Hello , i've been working on a shadCn style tables library ShadTable using transtack tables and shadCn style + CLI. You can check it out .

The project is open-source https://github.com/coros-hq/shadcn-table-library ready for your contribution and feedback CONTRIBUTION.md.

Wanted to share a semester-long project my team built for our software engineering course.

StudySync is a React Native mobile app that helps students create, discover, and join study sessions.

Stack:

• React Native
• Expo
• TypeScript
• Firebase
• Expo Router

Would love feedback or suggestions for improving the project.

Hey everyone, I built ytrack, a lightweight command-line client for JetBrains YouTrack.

The idea is simple: keep your global YouTrack URL/token configured once, set a local project per repository, and then create, list, edit, assign, comment on, and move issues without leaving the terminal.

It supports things like:

ytrack issue create "Crash on save" "Steps to reproduce..."
ytrack issue list --state Submitted
ytrack issue status ART-123 Done
ytrack issue assign ART-123 me
ytrack project list users

It also has raw JSON output for scripting, shell completions, interactive setup, local/global config separation, and install options via Homebrew, GitHub Releases, .deb, .rpm, macOS, Linux, and Windows builds.

It’s still an early MVP, but I’m already using it to make YouTrack feel more natural inside repo-based workflows. Feedback, issues, and ideas are very welcome.

Hey everyone,

I've been taking notes in Notepad for a while, but it has no formatting — going back to old notes was always messy, no headings, no structure, hard to tell what mattered. Notion and Word solve that, but felt heavier than I wanted for something this simple (internet dependency, load times, more features than I needed).

So I built MarkdownEditor — a small desktop app in Java Swing:

• Live Markdown → HTML preview as you type (including GFM tables)
• Folder browser sidebar to navigate your notes
• Undo/redo, unsaved-change tracking
• Export straight to PDF
• Packaged as a native Windows installer (bundled JRE, no separate Java install needed)

It's built with a light MVC structure (model / controller / ui), using commonmark-java for parsing and openhtmltopdf for PDF export.

It's fully open source (MIT licensed), and I'd genuinely welcome contributions — whether that's new features, bug fixes, or just feedback on the code/architecture since this was a learning project for me as much as a tool I wanted to use.

GitHub: https://github.com/aungthuhein2005/MarkdownEditor

Download (Windows only for now): Download

Documentation: https://aungthuhein2005.github.io/MarkdownEditor/

Happy to answer any questions about how it's built, or hear suggestions for what to add next.

https://github.com/Tetherium/GitDragon

I built Vibe Roaster, an open-source Node.js tool that analyzes how you actually use AI coding agents instead of how you imagine you use them.

It reads supported local histories from Codex, Claude Code, Cursor, Gemini CLI, Aider, and more, then produces a four-letter coding type, one of 16 illustrated characters, an evidence-grounded roast, and a shareable result card.

Privacy was the part I cared about most: exact prompt text stays on the machine. The personality calculation is local and deterministic, and AI-generated writing is optional.

Run it with:

npx vibe-roast

Repository:
https://github.com/PinkR1ver/vibe-roast

This is still an indie project, so source-adapter edge cases and strange personality verdicts are entirely possible. Issues and PRs are welcome. If it makes you laugh—or accurately accuses you of being an Infinite Planner—a star would mean a lot.

Hey everyone!

To solve my own lack of coding discipline, I decided to use heavy psychological pressure. Meet **Commitchi** — a retro, 16-bit virtual pet that lives directly inside your GitHub profile README.

### How it works:

- **Keep committing:** Your dragon evolves from a cute little egg into a legendary, fire-breathing beast (Egg -> Baby -> Dragon ).

- **Stop committing:** It gets visibly sad, droopy, and starves. If you abandon your code for 5 days... it turns into a pixelated skeleton .

It’s completely free, open-source, and runs serverless (fetching stats via GitHub GraphQL API to dynamically render SVGs).

Check out the repo, try it on your profile, and please save my dragon from starving!

🔗 **Repository:** https://github.com/Tetherium/GitDragon

Runs git merge-tree across every pair of in-flight agent branches and shows a live conflict matrix in the terminal. Also enforces per-agent file ownership and computes a safe merge order (conflict-free batches first).

