value: Flamehaven

value:
Hi HN — I built FlashRecord, a tiny (≈2MB) Python-native CLI tool for screenshots and GIF recordings aimed at developers who want automation-friendly, scriptable screen capture without a GUI.
### What it is
- CLI-first and importable (import flashrecord) so you can plug it into scripts, tests, CI pipelines, or docs generation.
- Outputs GIFs (and screenshots) with a pure-Pillow/NumPy implementation of a CWAM-inspired compression pipeline (multi-scale saliency, temporal subsampling, adaptive scaling).
- Cross-platform (Windows/macOS/Linux), zero-config defaults, and production-ready with tests/docs.
---
### Why it might be interesting
- Tiny install and no heavyweight GUI/tooling to manage.
- Designed for automation: generate evidence GIFs in CI, attach demo GIFs to PRs, or create tutorial assets from scripts.
- Compression focuses on preserving visually important regions while reducing file size dramatically in typical UI demos.
---
Repo & license: https://github.com/Flamehaven/FlashRecord
— MIT licensed.
---
I’m happy to answer technical questions, performance numbers, cross-platform quirks, or walk through the compression pipeline. Feedback, issues, and PRs welcome.
What it is
CLI-first and importable (import flashrecord) so you can plug it into scripts, tests, CI pipelines, or docs generation.
Outputs GIFs (and screenshots) with a pure-Pillow/NumPy implementation of a CWAM-inspired compression pipeline (multi-scale saliency, temporal subsampling, adaptive scaling).
Cross-platform (Windows/macOS/Linux), zero-config defaults, and production-ready with tests/docs.
Why it might be interesting
Tiny install and no heavyweight GUI/tooling to manage.
Designed for automation: generate evidence GIFs in CI, attach demo GIFs to PRs, or create tutorial assets from scripts.
Compression focuses on preserving visually important regions while reducing file size dramatically in typical UI demos.
Quick try (from source)
git clone https://github.com/Flamehaven/FlashRecord
cd FlashRecord
pip install -e .
flashrecord @sc            # instant screenshot
flashrecord @sv 5 10       # 5s GIF at 10 FPS (interactive by default)
Repo & license: https://github.com/Flamehaven/FlashRecord
 — MIT licensed.
I’m happy to answer technical questions, performance numbers, cross-platform quirks, or walk through the compression pipeline. Feedback, issues, and PRs welcome.

value: Show HN: FlashRecord – 2MB Python-native CLI screen recorder

author: Flamehaven


value: dandeto

value:
The Dead Sea Scrolls is one of the greatest archaeological discoveries in recent history, and its relevance is bolstered since it is of interest to Judaism, Christianity, and Islam. I had heard of the discovery as a kid, but was surprised to realize how little I knew about it once I started reading books and watching videos by Hebrew Bible scholars on the topic.
I made deadseainsights.com to explore the discovery in an interactive and visually-engaging way. I was also very interested in the differences between the Dead Sea Scroll texts, which are dated to 250 BC - 150 AD, and the Masoretic text (specifically the Leningrad Codex), which is dated to around 1008 AD.
To do this, I could not use information from the books I read, since the text and translations are under copyright. I was able to find permissively-licensed transcriptions of the Dead Sea Scrolls and the Leningrad Codex, for which I am grateful. You can find more information about that on the homepage.
Since HN is probably interested in my tech-stack: I kept it simple and built a static website that uses Bootstrap and D3. It’s hosted on AWS S3 and distributed to 108 edge locations via AWS CloudFront. So far, hosting has been under the free-tier limits and has cost me nothing.
Thank you for any feedback you’d like to give.
-dandeto

value: Show HN: The Dead Sea Scrolls Visualized

author: dandeto


value:
i built Launchy with the help of an open source base as a small experiment in bringing back the feel and vibe of old-school web directories, but with a focus on new product launches.
the goal was to see if directories could feel more human and less like a modern simplistic vibe everyone seems to be going for these days.
you can browse launches, submit your own, or just enjoy the aesthetic.
i'm curious what you think, does the minimalist and brutalist throwback design still appeal to today's builders, or are the modern clean and simplistic approaches better?
(p.s. there's also an unscrambling game hidden in the footer)

value: Show HN: I made a brutalist closer-to-retro directory for new product launches


value: legitcoders

value:
Hey HN! I built a tool that tracks when AI search engines (Perplexity, ChatGPT, Claude, Google AI) cite your website in their responses.
*The problem:* AI search is exploding (Perplexity does 100M+ queries/month), but there's no way to know if these engines are citing your content. It's like SEO in 2005 before Google Analytics existed.
*What it does:*
- Automated daily checks across multiple AI platforms
- Tracks citation rate, position, and trends over time
- AI-powered recommendations for queries where you're NOT cited
- Shows which platforms cite you most
*Technical approach:*
- Puppeteer for web scraping (no expensive APIs)
- Firebase for real-time data
- Groq for AI recommendations
- Next.js + TypeScript frontend
- Vercel cron for automation
*Why I built it:* I run llmscentral.com (a repository of llms.txt files) and noticed traffic from Perplexity was growing 50% month-over-month. But I had no idea which queries were driving it. Built this to scratch my own itch.
*Free tier:* 3 tracked queries, weekly checks on Perplexity
*Paid tiers:* More queries, daily checks, all platforms, AI recommendations
Try it: https://llmscentral.com/citation-tracking
Would love feedback from the HN community! Happy to answer any technical questions.

value: Show HN: I built a tool to track when AI engines cite your website

author: legitcoders


value: Mylinux-os

value: Show HN: Mylinux: a minimalist disro by a 13 year old

author: Mylinux-os


value: TopSecretHacker

value:
I built CVE Daily to cut CVE triage time. It pulls from NVD and OSV, puts vendor advisories up front, and adds short guidance on what to patch or mitigate now. There’s also a Transitive Upgrade Assistant that uses deps.dev graphs to suggest the minimum safe host version when a vulnerable dependency is pulled in transitively.
Highlights:
NVD + OSV aggregation
Vendor advisories first
Concise, neutral “what to do now”
KEV badges and prioritization notes
Tags/filters (vendor, product, CWE)
EOL/EOS context for impacted products
Would love feedback from SecEng/SRE/IT admins: If this helps, share it with your team; if not, tell me why.

value: Show HN: CVE Daily – fast, vendor-neutral CVE briefs for triage

author: TopSecretHacker


value: brockleyai

value:
Brockley Al is a strength training app with a conversational Al coach that designs and adapts programs through natural chat. Tell it your goals, schedule, equipment and preferences. It will propose a plan, explain the reasoning and update it on the fly so you can keep progressing without guesswork.
Email founder@brockley.ai to get 3 months free access (for HN community only).

value: Show HN: Brockley AI Fitness Coach and Strength Training App

author: brockleyai


value: DimitrisTheo

value:
Hi HN,
After getting encouraging feedback from early users, I wanted to share a side project I’ve been slowly building.
The idea is simple:
Candidates can only apply if their skills and location actually match the role.
Recruiters see only relevant applicants, no more noise in the inbox.
Profiles are free for candidates. Job posts are free for companies (for now). If budget’s an issue, just reach out, I’d rather see real teams using it.
This project started as a small experiment while working full-time and studying. It’s been a long journey through backend rewrites, self-hosting headaches, UI refactors, and a few AI ideas that didn’t pan out. Learned a lot along the way.
It’s still early, plenty left to improve. I’d love feedback, good, bad, or brutal. You can use the feedback link in the footer or drop me a note.
Thanks!

value: Show HN: I fixed what LinkedIn couldn't, no more unqualified applicants

author: DimitrisTheo


value: sultson

value:
Hi HN, I've built a low-friction web app for playing and recording MIDI keys.
Cozy Keys serves as a sweet spot between full-blown DAW/piano apps and lighter online tools. Former often have setup hassle, and might not be readily available on all devices and online options tend to be either learning-focused or filled with paid features/ads.
What you can do:
- connect MIDI and play keys, you've got the grand piano + additional synth presets (personal favourite is the Juno Synth modelled after the famouse Juno 60/106 lushness)
- choose an "environment" aka preconfigured delay/reverb setting
- record plays, both audio and MIDI are recorded
- playback with preview on keys
- share recordings
- download recordings
There's also a "Chords with Cora" option as an exploration of handing chord creation tooling to a voice agent.
Note: Mobile support is quite limited, working on that.
Source:
https://github.com/sultson/cozy-keys

value: Show HN: Cozy Keys, play MIDI keys in the browser

author: sultson


value: sourdesi

value:
Hey HN, I built VibeScrape — it takes a website URL and a JSON schema describing the data you want, then analyzes the page, writes real Python code to extract that data, and refines the code until the output is accurate.
While there's lots of tools these days (e.g. Firecrawl) that feed the entire HTML of a webpage to an LLM to extract data from it, this always seemed like a really slow & expensive approach to me.
On the other hand, handwriting web-scraping code seems archaic at this point. This type of code is incredibly tedious to write, and immediately becomes throwaway code once the webpage's layout changes even a little.
VibeScrape aims to automate the process of writing this type of code.
1. Grabs the rendered HTML — the same view a browser sees.
 2. Has an LLM extract data from the HTML into your target JSON schema (the “ground truth”).
 3. Generates Python scraper code to reproduce that "ground truth" output.
 4. Runs and compares results against the ground truth.
 5. Refines the code automatically until the outputs match.
I've found that letting the LLM take control of both the code generation and iteration process e2e has worked pretty well for producing working scraper code for many of the websites I've tested it on!
It still has some limitations in terms of handling pagination, captchas, infinite scrolling, etc. Hoping to get some early feedback from the HN community to see if this is a valuable tool. There's a promo code FIRST5 on the site that gets you 5 credits for free, but am happy to give more credits to anyone that reaches out at contact@vibescrape.ai !
Thanks!

