as my background is on the software side, not marketing, audio engineering, etc.
A lot of the initial catalog is stuff that I've sourced from Librivox [3] (legends), but I've done a lot of curation, clean up, editing, mastering, and packaging to make it more enjoyable. There's also some original audiobooks too, and more should be landing each month (they're expensive and time consuming to produce with real humans and AI isn't quite there yet IMHO).
It's at a point now where I think it's ready enough to release it to the public.
I'd love any constructive feedback (audio quality, UX, concept, etc) that anyone would be willing to provide. Finally, some of the things that are unique:
1) Subscribers vote on what content we produce next (new content monthly is the plan).
2) 3 referrals = a free subscription
3) A "lifetime" option (possibly naive, but it's what I want as a consumer)
Anyways, if you even read to this point I appreciate it!
[1] https://app.soundreads.io/discover/item/war-of-the-worlds
[2] https://archive.org/details/WarOfTheWorlds1938RadioBroadcast...
[3] https://librivox.org/

value: Show HN: An Audible alternative for classic audiobooks

author: jspizziri


value: tompccs

value:
Hi HN,
We’re definitely not the first to realise there’s something seriously wrong with how hiring and job-seeking works today. Zero-cost communication and LLMs have created so much noise that good candidates can’t get heard, and it becomes all too tempting to game the system with keywords and prompt-hacking.
In fact we discovered that 70% of early stage AI startups don't post their jobs on LinkedIn. Instead, many founders hire exclusively within their network, which works at the start but doesn’t scale.
We thought a lot about this problem, and pivoted through a few ideas including an AI voice agent recruiter. We even spent some time trying to be conventional tech recruiters to better understand the problem space.
And in the end we built...a job board.
But we think there are a few things that make ours different:
- We decided to not put barriers between the user and the data. You can search, filter or browse however you like from the minute you sign up. Zero onboarding
- We wanted to nail one niche, so we focused on surfacing opportunities at early-stage AI companies (over 30,000 jobs at 24,000 companies)
- You can navigate it using keyboard shortcuts!
- We built a voice agent, Nell, who conducts a technical recruiter call with you through your browser and immediately finds matches, the way a well-connected friend who knows you well would
- When you tell us you’re interested in a role, we make a best effort to connect you to founders directly, along with your profile, so no cover letters, no pointless forms
- We enriched jobs data with investor-grade intelligence - you can look at same data that VCs use to decide whether a startup is worth joining or not
Give it a try and let us know what you think: https://teeming.ai

value: Show HN: We tried to build a job board that isn't awful

author: tompccs


value: amthewiz

value: Show HN: Realizing Karpathy's dream of Natural Language Programming

author: amthewiz


value: tranhuucanh

value:
I'd like to share FastQR (https://github.com/tranhuucanh/fastqr), a high-performance QR code generator written in C++. This is my first open-source project, and I'm excited (and a bit nervous!) to share it with you all.
What it is:
- A fast CLI tool and library for generating QR codes
- Written in C++ with bindings for Ruby, PHP, and Node.js
- Full UTF-8 support (works great with Vietnamese, Japanese, and other languages)
- Supports custom colors, logo embedding, and precise size control
- Pre-built binaries included – no need to install dependencies separately
Why I built this:
- I needed a QR code generator that was fast, supported UTF-8 properly (especially for Vietnamese text), and could be easily integrated into different languages. Most existing solutions were either slow or had poor Unicode support.
Performance:
- Generating 1000 QR codes (500x500px): ~0.37 seconds
Tech stack:
- C++ core using libqrencode and libpng
- Language bindings for Ruby, PHP, and Node.js
- Precompiled binaries for easy installation
This is my very first open-source project, so I'm sure there are things that could be improved or bugs I haven't caught yet. I'd really appreciate it if you could try it out and share your feedback. If you find any issues or have suggestions, please open an issue on GitHub – I'll do my best to fix them quickly.
Any feedback, criticism, or suggestions would be greatly appreciated. Thanks for taking the time to check it out!
GitHub: https://github.com/tranhuucanh/fastqr

