https://oposs.oetiker.ch/thinfloe

I used yt-dlp and ffmpeg GUIs a lot and I was tired that every app has a lack of something, no option to convert for Discord here, no download feature here, no way to select specific segments to download here. And there are many of other things missing in this apps, too.

So I built Pulsar. App that merges three aspects: downloading, converting and compressing. And has every major option. You can choose format, quality, bitrate, codec, download thumbnail and subtitles, skip sponsors, compress by CRF, size or percent and many many other features which other projects do not have within a single application.

What it have?

• Downloader -> choose video/audio format, quality, codec, download a time range, skip sponsors, grab subtitles, embed metadata/thumbnail/subs, use browser cookies, set custom filename.

• Converter -> Convert video, audio, image, font and archive and set your bitrate or codec change before you start. 55 total formats supported.

• Compressor -> compress by percentage, target file size or quality (CRF) and see the estimated output size before you start.

• Queue -> add as many jobs as you want and start everything at once, with thumbnails and progress.

• Presets -> for each tool, so you don't have to re-pick the same settings every time

• Light/dark theme and multiple languages (translations are in TOML, so adding one is easy)

Why another one?

Most tools I found do just one of these things. Pulsar is meant to cover the whole "get a file, change it, make it smaller" workflow without ads, accounts or uploads to the server. The whole app runs on the efficient Rust language and small Pulsar-Bridge (yt-dlp wrapper that max out its performance) instead of heavy, slow Electron that many of these apps have today.

GitHub: https://github.com/FuzjaJadrowa/Pulsar

I have a bad habit. I start a course with a lot of energy, a YouTube playlist, a Udemy course, a PDF book, and after a week I stop. I forget where I was, which video, which page. And nobody notices, so nothing pushes me to go back.

So I built inPace with Claude Code. It's free, open source, and everything stays on your device.

What it does

- Put any course in one place: a folder of videos (even if it's messy, it sorts them), a PDF book (every chapter becomes a module), a YouTube playlist, or a course from the free library

- It remembers the exact second of the video and the page of the book where you stopped

- Pick someone you trust to check your progress: a friend, a sibling, a mentor. When you finish a module you send them a "milestone" with your work, your quiz score and an explanation in your own words. They approve it or not

- Milestones are signed with a key on your device, so you can't edit them later or fake the date

- A free library with 52 courses and 20 learning paths (Python, JavaScript, C#, Git and GitHub Actions, Docker, ML, and more), with written lessons and optional videos from freeCodeCamp and Harvard

- Reminders, notes on any line of a lesson, races with friends, and a little turtle called Tempo who grows a garden while you study

How Claude helped

- Claude Code was my pair programmer for the whole app: the Python server, the pages, the Android app, the release pipeline. I decided what to build and how it should feel, Claude wrote most of the code with me, and I reviewed and tested every change

- Tests were the key. Every feature came with tests, and now there are 237 of them that run on every push on Windows, Mac and Linux. When Claude broke something, a test caught it before a user did

- I asked Claude to test like a real user: open the app at phone size, take screenshots, and look at them. That's how we found the welcome tour was broken on phones

- Claude also wrote the free courses in the library. I made it run every code example, check every YouTube link, and check its own facts. It even caught two wrong facts in its own first draft

- The app itself works with Claude too: "Make a course with AI" gives you a prompt, you paste it into Claude, paste the answer back, and you get a full course with lessons, tasks and quizzes. No API key and no cost

It runs on Windows, Mac, Linux and Android. No account, no server, no ads.

Download: https://mahmoudyosrimahmoud13.github.io/inPace/

Code: https://github.com/mahmoudyosrimahmoud13/inPace

It's my first post here, so any feedback is welcome, good or bad. And if you try it, tell me what was confusing in the first 5 minutes, that's what I'm fixing next 🙏

built a random forest classifier while learning classical machine learning and model deployment

the project classifies 7 dry bean varieties using 16 numerical features

what's included:

• 100 trees with entropy splitting

• 5-fold cross validation: 92.54%

• test accuracy: 92.06%

• GridSearchCV for hyperparameter tuning

• FastAPI REST API and HTML/CSS interface

• Docker and automated pytest tests

• confusion matrix and feature importance plots

the README includes reproducible training instructions and evaluation results

github: https://github.com/Vaibh37/dry-bean-random-forest

would appreciate technical feedback. if you find it useful, consider starring the repo ⭐

Hey everyone, I'm the developer of Opensteer. I built it because I wanted a personal agent to work locally on my computer with all my existing apps, accounts, and files already on my Mac, and I wanted it to work with different models, including the subscriptions you already pay for.