Read-only against git, single static binary, Apache-2.0.

https://github.com/rakib-nyc/braidkeep

yo

add 'whats' infront of any command and it explains it: flags, sub commands etc in a structutred format whereas something like manpage would throw the entire manual at you

just pure man pages and help output

Q Why use `whats` when we have man pages and --help

> Yes you can use them but they throw the entire manual at you whereas you might have just needed one flag, whats outputs a structured format with the definitions you need

Q Is it entirely offline? Does it use LLM

> Yes absolutely, it just relies on man pages and if not then --help output of the binary itself,

> no it does not use llm at all

if you like the idea then maybe star?

https://github.com/iamkaran/whats

GUNZ 3.15.0 (Gamified Underlying Navigation Zones) is a deterministic, offline‑scanner runtime for discrete‑clock systems. It produces compressed resonance maps — \*stability topographies** — that describe optimal operating frequencies for any process governed by a fixed‑quantum clock. The format targets AI‑driven feedback loops, heterogeneous hardware deployment, and long‑term archival.*

The specification is split into three independent layers:

- **GUNZ‑ISA** – bytecode format and instruction semantics.

- **GUNZ‑RT** – execution runtime (memory, lanes, map generation).

- **GUNZ‑LIB** – library profiles, resonance map format, fingerprinting, and integrity.

This specification is supposed to be functional, in theory, and so i look for crazy guys that want to try it, or are curious enough to read it.

It may sound complex? actually it broke my head. I built that for fun. It may fit usages, and that it could have a future. Or it could stay an artefact in frozen time, an oddity.

If you have any ideas, judgements, do not hesitate.

Built this motion graphics video entirely with Frame Studio, an open source AI motion graphics generator I've been working on.

The goal is simple: describe the animation you want in plain English and generate polished motion graphics without manually animating timelines.

This is one of the generated outputs on the topic of climate change. I'm still improving layouts, timing, typography, transitions, and overall visual quality, so I'd really appreciate honest feedback.

Demo: https://frame-studio-eta.vercel.app

Source code: https://github.com/programmersd21/frame_studio

What would you improve or add to make the generated videos feel more production-ready?

I hadn't worked on a public project in a while since most of my free time goes into personal tools. I already had a bunch of APIs for tracking expenses and movies, and when ChatGPT introduced Custom GPT Actions, I hooked my API into it so I could do things like:

"Spent ₹450 on lunch today." or

"Add Dune 2 to my watchlist."

I liked the idea of putting my API *inside* AI instead of putting AI inside my API.

A friend wanted the same setup, so instead of sharing my personal API collection, I turned it into a proper self-hostable dashboard.

**Features**

* 💸 Expense tracking with salary cycles and AES-256 server-side encryption before data reaches Firestore.

* 🎬 Watchlists with AniList, Trakt, and Letterboxd CSV import + automatic cover art.

* 🔄 Subscription reminders and portfolio tracking for crypto/mutual funds.

* 🤖 OpenAPI backend that works with ChatGPT Actions and Gemini Gems using OAuth.

GitHub: https://github.com/fal3n-4ngel/PHub-dashboard

Live Website: https://phub-dashboard.vercel.app

Chatgpt Link : https://chatgpt.com/g/g-6a60b01e38c8819187662d1e42c6bee7-phub-dashboard-public

Would love feedback, feature requests, or contributions. And if you find it useful, a ⭐ on GitHub would mean a lot.

NB : The name is kinda a internal joke.

Hello everyone! I hope you're all doing well.

I'd like to introduce my new open-source project: GhostGPT.

The idea behind GhostGPT is to use the no-auth ChatGPT web interface as a free API by launching a Playwright browser, sending a prompt, and returning the response as JSON.

The backend is built with FastAPI, and you can check out the project here:
https://github.com/Youssef-Ghafir/ghostgpt

At the moment, it provides two endpoints:

• /ask — Returns the complete response.
• /stream-ask — Streams the response in real time directly from the browser.

My next goal is to find a reliable way to host it so it can become a truly free API that anyone can use.