value: Show HN: FastQR – A Fast QRCode Generator Supporting Batch Processing

author: tranhuucanh


value: edmundsparrow

value:
When you first open Gnoke Station, you're greeted by... well, almost nothing.
A clean desktop, a terminal, an app store, desktop settings, and silence. We understand why our previous post led to comments about the minimalism.
Our mistake was not making the core architectural intent clear. The empty screen isn't a lack of features—it's the feature.
The Philosophy of an Empty Desktop
Gnoke Station is a browser-based Web Operating System—a lightweight runtime environment, not a desktop clone.
We built it for those who need a modular, minimal canvas they can fully control, specifically in industrial, IoT, and dashboard contexts.
The emptiness is a design choice to minimize overhead and maximize extensibility.
Instead of wrestling with a bundled, heavy general-purpose OS, the user (or manufacturer) starts with a near-zero state and only loads the components they need.
Why Gnoke Station is a WebOS for Makers
The core value lies in the architecture, not the initial icons:
* Modular for Integrators: The entire desktop is designed as a minimal shell that manages external web applications. Manufacturers can swap out the login manager, default apps, and even the taskbar with their own specialized components using a simple JSON manifest.
* Built for Thin Clients: It transforms any modern browser into a desktop environment. There are no downloads, no installations, and no virtual machine requirements. This is crucial for environments where resources are constrained.
* Offline-Ready: We leverage modern browser APIs (like Service Workers and IndexedDB) to ensure the environment remains resilient to network interruptions—a necessity for reliable field and industrial applications.
This project is an experiment in rethinking what an operating system should be in the browser age: a flexible framework that lets you build your own digital control panel.
Proof of Footprint
As a testament to its resource lightness, Gnoke Station was built entirely on an Infinix phone by myself (EdmundSparrow). Innovation doesn't have to depend on expensive hardware—only imagination.
If you are an engineer or developer working on embedded UIs, industrial Human-Machine Interfaces (HMI), or specialized web dashboards, I'd love for you to explore this concept and check out the API for building your own apps.
Live Demo:
https://gnokestation.netlify.app
GitHub Repo:
https://GitHub.com/edmundsparrow/gnokestation
Pitch/Design Rationale:
https://gnokepitch.netlify.app
(Note: GnokePitch supports phone and tablet viewing, which is a big advantage over traditional C++ HMI solutions.)

value: Show HN: Gnoke Station – A WebOS for Industrial and IoT Dashboards

author: edmundsparrow


value: solumos

value: Show HN: PDF Link – Text deep links for PDFs

author: solumos


value: ramoz

value:
fun internal project, similar to the new --teleport feature, built for collaboration.
https://www.iroh.computer/ makes it happen.
P2P - Rated E, For Everyone.

value: Show HN: Agentbeam – P2P sharing for Claude Code sessions

author: ramoz


value: huedaya

value:
I made website that inspired by The Weeping Angles from Doctor Who
Basically, it will ask camera permission, and detect wether you blinking or not, if yes, it will make the Angles closer and closer.
https://x.com/huedaya/status/1980677893765402862
Inspired by: "Blink" (Season 3, Episode 10) and "The Time of Angels" (Series 5, Episode 4)

value: Show HN: Don't Blink

author: huedaya

title: Show HN: Don't Blink


value: zwilderrr

value:
Sharing my first app, Striver. Made with React Native/Expo, deployed with EAS.
Generally geared towards folks who want to be intentional about what they're thinking and where they're thinking about it.
Helps you seperate your attitudes/beliefs/approaches to, for example, going to the gym, and family time at home.
It's decidedly unengaging, un-doom-scrolling, un-super-fun. Maybe to a fault?
Would love to get the community's thoughts.

value: Show HN: Striver – organize and internalize what's important to you

author: zwilderrr


value: hidelooktropic

value: Show HN: A to Do List That Helps You Forget

author: hidelooktropic


value: mshubham

value:
Hey HN,
I built an offline-first voice AI that runs entirely on Apple Silicon using MLX + FastAPI.
It achieves <1s end-to-end latency for speech-to-speech conversations, with a minimal UI.
Repo: https://github.com/shubhdotai/offline-voice-ai
Would love feedback on performance, model choices, and other ideas...

value: Show HN: Offline-first voice AI (<1 s latency, MLX, Apple Silicon)

author: mshubham


value: peterdunson

value:
Hey HN!
I built arXiv News (https://arxiv-news.com) – a discussion space for research papers.
The problem: I browse arXiv constantly for new papers, but there's nowhere good to discuss them. Twitter is chaotic, Reddit is fragmented, and arXiv itself has no comments.
So I cloned HN's design (using https://github.com/clintonwoo/hackernews-react-graphql) and applied it to arXiv. Upvote papers, comment, sort by hot/new/discussed, filter by category, post ideas/papers you've found. A daily scraper pulls all new papers automatically.
I'd love to hear peoples thoughts. Trying to iterate/improve upon what I currently have so I need feedback.
https://github.com/peterdunson/arxiv-news
Thanks!

