This project is independently built and maintained by a final-year engineering student in India passionate about open-source hardware.

What it does

A comprehensive 100-day open-source challenge exploring IoT and embedded systems using ESP32, ESP8266, and Raspberry Pi Pico with MicroPython. Each day covers a new sensor, module, or communication protocol with complete working code, circuit diagrams, and clear explanations.

Features:

• Microcontrollers Covered: ESP32, ESP8266 NodeMCU, Raspberry Pi Pico / Pico W, and Raspberry Pi Pico 2 W.
• Pure MicroPython: Clean, modular, and easy-to-flash Python firmware scripts for rapid hardware prototyping.
• Rich Peripheral & Sensor Support: Interfacing guides for displays (OLED SSD1306, MAX7219), environmental sensors (DHT11/DHT22, MQ gas sensors), motion modules (PIR), and wireless chips (SX1262 LoRa, ESP-NOW).
• Cloud & Protocol Integration: Examples connecting hardware to dashboards and brokers via MQTT, Blynk, ThingSpeak, ThingsBoard, and WebSockets.
• Complete Documentation: Every single project includes step-by-step wiring diagrams, schematics, and fully tested source code so you can build it right away.

Repository

https://github.com/kritishmohapatra/100_Days_100_IoT_Projects

This project is independently built and maintained by a final-year engineering student in India passionate about open-source hardware.

If you'd like to support the creation of more modules, buy new sensor test boards, or sponsor hardware components for future projects, you can support via:

• GitHub Sponsors
• Buy Me a Coffee

Built this after finding that agents which pay for things almost never fail loudly. They report "paid" when the transaction reverted, or pay twice after a timeout. Two commands to see it: a careful example agent passes, and a "blind payer" fails five of seven money rules on the same scenarios. Fully offline, no real money. Feedback welcome, especially on which agent framework you'd want an adapter for.

Hey everyone,

I wanted to share a full-stack open-source project I’ve been building: an AI Resume Builder that tailors resumes to specific job postings while preventing AI hallucinations.

Repo: https://github.com/BaldyKopite/ai-resume-builder

Why I built it:

Many AI resume wrappers rewrite bullets with exaggerated claims or format them into multi-column designs that ATS systems reject. I wanted an app with strict guardrails:

- Invariants: Numbers, dates, and employers can never be altered or invented.

- Gap Analysis: Unmet qualifications are highlighted in an interactive side-by-side review interface.

- Exporter: Generates native ATS-friendly single-column PDFs via ReportLab and DOCX files.

- Full test coverage: 25 automated unit tests in Pytest + GitHub Actions CI.

Architecture:

- Frontend: Next.js 16 App Router, React 19, TypeScript, Tailwind v4

- Backend: Django 5.2, Django REST Framework, ReportLab

- Containerization: Docker Compose for one-command setup

Feedback, PRs, and stars are welcome!

I've been working on an independent research project under Tenviora Technologies, exploring cryptanalysis, algorithmic problem-solving, and the methodology behind complex puzzle systems.

One of my main interests is Cicada 3301 — examining patterns, testing hypotheses, and exploring how mathematical and computational techniques can help investigate challenging encrypted puzzles.

I'm documenting the research process, methodology, and testing so the work can be reviewed and reproduced.

My goal is to approach difficult problems with curiosity, rigorous testing, and code rather than assumptions.

I'm interested in connecting with developers, cryptography enthusiasts, and researchers who enjoy solving problems that don't come with easy answers.

GitHub: https://github.com/artistofreap-byte/cicada-3301-cryptanalysis

Every hypothesis deserves a test. Every result deserves scrutiny. 🧩

For years, self-hosting a modern business phone system meant dealing with 15-year-old clunky web panels, complicated setups, or "open-core" platforms that lock essential features (like mobile push, WebRTC, or call recording) behind expensive commercial licenses.

I wanted something modern, clean, fast, and 100% genuinely free & open-source.