value: Show HN: VibeScrape – Paste a URL and JSON schema, get working web scraper code

author: sourdesi


value: bediashpreet

value:
Hi HN,
Excited to share Agno, a framework and runtime for multi-agent systems. Think of it as FastAPI for AI Agents.
At its core is the AgentOS, a high-performance server/runtime that helps you run and manage AI agents, multi-agent teams, and step-based agentic workflows — all inside your own cloud, with full privacy and no external data sharing.
What makes it different
• Fast & lightweight — Agents instantiate in ~3μs and use ~6.6 KiB of memory on average (tested on M4 MacBook Pro).
• Runtime architecture — Async, stateless, horizontally scalable runtime built on FastAPI.
• Integrated UI — Test, monitor, and manage your agents and teams in real time.
• Private by design — Runs entirely in your environment. No vendor lock-in, no telemetry, no external tracing.
A key distinction: the control plane connects directly to your AgentOS runtime from the browser — so no data is ever shared with 3rd party systems.
Docs & links
• Docs → https://docs.agno.com
• GitHub → https://github.com/agno-agi/agno
• Examples → https://docs.agno.com/examples/introduction
What we'd love feedback on
• Whether the architecture makes sense for you
• Your thoughts on the DX and API
• Use cases you'd apply this to
Happy to go deep on internals, performance, or multi-agent design patterns if there's interest.

value: Show HN: Agno – multi-agent framework, runtime and control plane

author: bediashpreet


value: bietroi

value:
Hi r/rust,
I wanted to share with the community a Rust library I started a little while ago called typegraph. It lets you build graphs of types in the type system, for static analysis and stuff like that.
It's the fourth entry in my "Beginner Crates" series, which are crates made for computers learning to code all by themselves.
You can also use it to make diagrams like this one of the tokio current-thread runtime:
https://github.com/nicksenger/typegraph/blob/master/tokio_cu...

value: Show HN: Typegraph – type-level graphs of Rust types

author: bietroi


value: smakosh

value: Show HN: AI Models Group Chat

author: smakosh

title: Show HN: AI Models Group Chat


value: noiv

value: Hi there, I burned too many tokens with over-engineered tools, when all needed is navigate, execute JavaScript and read console logs to make Claude Code finish and verify tasks.<p>If you need more, Claude will happily do, docs included ;)

value: Show HN: A Minimal Playwright Skill for Claude Code

author: noiv


value: dvirbt

value:
Hi HN, I’m Dvir, a young developer. Last year, I got rejected after a job interview because I lacked some CPU knowledge. After that, I decided to deepen my understanding in the low level world and learn how things work under the hood. I decided to try and create an OS in C and ASM as a way to broaden my knowledge in this area.
This took me on the most interesting ride, where I’ve learned about OS theory and low level programming on a whole new level.  I’ve spent hours upon hours, blood and tears, reading different OS theory blogs, learning low level concepts, debugging, testing and working on this project.
I started by reading University books and online blogs, while also watching videos.
Some sources that helped me out were OSDev Wiki (https://wiki.osdev.org/Expanded_Main_Page), OSTEP (https://pages.cs.wisc.edu/~remzi/OSTEP), open-source repositories like MellOS and LemonOS (more advanced), DoomGeneric, and some friends that have built an OS before.
This part was the longest, but also the easiest. I felt like I understood the theory, but still could not connect it into actual code. Sitting down and starting to code was difficult, but I knew that was the next step I needed to  take!
I began by working on the bootloader, which is optional since you can use a pre-made one (I switched to GRUB later), but implementing it was mainly for learning purposes and to warm up on ASM. These were my steps after that:

  1) I started implementing the VGA driver, which gave me the ability to display text.
  2) Interrupts - IDT, ISR, IRQ, which signal to the CPU that a certain event occurred and needs handling (such as faults, hardware connected device actions, etc).
  3) Keyboard driver, which enables me to display the same text I type on my keyboard.
  4) PMM (Physical memory management)
  5) Paging and virtual memory management
  6) RTC driver - clock addition (which was, in my opinion, optional)
  7) PIT driver - Ticks every certain amount of time, and also
  8) FS (File System) and physical HDD drivers - for the HDD I chose PATA (HDD communication protocol) for simplicity (SATA is a newer but harder option as well).
     For the FS I chose EXT2 (The Second Extended FileSystem), which is a foundational linux FS structure introduced in 1993. This FS structure is not the simplest,
     but is very popular in hobby-OS, it is very supported, easy to set up and upgrade to newer EXT versions, it has a lot of materials online, compared to other
     options. This was probably the longest and largest feature I had worked on.
  9) Syscall support.
  10) Libc implementation.
  11) Processing and scheduling for multiprocessing.
  12) Here I also made a shell to test it all.

At this point, I had a working shell, but later decided to go further and add a GUI! I was working on the FS (stage 8), when I heard about Hack Club’s Summer of Making (SoM). This was my first time practicing in HackClub, and I want to express my gratitude and share my enjoyment of participating in it.
At first I just wanted to declare the OS as finished after completing the FS, and a bit of other drivers, but because of SoM my perspective was changed completely. Because of the competition, I started to think that I needed to ship a complete OS, with processing, GUI and the bare minimum ability to run Doom. I wanted to show the community in SoM how everything works.
Then I worked on it for another 2 months, after finishing the shell, just because of SoM!,  totalling my project to almost 7 months of work. At this time I added full GUI support, with dirty rectangles and double buffering, I made a GUI mouse driver, and even made a full Doom port! things I would've never even thought about without participating in SoM.
This is my SoM project: https://summer.hackclub.com/projects/5191.
Every project has challenges, especially in such a low level project. I had to do a lot of debugging while working on this, and it is no easy task. I highly recommend using GDB which helped me debug so many of my problems, especially memory ones.
The first major challenge I encountered was during the coding of processes - I realized that a lot of my paging code was completely wrong, poorly tested, and had to be reworked. During this time I was already in the competition and it was difficult keeping up with devlogs and new features while fixing old problems in a code I wrote a few months ago.
Some more major problems occurred when trying to run Doom, and unlike the last problem, this was a disaster. I had random PFs and memory problems, one run could work while the next one wouldn’t, and the worst part is that it was only on the Doom, and not on processes I created myself. These issues took a lot of time to figure out. I began to question the Doom code itself, and even thought about giving up on the whole project.
After a lot of time spent debugging, I fixed the issues. It was a combination of scheduling issues, Libc issues and the Qemu not having enough (wrongfully assuming 128MB for the whole OS was enough).
Finally, I worked throughout all the difficulties, and shipped the project! In the end, the experience working on this project was amazing. I learned a lot, grew and improved as a developer, and I thank SoM for helping to increase my motivation and make the project memorable and unique like I never imagined it would be.
The repo is at https://github.com/dvir-biton/MyraOS. I’d love to discuss any aspect of this with you all in the comments!

value: Show HN: MyraOS – My 32-bit operating system in C and ASM (Hack Club project)

author: dvirbt


value: GabrielMMMM

value: Meet INK. Part browser, part newspaper. It’s in beta, and I’m adding new features as I go.

value: Show HN: iOS 26 broke my favorite feature. I built my own mobile browser

author: GabrielMMMM


value: diego-aquino

value:
Zimic is a set of TypeScript-first HTTP integration libraries, designed with developer experience and type safety in mind.
https://zimic.dev
---
Background:
Ever since I first started using TypeScript, I felt that mocking HTTP responses was hard to scale with tools like MSW and Nock. Having used these libraries for a couple of years, primarily for testing, I often had to write, review, and duplicate a lot of custom abstractions on top of them, trying to ensure:

  • Mock compliance: every mock should be realistic and accurate with the real service it represents; mocks with incorrect parameters, incompatible responses, or out of sync with the actual API directly reduce test confidence;

  • Test completeness: if an application is expected make a number of requests with certain parameters, it should be clear from the tests what these expectations are and they should fail if not met;

Over the years, I've come to believe that the tools we use have a unique opportunity to shape our mental models and encourage good practices. So I started exploring a question:
How could a library help developers create better API mocks?
The insights I gained during my research led to the early drafts of @ zimic/interceptor and a published paper on IEEE (https://ieeexplore.ieee.org/document/11126628). From there, I started expanding Zimic's core principles to cover more aspects of the development process, not just API mocking:

  • @ zimic/http: declare HTTP schemas, infer types from OpenAPI, and type native Web APIs.

  • @ zimic/fetch: create type-safe Fetch API clients and have your requests and responses fully typed by default.

  • @ zimic/interceptor: mock HTTP services in development and testing, and simulate responses with type safety.

Earlier this year, Zimic reached 1.0 and I'm curious to hear what you think!
https://zimic.dev

value: Show HN: Zimic: TypeScript-first HTTP integrations

author: diego-aquino


value: tidalboot

value:
Heyo
My friend and I recently built a simple browser-based doodling site that lets you draw freely without needing to sign up or install anything:
 doodl.it.com
It’s intentionally minimal — you just open it and start drawing. You can save your doodle or clear the canvas instantly.
Works on mobile + desktop
We made it because we wanted something frictionless for quick sketches and brainstorming. Would love to hear your feedback, especially around performance and UX!

value: Show HN: Doodl – Free Online Doodling Canvas (No Account Needed)

author: tidalboot


value: TechSquidTV

value: I've been playing with my home server again, and I was looking for a video downloader. I found one that looked great, but was no longer functional. So, I vibe-coded my own.<p>Hermes is a REST API and web app built on top of yt-dlp. Why not just use yt-dlp? Additional features, phone support, and automations. Coming soon will be a very basic video editor so you can easily remux and trim your downloaded videos.