Opensteer is free and open-source. You can connect your phone through our mobile app and your other computers to control your agents remotely. It also streams your browser and apps directly, so you can basically work on your phone on the go.

We also decided to build a built-in browser so you can use Opensteer as your main browser and have your agents collaborate on all your work. It can of course use your computer to work in your desktop apps too. It's super easy to get set up and started. No need to spend hours integrating everything.

The latest Mac download (0.1.638 beta) is signed and notarized by Apple.

AI disclosure: AI tools helped build Opensteer! And I built a lot of Opensteer in Opensteer. Thanks Claude, GPT Sol/Astra, and Muse Wonder (surprisingly)

GitHub: https://github.com/steerlabs/opensteer
Mac download: https://github.com/steerlabs/opensteer/releases/download/v0.1.638-insider/Opensteer-mac-arm64.zip

Feel free to try it out, and would appreciate any feedback. Thanks!

I got tired of a certain app drifting toward commercialization, so I re-created my own version.

Its main selling (it's free, heh) points are:

- Minimal interface. The toolbar and window borders can both be disabled. Keyboard is enough to control most of the app. F1 opens the list of keyboard shortcuts. Drag-and-drop images or folders straight into the app.

- Small memory footprint.

- Portable. It stores its settings file into the same folder the executable resides, nor does it write any configurations anywhere within Windows/user paths, or registry.

- Support for JPEG, PNG, WebP, TIFF, BMP, GIF, ICO, QOI, DDS, HDR, TGA, and Netpbm images. Animated GIFs play automatically. Not the most extensive support, but enough for a basic user.

- Zoom, pan, and rotate images. Embedded EXIF orientation is applied automatically. Different modes for zooming (Fill, Fit, Fit Height, Fit Width, Lock Size, Auto).

- Run slideshows with fixed or random intervals, shuffle, repeat, and an option to let animated GIFs play through at least once.

- A playlist view with sorting by name, or shuffling. Drag and drop the files to change the order as you like. Playlists can be saved and loaded into files.

- Rename, copy, move, and recycle files or reveal them in Explorer.

- Smooth image browsing, thanks to a caching system.

Windows only, sorry. The app uses Windows APIs, so compiling for other platforms would require some rewriting.

MIT Licensed.

AI Disclosure

The app was developed with the aid of several AI models, including OpenAI's GPT-6 Astra, GPT 6.1 Sol, Mistral's Mistral Large 4, Z.ai's GLM 5.3 and GLM 5.3-Flash, and Deepseek's DeepSeek-V4.1-Flash.

Hope someone enjoys it. Let me know if you do!

RustedGlass (GitHub)

The demo is one real Claude Code session on an Android emulator, shown at 15x. I asked for a large pepperoni pizza from the Domino's nearest Leicester Square. Claude worked through the real dominos.co.uk checkout in six and a half minutes. At "Buy with GPay", phonedriver held the tap and asked me. I said no, and nothing was charged.

What it is

phonedriver is an MCP server and a CLI. The agent gets the screen as a short numbered text list, taps by number, types and swipes, and gets back only the lines that changed. It works with Claude Code, Codex, Cursor or any MCP client.

How it works

• Android: it pushes a small helper over adb and starts it as the shell user, the way scrcpy does. No root, nothing installed on the phone, no accessibility service to switch on.

• iPhone: it uses its own XCTest runner.

• Speed: reading the screen takes 13 ms, against 2.2 s for adb shell uiautomator dump (median of 50 runs on an emulator; the method and the raw data are in the repo).

• The Pay check: it asks before it taps Pay, Place order, Transfer or Delete account. The model cannot answer that question for you.

It also found two bugs I hid in a signup form in 49 seconds, and wrote the steps to reproduce them.

Where it is weak

• iPhone needs a Mac with Xcode.

• The Pay check reads button labels, so it misses a button that is only an icon.

• The real devices I have tested are a HONOR X8, two iPhones and an iPad.

