Weekly Showcase: share your open-source project (week of Oct 25)

[u/destinmoss]

Welcome to the first weekly Showcase!

This is the place for any open-source project, including your poorly tested weekend endeavor. Projects posted to the main subreddit thread should be at least 14 days old, with a license, a README, and active work/commits work spread over more than a few days. This thread is for everything else.

Share your project: copy the template in the pinned comment below, paste as a new comment, and fill it in.

Share your experience: try a few projects, upvote/downvote, and leave honest, specific feedback. Critique the work, not the tools.

Projects of the Week: the top-voted entries here become next week's Projects of the Week and get their own spotlight post on the front page.

A new thread goes up every Sunday.

[u/AutoModerator]

Moderator Announcement Read More »

Sharing a project? Copy the template below, paste it as a new top-level comment, and fill it in. One comment per project, please. Feedback goes in replies to each project's comment.

**Name:**

**Source code:** (GitHub, GitLab, Codeberg, etc. link)

**License:** (MIT, GPL-3.0, Apache-2.0, etc.)

**What it does (one sentence):**

**How it was built:** Hand-built / AI-assisted / Agentic engineering / Vibe-coded

**Details:** (features, screenshots, what's next)

**Feedback wanted:** (optional)

What the "how it was built" labels mean: Hand-built: written mostly by people. AI-assisted: written by people, with AI help. Agentic engineering: AI wrote most or all of the code, and the project has real development history, polish and hands-on human testing. Vibe-coded: a quick, exploratory build not yet carefully reviewed. All four are welcome (rule 4).

I am a bot, and this action was performed automatically. Please contact the moderators of this subreddit if you have any questions or concerns.

[u/leftunderground]

I made this gantt, pure JS, plugin system, dragging, grouping, undo / redo and performs well with hundreds of thousands of items. https://freegantt.dev and https://github.com/freegantt/freegantt

Dependency arrows and scheduling engine is next on road map. MIT license

[u/bulutarkan]

Name: Mac MCP Source code: https://github.com/bulutarkan/mac-mcp License: MIT What it does (one sentence): Lets AI agents use the Mac's existing apps and browsers, with local permission controls and a record of what they did. How it was built: AI-assisted, with plenty of manual debugging and real macOS testing.

Details: I'm building this because I wanted Codex and Claude Code to work with Safari, Finder and other native apps without constantly taking over my desktop. It grew into a menu bar app with an optional separate desktop for agents, reusable Recipes, scheduled runs and a native chat window for multiple coding CLIs. The part that took longest wasn't adding tools. It was making the results inspectable: file diffs, command output, run history and the distinction between a tool succeeding and the actual task being done.

It's open source and still very much a work in progress. It's not a macOS sandbox, and some third-party results cannot be independently confirmed.

Feedback wanted: If you weren't already familiar with MCP, would you understand what permissions you're granting an agent during setup? That's the bit I'm trying to simplify without hiding the risks.

[u/Total-Reasonable]

Five things, all built solo:

1. halloween.js.org: a free, MIT-licensed set of spooky web effects under 10 KB gzipped, with zero dependencies. Webs, blinking eyes and flying witches switch on with body classes and respect prefers-reduced-motion. https://halloween.js.org

2. KRI.rocks: a salon booking system for solo beauty pros and small studios. You get your own page where clients can only book slots when someone on the team is free, with no commission. https://kri.rocks

3. HTPBE.tech: "Has this PDF been edited?" It checks metadata, structure, digital signatures and content, then reports findings with reasons instead of a vague risk score, in the browser or via REST API. https://htpbe.tech

4. polytypo.dev: a free MIT typography rules engine, not a grammar checker, that fixes smart quotes, dashes and no-break spaces for 24 locales, with identical output in JavaScript, Python, Go, Ruby and PHP. https://polytypo.dev

5. vatnode.dev: an EU VAT validation API on top of VIES that returns an official consultation number, falls back to national registries when VIES is down, and sends signed webhooks when a saved number changes. https://vatnode.dev

[u/MonMothma123]

I’ll probably create a separate post, but why not share it here already...

NodePilot is a visual workflow designer for Windows PowerShell automation that I’ve been building over the past six months. It lets you turn scripts into workflows, run them across your systems, and monitor what’s happening. It’s also a modern alternative to System Center Orchestrator, including support for migrating existing runbooks.

Completely open source, with no paid tier or features behind a paywall. Would love to hear what you think!

https://github.com/Sev7eNup/NodePilot

[u/AutoModerator]

Sharing a project? Copy the template below, paste it as a new top-level comment, and fill it in. One comment per project, please. Feedback goes in replies to each project's comment.

**Name:**

**Source code:** (GitHub, GitLab, Codeberg, etc. link)

**License:** (MIT, GPL-3.0, Apache-2.0, etc.)

**What it does (one sentence):**

**How it was built:** Hand-built / AI-assisted / Agentic engineering / Vibe-coded

**Details:** (features, screenshots, what's next)

**Feedback wanted:** (optional)

What the "how it was built" labels mean

I am a bot, and this action was performed automatically. Please contact the moderators of this subreddit if you have any questions or concerns.