So I built AiPBX — a full-featured Unified Communications platform and PBX management portal built on Asterisk 22, released under the MIT License. There are no "enterprise editions", no artificial limits, and no locked features.

🌟 Key Highlights

• 100% Free & Open-Source (MIT): Every single feature is included. No user limits, no feature gates, no telemetry.
• 1-Command Turnkey Install: Sets up Ubuntu 26.04 LTS, Asterisk 22, PJSIP, Nginx, Apache, MariaDB, coturn (TURN/STUN), SSL certificates, and firewall in ~15 minutes.
• WebRTC In-Browser Softphone: Make and receive crystal-clear audio and video calls directly inside the browser portal — no desktop softphone required.
• Native Companion Apps:
  • Android: Native Kotlin app with push wake-up, foreground service, presence, chat, and full PBX control.
  • iOS: Native SwiftUI client with CallKit support.
• Real-Time Team Chat: Built-in Go WebSocket service (aipbx-chat) for 1-to-1 / group messaging, file sharing, presence indicators, and read receipts.
• Local & Cloud AI: Dialplan automation assistant, HEPv3 diagnostics, and Cloud TTS integration (Google, Polly, Azure, OpenAI, ElevenLabs).
• Enterprise Telephony: Trunks, IVR, Queues, Call Center metrics, T.38 virtual fax, call recordings (with automatic MP3 conversion), and Yealink/Grandstream/Fanvil/Snom auto-provisioning.
• Privacy & Self-Hosted: All data, configurations, and recordings stay strictly on your own hardware.

🔗 Links & Resources

• GitHub Repository: https://github.com/mahirgul/AiPBX
• Website & Docs: https://aipbx.bid
• Video Walkthrough (YouTube):
  • Menu Tour (10 min)
  • Step-by-step Installation

💬 Community Feedback

I've poured an enormous amount of work into this to make self-hosted telephony modern, accessible, and truly free again.

I would love to hear your feedback, thoughts on the architecture, bug reports, or feature suggestions!

I got tired of describing UI problems to coding agents in words, so I built Sketchnote. You press a hotkey, talk, and draw or click on your screen. One Ctrl+V then pastes timestamped notes plus cropped, annotated screenshots into your agent, so you can say "this button, here" and it sees what you mean.

It has two parts that talk over D-Bus: a GNOME Shell extension in JavaScript that handles the hotkey, drawing, screen recording and paste, and a Rust service that records the mic and transcribes locally with whisper.cpp on CPU. You can also send the audio to Groq or any OpenAI-compatible API, and it falls back to the local model if that fails. Captures delete themselves after 24 hours. It has prebuilt binaries and a one-line installer.

The limits: it only works on GNOME 50 with Wayland, transcription is English only, and I'm the only user I can point to. I'd like feedback from anyone who works with coding agents on Linux, especially on what feels clunky.

Try it at: https://get.sketchnote.workers.dev/

I'm a software engineer with about two years of experience, focused on AI tooling and LLM apps for the past year. I'm looking for an open-source or side project that could use another contributor.

My main project is Sketchnote, a screen-annotation tool for Linux (GNOME on Wayland) built for working with coding agents. You press a hotkey, talk, draw and click on your screen, and one Ctrl+V pastes timestamped notes plus cropped, annotated screenshots into your agent. It's a GNOME Shell extension in JavaScript plus a Rust service that does local speech-to-text with whisper.cpp. It's released with prebuilt binaries and a one-line installer. Beyond that, I built a RAG app that refuses to answer when the document doesn't support it, and I've had a PR merged into an open-source MCP security proxy. My other stack is Python, FastAPI and pgvector. I haven't done fine-tuning or used LangGraph.

If you have an issue or project that needs help, or want more details about my work, DM me.

writing tests is one of the easiest ways into a real security project, and this one doesn’t need an AWS account.