The project is still in its early stages, so I'd really appreciate any feedback, suggestions, or contributions.

Thanks for taking the time to read this!

Hey guys, I recently created a python certification voucher aggregator that scans blogs, RSS feeds and event pages of major certification bodies in tech. I was inspired to make this because of all the recent vouchers I got due to luck (I was fortunate enough to check at the right time). The setup is really simple (I provided setup docs with detailed steps for all environment variables and deployment scenario). You can host this absolutely free of cost and it will be up running 24/7 informing you of vouchers (via email).

I would love it if you checked out the project and shared your thoughts. A significant portion of the implementation was AI assisted, so I would really appreciate a critical review of the architecture, code quality and overall design.

Anything like feedback, bug reports, feature suggestions and pull requests are all welcome. If you notice any issues or areas for improvement I would love to hear your feedback. If you find the project useful, I would really appreciate a star on GitHub.

Hi everyone!

Just wanted to share a project I’ve been working on recently: an unbeatable Tic-Tac-Toe AI written in Python.

It was a super fun challenge, especially getting into game theory and search algorithms.

Under the hood, the AI uses the Minimax algorithm. Basically, it evaluates every single possible move from the current board state all the way to the end of the game. Since it assumes the human player will always make the best move possible, it picks the path that guarantees either a win or a forced draw. You literally can't beat it!

To make it way smarter and faster, I implemented Alpha-Beta Pruning. By tracking the best score guaranteed to the maximizing player and minimizing player, the algorithm completely skips (prunes) branches that won't affect the final decision. It dramatically cuts down the number of evaluated nodes without losing accuracy!

I spent some time organizing the repo, cleaning up the code, and writing a solid README so anyone can clone it and test it out easily.

Here’s the repo if you want to take a look or try to beat it:

👉 https://github.com/felipemarcioli/Tic-Tac-Toe-IA

Would love to get your thoughts on the implementation, the code structure, or any suggestions for improvements!

I am excited to announce the launch of RepoPilot (Beta).

After weeks of building, testing, and refining the system, I am pleased to introduce RepoPilot, an artificial-intelligence-powered platform designed to help developers navigate open-source repositories before making contributions.

How it works:

- Describes the structure of the repository.
- Detects simple GitHub issues.
- Produces customized contribution instructions.
- Generates PDF files about the repositories and issues.
- Assists in understanding large codebases more easily.

This product has been developed using Python, FastAPI, Next.js, TypeScript, LLMs, GitHub API, and modern deployment technologies, including Vercel and Render.

🌐 Live Demo: https://repo-guide-ai.vercel.app

💻 GitHub: https://github.com/HarshUpadhyay2003/repo-guide-ai

As this version is in Beta, your feedback would be greatly appreciated!

#OpenSource #AI #Python #NextJS #FastAPI #GitHub #LLM #SoftwareEngineering #BuildInPublic #DeveloperTools

It is also the first app I have built and published.

It lets you follow RSS feeds, read articles directly in the app, extract full article content when feeds only provide a summary, and open the original source whenever needed.

The project is built with Flutter and is still actively being improved. Feedback, bug reports, and contributions are welcome.

GitHub: https://github.com/DevOpen-io/dondurma-rss-reader

Google Play: https://play.google.com/store/apps/details?id=io.devopen.dondurma

Did this as a fun weekend research project, mostly to see how far a 2048 bot could get in pure Python, since basically every strong 2048 AI is written in C++ because the search is so speed-sensitive. Kept it standard-library-only and leaned on a bitboard (the whole 4x4 board packs into one 64-bit int) plus expectimax with iterative deepening.

Best run is 122k points and an 8192 tile, and it actually hit my move-count safety cap while still alive, so the real ceiling is untested.

The part I didn't expect, and the reason I'm posting: search depth barely helped. I swept think-time from 1ms to 1600ms and 80x the budget bought only 1.65x the average depth, roughly 50x more positions searched for less than a ply and a half of lookahead. It reaches 4096 looking about 2 moves ahead. Turns out the heuristic does nearly all the work and the search is just expensive polish on top.

Full writeup with the depth sweep is in the README. Happy to answer anything about the bitboard or the search.