The goal: Arc-style spaces in one window, but with real isolation. Each space gets its own cookies, storage, history, passwords, form data, extensions, permissions and downloads. Firefox containers only cover cookies and storage, and profiles need separate windows, so this needed a different approach.
How it’s put together:
app/: Swell is its own Gecko application, built inside a Firefox source checkout the same way Thunderbird’s comm/ is. It has its own window document, not a restyled Firefox UI.
core/: a Rust core owns the app state: the sidebar tree, spaces, and per-space data.
patches/: a small patch queue for the engine changes that can’t live outside Gecko, applied on top of a pinned Firefox revision (FIREFOX_REV).
Extensions per space: each space gets its own copy of an extension, scoped so it only sees that space’s tabs.
Passwords: stored per space, encrypted with a per-space key in the OS keychain.
Tests: an isolation suite checks 17 state stores for cross-space leaks. There are also Rust unit tests, xpcshell and browser tests, and an end-to-end restart test.
It’s an alpha: Apple Silicon macOS and x86 Linux, unsigned builds, no telemetry, MPL 2.0. Build from source takes about 30 minutes and 15–20 GB.
Feedback on the architecture and the isolation model is very welcome, and so are contributors. CONTRIBUTING.md explains the setup.
I first posted about Diskoryx when I released the initial version. I've kept working on it since then, and with v1.0.5 now available, I wanted to share how much has changed—not just in this update, but across the releases since that first post.
For anyone seeing it for the first time: Diskoryx is a free, open-source disk space analyzer for Windows. It helps you understand what's taking up space, explore large files, compare scans, and review duplicate files.
No account required, no uploading your files or filenames. Disk analysis runs locally and works offline.
The storage explorer combines a file tree, interactive space map, and file Inspector. This screenshot uses sample data, not benchmark results.
Faster scanning
Since the first release, I've improved the NTFS scan pipeline with compact binary data transfer and more efficient tree construction and indexing.
In a documented local comparison covering approximately 774,500 files, median scan + indexing time dropped from 7.951 seconds in v1.0.1 to 4.400 seconds in v1.0.3—44.7% less time.
Those were three repeated scans per version on the same machine and live C: drive, with warm caches. The timings exclude UAC waiting, and results will vary. This isn't a speed comparison against WizTree or other tools, and v1.0.5 doesn't introduce another scanner-speed change.
The original release didn't have the current Duplicate Finder workflow. You can now:
Find matching contents using full-file SHA-256 verification, with size checks and sampling to narrow candidates first.
Reuse a completed drive inventory instead of repeating the initial file discovery.
Review groups through a summary, file-type chart, filters, search, and expandable copy lists.
Choose copies manually or use Auto-select when a preferred copy can be identified.
Move selected eligible files to the Recycle Bin, keeping one copy by default.
Review each cleanup run in History and restore individual files or the whole run while the matching items remain in the Recycle Bin.
Project, dependency, application, and system locations have cleanup protections. Matching contents still don't mean a file is unnecessary—review your selections.
Review matching sample files and their locations before choosing which copies to recycle.
Duplicate processing and batch cleanup have also been improved. In v1.0.5, a local generated 120-file Restore all test dropped from roughly 39 seconds to 1–1.2 seconds. That's a specific workload, not a universal promise. Restored files now return to the duplicate results after verification without another analysis.
Saved scans and comparisons
You can now save scan metadata to a local .diskoryxscan file, reopen it without rescanning the original drive, and compare a saved baseline with a fresh scan of that location.
Compare shows added, removed, and metadata-changed files. It compares paths, sizes, and recorded modification dates—not file contents or reliable rename/move identities.
v1.0.5 also fixes an issue opening large saved full-drive scans and makes save/open validation consistent. The rebuilt packages were checked against an existing archive containing approximately 964,000 files. Large archives and comparisons still need substantial RAM; this isn't an unlimited-size claim.
More useful search and everyday improvements
Since launch, I've also added or improved:
Advanced search: filename wildcards, size/date conditions, and AND / OR / NOT expressions.
File-type exploration: category charts and filtering into extension details.
Multi-drive selection and switching between cached scan results.
Copy/Move destination navigation and completion feedback.
A portable download, alongside the standard installer.
A source CLI for read-only folder scanning and CSV export with Node.js.
Scanner validation and NTFS correctness fixes, including hard-link accounting and parent-record handling.
Long-path handling, file-action fixes, Compare cancellation, and live-update reliability.
Light-theme readability and controls that could remain unavailable after scans or actions.
v1.0.5 also adds an explicit option to manually select every copy in a duplicate group, behind two warnings. Keeping one remains the default, and protected items stay locked.
I'd love some real-world feedback
If you tried the first version, I'd really appreciate you giving the current one another look. If you're new to it, I'd love to hear what works—and what doesn't.
