Some weeks I burn my weekly early, some weeks usage is left over at the reset and just evaporates. So I built Overflow.

Spare week: take a priced GitHub issue from a registered repo, the merged PR gets you credit. Dry week: price an issue in your repo, someone with a spare week ships it, your credit pays.

If you want to contribute to open source and don't know where to start, that's kind of the point. You don't need to know the project, the issue is the brief. If your agent hits a decision, ask the maintainer on the issue.

First thing maintainers ask is "won't people spam junk PRs at me". Same as any repo, you block them on GitHub. You set the price after you've seen the work, and you only owe for what you actually merge.

Nothing gets forwarded, no keys, no money, no paid tier, MIT.

Main reason I'm posting: I want people to register their repos. Every open issue on the board right now is mine and I'm not after help with those, I want spare usage going into other people's projects. 30 users so far.

source at https://github.com/Nitjsefnie/Overflow

Hi. Ive been building Star from some time. Unlike most other languages, Star transpiles to C++ code instead of LLVM IR. Because it is more portable and allows me the execution model of C++ and things like classes etc

I am currently the only contributor so any contributions are welcome. You can also try out the good first issue

A ⭐️would be appreciated! The project can be found HERE

I’m currently in activist circles and been having thoughts on how open source could be a good tool to achieve change that’s desired. I’ve noticed many people in these spaces are very anti AI and i understand the sentiment but the truth is that AI is going to involve regardless if we like it or not. So then I had to eventually ask myself: would I want the future of AI to primarily be in the hands of corporations, techoligarchs, and the government who prioritize their own interests or communities, grassroots organizations, and people knowledgeable enough to use it more ethically? For me the answer was quite obvious and I believe open source can better help inform, protect, and organize in ways current tactics fully aren’t. I already have a few ideas of possible apps for this but I’m still rather new to really getting the basics. I figured since this would be collaborative work between people of varying backgrounds of knowledge, to share my thoughts on this. I wouldn’t be surprised if this has been in discussion on here already but I do know in real life the sentiment is quite different at least currently. The hope is that if done effectively a more positive shift is possible and can show everyday people AI is capable of accomplishing good outcomes. I’d love to hear anyone’s thoughts on this and sparking a productive/healthy conversation.

I made an Android app that runs the open-source [ByeDPI](https://github.com/hufrea/byedpi) engine locally and routes the phone's traffic through it using Android's VPN service. It's meant to help with DPI filters that interfere with connections.

Full disclosure: this project was written with AI. All the code and docs were generated by Claude (Anthropic) from my requirements, and I built and tested it through GitHub Actions. It has not been audited, so please read the code before you trust it. So far it has only been tested by me, on my own phone and network.

What it does

- Compiles the upstream ByeDPI C code with the NDK and runs it as the real engine (not a simulation)

- Local proxy on 127.0.0.1 + tun2socks tunnel (hev-socks5-tunnel) through `VpnService`

- The status only turns green after the proxy, the VPN interface and the tunnel have all been verified

- Settings for desync method, position, fake TTL, TLS record split, auto mode and custom arguments

- Diagnostics screen with an in-memory log (no hosts or traffic are logged) and a TLS connectivity check through the proxy

- Dark UI, no ads, no analytics, no accounts

What it is not

- It does not encrypt traffic or hide your IP, and it does not bypass DNS blocking

- There is no universal strategy: what works depends on your ISP, so you may need to try other settings

Details

- Android 8.0+, arm64 / armv7 / x86_64

- Debug-signed APK (uninstall old builds before updating)

- MIT licensed; ByeDPI and hev-socks5-tunnel are MIT too

Repo: https://github.com/Mireli5656/Byedpi

APK: see Releases on the repo page

Feedback and bug reports are welcome. If something fails, the "Copy" button on the Diagnostics screen gives a log that contains no traffic details.

Ever shared a file with someone and wondered what happens to it after that?

Yeah, that question led me to build BurnLink.

I'm a CSE student, building products through my startup, Paperfrogs HQ. BurnLink is one of the projects I've put a lot of time into, and the idea behind it is pretty simple: file sharing shouldn't always mean leaving a file accessible indefinitely.

So I built a tool that lets you share files through links designed to self-destruct.

Here's what it does:

• Files can burn after the first download.
• View-once sharing for temporary access.
• AES-256-GCM encryption and password protection.
• No account required.
• Open-source code that people can inspect.

The goal isn't to reinvent file sharing. It's to give people another option when they need to share something without leaving a link hanging around forever.