value: Show HN: Hermes – Self-hosted video downloader

author: TechSquidTV


value: ubutler

value:
Hey HN,
I'm excited to share the Massive Legal Embedding Benchmark (MLEB) — the first comprehensive benchmark for legal embedding models.
Unlike previous legal retrieval datasets, MLEB was created by someone with actual domain expertise (I have a law degree and previously led the AI team at the Attorney-General's Department of Australia).
I came up with MLEB while trying to train my own state-of-the-art legal embedding model. I found that there were no good benchmarks for legal information retrieval to evaluate my model on.
That led me down a months-long process working alongside my brother to identify or, in many cases, build our own high-quality legal evaluation sets.
The final product was 10 datasets spanning multiple jurisdictions (the US, UK, Australia, Singapore, and Ireland), document types (cases, laws, regulations, contracts, and textbooks), and problem types (retrieval, zero-shot classification, and QA), all of which have been vetted for quality, diversity, and utility.
For a model to do well at MLEB, it needs to have both extensive legal domain knowledge and strong legal reasoning skills. That is deliberate — given just how important high-quality embeddings are to legal RAG (particularly for reducing hallucinations), we wanted our benchmark to correlate as strongly as possible with real-world usefulness.
The dataset we are most proud of is called Australian Tax Guidance Retrieval. It pairs real-life tax questions posed by Australian taxpayers with relevant Australian Government guidance and policy documents.
We constructed the dataset by sourcing questions from the Australian Taxation Office's community forum, where Australian taxpayers ask accountants and ATO officials their tax questions.
We found that, in most cases, such questions can be answered by reference to government web pages that, for whatever reason, users were unable to find themselves. Accordingly, we manually went through a stratified sample of 112 challenging forum questions and extracted relevant portions of government guidance materials linked to by tax experts that we verified to be correct.
What makes the dataset so valuable is that, unlike the vast majority of legal information retrieval evaluation sets currently available, it consists of genuinely challenging real-world user-created questions, rather than artificially constructed queries that, at times, diverge considerably from the types of tasks embedding models are actually used for.
Australian Tax Guidance Retrieval is just one of several other evaluation sets that we painstakingly constructed ourselves simply because there weren't any other options.
We've contributed everything, including the code used to evaluate models on MLEB, back to the open-source community.
Our hope is that MLEB and the datasets within it will hold value long into the future so that others training legal information retrieval models won't have to detour into building their own "MTEB for law".
If you'd like to head straight to the leaderboard instead of reading our full announcement, you can find it here: https://isaacus.com/mleb
If you're interested in playing around with our model, which happens to be ranked first on MLEB as of 16 October 2025 at least, check out our docs: https://docs.isaacus.com/quickstart

value: Show HN: The Legal Embedding Benchmark (MLEB)

author: ubutler


value: jqssun

value:
Been working on an experimental Chromium-based browser that brings 2 major features to your phone/tablet:
1. desktop-style extensions: natively install any extensions (like uBO) from the chrome web store, just toggle "desktop site" in the menu first.
2. privacy/security hardening: applies the full patch sets from Vanadium (with Helium's currently wip).
Means you get both browsers' excellent privacy features, like Vanadium's webrtc IP policy option that protects your real IP by default, and security improvements such as JIT being disabled by default, all while being a reasonably efficient FOSS app that can be installed on any (modern) android.
It's still in beta, and as I note in the README, it's not a replacement for the full OS-level security model you'd get from running the GrapheneOS Vanadium combo. However, goal was to combine privacy of Vanadium with the power of desktop extensions and Helium features, and make it accessible to a wider audience. (Passkeys from Bitwarden Mobile should also work straight away once merged in the list of FIDO2 privileged browsers)
Build scripts are in the repo if you want to compile it yourself. You can find pre-built releases there too.
Would love any feedback/support!

value: Show HN: Helium Browser for Android with extensions support, based on Vanadium

author: jqssun


value: patrickdavey

value:
I made this basic website for my daughter (6) to learn how to move chess pieces.  I wanted a simple game which didn't have all the rules, just how to get from A to B with a piece.  Admittedly, as soon as I made this a friend pointed out https://lichess.org/learn which is really nice!
There are a bunch of settings you can tweak to set the difficulty etc. Anyway, maybe will be a fun (short) diversion.

value: Show HN: Learn Basic Chess Movements

author: patrickdavey

title: Show HN: Learn Basic Chess Movements


value:
I built a TypeScript validation library after getting frustrated with FormData in Remix/Next.js Server Actions.
The problem: Zod (the most popular validation library) doesn't have FormData support. It's their #1 requested feature with 60+ upvotes on GitHub [1], but they haven't implemented it.
So every Server Action looks like this:

    const name = formData.get('name') as string;
    const age = parseInt(formData.get('age') as string);
    // ... manual validation

I wanted:

    const result = validateFormData(formData, schema);
    // Automatic type conversion, validation done

While building this, I also added:
- Partial validation (return valid data even with errors - useful for auto-save)
- JSON Schema export (built-in, no external package needed)
- File validation (size, MIME types)
- XOR support (exactly one of these fields)
Zero dependencies. 3KB. MIT licensed.
GitHub: https://github.com/YOUR_USERNAME/lite-schema-check
npm: npm install lite-schema-check
Technical details in README. Happy to answer questions about the implementation.
[1] https://github.com/colinhacks/zod/discussions (search for FormData)

value: Show HN: FormData validation for TypeScript (Zod's most requested feature)


value: kirurik

value:
Hey everyone,
I made a small tool called osync, a setup that uses Git and rsync to sync and back up directories between devices.
It started as a personal experiment to sync my Obsidian notes between my PC and phone without relying on cloud storage or overcomplicated tools. I thought it would be simple, just SSH and rsync, but it turned into a great learning experience.
Now the script can, once SSH, systemd, and the works are set up, automatically sync between two computers reliably while also backing up to a Git repository.
GitHub: https://github.com/Kena-Njonge/osync
I also wrote a blog post
https://open.substack.com/pub/kenakiruri/p/how-i-backup-and-...
that goes over the motivation and acts as a tutorial if you want to use the tool to sync your Obsidian vaults. It also covers some of the differences between this setup and other alternatives.
Would love to hear your thoughts, especially on how I could improve it from a software engineering perspective.
Thanks!

value: Show HN: Osync – A Git and rsync tool for local syncing and backups

author: kirurik


value:
Hi HN,
As a huge manga fan and a translator by training, I've always been in awe of the incredible amount of work that fan translators put in. The process isn't just about translation; it involves manually cleaning the original text from the bubbles, redrawing the background art (inpainting), and then carefully placing the translated text back in (typesetting). It's a true labor of love, but it's incredibly time-consuming.
I wondered if modern AI could help automate the most tedious parts of this workflow. So, I built AIFandom.
It's a web tool where you upload your manga pages, and it extracts the text from the speech bubbles and translates the text, but with a key difference: The model doesn't just read the text, it also looks at the visual context of the panel to better capture the original tone and nuance.
Then, It automatically removes the original text, uses an inpainting model to intelligently redraw the artwork that was behind the text, and then typesets the translated text back into the bubbles.
The end result is a fully translated and readable manga page that you can download.
I use gemini for the translation process and various models for OCR, inpainting, masking, rendering.
It's not a free tool. This whole process is computationally expensive and requires a good amount of GPU time. To cover these costs, I've priced it at $7/month for 1000 pages.
However, I really want you to see the quality for yourself, so there is a 50-page free trial for everyone to test it out, no credit card required upfront.
I would be incredibly grateful for your feedback.
- How is the translation quality and tone?
- Does the automatic typesetting look natural to you?
- Is the pricing fair for the value it provides?
- What features should I prioritize adding next?
Thanks for checking it out! I'll be here all day to answer any questions.

value: Show HN: AI that uses image context to translate and redraw manga


value: bagusfarisa

value: Show HN: Simple Business Idea Validation

author: bagusfarisa


value: Leftium

value:
This replaces my previous HN client, which I've been using over 10 years.
- Major innovation: [Page Down] for mobile. I wish all sites had this: just tap the gray region to precisely scroll that item to the top.
- Defaults to all front page items in (hckr news[1]) reverse chronological order. But also supports the official HN "top" ranking (as well as most of the other "lists"[2])
- Interesting stories highlighted: point/comment icons turn orange after passing 50. The number also turns orange after passing 100.
- Extra info shown (when possible.) Good examples here: https://hn.leftium.com/hckrnews/2025.10.20
~ Last week a front page submission got 107 points before being killed. Besides the vote count, we can still see the domain.
~ The deltas after the time are how much time the story took before reaching the front page. Large times indicate the story was probably "re-upped," so they are highlighted. (Some human decided this item was worth inserting into the front page)
More details + source code: https://github.com/Leftium/hn
Currently individual item rendering is not implemented; I simply defer to to the previous version, but I plan some major innovations when rendering items, too.
Your questions/comments welcome!
[1]: https://hckrnews.com/
[2]: https://news.ycombinator.com/lists

value: Show HN: HN reader with "Page Down" for mobile and other QoL tweaks

author: Leftium


value: yar-kravtsov

value:
I built a Vite plugin that lets you write Go code directly in .js files using a "use
  golang" directive. It compiles to WebAssembly automatically.

value: Show HN: Write Go code in JavaScript files

author: yar-kravtsov


value: dtormoen

value:
I wanted AI agents to work for me in the background like a coworker, not require constant supervision. TSK lets you queue tasks for Claude Code or Codex in sandboxed containers - when they finish, you get a git branch to review. This frees up your time to focus on more interesting problems without the constant interruption of agent approvals.
As an example, here's what it looks like to kick off a new task:

    tsk run --type feat \
        --name greeting \
        --description "Add a greeting for users each time they run a command in TSK"

For this command, TSK will make a copy of your repo, create an isolated docker container with the tech stack you are using, start a forward proxy to limit internet access, mount your Claude Code configuration and repo into the container, and finally kick off the coding agent. Internet access is limited to agent API endpoints and common tools for managing dependencies e.g. crates.io or pypi.
The "feat" task template includes repetitive but important instructions like "write unit tests", "update documentation", and "write a detailed commit message". The "description" flag gets injected into the template. It's easy to add new task templates. They are very similar to slash commands in Codex or Claude.
When the agent finishes, a new commit and branch is non-disruptively created in your repository for you to review.
Additionally, you can also use the `tsk server` to run multiple agents in parallel. This command will tell the TSK server to run Claude Code and Codex in parallel with the exact same instructions:

    tsk add --type refactor \
        --name clippy \
        --description "Fix all the clippy linter errors in the codebase." \
        --agent claude,codex

TSK also supports a `tsk shell` command that starts up an interactive shell in one of the sandboxes. This works great with a multiplexer to manage multiple interactive agents.
I just finished Codex support and multi-agent comparisons today so thought it was a good time to share!

value: Show HN: TSK – agent sandbox, delegation, and parallelization tool

author: dtormoen


value: SoulLab

value:
A small web toy that turns emotional struggles into bug reports.
Example: “Hope.exe stopped responding after job rejection.”
It converts your line into a humorous, cathartic “grief CV.”
https://life-exe.vercel.app
Built with HTML, Tailwind, JS.
Curious if it resonates or just feels weird.