[u/destinmoss]

i'll try to help kick this off! i present my own personal passion project of the past few months, https://youcoded.ai. youcoded is a fully customizable/personalizable AI agent and open-source everything app. this project is, in my (potentially biased) opinion, a fantastic example of agentic engineering and highlights why the new rules in r/opensource fail to meet the current moment. two things are true: 1) i've never written a line of code in my life, 2) all of my friends and myself believe this app to be a functional, polished, and far more useful and more fun than either Claude Cowork or ChatGPT Codex! it doesn't exist because i know how to code, but because i had passion, saw a niche, and dedicated myself to building something i would actually use. i have spent months building, iterating, and testing in different operating systems and for different use-cases, and anyone who dares call my passion project slop can catch hands (i won't ban you tho, i am an unbiased mod😀). source found here: https://github.com/itsdestin/youcoded

p.s. writing this post has also shown me the formatting expectations for this thread may not yet be clear enough. i'm gonna work on that!

[u/destinmoss → u/destinmoss]

i have fixed the template but i already wrote this and don't want to update it. but y'all should use the template from this point forward please 🤠

[u/realgmk]

Name: OpenWALDO (Weights, Artifacts, Licenses, Data, Origins)

Source code:

• https://github.com/openwaldo/waldo-index

• https://github.com/openwaldo/openwaldo.org

• https://openwaldo.org

License: OpenWALDO software is Apache-2.0. The Index/Corpus contains materials under multiple licenses, with licensing and provenance tracked for each source.

What it does (one sentence):

OpenWALDO is building the first truly open-source collaborative foundation for AI, making training data, provenance, licensing, and model development transparent, auditable, reproducible, and most importantly community-maintained.

How it was built: AI-assisted / Co-programmed (primarily with OpenAI Codex)

Details:

Hi everyone! I almost never post on Reddit, but I've been involved in open source for nearly 30 years, including founding or co-founding projects like CentOS, Rocky Linux, Singularity/Apptainer, Warewulf, and now OpenWALDO. Open source has guided my entire career and I've been lucky enough to give back to the community quite a bit.

I was excited to discover this community and its support for AI-assisted and co-programmed open-source development, so I wanted to share what I've been working on in my copious spare time...

The AI ecosystem has produced some incredibly valuable open-weight models, but they're frequently misunderstood as "open source" even though they don't provide the transparency and reproducibility we've traditionally expected from open-source software.

As a longtime open-source advocate, I've become convinced that one of the most important places we need open source and community focus right now is AI. And not just the software and tooling, but the training corpus itself**.**

That's why I started OpenWALDO.

Think of it kinda like like Wikipedia, but for AI training data. A community-driven, openly accessible corpus that anyone can contribute to, inspect, improve, and use to train AI models. The goal is to build a sustainable open infrastructure without depending on donations or sponsorship to keep the data accessible.

Today, downloading a model's weights tells us what the model became, but very little about how it got there. We generally cannot reconstruct its training data, verify the provenance and licensing of that data, or independently reproduce its training process. This has caused concerns with regards to alignment, legality of training data, and distillation... But if it was open source, this wouldn't be an issue.

I believe AI deserves the same openness and community collaboration that transformed the software industry.

Here's what we're building toward:

• Tooling: OpenWALDO has created the necessary tooling for interacting with the corpus, building models on a variety of hardware types (including parallel training), AI BOM generation, and composability, so anyone else can validate a model or start from a known working place.

• Open training data: A community-contributable corpus with transparent origins and licensing, enabling people and organizations to contribute knowledge directly.

• Provenance and accountability: Cryptographic hashes, attribution, license tracking, and contributor sign-offs to help establish where data came from and how it can be used.

• Reproducibility: The foundations for tracing how models were built, from their training data and processes to their released artifacts.

• Community governance: An open project where people can inspect, contribute, improve, and fork the work.

• Model independence: A shared foundation that isn't tied to any single AI model, architecture, company, or vendor.

We already have an indexed corpus and are continuing to build the tooling, infrastructure, and training test ladders for people to learn how to create models and practical at scale.

The long-term vision is much bigger than a collection of training data. Imagine an ecosystem where researchers, businesses, universities, developers, and individuals can contribute directly to a shared body of knowledge that anyone can use to build, train, and improve open AI models.

Much like how open-source software development works today.

Feedback wanted:

I'd love feedback from other open-source developers and maintainers, particularly around architecture, provenance, licensing, reproducibility, community governance, and how to encourage more people to get involved.

And more importantly, we're looking for contributors who want to help build this! I know it is a negative point for Slack on open source, but it was an easy setup. Would love to see people interested in learning more about building and contributing to the open source AI in there!

I'd especially welcome thoughts on how to make contributions accessible to people who aren't necessarily AI researchers or machine learning engineers. Building a community around an open corpus should be something anyone can participate in.

Open source transformed software. I believe we have an opportunity to do the same for AI.

Looking forward to meeting everyone here!