Building this as a student founder has been a learning experience in everything from cryptography and backend infrastructure to shipping an actual product instead of just another project sitting on GitHub.

I'm still working on making BurnLink better, and I'd love some honest feedback.

What would make you trust a file-sharing tool like this? Is it the cryptography, transparent source code, the way files are deleted, or something else entirely?

Try it: https://burnlink.page/

GitHub: https://github.com/paperfrogs-hq/BurnLink

Would love to hear what you think.

I've finally been successful in developing a cheap open sourceaircrete mixer. At less than $500 it's about the cheapest one I've ever seen. Easily built from a modified tumbler mixer. It produces a top notch material in semi automatic operation (no struggling with a hand held "paddle mixer".

I'm also developing a number of open source composite aircrete wall designs. The block wall variant is retrofit only, to install continuous exterior insulation on a block wall. Although mud, straw, or rigid foam board could also be used, I believe my method is the highest performing, lowest cost and most accessible way to insulate the world's most common building method (concrete frame/ infill block walls). For newbuild homes of this type, this method and machine is the best way to produce a concrete frame home. It's criminally underused. I know the inventor of this machine and it's also open source. I have strong opinions but feel we could use an Apollo Program type investment to develop the use of these techniques globally, to improve access to better building science for unserved people.

Although I will have some success building these prototypes apparently I'm not clever enough to find any development money. My DM's are open if you have any way to help me in this area. Could be grantwriting or maybe you know someone with deep pockets who wants to make an impact on our housing technology. I have studied and worked on this stuff for two years. There are cheap, practical, common sense solutions that scale well. It's a profitable business idea, not a resource black hole.

Hi everyone,

I built Aman Check, a free and open source Mac app made for regular people, not for techs or enthusiasts. If you're about to buy a used Mac, or you just want to know what state yours is in, you probably don't know what to look at. The app does the checking for you and explains the results in plain words.

It shows the battery health and cycle count, how many hours the disk has been running, and whether the Mac is locked: Activation Lock, company management (MDM), or an Apple Account still signed in. Then it walks you through quick tests for the screen, keyboard, trackpad, speakers, microphone, camera and ports, one at a time. It won't replace erasing the Mac and checking the setup screen in person, but it tells you exactly what to ask the seller.

If you're the one selling, you can generate a report of the Mac's condition and share it with the buyer.

For a deeper look at the disk itself, there's also Aman Disk, my other app. Think CrystalDiskInfo, but for Mac, and free as well.

Everything is on GitHub, the link is on the site: https://midzai.github.io/aman_check/

It's a first release, so if you find a bug or have an idea, tell me here or open an issue on GitHub. Any feedback helps.

I published my first Python package on PyPI today 🎉

It's called gh-issue-lens.

It started as a small script I wrote for myself. I wanted to contribute to open source, but every time I opened a big repo, I got lost in thousands of issues. Which ones are actually beginner-friendly? Which ones already have someone working on them? Which ones are just old and forgotten?

So I built a tool that answers that for me. It fetches open issues, checks if they're assigned, checks if there's already an open PR against them, filters out bot comments, and gives you a clean JSONL file you can hand to any LLM to help you pick your first issue. Then I shared it on Reddit. Complete strangers gave me honest feedback, and I kept improving it. Now it resumes automatically if the API rate-limits you mid-run, and it caches what it already fetched so you never download the same issue twice.And now it's a real package:

pip install gh-issue-lens

It's still version 0.1.0. There's still a lot to build. But today, anyone in the world can install it with one command, and that feeling is great.
If you ever wanted to start contributing to open source but didn't know where to begin, this was made for you.

GitHub repo:
https://github.com/MohamedM216/gh-issue-lens
package on PyPI:
https://pypi.org/project/gh-issue-lens/

#OpenSource #Python #PyPI #GitHub #FirstRelease

After every vacation, and especially with kids I find myself with thousands of photos with many similar ones "because maybe we take one where everyone is smiling".

In the end there's a lot of afterwork choosing the best ones and cutting down on storage while keeping some quality selection.

Or maybe something that groups them by similarity or automatic albums.

Do you know anything smart that helps with this?

hey Reddit,

I'm Yash, founder of SupercodeAI. We're building Devin killer - Nova - an AI Engineer, powered by our own harness agent at SupercodeAI, and Supercode Review, our codebase-aware PR review product.

4.5k+ users, 10+ enterprises, 238 GitHub stars, 30k+ downloads, 700M+ token usage in just 2.5 months.

