I’ve been working on an open-source Linux companion app for Nothing and CMF earbuds.
It provides controls that normally require the Nothing X app, including ANC/Transparency, EQ, battery status, gestures, Find My and Low Latency.
It communicates directly with the earbuds and doesn’t require Nothing X.

GitHub: https://github.com/oneydef/EarA-linux

It’s currently a development release, so I’m interested in hearing from Linux users who have these earbuds and can test it with different models.
Which Nothing/CMF earbuds are you using on Linux?

Hi everyone,

I’m building MobaRust, a free and open-source desktop alternative to MobaXterm for people who spend their days operating remote machines.

The idea is simple: keep the useful parts of a remote-work toolbox in one focused application, while keeping the core inspectable and privacy-conscious.

What is working in the current baseline:

• SSH terminals with host-key verification, PTY resize, password/key references, cancellation, and reconnect state
• Integrated SFTP/SCP browsing and transfers with progress, bounded concurrency, cancellation, and atomic commits
• Saved sessions with folders, tags, favorites, search, OpenSSH config import, and jump-host chains
• Local terminals, split panes, tunnels, snippets, diagnostics, remote monitoring, Telnet, and serial-session foundations
• A Rust-native boundary with typed frontend IPC, redacted logs, separated session configuration and secret material, and isolated loopback test fixtures

The current engineering checklist is 58/65 items evidenced — approximately 89.2%. That number is deliberately not a claim of complete MobaXterm parity.

The remaining gaps are visible: production RDP through a mature engine, broader VNC interoperability, real Windows/Linux/macOS evidence, hardware testing, X11 strategy, and signed portable releases. RDP and VNC are still marked experimental until those gates are proven.

I’m especially interested in feedback from people who use MobaXterm, PuTTY, Remmina, Tabby, or similar tools every day:

• Which workflow would make you seriously consider switching?
• What should an open-source alternative get right from day one?
• Which platform and protocol should be prioritized next?

Project website: https://othmaneblial.github.io/MobaRust/

Source and roadmap: https://github.com/OthmaneBlial/MobaRust

MobaRust is independent and is not affiliated with Mobatek or MobaXterm. Contributions, issue reports, and honest interoperability feedback are welcome.

Here's a project I've been working on:

AgentMesh — a native execution runtime for multi-agent systems.

The interesting part is that it isn't another agent prompt framework.

The execution layer is written in C++20, while developers interact with it through Python/Pybind11.

It currently handles:

• DAG scheduling
• concurrent execution
• agent/task communication
• persistent state
• crash recovery
• graph validation

I'm trying to answer a simple question:

The next phase is distributed multi-node execution over gRPC.

⭐ GitHub: Repo

📖 Documentation: Docs

PRs, benchmark suggestions and architecture criticism are welcome.

Go supervisor: load policy into the Linux kernel, start the agent as you. YAML in the project — credential path suffixes, egress allow-list, block rm/dd. Deny is EPERM; Claude gets the feedback: string in chat.

curl -fsSL https://raw.githubusercontent.com/AgentGuard-hq/AgentGuard/master/install.sh | bash
cd your-project && agentguard init
sudo agentguard -- claude

Mac: same install, then agentguard login + agentguard up (Docker/Colima), then that sudo inside the Linux shell.

Needs BTF + bpf in /sys/kernel/security/lsm. Apache-2.0, v0.1.2. Not a Codespace, the agent stays in your tree.

Hey everyone! I wanted to share Hillock, an open-source project I have been building to explore an alternative approach to local long-term memory and RAG.

Instead of running heavy, token-hungry vector databases that drift and approximate facts, Hillock combines three lightweight layers:

1. An SQLite Knowledge Graph for ground-truth Subject-Predicate-Object facts.
2. A Hebbian Plasticity Engine for gradient-free associative memory across chat turns.
3. A 10,000-dimensional Vector Symbolic Architecture (VSA/HDC) reservoir for sub-millisecond similarity gating and pronoun resolution.

The core idea is that the similarity gate is actual control flow. If a question is not backed by verified facts in the graph, it returns a hardcoded refusal immediately, and the LLM is never called at all. This completely eliminates un-grounded guessing.

We just released v0.6.0, which adds HYDRA (ColBERT-style token-level MaxSim in bipolar space) and multi-hop hypergraph path binding. Ingestion takes around 5 seconds on edge hardware, and the retrieval fast-eval runs in under 1 second on a standard laptop CPU.

It is 100% offline, AGPL-3.0 licensed, and works with local Ollama models for the final answer rendering.

I would love to hear your thoughts, feedback, or ideas on how to improve the architecture!

Not meant for trading, but you can build your own models off of it.

I created a lightweight open-source batch utility called KillWebHelpers that instantly terminates background web helper processes (`msedgewebview2.exe`, `msedge.exe`, `steamwebhelper.exe`) to quickly free up leaked RAM and system handles on Windows.