value: Show HN: Life.exe – File bug reports for your feelings

author: SoulLab


value:
I built Ltx-2 AI, a next-generation video generation model that unifies sound, motion, and visual storytelling in one pass.
Unlike fragmented workflows that require separate dubbing, rendering, and editing, Ltx-2 AI delivers synchronized audio-visual output — precise, cinematic, and production-ready.
What it does:
Generates synchronized audio + video in a single pass
Delivers native 4K textures and frame-consistent motion
Offers multi-mode performance — fast preview to high-fidelity render
Supports multi-keyframe control, 3D camera logic, and LoRA style adapters
Accepts text, image, clip, depth, and audio inputs
Provides open APIs and SDKs for integration and automation
Who it’s for:
Filmmakers, marketers, and animation studios
Game and XR developers
Post-production and pre-vis teams
Anyone needing cinematic motion without full 3D pipelines
Try it here: https://www.jxp.com/ltx-2
Would love feedback from the HN community — especially on integration use cases, 4K performance, and creative direction tools.

value: Show HN: Ltx-2 AI – 4K Audio-Video Generation with Creative Control


value: thompalec

value: Show HN: 360 Panorama Game Demo

author: thompalec

title: Show HN: 360 Panorama Game Demo


value: droidHZ

value:
Hi everyone
I built vidflux.ai — a unified AI video generation platform that lets you create videos using multiple top-tier models in one place: Veo3, Sora2, Kling, Wan 2.5, and Seedance.
You can upload an image or text prompt, choose a model, and instantly generate short clips for creative storytelling, product demos, or experiments.
I was inspired by how fragmented AI video tools have become — each model has a different interface, format, and API. VidFlux aims to simplify this by giving creators one consistent workspace.
Would love your feedback on:
- Which models or features should be added next?
- How should pricing or credits work for fair usage?
Try it here: https://vidflux.ai
Thanks for checking it out!

value: Show HN: VidFlux – Generate videos using AI models like Veo3, Sora2,and Wan 2.5

author: droidHZ


value:
Hi ,
I built en-git to get deeper analytics from GitHub profiles.
The main app gives you a profile score (0-100), actionable tips to improve, analytics (heatmaps, language stats), and achievements.
The Chrome extension adds in-browser code quality analysis for files and PRs, plus some productivity tools (bookmarks, shortcuts).
I'm looking for any and all constructive feedback. Thanks!

value: Show HN: I built a tool to score and analyze GitHub profiles


value: eummm

value: Show HN: Free Tool to Grade Your Website for AI Visibility

author: eummm


value: JiangJason

value: Show HN: Mesh AI enables 3D creators to turn their imagination into reality

author: JiangJason


value: StellaMary

value: Show HN: Write JavaScript code that Runs on RUST hits 1M req/s

author: StellaMary


value: machinelearning

value: Show HN: Automate robot data quality improvement

author: machinelearning


value: weddpros

value: Show HN: SSL Certificate Expiration in Calendar App

author: weddpros


value: tajd

value: I built and shared a start up viability calculator on my blog. This is a huge and nuanced area but I thought I'd start to take a look at it by building something simple. Any feedback welcome - all lessons learned are good!

value: Show HN: Estimating startup viability using Nobel Prize economics

author: tajd


value: everettraven

value:
As a software engineer and open source maintainer, I've found that signal gets lost in the noise pretty frequently. Especially GitHub notifications.
To stay organized I've tried things like GitHub Projects, Notion, and Pen + Paper.
So far, pen and paper has proven to work the best for me but I had this nagging feeling that there is a "better" way to stay organized.
I've been working on wranglr to help me cut through the noise and get a focused view of what needs my attention across both GitHub and Jira.
Let me know what you've tried to stay organized, what has worked, and what you think of wranglr if you give it a try.

value: Show HN: Wranglr – A programmable CLI for tracking dev work

author: everettraven


value: jamalavedra

value: Show HN: OpenSigner – An open-source and non-custodial solution to issue wallets

author: jamalavedra


value: mapedia

value: HanView fetches the stunning daily Bing wallpaper (every 3 hours), uses AI to seamlessly overlay a random frequently used Chinese word, and sets the enriched image as your Windows wallpaper. It’s a perfect way to "encounter" a Chinese word, effortlessly—blending the beauty of the world with the richness of language, right on your desktop.

value: Show HN: HanView -Effortless Learning Chinese on Wallpapers

author: mapedia


value: Show HN: Submit a photo – I'll mail a piece of it to your friend each week


value: hellodryft

value:
Hey HN,
It was back in April 2023 when I was trying to build a voice agent with the Orpheus/Sesame CSM models it was my first time building something in AI and I absolutely hated the friction the platforms had to offer, mental prices, vast.ai instances not even connecting half of the time, and nothing in the platforms that said "you're welcome here"
Out of frustration, I spoke to some providers, sorted out a fine list, and built Runcrate.
We made the onboarding, UX, and overall experience as frictionless as possible.
The billing is just like you'd pay OpenAI or Anthropic, no contracts, no reservations, no quotas, no more contacting support "Hey I need more GPUs pls" and then get rejected. Whatever is in the stock, its available for everyone.
Oh and yeah, there's also a cool button that comes with all instances that spins up a vscode on the browser for you with a custom jupyter notebook extension installed.
Frictionless, that's all I wanted in this space.
I hope it'll genuinely help people looking to get started with AI & startups looking to cut their bills down. Would love your feedback pls
Jish

value: Show HN: Frustrated by GPU costs, so I built my own cloud

author: hellodryft


value: Sunfin

value: The best MP4 video downloader site for free online videos download. No registration needed — just paste the link and download video from URL in seconds.

value: Show HN: Videos Download Online for Free – Videosdownload.org

author: Sunfin


value: For Livewire, there isn't a solid WYSIWYG editor integration that handles syncing cleanly with the Laravel backend and Livewire itself, so I made one.

value: Show HN: CKEditor 5 Livewire Integration


value: RandomDailyUrls

value: Show HN: I recreated a 90s Halloween decoration from my childhood

author: RandomDailyUrls


value: tsormed

value:
Hey HN!
I built Chime - a macOS app that shows full-screen meeting alerts for people who lose track of time while in deep work mode (like me).
The problem: Calendar notifications are too subtle when you're in deep focus. I kept missing meetings/reminders and felt terrible about it.
The solution: Full-screen alerts 5 minutes before meetings that you literally can't ignore (time is customisable). Plus auto-detection of Zoom/Teams/Meet/etc links for one-click joining.
Tech stack: Native Swift/SwiftUI, EventKit for calendar integration, local-first (your data stays on your Mac).
Landing page: https://usechime.app
I'm looking for ~50 beta testers to try it via TestFlight before the official launch. Especially interested in:
- Techies who have this same problem
- Feedback on the alert timing and design
- Edge cases with different calendar setups
- Privacy-conscious users (happy to discuss implementation)
If you're interested, there's a waitlist link on the site. I'll send TestFlight invites to the first respondents.
Would also love general feedback on the concept!

value: Show HN: Looking for beta testers for my macOS meeting reminder app

author: tsormed


value: denisraslov

value: Show HN: BadgeFlow – Print-ready PDF name badges from a spreadsheet

author: denisraslov


value: eigenvalue

value:
I finally got around to making a tool I've wanted for a long time: you can basically think of it as being "like Gmail for coding agents."
If you've ever tried to use a bunch of instances of Claude Code or Codex at once across the same project, you've probably noticed how annoying it can be when they freak out about the other agent changing the files they're working on.
Then they start doing annoying things, like restoring files from git, in the process wiping out another agent's work without a backup.
Or if you've tried to have agents coordinate on two separate repos, like a Python backend and a Nextjs frontend for the same project, you may have found yourself acting as the go-between and liaison between two or three different agents, passing messages between them or having them communicate by means of markdown files or some other workaround.
I always knew there had to be a better way. But it's hard to get the big providers to offer something like that in a way that's universal, because Anthropic doesn't want to integrate with OpenAI's competitive coding tool, and neither wants to deal with Cursor or Gemini-CLI.
So a few days ago, I started working on it, and it's now ready to share with the world. Introducing the 100% open-source MCP Agent Mail tool. This can be set up very quickly and easily on your machine and automatically detects all the most common coding agents and configures everything for you.
I also include a ready-made blurb (see the README file in the repo) that you can add to your existing AGENTS dot md or CLAUDE dot md file to help the agents better leverage the system straight out of the gate.
It's almost comical how quickly the agents take to this system like a fish to water. They seem to relish in it, sending very detailed messages to each other just like humans do, and start coordinating in a natural, powerful way. They even give each other good ideas and pushback on bad ideas.
They can also reserve access to certain files to avoid the "too many cooks" problems associated with having too many agents all working on the same project at the same time, all without dealing with git worktrees and "merge hell."
This also introduces a natural and powerful way to do something I've also long wanted, which is to automatically have multiple different frontier models working together in a collaborative, complementary way without me needing to be in the middle coordinating everything like a parent setting up playdates for their kids.
And for the human in the loop, I made a really slick web frontend that you can view and see all the messages your agents are sending each other in a nice, Gmail-like interface, so you can monitor the process. You can even send a special message to some or all your agents as the "Human Overseer" to give them a directive (of course, you can also just type that in manually into each coding agent, too.)
I made this for myself and know that I'm going to be getting a ton of usage out of it going forward. It really lets you unleash a massive number of agents using a bunch of different tools/models, and they just naturally coordinate and work with each other without stepping on each other's toes. It lets you as the human overseer relax a bit more as you no longer have to be the one responsible for coordinating things, and also because the agents watch each other and push back when they see mistakes and errors happening. Obviously, the greater the variety of models and agent tools you use, the more valuable that emergent peer review process will be.
Anyway, give it a try and let me know what you think. I'm sure there are a bunch of bugs that I'll have to iron out over the next couple days, but I've already been productively using it today to work on another project and it is pretty amazingly functional already!

