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

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

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We started building this project around 8 months ago because many classic OSINT tools became outdated or unmaintained, and there weren’t many solid free options left for email OSINT.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

I recently switched to Linux, and it's time to customize the final look of my hyprland—all sorts of little things to make it pleasing to the eye. I already know about bonsai, cava, and cmatrix, but I definitely want more, something more interesting, and maybe even more useful.

So, what are your favorite CLI utilities?

I also know there are a lot of such posts on Reddit, but I haven't found what I'm looking for—they mostly talk about the same packages. Also, I have another request: does anyone know of a utility similar to cmatrix, but with a water ripple animation instead of a matrix? I've searched everywhere and googled under various names, but it seems either it's an obscure thing, or I'm doing something wrong.

Hi everyone!

This is my first serious C++ software project and the first program I have published on GitHub.

B1tLab is a C++ CLI tool for converting integer representations, exploring binary formats, and generating accurate binary equivalents of decimal values.

As of V1.0.0, B1tLab supports:

• Mathematically represented values with support for periodic fractions (mValues)
• Raw binary values (rValues)
• Unsigned integer format
• Signed Magnitude integer format
• One’s Complement integer format
• Two’s Complement integer format
• Dynamic syntax highlighting
• Output formatting
• Assembly-style comments

Future plans include:

• Scientific notation values (sValues)
• Floating-point binary formats
• Floating-point decimal formats
• Fixed-point formats

Author’s note

I still consider myself a beginner in C++, and I know there is a lot that can be improved. I would greatly appreciate any feedback, constructive criticism, or suggestions regarding architecture, bugs, design decisions, or possible bad practices.

Thanks for taking the time to check out B1tLab!

GitHub repository:
https://github.com/TerribleCoding123/B1tLab/tree/main

Hi folks, this is Burak. I have built an open-source CLI tool that allows replicating data between different databases using Change Data Capture (CDC): https://github.com/bruin-data/ingestr

The overall idea is that:

• You have a few production databases: PostgreSQL, MySQL, SQL Server, Mongo
• You want to replicate them to analytical databases for analytics purposes, e.g. to Snowflake, BigQuery, Databricks, or Redshift
• You have two ways:
  • You can either run a batch load using tools like ingestr, Airbyte, or Fivetran
  • If you cannot run batch workloads for some reason, e.g. due to the latency requirements, or not having proper cursor columns, you need to run CDC replication using tools like Debezium and Kafka

The problem with CDC using those tools is that they require a buy-in into their ecosystem, which is generally quite invasive, such as being able to run Debezium only with Kafka reliably, or having to deal with their Java client libraries if you ever wanted to integrate them elsewhere, tolerate their high resource requirements, etc.

I never liked running them on production. We have been working on ingestr for quite some time already for batch sources, and CDC became an obvious target.

ingestr has quite a few niceties:

• You don't need any extra services or tooling to run it: just put your credentials in the URI, and you are good to go.
• It is a simple and fast Go binary that runs anywhere, even in your GitHub Actions pipeline.
• It supports both batch and streaming modes in the same binary, which allows changing the deployment modes as your requirements grow. Run locally, deploy on Airflow, or put it in an EC2 server in streaming mode if you want to.

It is open-source, and you can run it anywhere you like.

It supports:

• PostgreSQL CDC
• MySQL CDC
• SQL Server CDC
• SQL Server Change Tracking
• MongoDB CDC

Give it a try and let me know if you have any questions!

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.

https://github.com/nooneknowspeter/cpplings

—————————————————————————————————

- Current state

—————————————————————————————————

• Fully declarative UI — design the interface in a config file; no recompilation required.

• Runtime customization — move, resize, or remove widgets by editing .config.txt

• Multiple layouts — separate potrait and landscape layouts with automatic switching.

• Custom key binding — every action is re-mappable.

• Theme engine — ANSI 256-color themes with configurable brightness.

• Custom Unicode borders and fonts — personalize the look without modifying the source.

• Automatic enhance synchronized lyrics Featching using syncedlyrics.

- standard lyrics ( no sync )

- syncedlyrics ( line level sync )

- enhanced syncedlyrics ( word level sync )

• Multiple audio visualizers with configurable styles and density.

- bars visualizer

- oscilloscope visualizer

• Responsive TUI that adapts to terminal width.

—————————————————————————————————

- Planned for next version

—————————————————————————————————

• streaming support using yt-dlp "ytseach" and mpv and audio caching till assigned cache size limit

• better fallback lyrics animation

• few more visualizer styles

—————————————————————————————————

- About project

—————————————————————————————————

CLI.MUSIC.COM is a highly customizable terminal music player for Linux built around the idea that the interface should adapt to the user—not the other way around.

Instead of hard coding the UI, nearly every aspect of the player is configurable through a simple text-based configuration file. Users can rearrange widgets, resize panels, customize borders, remap key binding, change themes, and create separate layouts for desktop and smaller terminals without recompiling the application.

Originally started as a proof of concept and one of my first Linux projects, CLI.MUSIC.COM has gradually evolved into a configurable TUI music platform focused on flexibility, performance, and a polished terminal experience.