Rust, AGPL-3.0, no account, no telemetry. Claude Code wrote nearly all of the code. The design decisions, and what I rejected, are logged in docs/decisions.md.

claude mcp add phonedriver -- npx -y phonedriver mcp

https://phonedriver.dev
https://github.com/hridaya423/phonedriver

GitHub: https://github.com/lingdojo/kana-dojo

As someone who loves both coding and language learning (I'm learning Japanese right now), I always wished there was a free, open-source tool for learning Japanese, just like Monkeytype in the typing community.

Here's the main selling point: I added a gazillion different color themes, fonts and other crazy customization options, inspired directly by Monkeytype. Also, I made the app resemble Duolingo, as that's what I'm using to learn Japanese at the moment and it's what a lot of language learners are already familiar with.

Back in January, I even applied to Vercel's open-source software sponsorship program as a joke. I didn't seriously expect to win, and did it more out of curiosity, and yet my project somehow won.

Anyway. Why am I doing all this?

Because I'm a weeb.

Source: https://kanadojo.com

どうもありがとうございます

Hi everyone! I'm **Lennes Daniel Varela Poveda (LennesVP)**, an independent systems technician and Systems Engineering student, and I want to share **TREMEND Toolkit V3.3**, an open-source desktop suite built in Python (`CustomTkinter`) that unifies over 95 diagnostic, maintenance, networking, and defensive cybersecurity tools into a single responsive interface.

🔗 **GitHub Repository:** https://github.com/LennesVP/TREMEND

### 🛠️ What does TREMEND Toolkit V3.3 include?

* **🌐 Network & OSINT (31 Modules):**

* Autonomous network repair (Winsock, TCP/IP stack, DHCP forcing, and malicious proxy purge).

* **Cyber Teams Command Center (#31):** Live Purple Team simulator (`Attack <-> Defend`), Blue/Green Team SOC & firewall monitor, `crt.sh` subdomain exposure auditor, Yellow Team static code analyzer (SQLi, XSS, LFI, RAM tampering), and White Team ROE report generator.

* **Senior Password Hashing Lab (CyberChef style):** Demonstrates `hashlib.scrypt` + 128-bit CSPRNG Salt + constant-time `hmac.compare_digest` verification, plus Base64/Hex/Binary decoding.

* Multi-threaded TCP port scanner, Sniffnet traffic visualizer, Geo-IP OSINT radar (Leaflet dark-mode maps), and RFC 5322 email header Anti-Phishing analyzer (SPF/DKIM/DMARC).

* **🧹 Maintenance & Automation (20 Modules):**

* **4-in-1 File Automation Suite:** Organizes messy folders by type with 1-click Rollback/Undo, classifies invoices chronologically (`YYYY-MM`), renames hundreds of files with their real modification date (`YYYY-MM-DD_filename`) in under a second, and isolates duplicates via `SHA-256` hashing.

* Deep disk cleanup (including `Windows.old` removal, `%TEMP%`, Prefetch, and DISM/SFC kernel repair), dynamic Virtual Memory (`pagefile.sys`) calculator based on physical RAM, and a Browser Hygiene shield with anti-2FA session cookie purge.

* Real-time Panic Mode (`EmptyWorkingSet` RAM liberation) and interactive storage tree radar.

* **🖥️ Hardware Diagnostics & Forensics (21 Modules):**

* Heuristic Anti-Keylogger hunter (cross-references established TCP connections against `Authenticode` digital signatures), RAM Integrity Shield (forces Kernel `ASLR` + `DEP` and hunts memory injectors), Binary X-Ray analyzer (Magic Bytes, EXIF, Strings, SHA-256), and S.M.A.R.T. disk health reader.

* Native Windows Sandbox manager, PnP hardware error Auto-Dorker, and Chromium SQLite History Visualizer (renders an HTML5 Chart.js dashboard).

* **📦 Software & Technical Support (25+ Modules):**

* Deep Uninstaller & Leftover Hunter (scans `AppData` and Registry hives + online `winget` updater) and Pre-Format Software Cloner (exports/imports clean `.json` and `.csv` inventories).

* **USB Forensic Vaccine:** Removes write protection, rescues files hidden by shortcut malware, and immunizes `autorun.inf`.

* **Android ADB Optimizer:** Cleans gigabytes of hidden app caches and old thumbnails via USB without touching personal photos or chats.

* Native Windows AI OCR screen scanner (with 3x Lanczos upscaling), local AI background remover (`U-2-Net` / `rembg`), and a built-in Cognitive Voice Assistant.

