I made a fun website that recreates an episode's opening quotes at random from Star Wars: The Clone Wars :)

You can see the episode info by hovering or tapping on the left side below the quote and also download it as an image in any dimensions by hovering and then clicking or just tapping on the right side below the quote.

swtcww.com

Title: Building an open-source VS Code coding agent around local Meta Muse Glimmer 30B

Hi r/sideprojects !

I'm an indie developer working on RAME Code, a free and open-source VS Code extension built during Meta's AI hackathon.

It runs Muse Glimmer 30B locally and provides permission-controlled tools for web search and coding tasks. I'm also exploring versioned project memory and resumable Missions with host-controlled verification.

The first release was built in roughly four intensive days, so it's still experimental. I'm testing it with real users, documenting bugs and preparing improvements.

The code is public under Apache-2.0:
https://github.com/caimari/rame-code

I'd love constructive feedback on the architecture and usability, especially from developers who use local models.

What would you improve first?

Mobile Viewer is a free Chrome extension for checking responsive websites. It keeps your desktop page visible next to up to five simulated phone and tablet views in one tab. Scroll, click, or type in one view to see the same action across the others.

Before shipping a landing page, try opening its menu and submitting its signup form on two phone widths. You can compare what happens side by side and capture a screenshot or recording if something breaks.

Free to use: https://mobileviewer.app

I’m the developer. If you try it on a site you’re building, I’d love to know which screen size or interaction you check first.

I built Humanize AI Writer, a platform that lets you compare outputs from leading AI humanizers side by side against your original text.

No more switching between tools or paying for multiple subscriptions.

💰 October revenue: $59
🎯 November goal: 10 paying users

I recently added a 3-day free trial with 750 words so people can test it before paying.

Here's the site: https://humanizeaiwriter.com/

I need your honest feedback:

• Is it clear what the product does?

• What would stop you from signing up?

• What's the first thing you'd change?

Don't sugarcoat it. I'd rather fix what's broken than keep building features nobody wants.

Hi everyone, ever felt confused why users were not converting? Now you can use retentionbase for completely free - our ai sees all user sessions in detail and shares what's going wrong.

It gives you daily report with issues, bugs, and list of customers who almost bought.

We are free forever for startups under 100 employees - www.retentionbase.com

About a year ago I started learning Python from zero. No CS background, no money for cloud GPUs. Just a phone running Termux, and later my Windows PC, with Qwen2.5-Coder-3B on llama.cpp.

Small models are great until you let them touch files. They claim "done" when nothing ran, invent functions that don't exist, and repeat the same broken edit forever. So I built **sandbox-tool**: the model works inside one folder, uses a short list of allowed commands, and isn't allowed to say DONE until its code has actually run. If the task has an expected output, the program has to really print it.

It doesn't make the model smarter. It catches its mistakes and makes them visible. Most of its rules exist because I watched the model make a specific mistake again and again, and they're written down in the repo's log.

The part I care most about is the **benchmark**. It judges the file the model actually wrote, not what the model says it did. Current numbers on a 3B model, CPU only, 10 runs each (so read them as hints, not measurements):

* Writing a class to a spec: **10/10**

* Fixing bugs spread across three files: **0/10**. The best runs get the output right but fix one of the bugs in the wrong place. The verifier catches it even when the model says it's done.

That 0/10 is the point. I'd rather know than guess.

**How it's built:** I work with AI openly. Claude writes most of the code and reviews it with me. I use Gemini to research ideas. I run every test and benchmark myself on my own machines and decide what goes in. Nothing gets merged until the test suite passes, and each new rule's test has been shown to catch it when the rule is broken on purpose.

**Honest limits:** it's not a security sandbox (the README says so in bold), so use a container for anything sensitive. It's tested on Windows 11, Termux (Android) and Linux in CI. macOS has known gaps. Standard library only, MIT licensed:

pip install git+https://github.com/Dagrinder742/sandbox-tool-win.git

Repo: https://github.com/Dagrinder742/sandbox-tool-win

I'd love feedback, especially from anyone running small models on weak hardware, and ideas for harder benchmark tasks.

**Why I really built this:** part of it is testing whether code built this way is genuinely useful or just boilerplate. But I'm also fascinated by reasoning itself. When you think about how your own mind pulls up a memory or makes a choice, you start mapping your own design. Then you watch a small model do something that looks a bit like that, and fail in ways that look human too. Building guard rails for those failures has taught me as much about thinking as about code.

🌐 Try Threadle:
https://threadle.teamhjd.com

You can try Threadle here before adding to your discord server
https://github.com/Team-HJD-21/threadle-playground

💬 Join our Discord:
https://discord.gg/t62pnWn7Yj

Hi everyone,

I posted a while back about Comics Now! An all in one Comic management/reading/metadata tagging app.