value: Show HN: MCP Agent Mail, Like Gmail for Coding Agents

author: eigenvalue


value: tomstig

value: Show HN: Combine multiple photos into a fun, flash-lit Polaroid snapshot 4 free

author: tomstig


value:
Hi HN,
Over the past several months we’ve been building Shivon AI, a platform aimed at candidates getting ready for interviews. The core idea: let you simulate real interviews with an AI (any domain, any role), generate a detailed performance report, and then share that report as part of your job-application portfolio.
Key features:
A chat-based AI interviewer that asks theory, practical usage and case-study style questions.
After each simulation you receive a breakdown of your performance across metrics (e.g., communication, problem solving, confidence) with actionable suggestions.
You can track improvements over time and share your interview-report as tangible evidence of your prep.
We just launched the beta at https://candidate.shivonai.com
 (no paywall; demo mode available).
Why we built this:
We’ve seen how difficult it can be for candidates to highlight their real skills beyond a résumé or LinkedIn profile. Interview preparation often happens in isolation, with no way to measure improvement or share results. Our goal is to make this process measurable, transparent, and empowering for every job seeker.
We’re looking for feedback from the HN community especially around:
How realistic/interview-like the AI questions feel (domain-agnostic).
Whether the performance report adds value and how it could be improved.
Thoughts on sharing such a report as part of a portfolio — does it meaningfully affect job odds, or feel gimmicky?
Happy to answer questions on the architecture, data pipeline, UI/UX, even business model if you’re interested.
Thanks for checking it out — looking forward to the discussion.
Vraj Patel,
Shivon AI

value: Show HN: Shivon AI – Practice job interviews with AI and get a shareable report


value: alperenz

value: Show HN: I quit doomscroll with this app

author: alperenz


value: thisisagooddayg

value: Show HN: ChartPilot – Simplified pricing and free daily signals

author: thisisagooddayg


value: timsul

value:
Hi HN! I'm Tim! We rejected 73% of our AI-generated content last month. Not because of grammar, but because it was substantively empty. AI made content production 10x faster, but quality checking didn't scale. I built FluffFilter to catch this before publishing.
Content teams went from producing 25 posts/week to 250+, but were publishing a lot of generic fluff—phrases like "in today's digital landscape," unsubstantiated claims, surface-level analysis.
Existing tools (Grammarly, Clearscope, etc.) focus on mechanics and SEO keywords, not substantive quality.
What FluffFilter Does:

  * Analyzes content against 20+ specialized evaluators
  * Automatically detects content type (blog post, case study, email, etc.)
  * Returns 3-5 surgical fixes with exact locations and suggested replacements
  * Batch processing for reviewing 50+ documents at once

Technical Stack:

  * Rails 8.0 + SQLite: Decided against starting with Postgres + Redis to launch with zero-dependency stack. Deploys in 30 seconds, is cheap to host.
  * Solid Queue replaced Redis: One less service to manage, job processing works identically.
  * Claude Sonnet 4.5: ChatGPT did pretty well too, but found Claude's analyses felt better.
  * Turbo Streams for real-time updates

Example Analysis:
I analyzed an AI-generated "marketing trends" blog post. It would score well on SEO tools (good keywords, readable), but FluffFilter found:
  * Zero concrete examples or verifiable data
  * Vague audience (unclear who it's for)
  * Ends with "Would you like that?" like a personal email
See the full analysis: https://flufffilter.com/examples/blog-post
More examples: https://flufffilter.com/examples
Try it yourself: 7-day trial with 15 analyses at https://flufffilter.com
Built this nights and weekends. Would love HN's thoughts on:

  1. The technical approach
  2. Whether the AI feedback quality is genuinely useful vs. generic
  3. What other content types would be valuable to evaluate

Launching on Product Hunt today as well, but genuinely curious what HN thinks.

value: Show HN: Content quality analysis that finds what SEO tools miss

author: timsul


value: cornfieldlabs

value:
TLDR: I built a "quick and dirty " private social network for my friends, posted on Reddit and HN,
got some interest so now have built it properly along with my brother.
site link: https://intimost.com/login/
demo creds:
test@example.com
Demo123!
Full version:
I needed a social network where I can just send updates and nothing
else. So I built it, my friends liked and now I have built it
"for the world".
Everything is private by default.
- Text-only updates
- No likes. Only views to acknowledge a post
- [in development] Comments are private between the poster and commenter
- Friends not followers
- Profiles are not searchable - You need the user's `Friend Code` to find a
profile
- Feed shows updates from your friends and nothing else
More context:
Original Reddit post (a few months ago): https://old.reddit.com/r/digitalminimalism/comments/1kuuv8h/...
Launch post (today): https://old.reddit.com/r/digitalminimalism/comments/1oh935z/...
I am looking for feedback and thoughts!
(You can use a dummy email to signup and delete the account a few clicks afterwards)
A lot of users are asking for photos, we are trying to figure out how to do
that in a "clean" way
Thank you
- J

value: Show HN: A minimalist, no-clout social network with chronological feed

author: cornfieldlabs


value: bfeist

value:
Today my collaborator and I are releasing issinrealtime.org, a multimedia project that plays back every day onboard the ISS. Feedback welcomed.
Here's an article that was just released about it: https://www.collectspace.com/news/news-102725a-iss-in-real-t...
I also wrote a "making of" post about it here:
https://benfeist.com/posts/iss-in-real-time/

value: Show HN: ISS in Real Time – 25 Years Aboard the International Space Station

author: bfeist


value:
I built a simple, free online video editor that runs entirely in your browser using FFmpeg compiled to WebAssembly.
No installs, no uploads, no server load — the processing happens locally, so your videos never leave your machine.
Currently supported:
•  Trim/cut clips
•  Adjust playback speed
•  Export locally (MP4)
•  Privacy-safe (client-side only)
It’s surprisingly fast, and works well for:
• Social video edits
• Quick meme/training clips
• Micro-content workflows
• When you don’t want to open Premiere/FCP

value: Show HN: Free Online Video Editor Powered by FFmpeg (Runs in the Browser)


value: I made pinpam, a PAM module and utility to enable authentication on Linux with a brute-force resistant, TPM2-backed pin, intended to supplement (not replace) traditional password based Unix authentication. I created this because I wanted the convenience of a phone-like PIN unlock for my Linux device, with improved security over existing solutions like simply setting your password to a number. Generally a pin is less secure than a strong password, but they can be more convenient and easier for users to embrace. Please carefully consider your threat model when implementing any authentication service.

value: Show HN: Pinpam, TPM2-backed pin authentication for Linux


value: ieuanking

value:
Hi HN!
Really grateful for the feedback and users over the past couple of months, the Show HN community has been so helpful! We've recently improved some core pain points affecting our Ubik users.
What's New?
1. Improved PDF ingestion: wait times have been reduced, varying times based on size & # of PDFs uploaded (DOCX soon, wait for files to turn green in context bar).
2. Simplified layout: Panel option added (top right of page).
3. Added models: 200+ frontier/experimental models.
4. Compare Canvas: See text documents (Canvas) side by side, apply changes where you see fit.
5. Improved system prompt/tool calling: Agents are more aware of all tool purposes.
6. Abstract page: not all papers are open-access - new abstract page has core info and routes to DOI.
What is Ubik?
Ubik is an AI Research Environment (AiRE). With context-aware agents, academic database access (ArXiv/Semantic Scholar), and consistent human approval, Ubik improves agentic capabilities, minimizes hallucination, and makes LLM-assisted writing usable in high-level research and citation-based work. How does Ubik do this?
Agent Orchestration
We build our agents optimized around their environments, not a specific model, making it easy to run them in the cloud, on devices, and eventually with local models.
Dynamic Context Engine
This helps the AI and the human understand the larger project at hand, as well as any research criterion (citation styling, topic area focus, finding new sources, context of a project)
1. NOT just embeddings or semantic search!
2. Custom document parsing and enhanced OCR for in-text citations and transparent AI output
3. Agentic analysis to extract, understand, and markup documents beyond single questions
4. Like Cursor, Ubik knows your workspace. For improved accuracy, you can reference all files and agent-made items (notes/canvas) while prompting using the @ symbol.
Why did we build Ubik?
Because generative tools help experts and hurt beginners, quick solutions to complex problems without friction/interactivity between the initial prompt and the desired output don’t build cognitive skills in beginners that experts have mastered without AI (vibe code, vibe physics, vibe xyz = AI slop). Unlike beginners, experts amplify their human intelligence because they can correct AI output and understand when the model/agent is unhelpful or hallucinating; this is intellectual agility, a critical skill for effective AI use.
https://stackoverflow.blog/2025/08/07/a-new-worst-coder-has-...
https://simonwillison.net/2025/Oct/7/vibe-engineering/
https://bigthink.com/starts-with-a-bang/vibe-physics-ai-slop...
The Cognitive Cost:
MIT is conducting an ongoing neurological study on ChatGPT users' brain activity while using the AI chatbot to complete tasks. MIT's early findings are worrying. LLM-assisted writers could not complete writing tasks effectively or efficiently. What does this mean? Critical thinking skills and intellectual agility crumble when we treat AI as an oracle.
https://www.media.mit.edu/projects/your-brain-on-chatgpt/ove...
https://bigthink.com/business/ai-will-never-be-a-shortcut-to...
Ubik v1 Today:
https://app.ubik.studio is live (v1). Our current 260 users (researchers, scientists, and students) who use Ubik for their citation-based work. Before we release the full Ubik App, the platform will be free! Sign up for our PDF analysis tools, and please reach out with any feedback.
Ubik App v2 (electron app) Coming Soon:
Reduces all wait times on PDF ingestion, unifies our agents, and is built ready for local, on-machine models. We are working on our custom eval suite for knowledge work/evidence attribution (reach out to learn more).
If you are interested in a demo of our full app, would like to enter a beta/testing group for the app, or want to understand more about Ubik, please email me: ieuan@ubik.studio

value: Show HN: Ubik - A new way to use AI in citation-based work and research

author: ieuanking


value: dmachard

value: Show HN: 16×16 LED Matrix Controlled via Web Bluetooth

author: dmachard


value:
Tired of copy-pasting the same question across ChatGPT, Claude, Gemini, and Grok to find the best answer?
I built ChatHawk to solve this exact problem: Ask once and get responses from all top AI models simultaneously, plus an AI-generated combined answer that pulls the best insights from each.
Perfect for when you need accurate answers (verified across models), strategic decisions, or multiple AI perspectives. Stop the tedious switching between platforms – get comprehensive AI insights in one place.
What questions would you want to run through all models at once?

value: Show HN: ChatHawk – Stop Copy-Pasting the Same Question Across Every AI Model


value: mauricio

value: Show HN: Rethinking the Interface for Vibe Coding

author: mauricio


value: K-dash

value:
I built nblm, a Rust-based toolset to automate Google’s NotebookLM Enterprise API reliably.
It aims to replace brittle curl snippets with a stable interface you can use in cron/CI or agentic systems.
* Python SDK (type-safe): IDE auto-complete, fewer JSON key typos, fits complex workflows.
* Standalone CLI: single fast binary for scripts and pipelines.
* Handles auth, batching, retries; you focus on logic. Rust core is fast and memory-safe.
* Enterprise API only (consumer NotebookLM isn’t supported).
Repo: https://github.com/K-dash/nblm-rs
Feedback is welcome—I'm especially interested in thoughts on the Python SDK’s design for building automated/agentic workflows. Thanks!