**Author:** Lennes Daniel Varela Poveda (`LennesVP`)

I'd love to hear your technical feedback, ideas for V3.4, or any suggestions! If you find it useful, a ⭐ on GitHub helps a lot.

I built Nuvo, a free and open source (AGPL-3.0) music player. Linux is the main platform, Windows is supported, and the macOS build needs testers.

What it does:

- Plays YouTube, SoundCloud and local folders in one queue

- Synced lyrics, karaoke, and word timing on your own CPU with a local Whisper model

- Home mixes ranked on your machine from your plays and likes, with a reason next to each pick

- Imports playlists by link or from Spotify CSV, Soundiiz, TuneMyMusic, Google Takeout, M3U, XSPF and TXT

- Statistics with a listening history you can pause, export or delete

How it's put together: the Electron window (React) does the screens and playback, and a Rust daemon (nuvo-core) owns the library, ranking, imports, local files and lyrics. They talk over a unix socket with a per-launch token. The library is SQLCipher with the key in your system keyring, and the audio cache is encrypted too.

The lyric timing runs Whisper in pure Rust (GGML parser, mel spectrogram, encoder and decoder on gemm, DTW over the alignment heads), with no whisper.cpp and no GPU. The benchmark scripts are in scripts/bench/, and the README lists every run, including where Nuvo loses.

I build it alone and use AI coding tools; the design, the review and the tests are mine, and the tests are in the repo.

Download: https://github.com/Ziuziuk-Denys/Nuvo/releases/latest

Since I started working as an FDE I implemented a multi-agent workflow and working for multiple clients sometimes I forget to answer the conversation when it needs my input. I wanted a very simple solution, so I built this using the mac notifications for claude code. It's free and OS, would love to hear what you think and what other things could be included while keeping it minimal

You can find it here: https://github.com/robertodf99/hook-me-up

Happy to announce release of 2.11 version of JellyBox player.

For those who missed previous posts - JellyBox is a native free and OSS crossplatform music player for jellyfin and navidrome, including carplay and android auto apps. JellyBox includes spotify-like auto generated playlists, continuity(just like spotify-connect), relay(remote access without vpn) and many other QoL features that makes everyday usage more like you just use spotify or apple music

I continue my idea with these image-changelogs since it feels like easier to read than through a wall of text, and easier to highlight whats the most important

Downloads here https://github.com/avdept/JellyBoxPlayer/releases/tag/v2.11.1 or through landing page - https://jellybox.app/

Full changelog can be found here https://jellybox.updatify.io/posts/release-2-11-0

Hey everyone!

I built a local music player from scratch using Rust, Tauri 2, and React. I had some help from Claude and DeepSeek along the way.

I’d love for you to try it out and let me know what you think!
GitHub (Free & Open Source): https://github.com/arya8skrash/pulse-player

Every recipe site, every coupon site, half the docs portals I use — they all

disable selection, kill right-click, or hijack ⌘C. The text is right there on

the screen and I just want to paste it into my notes.

So I built a tiny macOS app. Press ⌥⌘S, drag a box over the text, and it's on

your clipboard. No window, no paste step, no "copy" button. ~0.35s from

releasing the mouse.

Take a look: https://github.com/sambitar/argos-panoptes

How it works: it grabs the selected region with screencapture, runs Apple's

Vision OCR on it locally, and writes the result to the clipboard. Vision runs on

the Neural Engine, so there's no server, no API key, no model download, and no

network code in the binary at all — you can check with `strings … | grep http`

and get zero hits.

Why not just use an existing tool?

- Browser extensions break when a site changes its DOM, and can't read text

drawn into <canvas> or embedded in images/video

- "Reader mode" fails on exactly the layouts that block copying

- Disabling JavaScript breaks the site along with the blocker

A screenshot sidesteps all of it. Pixels are pixels.

Free, MIT, source in the reply. I'd honestly like to know where it falls over —

I suspect multi-column layouts are the weak spot, and it's English-only right

now.

I'm the author, nothing to sell, no telemetry.

I just open-sourced my agentic product starter, the setup I use to build products end to end with AI agents.

What’s inside:

• iOS app, React + TypeScript web app and back office, .NET backend, landing site

• Agent-driven SDLC built on Matt Pocock’s skills and Anthropic’s AI-native SDLC playbook

• Dev / SYST / PROD environments, accessibility on by default, smart pipelines

It’s v1.0.0 and MIT licensed, built by human experience and AI together.

