Show HN за 6 сентября 2025 г.

The idea is actually quite simple. As a Japanese learner and a coder, I've always wanted there to be an open-source, 100% free for learning Japanese, similar to Monkeytype in the typing community.

Unfortunately, pretty much all language learning apps are closed-sourced and paid these days, and the ones that are free have unfortunately been abandoned.

But of course, just creating yet another language learning app was not enough - there has to be a unique selling point. And then I thought to myself: why not make it crazy and do what no other language learning app ever did by adding a gazillion different color themes and fonts, to really hit it home and honor the app's original inspiration, Monkeytype?

And so I did. Now, I'm looking to find contributors and testers for the early stages of the app.

Why? Because weebs and otakus deserve to have a 100% free, beautiful, quality language learning app too！

For anyone interested, you can check it out at --> https://kanadojo.com and let me know what you think ^ ^

I kept re-Googling the same flags, so I built a tiny, fast directory of copy-ready CLI commands. It’s static (vanilla JS), instant search, keyboard nav (↑/↓ + Enter), favorites (localStorage), and linkable queries.

Examples: • grep errors → https://www.greppers.com/?q=grep%20error%20logs • list open ports (macOS) → https://www.greppers.com/?q=list%20open%20ports • show git branch graph → https://www.greppers.com/?q=git%20graph • tail with colors → https://www.greppers.com/?q=tail%20colors

Suggest a missing command: https://www.greppers.com/submit.html

I’m looking for gaps and better real-world examples. Feedback welcome.

It is simply a reason to be kind to one another, for kindness may be the only medicine for the world’s pain.

Hi HN,

I thought this would be a good place to share a little puzzle I've been working on. Inception is a Rust library that helps you share behaviors in Rust using structural induction. Practically, this means that instead of having a derive macro for each behavior, a single derive can be used to enable any number of behaviors. It doesn't do this using runtime reflection, but rather type-level programming - so there is monomorphization across the substructures, and (at least in theory) no greater overhead than with macro expansion.

While there are a lot of things missing still and the current implementation is very suboptimal, I'd say it proves the general concept for common structures. Examples of Clone/Eq/Hash/etc replicas implemented in this way are provided.

The code is not idiomatic, which is my biggest reservation about continuing this work. It was fun to prove, but is not so fun to _improve_, as it feels a bit like swimming upstream. In any case I hope some of you find it interesting!

Recently, I was part of a dog rescue transport from Denver to Frisco, CO, and it opened my eyes to a major problem: coordinating volunteers shouldn't be this complicated. Between fragmented communication (Facebook, phone calls, emails, texts...), missing handoff details, and manual route planning, I wanted to work on a better solution.

Meet puptransfur.org - purpose-built to make rescue transports seamless and paw-fect. Easily plan routes, coordinate handoffs, manage timezones automatically, and document the journey with photos. Use the demo option to create your own route, or look at an example route: puptransfur.org/route/4041

If you are part of a dog rescue and need to organize dog transports frequently, would you want to use this website? Let me know and I can guide you through the first steps and show how everything works.

Some features: - address completion when setting up the route - suggested handoff locations to easily break up the route into multiple segments - handles timezones by adjusting the times to local times - volunteer information available to other drivers (car model and color, license plate, if available) - integrated email communication when drivers sign up, and when drivers are confirmed

And the best feature I think is this one: this site can bring all volunteer drivers of all rescue organizations together in one place!

This website is free to use for administrators of dog rescues as well as for volunteer drivers. I'd love to get some feedback on this. Thanks for looking!

I built Claudio to solve a simple problem: typing is slow when you have complex thoughts to share with Claude. This Chrome extension adds a microphone button to Claude.ai that uses OpenAI Whisper for transcription.

  Key features:
  - One-click voice recording with intelligent progress tracking
  - Audio file upload support (perfect for mobile voice notes → desktop Claude workflow)
  - Speed control (1-2x compression) to reduce API costs
  - Private and secure - your OpenAI API key stays local
  - Real-time transcription stats and performance analytics

  Latest v1.2.1 fixes:
  - Improved audio duration detection using Web Audio API
  - Fixed NaN calculations in transcription time estimates
  - Better error handling for edge cases

  The extension integrates seamlessly into Claude's interface - just click
  the mic button, speak naturally, and your voice becomes text. Especially
  useful for content creators, researchers, and anyone who thinks faster
  than they type.

  Use cases I've found most valuable:
  - Recording ideas during walks/commutes, then uploading the audio files to
   Claude desktop
  - Dictating complex code explanations and documentation
  - Converting meeting recordings into structured notes
  - Hands-free email composition

  Installation takes under 2 minutes via Chrome's developer mode. The
  extension is free and open-source.