Source: github.com/yashdev9274/supercli

Products:

1. Nova: supercodeai.tech
2. Supercode review: supercodeai.tech/review

Nova's workflow is to read a codebase, plan a change, edit files, run commands and tests, and prepare the result for human review. The harness connects the model to context and execution tools. You still inspect the diff and decide what gets merged.

Supercode Review looks at pull requests in the context of the wider codebase, rather than treating the diff as the whole project.

We're powering Indian startups with code review through Supercode Review.

We're sponsored by Vercel.

The Supercode repo is MIT-licensed and includes the coding-agent CLI, dashboard, docs and shared packages. Nova uses existing model providers; I'm not claiming a new foundation model or benchmark superiority.

If you'd like to try it, start with one small task in a repo you understand and compare the plan, diff and checks with how you'd do the work yourself.

If you'd like to contribute, open an issue with a reproducible problem or propose a change in a PR. Keep credentials and private code out of reports. If the project is useful to you, consider starring it and following its progress.

What would you need to see before trusting an agent to handle a real task in your repo?

FralRater is a desktop app (Electron) that: - scores text with Flesch-Kincaid, Gunning fog, SMOG, jargon density… - rates it for 8 reader personas (child, general public, executive, patient, developer, legal, academic, professional) with per-paragraph confidence - draws a "lost reader" curve: one point per sentence, showing exactly where readers disengage - rewrites the hard sentences with a sentence-by-sentence diff (passive→active, buried-lead fix, jargon swaps, splitting)

Everything runs locally. Zero dependencies for the app logic, no build step, no network calls, no AI — it's deterministic rules you can read in the source. Your text never leaves the window.

Free, MIT-licensed, Windows + Linux. Built solo, CI builds all artifacts.

Repo: https://github.com/fralsare/FralRater Downloads: https://github.com/fralsare/FralRater/releases

I run a bunch of coding agents at once and kept changing my mind about how the screen should look. So in hivemind the layout is just a plugin. You get the agents, their status and the real terminals, and you draw whatever you want around them. I've got a queue, a kanban board and a tiled one so far. hive views new gives you a starter with a prompt file you can hand to Claude or Codex to build it for you. Curious what people would make with it.
https://github.com/dip497/hivemind

I work in DevRel. The main platforms I interact with are Discord, GitHub, and Slack, answering questions from the community, and a lot of them are repeat questions. Some of the time the answer is in the docs, and some of the time it isn't.

So I built answerLoops to do that part for me. You upload your knowledge (docs, PDFs, a GitHub repo or Notion pages), and an agent answers questions in Discord, Slack, Discourse, Telegram, GitHub issues, email, or a chat widget on your site.

The agent drafts a reply with the sources it used, then a second agent double checks it's work against those sources. Nothing gets sent automatically unless you turn that on for a channel. Until then, every reply waits for a person to approve it.

Fully open source, run it yourself with Docker and Postgres. There's no subscription for self-hosting, just use your own API key or a local model if you don't want questions leaving your server.

There are skills to setup with one command:

npx u/answerloops/agent-sdk setup

If you use Claude Code, you can also have it walk you through the install. This adds a setup skill so you don't have to read the self-hosting docs first:

npx u/answerloops/agent-sdk skills answerloops-setup

GitHub: https://github.com/answerLoops/answerLoops

I'd really like to hear from anyone running a community (volunteer or nonprofit). If you try it and something is broken or missing, just open an issue, and I'll look at it.

It does two things. First, it makes voting easier. Enter your address once and it shows the races and judicial contests actually on your ballot, including judges and their bar association ratings. It also shows your ward's early voting site and important election dates. Every mayoral candidate's platform is in there, including mine, and mine gets exactly the same treatment as everyone else's.

Second, it gives you a say between elections. Every ward has a board where residents can raise issues and rank how urgent they are, and anyone can ask their alderman a question in public. The community, not the politician, decides whether the answer actually answered it, and that feeds a public report card. Most aldermen aren't on it yet. Until they join, I'll take the top questions to their ward offices. Aldermen and candidates already have a profile and can claim it with their office email. You can also see upcoming City Council meetings and how your alderman voted on every divided roll call.

Verifying that you live in your ward is optional. It makes your votes count in the verified tallies, which are shown alongside the overall tallies. Verification is done by Didit, a separate ID company, and Didit deletes your data once the check is done. The app only keeps that you're verified, your ward and districts, and a code that stops one ID from making two accounts. The first 500 checks each month are free, then it's 49 cents to cover the cost.