If it inspires you or is useful, a ⭐ and a share would mean a lot. Ideas, bugs or want to contribute? Open an issue or start a GitHub Discussion. I’d love to hear what you’d build with it.

🔗 https://github.com/erumkatzwan/agentic-product-starter

https://github.com/saqibsiddiq/QurbSpace

Hello Everyone,

Many of you may not know this but many of the people in this world does not have a laptop or computer they can use. Also most of the daily use computers are for just lightweight office work and most of them run windows. But all of the real servers run on linux. We cannot learn something properly without doing that. Also many may provide a webhosting platform but things like bot hosting doesn't come free.

Now to solve the problem I've built Rconsole. It gives linux development environment for free. It is practically a website built in Flask(python). It let's you run commands in the host shell. I highly suggest using render for it. Many of you may wonder about the restrictions in the render. To bypass that you will have the options to install a linux vm with the help of proot that provides almost full linux environment. The current options are arch, kali, debian, ubuntu, alpine.

For consistent data and storage that is also possible but to know about that you have to see the project yourself. It also has an inbuilt file editor, file Explorer. You can upload files/folder directly and also compress/decompress, see properties in there.

There a ton of features in there. So kindly check it out. It also let's you run free bots, websites and things like those.

Repo: https://github.com/Salehin-07/rconsole-ark

Docs: https://salehin-07.github.io/rconsole-ark/

Wiki: https://github.com/Salehin-07/rconsole-ark/wiki

Discussions: https://github.com/Salehin-07/rconsole-ark/discussions

Issues: https://github.com/Salehin-07/rconsole-ark/issues

Hey everyone,

I wanted to share a project I've been building called Gami.Fied. It is an open-source, self-hosted gamification engine that lets you add progression and reward systems to your web or mobile apps without having to build everything from scratch or send your users' data to a third-party paid service.

How it works Your app just sends basic activity events to the API (like lesson_completed or post_created), and the rules you set up in the dashboard automatically turn those events into XP, levels, streaks, achievements, or points.

What is included right now (v1.2.0)

• Rules engine: A visual editor to set up conditions and rewards, plus a simulator so you can test your rules before making them live.

• Progression: XP, custom levels, daily and weekly streaks (with automatic freezes), tiered badges, and multi-step challenges.

• Points & Reward Store: Virtual currencies with expiring points and a built-in store where users can redeem rewards or coupon codes.

• Leaderboards & Social: All-time, daily, weekly, and monthly leaderboards, weekly leagues with promotion and relegation, friend lists, and referral codes.

• Notifications & Integrations: In-app notifications, email reminders, push notifications, webhooks, and ready-to-use connections for Discord, Slack, Stripe, and GitHub.

• Admin Dashboard: Manage everything in one place with analytics, staging environments to test changes safely, and easy JSON export/import for your setup.

Try it out

• Website, Docs & Live Demo: https://gami.fied.cc (You can spin up a temporary workspace right in your browser without signing up)

• GitHub Repo: https://github.com/gami-fied/gami.fied

How it was built I started this project by hand and also used Claude to help speed up development across the codebase, dashboard, docs, and tests. You can run the whole thing on your own server using Docker Compose. The main server and dashboard are licensed under AGPL-3.0, and the TypeScript and React SDKs are MIT licensed so you can safely use them inside any closed-source app.

I am actively working on this as a solo maintainer, and more updates with new features are coming soon. If you check it out, I would love to hear your feedback or any ideas on what I should build next!

P.S. The integrations, webhooks and platform admin panel are disabled for the demo site. To test them, you need to host it yourself.

I've been building Relay, a self-hosted event-driven runtime for declarative apps.

The idea is to provide some of the developer experience I like from AWS Lambda and EventBridge, but on infrastructure you control.

One thing I didn't want was to force everything into the function model.

An app can use event-driven functions where they make sense and run something like FastAPI or Express.js as a persistent service when that's a better fit.

The goal isn't to reproduce AWS service by service.
It's to keep useful serverless and event-driven abstractions while making them self-hosted and independent of a specific cloud provider.

Relay currently runs on Docker and uses Redis for its event infrastructure.

GitHub: https://github.com/sergiors/relay

I'd be interested in feedback on both the programming model and the architecture, especially from people already running event-driven workloads outside the major cloud platforms.