value: Show HN: nblm - Rust CLI/Python SDK for NotebookLM Enterprise automation

author: K-dash


value: Show HN: The Struggle of Sending a 2GB File on WhatsApp


value: olism

value:
I built this after spending days every year manually searching through Jira tickets to remember what I'd accomplished for performance reviews.
whatdidido is a CLI tool that:
- Pulls tickets from Jira or Linear for a date range
- Uses an LLM to create short summaries of each ticket
- Generates an overall summary to help you build your self-evaluation
The tool doesn't write your review for you—crafting thoughtful, contextual feedback still requires human judgment. It just eliminates the busywork of finding and organizing what you worked on.
Key details:
- MIT licensed, open source
- No data storage—everything stays local
- Requires OpenAI or OpenRouter API key
- Works with Jira and Linear (more integrations welcome/coming soon)
GitHub: https://github.com/oliviersm199/whatdidido
I'm releasing it now because I think others might find it useful during review season.
Would love feedback on the approach and what other integrations would be helpful. Happy to answer questions about how it works.

value: Show HN: Whatdidido – CLI to summarize your work from Jira/Linear

author: olism


value: andreas-schrade

value:
Years ago, I was part of a small tech startup that went through the usual rollercoaster. When it all ended, I couldn’t stop thinking about how surreal it had been: the long nights, the weird meetings, etc.
A friend of mine, who used to work in the film industry in Thailand before also moving into the tech world, had gone through similar ups and downs as a founder: burnout, crises, and the familiar feeling of questioning why we build things at all.
So we decided to make something just for the sake of building: our first movie.
It was entirely self-funded with $2,045. No investors and zero financial motivation. We simply wanted to create something we actually love!
With our entrepreneurial background, we knew getting attention for an art project would be really tough. Therefore we tried to use our startup mindset as a competitive advantage.
For example, a co-working space location that normally rents for $1,500/shooting day (we needed 4 days) became affordable when we made a deal with a smaller co-working space. We offered them photos and footage of the prodouction which they could use for their social media marketing.
During editing, we ran into something unsatisfying and we realized that
Art doesn’t obey objectivity, it thrives on (personal) interpretation.
Trying to “A/B test” scenes or endings didn’t work. The feedback was all over the place.
But, once we defined a clearer target audience, it became easier to decide which voices to listen to.
Now we’re in the promotion stage, again thinking like a startup: using our network, creative outreach, and unconventional channels to get the word out.
Our movie is a fictional story inspired by real experiences and not the glossy "founder journey" version.
Here is the trailer on Youtube, would love to hear what you think of the trailer (good or bad).
https://www.youtube.com/watch?v=Ottt_qTr2No
Thanks for reading, any feedback is genuinely appreciated.

value: Show HN: I Made My First Movie About a Tech Startup for $2,045 [video]

author: andreas-schrade


value: mstipetic

value: Show HN: Reynote.com AI couples therapy that helps you understand your partner

author: mstipetic


value: Jabbs

value:
This press release describes the product (which you can use for free with promo code "ULAUNCH").
The app gathers job listings directly from company websites (different than aggregators that collect directly from ATS's). So there are about ~30% of 300k+ jobs listed not found on paid sites like Indeed.
This job search site is geared towards job seekers (rather than employers). Would love any feedback

value: Show HN: Unlisted Jobs

author: Jabbs

title: Show HN: Unlisted Jobs


value: mkagenius

value: Show HN: OpenSkills - Run Claude Skills Locally Using Any LLM

author: mkagenius


value:
Hello HN!
I just published my first npm library as a small way to give back to the open source community.
I built `spoilerjs`, a lightweight web component that lets you hide text with an animated spoiler effect. Think Reddit spoilers, but with more flair! It works with plain HTML, React, Vue, or Svelte, and you can customize attributes like particle density, velocity, and scale. The effect is totally inspired by the Telegram app!
Demo: https://spoilerjs.sh4jid.me
NPM: https://www.npmjs.com/package/spoilerjs
GitHub: https://github.com/shajidhasan/spoilerjs
I'm sure there are probably some bugs and rough edges, but I'd love to hear your feedback!
Thanks!

value: Show HN: spoilerjs – Reddit-style spoilers with particle animations


value:
I just shipped something I’ve needed for years - a more efficient email client.
I finally built Omnia OS because my inbox turned into a landfill of AI-generated noise. If you're going to email me going forward, I suggest including a more compelling subject and opening line, otherwise all emails from unknown people will not make it to my inbox. AI draft-suggestion tools never solved the real problem: finding the messages, files, or company I actually need to follow up with. After securing AI systems for a living, I know how easy it is to weaponize prompt injection, so bolting AI onto email without redesigning the core experience felt reckless. First, we need to separate trusted from untrusted senders, then decide whatever touches automation.
Omnia OS is the email client I now rely on: New senders/orgs are isolated until you approve them, so domain spoofing means you will not make it to the inbox anymore, because it will be isolated as a new organization that needs approval.
Catch-up view shows everything that happened since you last checked:
- meetings, threads, urgent items.
- Every company you work with has its own space for contact lists, file management, and basic company intel, so you stop searching through old chains.
- Mass unsubscribe and delete emails
Coming back to work on Monday or a long weekend used to take half a day reviewing emails. Now you see what matters, act, and move on.
It's free to use as a desktop app for your email client on MacOS.
Install from https://omniaos.co
*Since this is my side project, the initial build only supports MacOS and Gmail. Happy to collaborate on new capabilities.

value: Show HN: Omnia OS, the Most Efficient Email Client Without AI


value: paulmbw

value:
Hi HN!
We're introducing Fibre - secure file uploads for Intercom.
Fibre came out of a real pain point we hit using Intercom for support.
We needed customers to upload sensitive docs all the time - proof of address, ID verification, business documents etc. However, customers kept pushing back - they didn't feel comfortable sending sensitive files to Intercom. Not forgetting the privacy and GDPR challenges, and the 100MB limit for file uploads.
So what happened? Everyone just fell back to email. Which made things worse - unencrypted attachments flying around, compliance nightmares, documents scattered across channels.
That's why we built Fibre. The idea is simple: files go straight from the customer's browser via Intercom Messenger to your storage (Google Drive, S3, or Azure). Nothing touches our servers or Intercom's. Customers stay in Messenger where the conversation already is, you get documents exactly where you need them.
We're currently in beta - if you want to try it out, simply sign up to the platform and DM me requesting an invite code - this will allow you to try out the product free of charge for 7 days.
It's early days, but we're excited about where this is going. Next up: AI-powered document understanding to help ops teams triage faster.
Would love to hear what you think, especially if you're dealing with document collection in your support workflow!

value: Show HN: Secure File Uploads for Intercom

author: paulmbw


value: jorgeoguerra

value:
Hey HN! We’re Jorge and Will from Lotas (https://www.lotas.ai/), and we’ve built Erdos, a secure AI-powered data science IDE that’s fully open source (https://www.lotas.ai/erdos).
A few months ago, we shared Rao, an AI coding assistant for RStudio (https://news.ycombinator.com/item?id=44638510). We built Rao to bring the Cursor-like experience to RStudio users. Now we want to take the next step and deliver a tool for the entire data science community that handles Python, R, SQL, and Julia workflows.
Erdos is a fork of VS Code designed for data science. It includes:
- An AI that can search, read, and write across all file types for Python, R, SQL, and Julia. Also, for Jupyter notebooks, we’ve optimized a jupytext system to allow the AI to make faster edits.
- Built-in Python, R, and Julia consoles accessible to both the user and AI
- Plot pane that tracks and organizes plots by file and time
- Database pane for connecting to and manipulating SQL or FTP data sources
- Environment pane for viewing variables, packages, and environments
- Help pane for Python, R, and Julia documentation
- Remote development via SSH or containers
- AI assistant available through a single-click sign-in to our zero data retention backend, bring your own key, or a local model
- Open source AGPLv3 license
We built Erdos because data scientists are often second-class citizens in modern IDEs. Tools like VS Code, Cursor, and Claude Code are made for software developers, not for people working across Jupyter notebooks, scripts, and SQL. We wanted an IDE that feels native to data scientists, while offering the same AI productivity boosts.
You can try Erdos at https://www.lotas.ai/erdos, check out our source code on our GitHub (https://github.com/lotas-ai/erdos), and let us know what features would make it more useful for your work. We’d love your feedback below!

value: Show HN: Erdos – open-source, AI data science IDE

author: jorgeoguerra


value: wofo

value: I'm working on a tool that will probably involve querying JSON documents and I'm asking myself how to expose that functionality to my users.<p>I like the power of `jq` and the fact that LLMs are proficient at it, but I find it right out impossible to come up with the right `jq` incantations myself. Has anyone here been in a similar situation? Which tool / language did you end up exposing to your users?

value: Show HN: JSON Query

author: wofo

title: Show HN: JSON Query


value: mirodosta

value:
Hi, I’ve been developing a set of free CSS tools for web designers.
Goal is to make small and useful tools that don’t rely on CSS frameworks.
I’d love your feedback on the design and any missing features.
You can try it here: https://cssify.co/
No login.
Thanks for checking it out!

value: Show HN: I built a free tool to generate vanilla CSS code easily

author: mirodosta


value: sfeizi

value:
What
relai-sdk is an open-source toolkit for making AI agents reliable via a complete learning loop:
simulate → evaluate → optimize.
Why
Agent runs are stochastic; tool-calls fail; hard to reproduce, measure, and fix at scale. It’s also hard to align behavior with goals across output quality/format, cost, and latency. We need a loop that integrates user feedback and LLM evaluators directly into the agent code (prompts, configs, models, graphs) without overfitting.
How
- Simulation: LLM personas, mocked MCP servers/tools, synthetic data; can condition on real traces
- Evaluation: code-based + LLM-based evaluators; turn human reviews into optimization-ready benchmarks
- Optimization with Maestro: tune prompts, configs and even agent graph for improved quality, cost and latency
Try it
pip install relai
GitHub: https://github.com/relai-ai/relai-sdk
Docs:   https://docs.relai.ai/
(2-min overview: https://youtu.be/qKsJUD_KP40)
Looking for feedback on
- Where graph-level suggestions help (beyond prompt tuning)
- Evaluator signals you rely on for reliability (and what we’re missing)
- Simulation setups/environments you’d want out of the box
Notes
Founder here. Happy to share internals, tradeoffs, and limitations.
Works with LangGraph / OpenAI Agents / Google ADK /  etc. SDK Apache-2.0 license.