I'm particularly interested in large-drive behaviour, saved scans/Compare, Duplicate Finder, and anything that feels slow or confusing. Honest criticism and reproducible bug reports are welcome.
A few important notes: Windows x64 only. The builds are currently unsigned, so SmartScreen may show a warning. Launch normally; only the separate NTFS scanner requests administrator permission when needed. Sizes are logical file sizes, not allocated disk space or guaranteed recoverable space. Portable settings and History use AppData, not the executable's folder.
Please keep backups and test file actions on disposable files first. If you report a bug, include your Windows version and reproduction steps, and hide private filenames in screenshots or shared scan exports.
What it does: ask Claude Code a question about your spreadsheets ("which regions are behind target?") and a dashboard appears in your browser: charts, a table, the headline numbers.
- Works on messy real-world files: title rows above the headers, "Total" rows, N/A, numbers stored as text.
- Every chart shows exactly where its numbers came from, so you can check them.
- It only reads your files, never changes them. SQLite and Postgres work too.
- About 7¢ and 19 seconds an answer, against 20¢ and a minute when Claude Code writes its own Python + HTML (my benchmark; details in the repo).
Hi, I built Yata, a notch that sits at the top of the Windows screen, just below the camera. Closed, it's a black pill with the time; hover it and it opens into tabs: now playing from any app that uses Windows media controls (with synced lyrics from LRCLIB), your next Google Calendar meeting with a Join button, a Pomodoro, tasks with reminders and a shelf for dragging files around.
I wanted one of these I could actually audit. So: no account, no telemetry, no keyboard hook (Caps Lock and layout come from key state), and nothing goes online unless you turn it on. Google tokens are encrypted with DPAPI. The site has a table of exactly what leaves the PC.
The installer isn't code-signed yet (SignPath's free program wants more public traction first), so SmartScreen will warn. Releases are built by GitHub Actions from the public source, with SHA256 sums and a build provenance attestation you can check with `gh attestation verify`, or you can build it yourself.
Happy to answer questions about the implementation.
getyata.app
I created Awesome Easy-to-Join Orgs repo, a curated list of GitHub organizations that welcome people who want to get involved without necessarily writing code.
The goal is to make open-source communities more accessible to beginners, students, and non-coders who want to participate, learn, or contribute in other ways.
I'm sharing the project here in case it's useful to anyone looking for communities to join. Suggestions for additional organizations and feedback on the list are welcome!
For the past few months I have been working on a domain-specific language (DSL) for making UIs in game engines (or any real-time renderer).
It's a functional language inspired by languages like Elm and Typst - as well as UI frameworks like Flutter, but compiled (using llvm/clang).
The whole idea came about when I was working on my toy game engine and found myself in a conundrum of how to properly do UIs.
Things like Dear ImGui, ea-webkit, etc are great - until they aren't, mostly ImGui becomes a mess of spaghetti code and ea-webkit is bloated beyond belief.
I initially wanted to make some form of abstraction layer that would parse something like JSON to build the UI but then determined that would become a mess of figuring out how to bind logic tot he UI.
Then I thought about making a simpler version of the embedded chromium like with ea-webkit but then that became a mess of getting the right libraries, figuring out bindings, etc and still being left with a bunch of bloat that I didn't want.
I love Typst and Haskell and was learning about Elm at the time and thought about my dilemma and considered if I could apply my knowledge of building compilers towards creating a DSL that would allow me to have the ergonomics of a browser based UI framework with the performance of immediate mode UIs like dear imgui.
After working on the language design for a bit and playing around with ideas I have come up with something interesting I think.
It's not a turing complete language per se, the entire language is designed to be strictly for rendering UIs.
I know a lot of devs already have frameworks they love for this, and I know making good UIs is hard conceptually. So my goal with creating this was that on top of being compiled - to satisfy my performance goals, it needed to be able to be integrated into any rendering framework or engine without a huge hassle - and it needed to be reasonably scoped to do the one thing it was designed for well: build UIs.