value: Show HN: I'm building an open source discussion forum for latest ArXiv papers

author: peterdunson


value:
Hey everyone,
I recently built OpenJobHub, a free and open source job board for engineers.
My goal is simple: in these tough times, I hope more people can find good jobs,
and that job information can be more open and transparent.
Feel free to share it with any recruiters, HRs, or friends who are hiring.
Let's build a healthier job ecosystem together.
GitHub: https://github.com/junminhong/jobs
Website: https://jobs.wowkit.net

value: Show HN: OpenJobHub – A Free and Open Job Board


value: Show HN: Voice AI App - skipping ads, predictive commands


value: MZUHB

value:
I got tired of spending time in design tools just to make screenshots look presentable for social media. So I built this simple and minimalistic web app where you can drag and drop a screenshot, pick a gradient background, adjust padding and shadows, and download the result.
It's completely free, works in the browser, and doesn't require any sign-up. The images are processed client-side, so nothing gets uploaded to a server.
Would love to hear feedback on features you'd find useful!

value: Show HN: Give your screenshots a sick background

author: MZUHB


value: johnzakkam

value:
Hey HN,
I built Don’t Ask Me
 — an AI chat app that does the opposite of what most AIs do.
Instead of giving you instant answers, it helps you reason things out, reflect, and build your own conclusions.
The idea came from noticing how easy it’s become to outsource thinking to LLMs. I wanted to experiment with a tool that doesn’t take over your thinking — but guides it.
How it works:
You ask a question or describe a problem.
Instead of replying with a final answer, the AI asks you questions back.
It helps you unpack assumptions, find contradictions, and explore perspectives.
The goal isn’t to “get an answer” — it’s to think better.
Why:
I wanted something between journaling, Socratic dialogue, and ChatGPT — something that builds resilience of thought instead of dependency.
Note:
This is very much an MVP — just the first working version of the concept.
There’s still rough edges, limited depth, and no fancy onboarding yet.
I’m more interested in validating whether this type of AI interaction feels valuable at all before polishing it.
I’d genuinely like your thoughts on:
Whether the “refuse to answer” approach feels helpful or just frustrating
The UX of being challenged instead of spoon-fed
Any ideas for making the reasoning scaffolding smarter or less repetitive

value: Show HN: Don't Ask Me – An AI that refuses to answer and makes you think

author: johnzakkam


value: imadbkr

value: Show HN: I scraped 10k+ remote tech jobs into one feed

author: imadbkr


value: greatgenby

value:
Hi HN,
I've spent the last 2 months building Playbook AI. It's my attempt to solve a problem I see in many teams: everyone is excited about AI, but its use is often seen as ineffective. As a result, many teams either don't use it or use it poorly.
My core belief is that the main issue isn't the AI itself, but how we manage context. The quality of AI output is 90% dependent on the quality of the context you provide.
So, I created this interactive playbook. I've built out the content for the first 4 stages of the product lifecycle (from Discovery to Development), complete with step-by-step guides, 35+ battle-tested prompts, and examples of the final artifacts. The project is completely free to use right now.
My next big step is to build an AI artifact generation feature (e.g., creating a draft PRD or system design document based on insights from the Discovery phase).
I'm also considering open-sourcing all the content—the prompts and examples—so the community can contribute and add their own activities and best practices.
I'd love to get your feedback on the core foundation of the project:
Does the proposed methodology seem sound and practical?
Would this structure be useful for your team?
What's the biggest pain point in your current AI workflow that this playbook could solve?
Would a "Projects" feature, where you could store generated artifacts and project context, be interesting to you?
Looking forward to all your thoughts and critique!

value: Show HN: Playbook AI – knowledge base for using AI in product development

author: greatgenby


value:
Hi HN,
For years I’ve missed the feeling of an always-on chatroom without the silos and social overhead of Discord. So I built Together: a single-room, no-signup group chat that you join with one click. No channels, no rules (yet), no onboarding flow. Everyone lands in the same place and can start talking in under a second.
Why I made it
- Forums and blog comments are great but slow; Discord/Slack feel heavy for casual drop-ins if you aren’t already a member of a community.
- I wanted the simplest possible space where ~100 people could idle, share shower thoughts, and keep the conversation rolling.
- I’m cautiously (naively?) optimistic that a friction-free room can stay civil and interesting without much structure.
Bonus features
- Universal comments: Share any (mostly any) web page link and view it inside the site, with a live comment section.
- Inline comments: Add your comment within the page, and others can join the discussion.
- Share your commentary After you’ve added all your clever snark to some blog post, share with your friends so they can all see how smart you are!
- No sign-up needed: Just start reading, chatting, and commenting. Pick a username if you want.
Looking for feedback on:
1. What would make you leave the tab open all day?
2. Is the UX confusing in any way?
I’ll be in the chat (and here in the comments) all day fixing bugs and answering questions.