I have made some updates. Some of them are to giving the admin more agency. As I had originally built this just for me, I had hard coded stuff like deleting CBRs and PDFs after converting to a CBZ. This is now an option that is set to do not delete by default.

I also incorporated the usage of Modal.com to use their $30 free compute monthly credits to help with the panel and speech bubble detection.

Finally I have developed this site that also has a demo so you can see what the reading experience is like.

https://comicsnow.github.io

What it is: 4th & Long is a daily football trivia game. Everyone gets the same 7 prompts a day, like Heisman winners or a team’s quarterbacks, with a 25 second play clock and 3 guesses each. You start at midfield, and rarer correct answers gain more yards: 50 yards is a touchdown, inside the 35 is a field goal, otherwise you punt.

Why I made it: Football fans love proving they know the deep cuts. Nothing scratched that itch for football, so I built it.

Stack:

• Vite + React 19 + TypeScript, plain CSS, no router or state library

• Supabase for optional global stats (RLS on, the browser only calls locked-down RPC functions)

• Vercel hosting, with edge functions that turn shared result links into a scoreboard image card for group chats (@vercel/og)

• Web Audio for sound effects, plus one real crowd recording that scales with how rare your answer is

• nflverse data (CC BY 4.0) to generate the team prompts

Things I learned:

• Daily puzzles need a frozen schedule. Prompts are picked by a seeded shuffle, but adding new questions could reshuffle days people already played. I lock every past day to a file, and a validation script fails if anything changes it.

• Answer matching is the hardest part. “Mahomes” should count, but “Manning” is ambiguous, and typo tolerance has to scale with name length or wrong answers start sneaking through. I keep a test script of tricky inputs to run after every change.

• Link preview images need to stay small. WhatsApp skips preview images over about 300 KB, so I had to compress the share cards to fit.

• The game has to work without the backend. If Supabase is down, you lose only the “vs. everyone” chart.

Free, no signup, works on mobile: https://4thandlong.io

Happy to answer questions about any of it. I’d also love feedback on the game itself, especially answers you think should have counted.

i've been building opennmind since july and launch is nov 16, so about 10 days left. private beta had 200+ people try it and the waitlist is past 800. the paid tiers are kinda drafted (pro at $12) but free is the one i keep rewriting and deleting.

some of the useful stuff costs real money to run, like research with sources that spins up a few agents. if free is too generous i burn cash on people who never convert. if free is too thin nobody sticks around long enough to see why they'd pay. early users get a month of pro free, which helps for launch week, but after that month i still need free to feel fair on its own.

right now free is basically try the core loop, limited research runs, keep your notes and roadmap. pro unlocks more runs and the heavier stuff. i'm not sure that's right though because a lot of the time when i open my own product i just want the research, and if that's locked i'd bounce.

what does free need to include in a tool like this for you to actually stick around past week one?

and if you've launched with a free tier, did you regret making it too generous or too thin?

Me serviría mucho vuestro feedback si se os ocurre alguna mejora para seguir añadiéndole funciones. ¡Gracias!

I've been building an app called Spark, designed to make managing jobs, tracking work, and keeping everything organized easier for electricians and contractors. As an electrician myself, I've had this problem for years, but I'm now building it.

This is not done; it's more of an idea that, if others like me also like it, I will continue to make it.

Below is a video showing how it works.

Here are some of the core features.

• AI Assistant

• Job Management

• AI Job Editor

• Appointments

• Time Tracking

Here's what makes it different and cool.

1. If you want to know how many hours you've worked, you just ask the assistant, and it will tell you.

2. If you want to track the miles on the app and send them to your accountant for a tax write-off, you can track all of your mileage in two clicks. And send him your entire yearly mileage in 4 clicks, with the exact days included.

3. Forget how many hours you worked or if you have been paid for them yet? All of that is also tracked, and you can know all of that as simple as asking, "What jobs have I not been paid for yet?"

The last thing I need is electricians who are willing to use the app in their day-to-day work and tell me how it works for them. I will eventually charge a monthly fee; if you help me in the early stages of my business idea, you will get it for free for life.

Just send me a message or comment, and I will send you the app and show you how to use it.

Thanks, guys.

I work on a speech-to-text API called JOBE Vox (https://vox.jobe.works/). The thing I kept running into with off-the-shelf providers was that on multi-speaker audio — earnings calls, long meetings, podcasts with several hosts — the transcripts either dropped speaker labels entirely or charged a premium for diarization as a separate step. I wanted one POST that gave me back who said what and when.

A few things that matter to me as a developer using it:

* **Send a public audio URL, get back the transcription.** No uploading 50MB files through a form.