It isn't entirely complete yet, it's got a long way to go but I'm making some good progress:
code gen is working for most of the control-flow syntax (llvm)
it has good C-interop because this provides a good bridge to other languages and frameworks
it has a headless renderer (enumerates the draw commands to a buffer or file for unit tests), along with an image renderer (to jpeg/png) so you can do visual regression testing
UI elements are starting to compile down to render command sequences and Im scoping the opengl renderer as a v1.0.0 target.
and more
It is written in C++
llvm orcjit example:
fn view(count: Int): Node => {
let text = if count > 1 { "Done" } else { "Hello World" }
#button{
#text(text)
}
}
$ kura examples/hello-world.kui --run view 11
(seq (set text (if (binary GreaterThan count Int(value=1)) (seq String(value=Done)) (seq String(value=Hello World)))) (#Button (#Text value: text)))
compilation finished in 29ms
renering frame 1024x1024
void kura_rt_check_renderer() is not implemented!
void kura_rt_fill_rect() is not implemented!
void kura_rt_check_renderer() is not implemented!
rendering text: Done
void kura_rt_check_renderer() is not implemented!
void kura_rt_end_frame() is not implemented!
void kura_rt_check_renderer() is not implemented!
finished in 60us
I have plans to make this ahead-of-time compiled - but currently using orcjit for testing, the orcjit will remain as a way to debug during development
I'm open to questions, comments, concerns, feedback, contributions etc.
I’ve been building RunContainer, an open-source Windows project that aims to make installing, running and managing Windows applications in their own contained environments easier.
The basic idea is simple: instead of treating every application as something that has to be installed and managed directly on your desktop, you can use RunContainer as a place to install, launch and manage apps within the app itself.
What makes it interesting?
Application containment: Run Windows applications through different containment backends, depending on the environment and requirements.
Configurable memory limits: Set a memory limit for individual applications.
JIT support: Support for applications that require just-in-time compilation.
RC-Brain 5: My own lightweight AI model, designed to monitor application behaviour against a ruleset and help with troubleshooting.
Open source: The project is released under the MIT licence, so anyone can inspect the code, report issues or contribute.
I'm still developing the project, and I want to be transparent: different containment methods provide different levels of isolation, and this isn't a guarantee that every application will work or that all threats will be blocked.
I'd love your feedback!
I'm particularly interested in hearing from Windows developers, people who test unfamiliar software, and anyone interested in application isolation.
I'd love feedback on:
Whether the concept is useful to you.
What features you'd want in an application containeriser.
Bugs, compatibility issues or improvements you'd suggest.
Whether you'd be interested in testing it or contributing.
it has a huge amount of fetures to many to list all fetures are in get hub or hyou can get the app to see for your self ive worked hard to maek this look and work great (aka not vibe coded) and take user requests for fetures and i need help with bug testing if anyone wants to submit bug reports that would be great. (just let me know if you like it)
You can search for torrents within qBittorrent itself; across TPB,1337x, YTS, etc. all at once, using Jackett (guide below). But, if the same torrent is listed five sites- you get multiple rows with different names and seed counts for the same torrent. This gets confusing/ cluttered.
I built a tool that fixes this. Same search & sites- 139 hits with Jackett → 66 hits with mine. It:
Merges torrents with the same infohash into one row
Merges trackers for different sites- so you connect to more peers
Resolves missing torrent hashes by fetching it for sites like Lime
Supports BitTorrent v1, v2, and hybrid torrents
Alt Folds same-title, same-size reuploads behind a +N alt marker
Best seed count: Keeps the highest reported seed count
Private/ public tracker configurable handling
Retries transient Jackett/indexer failures
Limit: Jackett only (no Prowlarr), hash lookups on public sites only. Open source, GPL-2.0.
Installation Guide
The steps below assume Jackett is already set up; the README covers installing Jackett too.
In qBittorrent, open Search → Search plugins → right-click Jackett → untick Enabled
Search Plugins → Click Install a new one → Web link → paste below URL
Disclaimer: You are personally responsible for following the copyright laws and other applicable laws in your country. Use the plugins and websites they connect to at your own risk.
I've been working on Spring AI Privacy Guardrails, an open-source library for privacy and security in Spring AI applications.
One problem I wanted to address is that masking personal data before an LLM call isn't always enough. A tool might need an original value to do its job, and its response might contain more sensitive data.
For example, a customer lookup request might include a customer ID and a phone number. Both can be tokenized before reaching the model. If the user's permissions and the tool's disclosure policy allow it, the lookup tool receives the original customer ID while the phone number stays tokenized. Detected PII in the tool's response is protected again before the next model call.
The library covers three areas:
1. Privacy Protection
Detected PII is replaced with request-scoped tokens before reaching the model. Tools can receive only the original values allowed by their disclosure policies, and detected PII in tool results is protected again. Protection can also cover RAG, chat memory, and MCP.
2. Tool Authorization
Spring Security integration controls which tools the model can see based on the current user's permissions. Authorization is checked again before execution, including before any permitted original PII is restored.
3. Content Inspection
Application rules, local ONNX models, or HTTP guard models can inspect inputs and optionally final outputs. This can be used to check for issues such as prompt injection and inappropriate content. When privacy protection is enabled, detected PII remains tokenized before content is sent to an external inspection model.
All three features can be used independently or together in a Spring AI ChatClient.