value: Show HN: Together, a no-signup chat and universal comment/discussion tool (beta)


value: vmcallsm

value:
Hi HN,
My motivation for this came from frustration with existing workout trackers. Most felt clunky, hid core features like performance graphs behind a paywall, or forced a native app download. A few people close to me who take their training seriously shared the same sentiment, so I decided to build my own.
I'm working on mTOR, a free, science-based workout tracker I built to automate progressive overload. It's a local-first PWA that works completely offline, syncs encrypted between your devices using passwordless passkeys, and allows for plan sharing via a simple link.
The core idea is to make progression easier to track and follow. After a workout, it analyzes your performance (weight, reps, and RIR), highlights new personal records (PRs), and generates specific targets for your next session. It also reviews your entire program to provide scientific analysis on weekly volume, frequency, and recovery for each muscle group. This gets displayed visually on an anatomy model to help you learn which muscles are involved, and you can track your gains over time with historical performance charts for each exercise.
During a workout, you get a total session timer, an automatic rest timer, and can see your performance from the last session for a clear target to beat. It automatically advances to the next incomplete exercise, and when you need to swap an exercise, it provides context-aware alternatives targeting the same muscles.
It's also deeply customizable:
*   The UI has a dark theme, supports multiple languages (English, Spanish, German), lets you adjust the UI scale, and toggle the visibility of detailed muscle names, exercise types, historical performance badges, and a full history card.
*   You can set global defaults for weight units (kg/lbs), rest times, and plan targets, or enable/disable metrics like Reps in Reserve (RIR) and estimated 1-Rep Max. The exercise library can be filtered by your available equipment, you can create your own custom exercises with global notes, and there's a built-in weight plate calculator.
*   The progression system lets you define default rep ranges and RIR targets, or create specific overrides for different lifts (e.g., a 3-5 rep range for strength, 10-15 for accessories).
*   Editing is flexible: you can drag-and-drop to reorder days, exercises, and sets, duplicate workout days, track unilateral exercises (left/right side), and enter data with a quick wheel picker.
I'll be here all day to answer questions. I'm also thinking about making the project open-source down the line and would be curious to hear any thoughts on that. Thanks for checking it out!

value: Show HN: MTOR – A free, local-first PWA to automate workout progression

author: vmcallsm


value: domid

value:
I built RepublishAI for three reasons.
First, AI content quality. With the rise of AI, we needed a reliable content generation solution that creates well-researched content. I'm tired of businesses using AI to generate bad content: articles produced without context or research. RepublishAI AI Agents analyze top-ranking content, identify gaps competitors miss, and write comprehensive articles that actually compete in search results.
Second, true automation with optional oversight. Real autopilot means setting it once and never touching it again. We're moving towards full automation across the entire content pipeline: planning, keyword research, content gap analysis, outline creation, content writing, image generation, featured image creation, SEO meta tags, and publishing. But you're always in control. Each article can be quickly reviewed, edited, and updated in our app before or after publishing. Full automation when you want it, human refinement when you need it.
Third, a faster content editor for WordPress. The existing WordPress CMS is painfully slow for editing and updating marketing blogs. We needed an editor that's fast and allows us to manage multiple blogs quickly. You shouldn't have to click around just to navigate to a different post. Our editor works with one click. Everything can be done with one click, including working with our smart AI agents that can refresh underperforming content in just a few minutes. All of your WordPress blogs can be managed from our editor.

value: Show HN: WordPress SEO AI Autoblogging – Republish AI

author: domid


value:
Hey folks
After years of manually tracking Netflix, Spotify, and random SaaS renewals in Excel sheets, I finally decided to build something that actually makes sense — Submind.
We’ve spent the past few months designing and polishing it with a focus on ease of use and powerful features that make managing recurring payments simple (and kinda satisfying).
It’s completely free for now. More advanced features are planned and early users will be grandfathered — meaning you’ll keep full access even after we introduce paid plans later on.
What Submind does
Supports hundreds of services — Netflix, Spotify, Adobe, Disney+, Apple iCloud, and more
Calendar View — see all your upcoming renewals at a glance
Smart Reminders — get notified before payments
Detailed Analytics — total cost, categories, and monthly averages
Widgets & Filters — added recently based on user feedback
Dark Mode + Liquid Glass design for that clean iOS 26 look
We’re improving it every week and would love your feedback!
What features would you love to see next?
Family/shared subscriptions
Currency conversion
Auto import from bank or email
AI insights like “you never use this — cancel?”
Something else entirely?
Download it here: https://apps.apple.com/us/app/subscription-tracker-submind/i...
No sign-up, no ads — just clean subscription tracking.
Hope you find it useful, and I’d love to hear what you think!

value: Show HN: Submind – Free Subscription Tracker


value: modinfo

value: Show HN: I built an LLM that never forgets – persistent user memory with RAG

author: modinfo


value: exprtk

value: ExprTk compiled to WebAssembly lets you explore and evaluate math expressions instantly in your browser. Everything runs client-side at near-native speed.

value: Show HN: ExprTk REPL – Explore math expressions in the browser with WebAssembly

author: exprtk