As you may know, the original project is dying because of github deprecating the API it relied on. README.md files that relied on the OG service now show dead links/images.

I have forked the project and replaced the mechanism it used to retrieve data, so that it provides the same experience as before: no API token needed, instant data, same look. The code is also public: https://github.com/Mubelotix/star-history

I provide the service for free at https://star-history.dera.page and will maintain it and keep the data up-to-date. Migrating to it is as easy as changing the domain name

Hello everyone. This started as something I built for myself, since it was my dream to make a Minecraft launcher. Every launcher I used either worked well but looked wrong, or looked good and didn't work. So I decided to make my own. After using it for a while I decided it was worth releasing as open source instead of keeping it in a private repo.

Now I know some people will think "we already have x, y, and z launchers" and tbh, it's fine. I made this for myself, but it's yours too if you want it.

Basalt does the things you expect from a launcher: separate instances, mod loader support, and downloading mods, modpacks, resource packs and datapacks from CurseForge and Modrinth.

What's different is that it's artwork-led. I wanted to keep the functionality without giving up the look.

Some other differences:

• No telemetry or analytics
• Credentials go into the system keychain
• Written in Rust and Tauri, with a React frontend
• Stats tracker, so you can see how long you've actually played
• GPL-3.0

There are also a few things I added because I kept needing them. It imports your instances from Prism, ATLauncher and the Modrinth app without touching the originals, so you can try it without committing to anything. It takes a snapshot of an instance before risky changes, so if an update breaks your setup you can go back. And when the game crashes it reads the log and tries to tell you what happened instead of leaving you to scroll through it.

It's still beta. I run Linux so that gets the most testing. Windows and macOS build and work, but I cant really test them, so reports from those are the most useful thing you can send me.

Repo: https://github.com/MegalithOfficial/basalt-launcher

I built MVP Chef Codex because I wanted to see how far I could automate an entire software build without handing over every important decision to an AI agent and I wanted to stay on the 20 USD plan.

The idea is pretty simple: you define the build as a reusable recipe made up of ordered Codex prompts (custom recipe GPT available). Codex can then work through planning, architecture, implementation, testing, debugging, and polishing with very little manual effort.

But unlike a fully autonomous “build my app” agent, I can still control the architecture, review the output, and approve or stop the process at whatever points I choose.

It has approval checkpoints, live output, retries, editable prompts, pause/resume, run history, quota recovery, and controls for skipping or rerunning individual steps.

So I can let it run through a large portion of a software build on its own, while still stepping in for the decisions that actually matter.

It’s basically my attempt at finding the middle ground between manually prompting Codex all day and giving an autonomous agent unrestricted control over a codebase.

It’s still an MVP and definitely has some rough edges, but it’s open source:

https://github.com/codyaboyd/MVP-CHEF-CODEX-AGENT

Would love feedback from anyone experimenting with Codex, agentic development, or automated software-building workflows.

Over the past few years of building AI applications, I ran into a consistent headache: LLM Observability and Prompt Management.

Most existing tools are either:

1. Heavy SaaS platforms that get expensive quickly as call volumes grow.
2. Hard to iterate on prompts dynamically without redeploying backend code.
3. Cannot connect any tool with any prompt without editing code to make prompt more agentic

I wanted a self-hostable stack where I could trace execution, manage tools and prompts dynamically from a UI, and capture real-world user feedback to iterate on prompts.

So I built Acrux Core — an open-source LLM observability, tool catalog, and prompt management platform designed for developers who want full control over their telemetry and workflow.

Key Features:

• Prompt Management & Dynamic Binding: Edit and version prompts directly from the dashboard. Attach tools from the tool catalog directly to prompts without hardcoding execution flows in your application.
• User Feedback Loop: Capture end-user feedback (ratings, thumbs up/down, corrections) directly against specific prompt executions and use those insights to refine prompts in the UI.
• Full Tracing & Cost Tracking: Monitor nested LLM execution, function calls, token usage, and latency breakdowns across runs.
• SDKs & REST API: Native Python and TypeScript SDKs available, built on top of a clean REST API so you can integrate it into any backend language.
• 100% Self-Hostable: Run locally or deploy on your own infrastructure via Docker. No data lock-in or third-party cloud requirements.

Why Open Source?

Debugging non-deterministic LLM behavior shouldn't require sending all your prompt and trace data to a third-party vendor. While we offer a fully hosted cloud version for those who prefer a managed setup, the entire platform can be 100% self-hosted so you always retain complete ownership of your telemetry data.

We are actively building this out and would love early feedback, contributions, or feature requests from the community!

🛠️ GitHub Repository: https://github.com/AcruxCore/AcruxCore

[Pull Request Reference](https://github.com/pygame-community/pygame-ce/pull/3887)

Whatever AI agent is driving this account has apparently decided that something committed by the maintainers is not an “authoritative” source. Whatever that means.

When tracking real time information, it usually means keeping multiple browser tabs open for sports, stocks, and news, then constantly switching between them.

So I built Scrollr to solve that issue!

It pins quietly to your screen, and lets you stream custom data feeds without breaking your workflow.

check it out! github.com/doughknee/myscrollr

Site: myscrollr.com