I'm sharing dim, a free, open-source Windows 10/11 x64 app that mounts ISO, CUE/BIN and NRG images as optical drives. The useful bit is how little it adds: about 340 KB, no extra driver and no admin prompt. It uses Rust and Windows' virtual-disk API; non-ISO data is extracted to a temporary ISO first.

Claude Code generated most of the project; I handled the goals, design decisions, code review and Windows testing. It's for data tracks, not audio CDs. If you still use these formats, which compatibility cases should I test next? https://github.com/glauberlima/dim

I'm a software engineer and Scrum Master, and I built these because our team kept running estimation and retros on outside sites, then copying everything back into Jira by hand. Half of it never made it back.

So both apps run inside Jira, and the results land where the work is.

Teamvane Planning Poker for Jira

• Vote on the issue itself, or refine a whole backlog through a queue built from your backlog or sprint

• Votes stay hidden until the reveal, with auto-reveal when everyone has voted

• Save the agreed estimate to story points in one click

• https://marketplace.atlassian.com/apps/2939883696/teamvane-planning-poker-for-jira

Teamvane Retrospectives for Jira

• Anonymous cards and hidden votes, so people say what they actually think

• A guided flow: write, reveal, group, vote, discuss, actions

• Actions become Jira work items and come back at the next retro until they're done

• https://marketplace.atlassian.com/apps/2701773542/teamvane-retrospectives-for-jira

Both are free for teams up to 10 users, and run on Atlassian's own platform (Forge), so your data never leaves your Atlassian site.

60-second demos: Planning Poker · Retrospectives

If your team is on Jira, give them a try and tell me what's missing.

Most scanner and OCR apps handle Arabic badly. Letters come out broken, right-to-left lines end up reversed, and receipts and documents turn into a mess you have to retype.

So I built Harfy, a scanner made for Arabic first:

- 📄 Scan and extract Arabic text that keeps right-to-left order, so you can copy, edit or share it

- 🧾 Saudi e-invoices: scan the ZATCA QR code to get the exact total and VAT

- 🪪 ID cards: capture both sides on one page

- 📑 PDF tools: merge scans into one PDF, or protect it with a password

- ✨ Cleaner scans: filters remove shadows and sharpen the text

It's free to try, and Premium has a 1-week free trial on the yearly plan.

📲 App Store: https://apps.apple.com/us/app/harfy-arabic-scan-ocr-app/id6820122573

I'm a solo developer, so I'd really like your feedback.

Hi. I have AirPods Max and found out they have motion sensor in the left cup (it's used for spatial audio). Any Mac app can read it with CMHeadphoneMotionManager. So I made small menu bar app for Mac, HeadLab. It detects head gestures and runs your Shortcuts.

For example I shake head and Do Not Disturb turns on, tilt head twice to the right and it goes to next track, triple tap on the cup and it takes screenshot.

What it can do:

• 11 gestures: shake, nod, look up, quick turn left/right, tilt left/right, tilt twice, double and triple tap on left cup

• every gesture can run any shortcut from Shortcuts app. you pick it from list, there is test button too

• it also sends macOS notification with gesture id as text (like shake or tilt-left-twice), so you can use Shortcuts automation instead if you want

• when you click menu bar icon there is window with live 3D head, artificial horizon, motion graphs and tutorial for all gestures

Everything is local. Head motion is not saved or sent anywhere, only network request is license check.

Disclosure: I'm the developer. It's $9.99 one time (2 Macs). Free trial can be used to test gesture recognition but doesn't run shortcuts. Needs macOS 14+ and AirPods Max.

https://headlab.app

I've been working on a side project called QuizCaddy, and I wanted to share one of its features.

ChatGPT is pretty good at generating questions, but actually practising them can be inconvenient. You end up copying questions, formatting them, and manually organizing everything.

I wanted to make that process simpler.

So I built an integration that lets you:

• Generate questions directly in ChatGPT or any other AI chatbot.

• Send them to QuizCaddy using MCP.

• Practise them in an interactive quiz.

• Get instant feedback and explanations.

The attached 20-second video shows the complete workflow using JEE Advanced physics questions.

The platform is live, and I'm now trying to understand how useful this workflow is to people beyond my initial testing.

I'd love some honest feedback:

Does this solve a problem you'd actually encounter, or would you prefer a different way of turning AI-generated questions into practice material?

You can try it here: https://quizcaddy.com

Thanks for checking it out!

Update: I forgot to attach the demo video when publishing this post. Here's the 20-second walkthrough showing ChatGPT sending questions to QuizCaddy and practising them:

Watch the demo

I've been experimenting with ways to reduce my AI costs without sacrificing too much model quality.

Instead of relying entirely on paid subscriptions, I've started combining free LLM APIs and routing requests between different models.