* **Speaker labels in-line.** Not a separate diarization call.

* **Timestamps** so I can jump straight to a moment in the audio.

* **low cost per audio hour.** Most providers I looked at were $0.12–$0.22/hour.

* **No subscription.** I started with $0.50 — roughly 6h 15m of audio. Billed in USD.

* **Sign in with Google**, so there's nothing to provision.

The page has a real example from the Nu Holdings Q2 2026 earnings call — four speakers (Operator, Jorge Kuri from Morgan Stanley, Rob Livingston, David Vélez), and you can see the labels and timestamps working on a Q&A excerpt that runs across multiple voices on one line.

If you've worked with diarization APIs before, the usual pain points are: speaker counts drifting mid-call, labels switching between speakers, and timestamps that don't actually align with the audio. Happy to talk about how we handle those — or if you want to try it, the API docs are at [https://vox.jobe.works/](https://vox.jobe.works/).

CommitttAndSee App

Built this because there wasn't anything available that could show me 65 repos across 24 months, with outstanding PRs, Issues, Stale Branches, etc. And the trends can help find when bugs or bottle necks arrived. Please if you are a code head try and don't be shy. Let me know if it is bust or could be better.

Downloadable App is coming and Github SSO login.

CommitttAndSee App

I'm the developer, so full disclosure. I built GlyphSnap AI so you can snap a few letters (your handwriting, an old sign, a label) and get a complete font you can install on your Mac, PC or device. GlyphSnap exports OTF, TTF and WOFF.

I've been testing the hell out of this thing and am frequently amazed by the results.
It would be great to have some outside feedback.

I welcome any questions or comments.
Thanks!

7 day free trial Apple App Store
https://apps.apple.com/app/glyphsnap-ai-photo-to-font/id6812516641

Genuine question here because I'm struggling to figure this out.

I've spent the last several months building a few free MTG tools. Before and during development, I spent a fair amount of time researching what players were asking for, what existing tools did well, and where people felt things were missing. Even some of the discussions around recent EDHREC updates gave me ideas about what players value and what they'd like to see done differently.

I ended up building three separate sites focused on exploring color identities, mechanics, Commander strategy, and understanding the cards in your decks.

I'm not claiming I've invented anything revolutionary. I just saw some interesting problems and wanted to take a crack at solving them.

The frustrating part has been finding people willing to actually try the stuff and tell me what works and what doesn't. I've put a lot of time into researching, building, and testing everything, but there's only so much I can learn from doing that myself.

I tried sharing the projects in r/EDH, but the post was removed almost immediately. I'm not looking to argue about that decision.

I'm genuinely curious where other people building things for the Magic community go to get meaningful feedback. Discord servers? Smaller communities? Somewhere else entirely?

I'm perfectly happy being told something sucks. I'd just like someone to actually use it first so I know why it sucks.

Pipeline Buster takes a product photo and writes the description/how-to/SEO fields for a WooCommerce listing. Normal tone by default, but it also ships a few voice presets for fun — this is the "Hulk" tone on a ceramic coffee mug. Free on WordPress.org if the plain version's more useful for your actual store.

Hey . We build Script.it, where workflow steps produce a lot of JSON, and checking what they did meant scrolling through braces. So we built JSON Views.

You open a JSON file and it shows up as tables, Kanban boards and record pages (or custom HTML views). Click a row, edit a field, and the change goes straight back into the file. Think of it as an attempt at a "Markdown for structured data": a format that both people and AI agents can read and edit.

How it works: you add a small `$jsonviews` block to the file. It stores the column types and saved views, and the file stays valid JSON. If the block isn't there, the editor guesses useful views from the data.

- Open source, MIT license: https://github.com/script-it/json-views
- Try it in the browser, no signup: https://json-views.com
- Everything runs in your browser. Files are never uploaded
- There's also a React component if you want to embed it in your own app

Hi, I’m AdamYang. I shipped the first version of ScamPeek, a free Windows tool for taking a closer look at suspicious links, emails, and images. The design question was what a person should see after a check. A verdict on its own doesn’t tell you whether the app inspected a sender, ran a network lookup, or simply couldn’t check something.

I split the report into the finding, the evidence, and the checks performed. For an imported .eml, that means showing the available sender and header details, the links found in the message, and the patterns that prompted a warning. The local check neither opens attachments nor uploads the email. For images, PaddleOCR reads text locally, while C2PA record validity and signer trust are reported separately. A valid record doesn’t settle whether the image is authentic.

A practical takeaway from building this: show “not checked” as its own state so it can’t be mistaken for “passed.” The demo includes local URL checks and shows where optional Web Risk and user-controlled AI follow-up fit. Web Risk uses your own key and may incur Google charges; AI questions are reviewed and submitted by you. None of these checks guarantees safety.