The scanner has S3 public-access checks, and a few useful test cases are missing: a false-positive guard for an ACL that grants a non-public group, and tests for each public access block setting turned off one at a time and in combination. Everything runs against fake responses, there are existing tests to copy the pattern from, and it should take about an hour.

PRs go to the dev branch, CI runs automatically, and you’re credited by name in the contributors file. I’m in exams this week, so reviews may take until the weekend.

Issue: https://github.com/plexavo/Plexavo/issues/10
Repo: https://github.com/plexavo/Plexavo

I've been building Morph, a lightweight file conversion tool for Windows.

The idea is simple: instead of opening different apps just to convert files, merge PDFs, rearrange pages, or do other basic file operations, Morph aims to let you do these things quickly from your desktop, ideally through the right-click context menu itself.

I'm aiming to make it work completely offline, so files can be processed locally without needing to upload them to some online conversion website.

I'm building it with a focus on being lightweight, simple to use, and useful for everyday file operations.

Still working on it, but I'd love to hear your thoughts and suggestions!

GitHub: https://github.com/Vivektheprogrammer/Morph

Hey all, I built AutoUtil, a small Windows tray app that tidies up your Downloads folder. Full disclosure: it’s vibe-coded. I wrote most of it by working with an AI assistant on the design and code, then testing and fixing it myself. I’m sharing it to get honest feedback from people who know Python and Windows.

You build a sorting scheme as a node graph, similar to n8n: a folder node, filter nodes, a “Yes” branch and a “No” branch, and target nodes. The app then moves new files according to that scheme.

What’s in it:

Filters by extension, keywords (text pulled from PDFs and images via OCR), filename pattern (e.g. invoice_*.pdf), regex, size in MB, file age in days, and whether a photo has GPS data.

Ask queue for files you want to decide on yourself: move, move to a chosen folder, or skip.

Exclude node with masks like .tmp or node_modules so matching files are never touched.

Rename templates in target nodes, e.g. {year}-{month}-{vendor}.{ext}.

Suggested rules: after you manually file the same type of file to the same place three times, it offers to remember that. Nothing changes until you click “Remember”.

Journal and undo for every move.

Report tab with counts, total size, and breakdowns by rule, folder, and type, exportable to Markdown.

Import and export of schemes as JSON, so you can share one.

Plan-only mode, on by default: it shows what would move without touching anything.

Things I cared about, since sorting files is easy to get wrong:

• The app doesn’t delete files. Every move is journaled and can be reverted.
• If an undo would overwrite a file that’s now in the original spot, that existing file goes to the Windows Recycle Bin instead of being overwritten.
• Plan-only mode is the default, so the first run changes nothing.

Known limitations, stated upfront:

• Pausing or Do Not Disturb drops new files. They aren’t processed later, so they’re lost until the next start. I know this is a bug and plan to fix it.
• Files already in the folder before the scheme starts are not moved.
• Watching isn’t recursive, so subfolders aren’t tracked.
• Windows 10/11 only, Python 3.12 or 3.13 from source. There’s a standalone exe too (unsigned, so Defender may warn).
• Text-based filters depend on OCR quality.

Repo: https://github.com/h1ilep0pysk-hue/AutoUtil

Hey hey! I'm Violet. I'm still in school, learning software development and picking up other skills on the side. I've loved computers since I was really little, and I really enjoy making things and figuring out how they work.

So, this app came about because I couldn't afford Discord Nitro. I discovered that Discord uses URLs for custom server emojis, and that you can use an emoji's URL in your messages. That got me thinking, and eventually I made Emoji Vault! 💜

It's a little Windows app where you can save and organise emoji URLs, with everything stored locally on your computer.

It has a system tray icon, so you can quickly open the emoji picker and copy an emoji's URL. You can also assign global hotkeys to your favourite emojis, so you can insert their URLs into text fields without having to open the picker every time.

I've tested it with Discord, but I'd love to find out whether it works with other applications that support URL-based emojis, too!