The project is Apache 2.0 licensed and available on Maven Central. It was also mentioned in the official Spring blog's This Week in Spring and listed in Awesome Spring AI.
Something like IDM, but free, MIT and on every OS. Up to 32 connections per file, resume after crashes and expired links, torrents, video streams saved as MP4 without ffmpeg, and Google Drive/MEGA/Dropbox/OneDrive links. Installers for Windows, macOS (universal) and Linux (.deb, .rpm) are on the releases page: https://github.com/Oshan96/Zipline/releases/latest
When Claude Code reads or generates an image, the chat just says [Image]: the agent sees it, you don't. I hit this every day making game sprites with Claude on a VPS over Remote-SSH, so I built a panel that follows the session files and shows every image, SVG, HTML page and video the agent touches, live.
Before/after slider when a file gets overwritten, a grid to compare variants, crisp pixel-art zoom, and sandboxed HTML preview. Runs on the remote host with Remote-SSH. MIT, no network calls, TypeScript.
Stars and issues welcome, it's my first extension.
I’ve used DataGrip for years and love the care in its small details. TableCraft is our attempt at a database IDE in that same spirit, for PostgreSQL, MySQL, SQLite and Redis on macOS, Windows and Linux.
Highlights:
DataGrip’s keymap and layout
Schema-aware completion, including join conditions from foreign keys
A table editor that previews SQL before committing
Large results that stay responsive
Import your connections from DataGrip or TablePro
It’s MIT licensed and still early, so feedback is very welcome.
Hi! I made tuna-dlp, a small Windows app that puts buttons on top of yt-dlp and ffmpeg, for people who don't want to use the terminal.
It's not a new downloader: yt-dlp and ffmpeg do all the work (both are bundled, nothing else to install). You paste a link, pick video / audio only / subtitles, and hit download.
What it does:
- Video (up to 4K, mp4/mkv/webm), audio (mp3, flac, opus…) or just subtitles, showing which languages the video actually has
- Playlists: preview the list and pick which videos you want
- Queue with pause/resume, progress on the taskbar icon
- Stays in the tray, optional start with Windows
- Optional: trimming, file name templates, history, channel subscriptions (download only new videos)
- Updates yt-dlp from inside the app
- No accounts, no telemetry. MIT licensed. English and Spanish.
I'm a computer science student from Senegal, and I've been working on a Python project to automate online class recordings using Google Meet and OBS Studio.
I'm sharing it here to get feedback from other developers and improve it.
Spent a week on rooting my samsung tizen tv. its tested only on my tv (2024 Samsung Neo QLED)
It can be rooted from its own browser. No sdb, no developer mode, no firmware flashing. The root is persistent because the payload replaces the IL of a stock on-boot app, and there's an uninstall path that puts the original app back.
Over the past few years I've been searching far and wide for a wiki-style knowledge base that feels as modern as the big commercial tools. There definitely are some fantastic open-source wikis out there, but the established ones often feel dated, and the newer ones tend to be either too bare-bones or too sprawling.
So here's my contribution, or rather the beginnings of it. It's early and rough in places, which is why I'm looking for people to help shape it, but it's also fairly usable already.
Wikid is a self-hosted wiki and collaborative workspace:
Nested pages, a block editor with / commands, live co-editing
Databases inside the wiki: table, board and gallery views, filters and sorts
Forms that submit straight into a database
An optional compliance mode with workflows and an audit trail, for records that need one
It's AGPL-licensed and runs with docker compose up. Built with Vue 3/Tiptap, NestJS, Postgres and Yjs.
I've marked each feature as stable, beta or experimental in FEATURES.md, and there's a roadmap (search is done; hardening and page history are next).
It's a party of one + Claude at the moment, so I'd love some feedback, and contributors – let's get this thing off the ground! There are good first issues if you want a way in...and it needs a favicon, since I don't have the time to be very creative these days 😪
I built it with heavy use of AI coding tools. I'm a systems engineer by trade, and every change is reviewed and backed by automated tests (unit, API and browser, run in CI on every change). AI-assisted contributions are obviously welcome too; just take care to understand and test what you submit.
He creado Wingetix, una interfaz visual de código abierto para el Administrador de paquetes de Windows de Microsoft (winget) con un desinstalador limpio y la estética de cristal de Windows 11.
Características principales:
Administrador visual de Winget: Explora, busca y gestiona paquetes sin necesidad de escribir comandos en la consola.
Actualizaciones por lotes con un clic: Comprueba y actualiza todo el software instalado a la vez.
Desinstalador profundo: Elimina aplicaciones y ayuda a limpiar archivos residuales y rastros del registro.
Integración con puntos de restauración: Crea puntos de restauración del sistema antes de modificar el software.
Sin sobrecarga: 100 % de código abierto, sin rastreadores ni telemetría.