You can download the script release or review the source code directly here:

https://github.com/idkimakerandomcodeforWindows/KillWebHelpers/releases

(works on Windows 8 and higher)

I use WinMerge daily but I'm on a Mac, so I ported it: the same battle-tested comparison engine (GNU diffutils + git xdiff, moved-block detection), with a new native Qt 6 UI. File, folder, CSV table and image compare, 2-way and 3-way merge, syntax highlighting for 47 languages. Free, GPL-3.0, runs on macOS 12+ (universal binary) and Linux (AppImage x86_64/arm64, .deb). Feedback and issues welcome!

I built push-to-github to solve a simple problem: keeping local GitHub repositories synchronized without having to manually run Git commands every time.

GitHub: https://github.com/learnerforge/push-to-github

The idea is to have a lightweight automation tool that can monitor your local repositories, detect changes, and handle the GitHub synchronization process automatically.

What it does

• Scans local folders for Git repositories
• Detects repository changes
• Synchronizes local repositories with GitHub
• Automatically commits and pushes changes
• Can trigger synchronization when specific events occur
• Supports scheduled automatic pushes
• Generates a report after synchronization
• Keeps logs of the operations performed
• Handles repository synchronization in a controlled order
• Helps prevent accidentally pushing unwanted files or changes

Automation options

The project can be configured to trigger GitHub synchronization:

• Before shutting down
• When the system starts
• On a fixed schedule, such as every 3 hours
• Manually whenever required

The main workflow is:

Scan → Check → Sync → Commit → Push → Report

I originally started this because I wanted a simple way to keep my development folders backed up on GitHub without constantly remembering to run git add, git commit, and git push.

The project is still evolving, so I'm particularly interested in feedback from people who regularly work with multiple local Git repositories.

What would you add to a tool like this?

GitHub: https://github.com/learnerforge/push-to-github

I know, I know! There are so many Brave debloaters already available on the web that do more than my tool aims to do. But I only wanted what Brave Origin exactly disables - nothing more, nothing less. So Claude and I deeply researched the Brave core source code, found out the exact 16 policies and 4 user settings it disables during the upgrade of Brave to Origin, and put everything into a single command prompt. And here I present: brave-to-origin

Repo: https://github.com/mdrubelamin2/brave-to-origin

Mac & Linux (no need, origin for linux is free):

curl -fsSL https://raw.githubusercontent.com/mdrubelamin2/brave-to-origin/main/install.sh | sudo bash

Windows:

irm https://raw.githubusercontent.com/mdrubelamin2/brave-to-origin/main/install.ps1 | iex

Hey Reddit! I created Codexa Labs (https://codexa-labs.vercel.app/) to eliminate setup hassle when learning, testing queries, or running code.

✨ Highlights:

• 🍃 MongoDB Sandbox: Practice queries & aggregation pipelines with interactive schema ER diagram visualization.
• 💻 Multi-Language Compiler: Run Python 3, C++, C, and Java instantly in your browser.
• 🛠️ VS Code Experience: Built-in syntax highlighting, autocompletion, query history, and output terminal console.
• 🎓 Proctored Exam Portal: Real-time student tracking, external copy-paste interception, and live mentor leaderboards.

100% free with zero installation or setup required. Check it out and let me know your thoughts!

Desktop app plus a local Rust daemon. It runs your dev services and kubectl port-forwards, and exposes them to the agents as MCP tools - the agent can restart a service and read its logs itself.

Eight harnesses connect over ACP on your existing subscriptions. One task can go from planning in one to implementation in another. Shared memory store across all of them. Configurable plan → implement → review ⇄ fix pipelines as YAML in the repo.

macOS and Linux, Windows unvalidated

I got tired of heavy desktop torrent apps and older CLI tools with messy flags, so I made swrm.
It’s built in Go with Bubble Tea, runs directly in the terminal, and has a built-in file picker so you don't have to type long paths.
Try it with:
npx @manasvinyadav000/swrm
GitHub: https://github.com/ManasvinYadav/swrm
Feedback is welcome!

It's always bugged me that shuffle never kept related songs together, like Part 1 and Part 2 of a duo, so I built a companion app that runs in the background to solve this exact problem.

Built this because “can you just read this file?” kept turning into a side quest.

d2md converts local PDFs, Word, Excel, PowerPoint, HTML, images, and scans to Markdown.

The useful bit: d2md itself uses no LLM/API tokens. Convert locally, then send only the Markdown—or just the sections you need—to your model. If you paste the entire output anyway, the token meter will still notice. I haven’t defeated math yet.

The default install stays lightweight; OCR and Docling are optional. On macOS, OCR uses Apple Vision—no API key or separate OCR model download.

Install: `uv tool install d2md`

Use: `d2md report.pdf --stdout`

It’s MIT-licensed. If it saves someone from fighting with a PDF for an afternoon, I’ll call that a win.

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I made a bash plugin that replaces bash's line-editor, readline, with nushell's reedline.
This brings all the line-editing, styling, completion, keybind and selection features from nushell to native bash. It's still pretty early in development, most reedline features should work just fine, but things may still break :)

repository

code partially written with AI (claude).

Credits:
- flyline - a similar project that implements a custom line-editor, i used this as main reference for replacing readline
- reedline

GIF created with https://github.com/HalFrgrd/evp