It's in seven languages (English, Spanish, Chinese, Polish, Tagalog, Korean, and Hindi), every screen has a help button, and the code is open source: [https://github.com/knightofknee/direct_democracy](https://github.com/knightofknee/direct_democracy))

No iPhone? It also runs in your browser at [https://www.waldgrave.com/directdemocracy/app](https://www.waldgrave.com/directdemocracy/app)), and the Android app is in Google Play testing now. Message me the email on your Google account and I'll add you.

It's a full working app today, but I expect it to change a lot as people use it. What do you think? Let me know what's missing, confusing, or broken and I'll update it quickly.

App Store: [https://apps.apple.com/app/id6797189381](https://apps.apple.com/app/id6797189381))

Fralculator is a desktop calculator. It's free, open source (MIT), and runs fully offline.

• It shows every step of the math, in real math notation, with a plain-English explanation (no LLM needed)
• You can type in plain English, or speak. The speech model is ~40 MB, downloaded once, then fully local
• Live f(x) graphs, and unit + currency conversion (currency is the only optional network call — ECB rates)
• EHCalc: subnet calculator, MD5/SHA-1/256/512, 10 encoders, secure password tools, port lookup

Windows + Linux, 5 install formats. Open issue tracker. Source:
https://github.com/fralsare/fralculator
https://github.com/fralsare/fralculator/releases/tag/v0.1.0

Standard RAG on codebases has been driving me crazy—blindly slicing functions in half by character count just ruins the context for AI agents. I've been developing a project for several months to fix this, and i want to see if it’s genuinely useful to others in real environments.

I call it Vex (Vex's Skillgit). It’s an open-source, headless cognitive tool that treats context as immutable, versioned skills for your agents.

Instead of your IDE doing the heavy lifting, Vex runs silently in the background (via Docker Compose or local bare-metal). You point a GitHub webhook to it (or use the local file watcher), and it automatically ingests your repositories. When your agents need context, they simply query it in real-time via the Model Context Protocol (MCP). It works out of the box with Claude Desktop, Cursor, or any MCP client.

Now, the cool part (GitOps Memory):

It treats agent memory like version control. Vex reads conventional commits (feat:, fix:) to update context, and operational ones (roll:, branch:) to automatically fork or revert the agent's memory state. Zero manual intervention. It uses Tree-sitter to logically parse and chunk the code, keeping syntax trees intact.

I specifically designed this not to fry my potato PC. By using a pointer-architecture with SQLite for metadata queues and Qdrant for dense vectors, RAM stays completely stable. In my local stress tests, the async FastAPI + Huey architecture:

Swallowed 500 concurrent GitHub push payloads without a single SQLite lock.

Maintained real-time latency (under 300ms) under a 50-agent concurrent read swarm.

What's next?

I’m currently working on a Rust-based sub-chunking engine to handle massive monorepos even faster, alongside global GraphRAG, shared memory and more language support.

I decided it was time to share it and see who else might find it useful. I’d love for you to check it out, throw your code at it, and break it.

Here is the repo:

https://github.com/Shuuida/Vex-Skillgit.git

Thanks for taking the time to read!

Hey - I've been building Curate, a private bookmark library for developers (Chrome/Edge extension), and just made it open source under MIT.

The idea: save docs, repos, tools, and articles from a popup, file them into collections, and actually find them again later. No public feed - it's meant to stay a personal library, not a social bookmarking site.

Stack is Manifest V3 + vanilla JS on the extension side, Express 5 + MongoDB on the API, with an automated test suite running in CI.

I'm opening it up because I'd genuinely like help - there are 9 open issues, a couple labeled good first issue, and CONTRIBUTING.md / CODE_OF_CONDUCT.md / a roadmap are all written out if you want to see how contributing works before diving in.

Repo: github.com/DevOlabode/curate

Happy to answer questions about the stack or the extension architecture if anyone's curious.

Hi everyone,

I built a free, open-source map of STEM for my own learning. It covers 11 subjects, from maths and physics up to aerospace, and every chapter lists what you need to learn before it.

I'm hoping the community can take it up. It'll only be really useful if people who know these subjects check it and improve it. I used AI to help put it together, so I'm sure there are gaps and some prerequisites in the wrong place.

You don't need to code to help. Every chapter has "Report a problem" and "Edit on GitHub" buttons, and each chapter is just one small JSON file if you do want to send a pull request.

Repo (MIT code, CC BY-SA data): https://github.com/MohamedMuneerM/knowledge-navigator
Site: https://mohamedmuneerm.github.io/knowledge-navigator/

Any help is really appreciated, even just reviewing one chapter in a subject you know. Thanks!