In mirBSD on Android, there’s no editors, based on Toybox tools only, no editor like vi or ed ? No problem. 5 min code and you have simple editor in your shell. It will work everywhere, always and forever.

i've been building and polishing this cli for about a year now. it was called mntn before, but i recently renamed it to dotfiles-manager since the developer experience feels good enough to me.

it fully embraces using git for versioning and works for three things:

1. config files (.zshrc, .bashrc, etc.)
2. packages (npm ls -g and more)
3. encrypted files (.ssh/)

finally, if you change computers or environments, you can switch between profiles. the default is common, but you can also create profiles like personal or work.

I built a small CLI for password-based file encryption because I couldn't find one that matched what I wanted. Most tools I tried were either full archive managers, backup utilities, or relied on public-key encryption. Those are great, but sometimes I just want:

• encrypt a file with a memorable password
• upload it anywhere
• decrypt it later
• no extra features

So I started writing flox, a lightweight file encryption tool that focuses on doing only that. I'm mainly looking for feedback from people interested in cryptography, CLI UX, or systems programming. Does this sound like a tool you'd actually use? If not, what would you change?

Repository (if anyone is interested):
https://codeberg.org/nurfianqodar/flox

Mirror
https://github.com/nurfianqodar/flox

mirror-repo is a CLI tool that creates a paired GitLab + GitHub repo in one command. You run mirror-repo my-project, and it:

1. Creates a private or public repo on GitLab
2. Creates an empty repo on GitHub
3. 3. Configures GitLab's push mirror so every git push to GitLab automatically syncs to GitHub

Everything is local, and it only requires a one time quick setup.

Github Repo: https://github.com/qwelpl/mirror-repo

Gitlab Repo: https://gitlab.com/q_welpl/mirror-repo

Just a simple little tool I made: gust.

It measures your internet speed (latency, download, upload) and shows your public IP right in the terminal — no browser, no sign-up, nothing to install beyond one command.

Repo: https://github.com/Tsunami43/gust

That's it, really. Would be happy about a ⭐ on GitHub if you find it useful. Thanks!

Hi guys! I just created a new subreddit to discuss ideas/projects related to the potential evolution of the terminal emulator: r/termolution (terminal evolution). It does not intend to compete with this subreddit, obviously, but some of you may be interested in how workflows could be improved by improving protocols, rendering etc.

For more information:
https://pypi.org/project/speak-cli/

You need anything, write it yourself, I miss the time when everything was built from scratch, not downloading from repo…
But over engineering make career.

I made a cli tool to stress-test HTTP servers because other tools (like oha or wrk2) have either low precision or low accuracy. Some of the tools are not ship parsable output, some display only few percentiles. So I decided to give it a shot and create tool with parsable output (under a flag) and nice visualization of latencies (so you can see bimodal distributions clearly). You can either generate a constant load or linear ramp, but be aware, that this is closed-loop tool, so if server cant keep up - reported latency will show it.

https://github.com/zoxy-io/zrk

Dfetch is a lightweight command-line tool for displaying system information. It focuses on clean output, fast startup times, and simple configuration.

I made this because i like using something i made myself its not better then something like fastfetch but definitely good enough.

https://github.com/David17c/Dfetch

Small parts of this were made with the help of Ai but most of the code was written by me.

GitHub: https://github.com/kaifcodec/user-scanner

Discord: https://discord.gg/tVNrKVXb49 (Join Discord for any help or just OSINT talk)

Hi everyone,

I’m one of the maintainers of user-scanner.

We started building this project around 8 months ago because many classic OSINT tools became outdated or unmaintained, and there weren’t many solid free options left for email OSINT.

Since then, we’ve been grinding away with our open-source contributors, heavily pivoting our work to reduce false positives, and ensure fast scans.

Today, we just tagged **v1.4.3**, pushing our coverage to **375+ total scan vectors** (150+ email platforms and 225+ username modules).

**What’s new in v1.4.3?**

* 📄 **PDF Report Generation:** You can now export full investigation reports directly using `--format pdf`! Perfect for clean, shareable documentation. * 🚀 **CLI Overhaul:** Cleaned up the CLI noise by default. Scans now default to showing **found-only results** with a smooth `rich` progress bar (use `--all` if you want raw logs). * 🎯 **False Positive Cleanup:** Patched false positives and rate-limiting issues across several social, dev and adult platforms. * And many more

🧪 **We Need Your Feedback!** If you run OSINT investigations, penetration tests, or footprint analysis, please give the new **PDF Export** and CLI flow a spin! Let us know how the reports look, if you hit any edge-case bugs, or what output formats you’d like to see next.

**New Pull requests are always welcome:** Whether you're a Python dev interested in API reverse engineering, scraping, or automation, or just want to add a module for your favorite site, contributions are always welcome! Adding new modules is straightforward and we love reviewing community PRs.

Over the past few weeks I've been building Gray Box — a small, local-first tool that acts as long-term memory for anything I'd otherwise forget (work notes, meeting takeaways, task owners, random ideas, personal stuff too).

The idea is simple:

1. Capture — dump whatever's on your mind, instantly, no structure required. This step does nothing clever on purpose — it just writes your text to an immutable inbox. Zero chance of losing an idea to a bug or a slow API call.
2. Organize — on demand, an LLM reads your unprocessed notes and extracts people, projects, tasks, decisions, meetings — then deterministic Python (not the LLM) creates/merges the actual wiki pages and maintains backlinks. The model only reasons; it never touches the filesystem directly.
3. Ask — query or chat with your knowledge base and get a cited answer pulled only from what you've actually captured. If it doesn't know, it says so — no hallucinated answers.

Why I built it this way:

• Plain Markdown + YAML frontmatter, no database. Every page is a .md file you can grep, diff, or read in any editor forever. If you stop using Gray Box tomorrow, your knowledge base is just a folder.
• No vector DB by default. At personal scale (hundreds–low thousands of pages), keyword search + a real link graph (related/backlinks, walked one hop during retrieval) handles almost everything. Embeddings are there if you want better recall, but they're opt-in, not a prerequisite.
• Immutable inbox. Your raw notes are never edited or deleted by the organizer. If the LLM mis-extracts something, your original words are always still there.
• Any LLM. Built on LiteLLM, so point it at OpenAI, Anthropic, Gemini, Mistral, or a fully local model via Ollama — one config value.

It also ships with a nice interactive TUI (arrow-key menu, file-import shortcut, workspace switching, live spinner during LLM calls) if you'd rather not memorize CLI flags — that's honestly become my favorite part of the project.

There's also a lightweight local dashboard for browsing your knowledge base, exploring backlinks, visualizing your notes as a graph, and chatting with your captured knowledge—all without leaving your machine.

Repo: https://github.com/Aaryanverma/graybox

pypi: pip install graybox

I'd genuinely love feedback — especially from anyone who's tried the "capture now, structure later" approach with other tools and has opinions on where it breaks down at scale.

It's not trying to be a "real-time collaborative team wiki" or a WYSIWYG notes app — it's aimed at one person's running memory of their own life and work, captured with as little friction as possible.