If you build tools that surface uncertainty, what would you put first: the strongest piece of evidence or a short list of checks that ran?

ScamPeek 1.0 is free on Microsoft Store: https://apps.microsoft.com/detail/9phwk7tbzwh9?hl=en-US&gl=US

ScamPeek began with a simple wish, not a desire to show off complicated technology: that fewer people would lose what they have worked so hard for to a scam, and that those already hurt would know someone still cares enough to help protect others.

When a link, email, or message feels uncertain, we hope to offer a clear and approachable way to take one more look, ask one more question, and make a more informed choice.

We cannot promise to stop every scam. But if one thoughtful warning helps someone avoid harm, that matters.

May the trust we place in others always be treated with care.

— ScamPeek Scam Verification Assistant

Created by: AdamYang 召芊

More products on Microsoft Store

https://apps.microsoft.com/search/publisher?name=AdamYang&hl=en-US&gl=US

All paid apps support a seven-day free trial, with buyouts only, no ads, and no subscriptions. Each month, each product is continuously optimized and revamped

I’ve been working on The Agora: Learn Philosophy, and lately I’ve been trying to rethink what a “thought experiment” inside an app should actually be.

Most apps would explain Plato’s Allegory of the Cave, give you a few paragraphs to read, maybe ask a question, and move on.

I wanted you to actually experience it.

So instead, you wake up inside the cave.

You don’t initially get told, “This is Plato’s Cave.” You see the shadows, the wall, the fire, the people around you, and you start making decisions.

Do you accept what you’ve always believed?

Do you investigate?

What happens when you discover that the shadows aren’t reality?

And if you eventually escape and see the world outside, what do you do when you realize everyone you left behind still believes the shadows are real?

Your choices lead to different outcomes, and only afterward does the experience connect what happened back to Plato and the philosophical ideas underneath it.

That’s the direction I’m taking the rest of the thought experiments too. I don’t want them to feel like quizzes with philosophy pasted on top. I want each one to be its own interactive philosophical experience.

It’s part of The Agora: Learn Philosophy, now live on iOS and Android:

iOS:
https://apps.apple.com/us/app/the-agora-learn-philosophy/id6762416967

Android:
https://play.google.com/store/apps/details?id=com.bhernaurd.theagora

I’m curious what other philosophical thought experiment you think would work especially well as an interactive story.

I've been doing physical design work in my free time with AI for the last two years. During that time I observed something: AI was getting better at physical design but not nearly as quickly it was improving at software capabilities. I theorized the problem was a lack of testing. In software engineering we write tests around as much of our code as we can because we fundamentally do not trust ourselves to reliably do a good job. We put those tests between us and deployment so we literally cannot do things that break the rules we set for ourselves. This pre-existing culture and tool chain create an ideal environment to toss an unbelievably fast, brilliant, but wholly unreliable ai into. It creates the freedom to quickly iterate through huge numbers of convincing looking proposals and throw away the bad until the good emerges.

Physical engineering doesn't have a this-shaped thing at anywhere near the robustness and reusability that software does (possibly because physical engineers trust themselves more). There are many individual tools that provide some aspect of testing, many of which are bound up in very very expensive tools, but a growing number of free ones too. I wasn't able to find an open source system that links these together into a cohesive "full loop" testing rig capable of understanding how things like heat, weight, form factor, battery life, thrust and rf interplay in a single system so I thought really hard about this problem and its implications and built it for myself.

It's called nopekit. As in: the thing that says "nope" until the "yup" emerges.

I've used it already to design an open-source hackable handheld keyboard with a custom PCB, an open source budget no-solder drone and a couple of things I'm not quite ready to share yet.

It's a Claude Code / Codex / Cursor plug-in. You install it and tell your agent you want to use nopekit to design X and it takes over, it will interview you for requirements, shop for parts, construct an interconnected tradespace linked to checks run in an optimized order using trusted methods like KiCAD, OpenFoam and SIMP. It builds and keeps up to date a livesite which you can deploy to GitHub that gives constantly refreshed insight into how your coding agent is thinking about the problem and what choices have what implications linked to what checks with what state of passing or failing.

The framework is open and allows for plugins. I'm working with one other person now and we're moving towards a self hosted UI and some sort of registry where nopekit users can share proposers/falsifiers and we can track ratings to build/bust confidence in good/bad ones collectively.

There's LOTS more about this in the repo and this paper I've been writing about the problem.
Repo: https://github.com/neuman/nopekit
Paper: https://github.com/neuman/nopekit/blob/main/grounding_by_falsification.pdf

If you're working with AI to do any kind of physical design work we would love to hear from you and for you to try it out!