value: Show HN: Relai-SDK – simulate → evaluate → optimize AI agents

author: sfeizi


value: quadtree

value:
I built a new kind of voter guide you can read directly or explore conversationally with AI. It's a prototype with California's Proposition 50 (special election Nov 4) as the test case.
For pragmatic reasons, it uses a Custom GPT for the AI (direct API integration is currently cost-prohibitive at scale for a public-service project). Assume better AI integration scenarios in the future (browser side-panel, better API economics, etc). But the more fundamental concept is, any integration scenario will need a highly curated, issue-specific knowledge source (the guide content and format).
Would love feedback on the content format (organization, depth, balance), overall concept, and user experience.
Other context for those interested...
Audience: People who want to think through issues for themselves at reasonable cost to their time and sanity.
Problem: Public debate is dominated by advocacy rhetoric—facts twisted to fit narratives, nuance lost to slogans. No one enjoys sifting through that noise for signal. And AI assistants trained on (or searching) the discourse can end up echoing the distortions, or diluting valid arguments along with invalid ones while attempting balance.
Approach: Provide highly curated, balanced, and verified content for informed decision-making. Structure content both for people to read and for their AI assistants to use conversationally. Prompt the AI for strict adherence to guide content in presenting arguments and key facts.

value: Show HN: A new approach to voter guides (human and AI) – CA Prop 50 example

author: quadtree


value: Show HN: LinkPatrol – Free merchant-agnostic tool to find broken affiliate links


value: merge-conflict

value:
GAC is a tool I built to help users spend less time summing up what was done and more time building. It uses LLMs to generate contextual git commit messages from your code changes. And it can be a drop-in replacement for `git commit -m "..."`.
Example:

  feat(auth): add OAuth2 integration with GitHub and Google

  - Implement OAuth2 authentication flow

  - Add provider configuration for GitHub and Google

  - Create callback handler for token exchange

  - Update login UI with social auth buttons

Don't like it? Reroll with 'r', or type `r "focus on xyz"` and it rerolls the commit with your feedback.
You can try it out with uvx (no install):

  uvx gac init  # config wizard

  uvx gac

Note: `gac init` creates a .gac.env file in your home directory with your chosen provider, model, and API key.
Tech details:
14 providers - Supports local (Ollama & LM Studio) and cloud (OpenAI, Anthropic, Gemini, OpenRouter, Groq, Cerebras, Chutes, Fireworks, StreamLake, Synthetic, Together AI, & Z.ai (including their extremely cheap coding plans!)).
Three verbosity modes - Standard with bullets (default), one-liners (`-o`), or verbose (`-v`) with detailed Motivation/Architecture/Impact sections.
Secret detection - Scans for API keys, tokens, and credentials before committing. Has caught my API keys on a new project when I hadn't yet gitignored .env.
Flags - Automate common workflows:

  `gac -h "bug fix"` - pass hints to guide intent

  `gac -yo` - auto-accept the commit message in one-liner mode

  `gac -ayp` - stage all files, auto-accept the commit message, and push (yolo mode)

Would love to hear your feedback! Give it a try and let me know what you think! <3
GitHub: https://github.com/cellwebb/gac

value: Show HN: Git Auto Commit (GAC) – LLM-powered Git commit command line tool

author: merge-conflict


value: dr-j

value:
Hi HN! I’m Johan. I built Dlog, a journaling app with an AI coach that tracks how your personality, daily experiences, and well-being connect over time. It’s based on my PhD research in entrepreneurial well-being.
Edit: here's a video demo so you can see it before downloading: https://www.youtube.com/watch?v=74C4P8I164M - it's unvarnished but I'm told that's how people like it here :)
How Dlog works
- Journal and set goals/projects; Dlog scores entries on-device (sentiment + narrative signals) and updates your personal model.
- A built-in structural equation model (SEM) estimates which factors actually move your well-being week to week.
- The Coach turns those findings into specific guidance (e.g., “protect 90 minutes after client calls; that’s when energy dips for you”).
- No account; your journals live locally (in your calendar). You decide what, if anything, leaves the device.
The problem
- Generic AI coaches give advice without understanding your personality or context.
- Traditional journaling is reflective but doesn’t surface causal patterns.
- Well-being apps rarely account for individual differences or test what works for you over time.
What my research found (plain English)
In my PhD I modeled how Personality, Character, Resources, and Well-Being interact over time. The key is latent relationships: for example, Autonomy can buffer the impact of low Extraversion on social drain, while time/energy constraints mediate whether “good advice” is actionable. These effects are person-specific and evolve—so you need a model that learns you, not averages.
The solution
Dlog pairs on-device journaling analytics with an SEM that updates weekly. You get a running estimate of “what moves the needle for me,” and the Coach translates that into concrete suggestions aligned with your goals and constraints.
Early stories (anonymized from pilot users)
- A founder saw energy dips clustered after external calls; moving deep work to mornings reduced “bad days” and improved weekly mood stability.
- A solo designer’s autonomy scores predicted well-being more than raw hours worked; small boundary changes (client comms windows) helped more than time-tracking tweaks.
Tech & security
- Platform: macOS (Swift/SwiftUI). Data: local storage + EventKit calendar for entries/timestamps.
- Analytics: on-device sentiment + narrative features; SEM computed locally; weekly updates compare to your baseline.
- AI Coach: uses an enterprise LLM API for reasoning on derived features/summaries. By default, raw journal text does not leave the device; you can opt-in per prompt if you want the Coach to read a specific passage.
- Why 61 baseline variables? The SEM needs multiple indicators per construct (Personality, Character, Resources, Well-Being) to estimate stable latent factors without overfitting; weekly check-ins refresh those signals.
What I’ve learned building this
- Users value clarity with depth: concise recommendations paired with focused dashboards, often 5–10 charts, to explain the “why” and trade-offs.
- Cold start matters: a solid baseline makes the first week of insights credibly useful.
- Privacy UX needs to be explicit: users want granular control over what the Coach can read, per request.
I’m looking for feedback on:
- Onboarding (baseline survey and first-week experience)
- Coach guidance clarity and usefulness
- Analytics accuracy vs. your lived experience
- Edge cases, bugs, and performance
Download: https://dlog.pro
If you hit token limits while testing, email me at johan@dlog.pro
Background
PhD (Hunter Center for Entrepreneurship, Strathclyde), MBA (Babson), BComm (UCD). I study solo self-employment and well-being, and built Dlog to bring that research into a tool practitioners can use.
Note: The Coach activates after your first scored entry. If you haven’t written one yet, you’ll see a hold state—add a quick journal entry and it unlocks.
Appearance: On a few Macs the initial theme can render darker than intended. If you see this, switch to Light Mode as a temporary workaround; a fix is incoming.
Edit: For general users it's free for 14 days with 10K free tokens; then its 1.99 per month at the moment.
However, for HN readers that DM me or email me with the email they register with, I'll give a free perpetual license so there's no monthly fee; and add 1 million tokens.

value: Show HN: Dlog – Journaling and AI coach that learns what drives wellbeing (Mac)

author: dr-j


value: nadermx

value:
Hey HN,
This project has been a few years in the making.  I've been doing standup for a bit and felt there where some things that I wanted to have a place for.
You can upload clips, post links, post jokes, create events, schedule events, ask to be a comedian on events, follow people, etc.
Let me know what other features are missing or think or wish you could add.
Nadermx

value: Show HN: Standup.net – All your Stand Up Comedy needs or wants

author: nadermx


value: tylertreat

value:
Meals You Love is a meal planning app that creates weekly meal plans tailored to your tastes and dietary preferences. It integrates with Kroger and Instacart's APIs so you can add your meal plan groceries directly to your cart. You can also import your own recipes to include alongside AI suggestions.
I originally built this to help my wife with meal planning and grocery shopping. We were always struggling to decide what to make and inevitably forgot ingredients. Most meal planners felt too rigid or generic, and few handled the grocery side well (or at all). We've also used meal kits like Home Chef in the past but they end up being quite expensive and produce a comical amount of packaging waste, plus you still wind up needing to purchase groceries anyway. In all honesty, I also wanted an excuse to try building something "real" using AI and to see if it could be used in an actually useful manner.
Would love feedback from anyone interested in food, meal planning, or product design!
Tech stack:
- Cloud Run
- Firestore
- Vertex AI / Gemini
https://mealsyoulove.com

value: Show HN: Meals You Love – AI-powered meal planning and grocery shopping

author: tylertreat


value:
Hey HN!
I built vetr.is, a cloud hosting in Iceland focused on privacy and renewable energy.
*What it offers:*
- Iceland location with 100% renewable energy
- AMD Ryzen CPUs + NVMe storage
- Hourly billing, no contracts
- Price-locked subscriptions
- Tor-friendly interface
*Pricing:* Starting at €5/month for 1 CPU, 0.5GB RAM, 10GB storage. Pay only for what you use.
https://vetr.is
Happy to answer questions!