  Download: http://earthpilot.ai/claudio/

  What voice-to-text workflows have you found most useful in your daily
  work?

  ---
  Independent project, not affiliated with Anthropic or OpenAI. Uses your 
  own OpenAI API key.

If you'd like an invite to our weekly AI Playground as my VIP visit http://earthpilot.ai/play

I tracked protein powder prices in a spreadsheet for years and found that identical protein content can have wild price differences.

I built PricePerProtein to automate it. It pulls real-time Amazon data (Keepa API) and uses Gemini 2.5 Flash to extract nutrition facts from product images/descriptions. Calculates actual protein per dollar, not just package price.

Technical: FastAPI + Celery backend, Next.js frontend with virtual scrolling to handle 3000+ products. Deployed on a VPS (migrated from GCP - much simpler). The AI handles everything from blurry nutrition labels to understanding flavor categories.

No signup, no ads, no affiliate links. Updates hourly.

I used to work in VC and watched good teams lose months chasing the wrong investors. I’m building Evalyze to make the unglamorous parts faster and more precise.

After sign-up (email only, no card) you can:

- upload a deck or paste your site - get a ranked list of relevant VCs/angels with a short “why” for each

What’s different: instead of dumping a big list, we try to explain why an investor fits based on stage, sector, check size, and portfolio patterns. It’s far from perfect and we want blunt feedback before opening wider.

Limits to know:

- newer funds and emerging managers can be underrepresented - geo nuances are still rough - matching can over-weight buzzwords if the deck is vague

I’d love critique on the ranking logic, signals you’d add/remove, and any privacy concerns. If you don’t want to upload a deck, there’s a sample you can use to see the flow.

I’ll be here replying and shipping fixes as comments come in.

Hello HN,

I'm sharing a little open-source utility I wrote recently.

I'm a huge fan of Brendan Gregg's "BPF Performance Tools" book. However, every time I SSH into a fresh server, most of the diagnostic tools aren't installed there and installing them can be really annoying.

I decided to use Nix package manager and LLMs to make this process straightforward. My utility first downloads a "toolbox" of Linux utilities (built with Nix), runs Brendan Gregg's famous "60-second Linux analysis" playbook and then summarizes the results with an LLM. So "60-second Linux analysis" now becomes a single one-line command and actually takes less than 60 seconds! The utility can execute all commands in parallel and the LLM can analyze them faster than a human would.

I have a few ideas for the future, for example implementing more powerful playbooks - thanks to Nix I can easily bundle all tools I need and LLMs have no trouble analyzing outputs of tens of commands.

I'd love to get your feedback and hear any ideas you have. Thanks for checking it out.

You can launch the utility with this command:

$ curl -fsSL https://gradient.engineer/60-second-linux.sh | sh

Meet Seedream 4.0, a revolutionary AI that surpasses Nano Banana in versatility and precision. Seamlessly combining text-to-image, editing, and group generation capabilities, it delivers superior results through advanced natural language control, setting a new standard in AI image generation.

I wanted a project to learn the Dioxus framework. It needed to be relatively simple and fun. Here is a site that lets you rate horses.

The horse people I know have taken issue with this site because they say all horses are beautiful. What do you think?

Images are from an open source AI training dataset of horses, so there are some odd ones in there...

I built an iOS app called HabitCrush to help me (and hopefully others) quit bad habits (like procrastination, porn, junk food, or over-eating..)

It is like an inverse habit tracker. The idea is simple: name the bad habit, and every day you say no to the bad habit you get the satisfaction of “crushing” it in app. As a Bonus, each day you succeed, you get a unique gemstone as a small symbol of progress. The gemstone is computed on the day timestamp so it is unique and never comes back.

Would love feedback especially on the approach and whether the daily gemstone mechanic feels useful or gimmicky.

Built an interface for image → 3D with PBR materials. Exports GLB; typical runs take ~1–2 minutes depending on complexity. It’s powered by Tencent’s open-source Hunyuan3D 2.1 models (https://hunyuan-3d.org).

Hi HN, I am Max and I am building QuickDeploy! It lets you deploy web applications of all sorts to your VPS with one command! Here is a little showcase of the tool itself: https://youtu.be/Feauj4OaePg

Under the hood quickdeploy detects the language and framework you use, so e.g. Next.js and then creates a Docker image. After that it starts the container and waits until it is in a healthy state before using a reverse proxy to redirect traffic to the app. Added benefit is the use of your own domain with instant https!

I am super happy with the result and the ease of use. After it is configured once it just works with one command, that's so cool! Hopefully it will enable more developers to host their own apps and get them interested in that kind of stuf..

Would love your feedback on the tool!