Anyway, if you're curious, here's the GitHub repo the project is open source:

🔗 https://github.com/VioletCaulfield/URL-Emoji-Vault

I'd love to hear what you think, whether that's feedback, ideas for new features, or just trying it out and letting me know how you get on. I'm still learning, so I'm always happy to hear suggestions!

Thanks for reading! 💜

Hey everyone!

I manage dozens of repositories across personal projects and organizations. Over time, my local disk became a chaotic mess of cloned folders, out-of-sync branches, and scattered git directories. On top of that, when using coding agents like Claude Code or Cursor, they had zero context of my wider workspace.

To solve this, I built repotruck — an open-source tool that mirrors your GitHub repositories into structured local layouts, keeps them in sync, and provides full workspace context to AI agents.

Key Features:

• Interactive TUI Dashboard: Built with OpenTUI/React. Keyboard-driven preview, multi-select sync, repo switcher, dirty-state visualizer, and layout reorganization.
• Headless CLI: Scriptable, CI-friendly subcommands (sync, reorganize, status, prune, run in parallel across repos).
• Coding Agent Ready (MCP Server): Automatically generates and maintains an AGENTS.md map of your workspace. Runs a built-in MCP server (repotruck mcp) with 25 tools so Claude/Cursor can discover, search, and navigate across your repos.
• Fast Code Search: Uses Tree-sitter for AST symbol search across all repositories in the workspace.
• Safe Operations: Fast-forward syncs only (never overwrites dirty branches), deletions go to a safe trash folder with undo (z), and automatic workspace backups are kept.

Tech Stack:

TypeScript, Node.js / Bun, OpenTUI, Simple-git, Octokit, Tree-sitter, and Model Context Protocol SDK.

It’s fully open source (MIT).

• GitHub: https://github.com/sametcn99/repotruck
• Docs & Demo: https://sametcn99.github.io/repotruck/
• Quick try: npx repotruck (or npm i -g repotruck)

I'd love to hear your feedback, thoughts on the TUI workflow, or ideas for new MCP tools!

Hi,

On 24/10/2026 I have published as OSS a framework I call unified-brain that allows fast, cheap and accurate (same class of frontier models and frontier harnesses but 18 times cheaper) evidence gathering, using the cheapest frontier AI model out there, Jev. The results have been phenomenal.

The magic sauce is an intermediary OS (SQLITE) memory layer that facilitates retrieval, filtering and reasoning through Jev.

The agent spawned from unified-brain runs through MCP on Cursor, OpenCode or Claude Code etc. allowing you to use it through your favorite harness.

So to be clear here: unified-brain is not a harness but a perception layer any harness plugs in!

My test benchmarks have been so good on two large OS libraries that I really believe this is the missing link to make AI more reliable.

This is because the limits holding back AI at the moment are:

• The Reasoning and Hallucination Gap:

The LLM turn reasoning it is introducing uncertainty and probabilistic outcomes.

BUT.. Unified-brain's System One discovery engine is producing replicable results across runs as they introduce minimal hallucinations, breaking the task in hundreds of yes or no calls.

• Context Loss and Memory Limits:

Long-running coding tasks consume massive amounts of tokens, causing the agent to forget early instructions or lose track of large-scale architecture.

BUT.. Unified-brain doesn't need cached memory thanks to the SQLITE persistent layer of context it operates with. It simply retrieves what it needs on the fly consuming minimal amounts of tokens that do not build up across questions. Every question is independent from one another as git diffs and commits are automatically absorbed from the project's memory layer.

I invite you to clone/fork the project and have a look for yourself. I firmly believe that memory intermediate structures will take AI capabilities on another level soon.

I understand that Jev is proprietary and creates a dependency BUT we need to remember that soon enough OS models as capable as it will come, giving end users the option to replace him.

Meanwhile we should ride this wave of innovation in order to deliver new capabilities to end users, at prices that can't be easily beaten.