value: Show HN: Vetr.is – Privacy-First Cloud in Iceland


value: AndreiBargan

value:
Hi HN,
While renovating my apartment, I was keeping track of all my tasks and meetings — things like “Buy paint” or “Meet the designer on Tuesday at 1PM” — in Apple Notes. And there were a lot of them. Anyone who’s done a renovation knows how endless those lists get.
Note-taking or to-do apps are great because it’s super easy to quickly jot down many small tasks.
But they lack important things: notifications, day-based structure, sharing tasks or meetings with others so they appear in their calendars.
Traditional calendar apps do the opposite — they’re more interactive: you can set notifications, view by day, invite participants, etc.
But they’re painful when you just want to add many simple tasks. Those “add event” forms feel huge and clunky.
So we thought — why not combine the ease of note-taking apps with the interactivity of calendars?
That’s how the idea for Mainn.app was born — a simple yet powerful calendar reimagined from scratch, with features you won’t find anywhere else.
Key ideas:
- On any day, just place the cursor and add as many simple items as you want — “Fix the bike”, “Buy groceries” — no heavy forms, just type like in a to-do app.
- Want a timed event? Type “Gym 11” and pick 11:00 AM/PM from quick suggestions.
- Need a meeting like “Discuss design 11:00 Alex”? Choose a contact from your phonebook shown on suggestion panel while editing the event!
Alex will automatically get an SMS invite, and once he installs the app, the event instantly appears in his calendar.
Most people don’t know each other’s emails anymore, but everyone has phone numbers — so we built the calendar around that.
- You can contact participants directly via their preferred messengers (Signal, Telegram, WhatsApp, etc.).
- Add a location — and with one tap, launch maps or a taxi app to get there. Works for all participants.
- We also have classic to-do and shopping lists, and you can mark them as “Always show today” — so your daily agenda always includes your lists.
- Share lists with your spouse or friends from your contacts — they’ll get an SMS invite too, and once they install the app, you’ll have a shared list in real time.
- Google Calendar integration (currently read-only).
And the most fun — a Social Hub where you can:
- Check in at places,
- Create invites for sports, games, or activities with friends at a chosen location (via SMS invites),
- Make public invites — e.g. “Looking for a tennis partner nearby” — so people around you can join.
- Those who join get the event in their calendar and can chat or navigate there instantly.
- You can also favorite invites and revisit them later — all accessible right in the calendar.
Right now, it’s a lightweight but capable calendar for personal tasks + a social hub for planning real-life activities.
Next, we want to add professional features — a booking module like Calendly, but designed for freelancers and small service providers (stylists, coaches, electricians, etc.) where they can set working hours, manage bookings, and even promote their services in the Social Hub.
We already have designs and part of it implemented.
We’re a small team (3 developers and a designer) working part-time, so there are still bugs and things to polish — please don’t judge too harshly :)
We've got tons of ideas and if we had funding, we could go full-time and build a lot more monetizable services — we see huge potential here.
Would love to hear your feedback!
Thanks to everyone who read till the end!
— Andrew

value: Show HN: Mainn – a calendar that merges tasks, meetings, events, and social life

author: AndreiBargan


value: janpmz

value:
Hey HN,
I’ve built Clarisu, an app that generates short educational podcasts from any topic you give it: https://clarisu.com
It started from https://pdftomp3.com, a tool I made to turn PDFs into audio. I mostly used it to listen to AI papers, but I still had to download the MP3s to my phone. So I made an app instead!
Now you just enter a topic in a textbox, and it builds a “podcast episode” with paragraphs and chapters. It has a “Clarify” button which goes deeper into a topic. This is where the name comes from :) I think I’ve learned a lot of new things by listening to my own episodes!
Next up: adding PDF uploads directly into the app.
I would love your feedback!
Android: https://play.google.com/store/apps/details?id=com.jbuild.und...
iOS: https://apps.apple.com/us/app/clarisu-understand-app/id67511...

value: Show HN: Clarisu – Create educational podcasts

author: janpmz


value: Hello. This is an updated version of my TrueType rasterizer - now it has few solid color modes, gradient color modes and underline functionality. Also, it's a C project now (it started as a C++). I wanted to implement precomputed glyphs (and maybe strings) in this version but this will wait for some time, as this is a side project for me and this functionality is not that trivial as it may sound at first.

value: Show HN: TrueType Rasterizer

title: Show HN: TrueType Rasterizer


value: tuxxness

value:
Just got the first open testing release approved on google play store for a minimal android launcher i'm developing.
I recently switched to a phone with an e-ink display and was missing features in current minimal launchers, so i decided to make my own.
Would love to hear your opinion, improvements that could be made or features to change/add.
Thanks!
=== Links ===

    - https://play.google.com/store/apps/details?id=com.kolktech.mnml
    - https://www.youtube.com/watch?v=6gcF9lSDBPY (video demo)

=== Current Features ===

    - Multiple rows of apps
    - Material Font icons can be set as app names
    - When reducing or increasing apps you can re-order and select which apps to keep (this is missing from a lot of minimal launchers imo)
    - App shortcuts (long press on an app to show that app's own shortcut menu)
    - Backup your launcher settings with Export/Import
    - App drawer list (swipe up)
    - You can hide apps from the app list
    - You can uninstall apps from the app list
    - App rows can have their size individually set.

=== Planned features ===

    - Background images or static colors
    - Show weather information
    - Screen time usage information
    - Possibly some limited widgets
        - google search bar on the bottom?
        - Notes on the main screen
    - App folders (so you can assign multiple apps to one slot)
    - App slot assignment other than apps
        - URL's
        - Files
        - Intents
        - Contacts
        - etc.
    - More gestures that you can assign actions to
        - 3 or 4 finger swipe
        - triple tap
        - pinch zoom
        - etc.
    - Find contacts and files in the app list
    - Localization

value: Show HN: MNML – Android Launcher (Open Testing Release)

author: tuxxness


value: YourOldNemesis

value:
Smart contract escrow on Base for safe USDC transactions. Deploy time-locked contracts with a few clicks - funds release automatically at payout time unless dispute is raised.
Key features:
- Verified and audited contracts on Base
- Auto-arbitration: when both parties agree on refund amount, funds distribute instantly
- Non-custodial: users own their contracts, I provide infrastructure
- 1% fee (vs 2-3% traditional escrow), gasless for users
Two implementations:
- P2P:              https://app.instantescrow.nz          (eg. NFT trades, freelance, vehicle sales)
- Merchant plugins: https://app.instantescrow.nz/plugins  WordPress/Shopify checkout integration
I built this because crypto needs safe transaction rails. Traditional escrow economics don't work at scale - smart contracts make 1% viable.
I'm looking for feedback from first customers/merchants. Test with $0.001 USDC (fees waived). Demo videos on plugin site.

value: Show HN: Instant escrow for crypto purchases with automated dispute resolution

author: YourOldNemesis


value: nolansym

value: Show HN: AI SDK Agents – Shadcn but for the AI SDK

author: nolansym


value: helenapankov

value: Show HN: Action Engine — An API/Agent Buildkit Putting Flexibility First

author: helenapankov


value: homayonam

value: "It's an open-source [Your Tool Type]. We offer a generous, feature-complete free tier for individual use. We are gathering feedback on the initial launch and would love your thoughts on the approach!"

value: Show HN: My free tool that eliminates [pain point]

author: homayonam


value: kyrylo

value: Show HN: Coffee world rush – drink coffee for your country

author: kyrylo


value: jtechy

value:
Hi HN, I’m the founder of Palm Trees AI, and I’m excited to share what I’ve been building. Palm Trees AI is a Software Robot Network (SRN) – a platform of AI-powered personas you can use for different tasks (coding help, legal Q&A, real estate analysis, medical info, entertainment, etc.) with one account.
The idea came from my frustration using separate AI tools for different needs and having multiple ideas for AI applications. I wanted a unified home for multiple specialized AI agents with a consistent, user-friendly UX.
What It Is
Palm Trees AI is a curated library of AI personas, each tuned for a specific domain. Rather than one general-purpose AI trying to do everything, each persona focuses on its niche – a coding mentor, legal advisor, or real estate analyst, for example. All share the same design and hub, so you can switch between them easily without juggling multiple apps or logins.
Unified Credits (Gasergy)
Palm Trees AI runs on a single credit system called Gasergy – short for “gas/energy,” the shared fuel for all personas. You get a monthly pool of credits to spend on any AI-powered action. For example, you could use 60 credits with the coding persona and the rest with a legal or real estate bot. Non-AI actions (like browsing free content) cost nothing, and each AI action clearly shows its Gasergy cost upfront.
This unified model eliminates the need for multiple subscriptions or credit systems. Gasergy plans are currently 50% off during pre-launch.
First Persona – HTML Master
The first persona, HTML Master, is a friendly coding tutor that combines an interactive HTML course with an AI companion. The course is free to explore; using the AI for debugging, explanations, or examples consumes a small amount of Gasergy.
HTML Master will be fully released within one week. You can join the waitlist now on palmtreesai.com
 and receive free Gasergy credits when it launches.
Coming Next
Immediately after HTML Master, I’m rolling out JavaScript Master and CSS Master to complete the front-end trio.
After that, the SRN will expand into other domains like legal, real estate, medical, and entertainment. For instance, a legal persona might help explain contract clauses (not a lawyer replacement, but an assistant), and a medical persona could summarize articles or answer general health questions with disclaimers. The goal is to have an ever-growing network of domain-specific AI helpers that feel coherent and connected.
Build Your Own Persona
We’re also developing a Custom Persona Builder, letting users design their own AI personas by defining tone, tools, and behavior guardrails. You’ll be able to create private or shared personas for your team or the public. And we also plan for the builders to be able to make money off their AI creations. This feature is in active development, and early testers will be invited from the waitlist.
Try It Out & Feedback
The SRN main site is still in pre-launch until more personas are available, but the platform is live now. You can sign up once for access to everything, join the HTML Master waitlist, and purchase a Gasergy plan early which is 50% off on pre-launch.
I’d love your honest feedback:
– Is this concept useful to you?
– Which personas would be most valuable?
– What would make the UX or pricing better?
I know “AI for X” is a crowded space, so I’m especially interested in skeptical takes. Palm Trees AI is a labor of love built around the belief that specialized, well-scoped AIs are more useful than general ones when you’re learning or solving real-world problems.
Thanks for reading – and for any feedback the HN community can share.

value: Show HN: Palm Trees AI – A Software Robot Network of Specialized AI Personas

author: jtechy


value: This community helps Indian tech builders (including NRIs) and solo makers get feedback, beta testers, mentorship, and support.

value: Show HN: Feedback and Beta Hub for Indian Tech Builders and Solo Makers


value: HardikVala

value:
hey hn, wrote a python library for myself to visualize tensors. Makes learning and debugging deep learning code so much easier. Works seamlessly with colab/jupyter notebooks, and other python contexts. It's built on top of the graphics backend, chalk (https://chalk-diagrams.github.io/).
why?
Understanding deep learning code is hard—especially when it's foreign, because it's hard to imagine tensor manipulations, e.g. `F.conv2d(x.unsqueeze(1), w.transpose(-1, -2)).squeeze().view(B, L, -1)` in your head. Printing shapes and tensor values only get me so far. tensordiagram lets me quickly diagram tensors.
Other python libraries for creating tensor diagrams are either too physics and math focused, not notebook-friendly, limited to visualizing single tensors, and/or serve a wider purpose (so have a steep learning curve).

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