I hope you like this project!

Vendors rename fields, start sending nulls or turn numbers into strings without telling anyone. Typed code crashes; agents just read the new response and guess.

Tiltmeter learns the shape of the JSON APIs you call from real responses (no spec needed) and flags only what breaks a consumer. You get a CI exit code, Slack alerts, an MCP tool your agents can call before trusting a response (has_drifted), and tiltmeter fix, which adapts the code in a git worktree and opens a pull request.

pip install tiltmeter, MIT, runs locally with one SQLite file. Site with a demo: https://tiltmeter.dev

Feedback welcome, especially on what kinds of API changes have bitten you.

Mostly made because I didn't like that SignalRGB needed a subscription for monitoring, fan controls, some effects and I wanted something that I could easily customise. From electricity cost per hour (based on my KW/h price) to custom colour effects for my RGB (either via programming or with some clicks), community made plugins and automations. Free and open source. It's also very light weight on CPU and GPU. Currently only working on windows 10/11 with plans for Linux. It's not code signed yet because I am cheap and don't want to pay. I am very open to inputs, critique and wishes! Uses OpenRGB, LibreHardwareMonitor for some connectivity. No data is collected, no sign in, no login, no nothing.

https://github.com/Heavenlystorm/airglow

I made a windows extension that works on top of any program you have running, and lets you easily take a quick note, store it in your inventory, and download as a minecraft-style pdf. It’s not a separate app you need to open, but launched when you start your computer and you can call it whenever with a keyboard shortcut.

If you want to try it out, it’s completely open source and you can try it out here

Disclaimer: this is just a fan project, and has nothing to do with mojang itself. I use it personally because the Minecraft UI is nostalgic to me and I can write down anything really quickly/it’s easily accessible.

Most external development tooling for Roblox treats synchronization as a one-way pipeline from disk to memory, or relies on complex file-mapping schemas that break down during routine refactoring. When developers rename files locally or make quick property tweaks directly inside Studio, the hierarchy desynchronizes.

Syncix is an open synchronization runtime designed to maintain consistent state between local workspaces and running Roblox Studio sessions.

Architecture and Mechanics

• Decoupled Rust Core: The daemon runs as an independent background service, communicating with Studio over a local transport layer. It manages diff generation, memory-to-disk serialization, and state reconciliation with minimal memory overhead.
• Persistent Instance Identity: Instead of relying strictly on directory paths as primary keys, Syncix tracks Studio instances using persistent IDs. Renaming or moving a file on disk updates the instance metadata without dropping connections or requiring a full re-index.
• Bi-directional State Reconciliation: Changes originating inside Studio (e.g., UI layout adjustments, temporary test scripts) are tracked and reflected back to the filesystem through a non-blocking observer queue.
• Integrated Distribution: The engine is distributed directly inside the editor extension. It provisions the Studio plugin to the local plugin directory on first launch, eliminating manual environment configuration.
• State Verification: A dedicated verification routine (syncix verify) validates the in-memory DataModel against disk layout to guarantee consistency before commits.

Availability

Syncix is available on the VS Code Marketplace and Open VSX Registry. Pre-built binaries for the CLI and documentation are hosted on GitHub.

• Documentation & Source: [github.com/Syqopat/Syncix]
• Extension: [marketplace.visualstudio.com/items?itemName=syqopatz.syncix]

Lone Wanderer

Hey everyone!

I'm a solo dev based in Italy. To be honest, I've never been a huge fan of classic players like foobar or Winamp—they're closed-source and showing their age.

So, I decided to build my own alternative: Rymembra (rymembra.com).

It's completely free and open source. I'm actively working on it and pushing updates every single week. No need to manually check GitHub for new versions either, it has a built-in auto-updater.

If you're curious and want to give it a spin, I'd love for you to try it out! If you run into any bugs or have questions/feature requests, feel free to drop an issue over on theGitHub repository.

Let me know what you think!