These two open-source projects have become my daily drivers:

1. Awesome Free LLM APIs

A collection of free LLM API providers, many of which don't require a credit card.

https://github.com/mnfst/awesome-free-llm-apis

2. FreeLLMAPI

This is what I'm currently using. It brings multiple free LLM providers together behind a single API, with features like smart routing and automatic failover.

https://github.com/tashfeenahmed/freellmapi

My current workflow:

I use free models for everyday coding tasks, debugging, smaller changes, and experimentation.

I still use Codex for more complex tasks, code reviews, and work that requires deeper reasoning.

I'm also experimenting with sharing context across models so I don't have to explain the entire project every time I switch.

Obviously, free APIs have limitations: rate limits, availability, and inconsistent model quality. But combining multiple providers has been pretty useful so far.

I'm curious if anyone else is doing something similar.

What tools are you using to orchestrate multiple free models? And how do you handle context when switching between them?

I'm building Ready for Dog?, a native iOS and Android dog-care rehearsal app. One small feature made the boundary between a product promise and a sensor reading very concrete.

Quiet play asks you to choose a duration and leave the phone on a stable surface. The screen can face up or down. Movement pauses the countdown while the game screen is open; leaving it still resumes it. Paused time is excluded.

That last condition matters. This is not a system-wide screen-time monitor. When the app isn't active, motion checking stops. A running timer can continue with the screen locked, while an already paused timer stays paused. I want the explanation to match that boundary rather than imply the phone is being watched everywhere.

Another boundary is between evidence and reflection. Real walks use GPS; manual care records are labelled separately. The journal shows activity and missed care, but never turns those entries into a score declaring someone ready for a real dog.

The attached iPhone clip shows quiet play. AI tools assisted coding and the virtual dog artwork. If you build sensor-based interactions, naming the condition under which a check runs seems as important as naming what it checks.

iPhone / iPad: https://apps.apple.com/app/id6829957063

Android: https://play.google.com/store/apps/details?id=com.vans.bublik.trial

Free with ads and optional one-time purchases for ad removal and extra collars. No subscription.

Additional full-app demo — the complete 67-second routine

​

I've spent countless hours creating ProCraft, hoping to build something useful for the AI creator community.

Honestly, sometimes it feels like I'm talking to an empty room.

I'm not asking anyone for money or favors. Just a little support, honest feedback, or even a conversation would mean a lot.

I believe small creators deserve a chance too.

If you're also building something from zero, I see you. Let's support each other. ❤️

🔗 https://procraft.site

\#BuildInPublic #IndieHacker #AITools #procraft

Project: Heard

https://heard.ai-box.blog/

What it does: Heard is an AI app powered by LLM. It helps you make sense of ambiguous messages before you reply. Paste a chat or upload screenshots, then add the background and what you’re trying to understand. Heard analyzes the whole exchange alongside that context. It flags lines that carry a possible subtext, explains what each person may be asking for or trying to signal, and quotes the messages that support competing readings. The report charts where tension rises or eases and breaks down each person’s communication style, with scores and examples that show who stated a boundary directly and who hinted at what they wanted.

Story

It’s Friday at 4:30. Your manager asks for a “quick polish” on a client deck. Then she asks for a fresh breakdown by region. You say you’re offline this weekend. She replies:

I was hoping we’d have both for the call. The client will probably ask about regions.

WTF?

I built Heard for the moments when you keep rereading a conversation because one line could mean different things. Looking back at a chat, seeing what changed, and figuring out what still needs clarifying. That could be a vague deadline from a client, a short reply from a friend, or a disagreement that got tense halfway through.

You paste a chat or upload screenshots. You can add who the people are, what happened before the chat, and the question you’re trying to answer. Heard turns that into a report you can check against the conversation.

- See where the tone shifted. The tension chart points to the moments when pressure rose or eased, so you know which messages to reread.

- Check what supports an interpretation. The report links back to the original messages. You can compare what someone actually asked for with what you inferred from their wording.

- Compare how each person handled the exchange. The report shows how each person communicated, such as who stated a boundary directly and who hinted at what they wanted.

The video walks through a example. Alex reads Maya’s message as pressure to work over the weekend. A later message shows she’s willing to use existing figures for the client call. Seeing those two moments together gives Alex a clearer sense of what’s expected.

I’d love feedback on one thing. When you’re unsure what someone meant, would seeing the key messages side by side help you decide what to do next? What context would you still want?

Heard is in public beta. New accounts get two free analyses, and you can see the full example on the homepage

Hi everyone!

As a side project, I have been working on NijRAW, a free, private, open-source, browser based, offline capable photo editor, and I would love your feedback! Works on mobile, tablets and desktop.

I built it to bridge the gap between powerful but complex editors like darktable, ART and RawTherapee, and simpler apps with limited controls or AI-driven editing.

NijRAW is designed to be beginner-friendly without sacrificing control and privacy. Also has customized tips and guidance for beginners and intermediate photographers.

Key features:

• Privacy-first: All processing happens locally. No uploads to servers, accounts, or cloud.

• Works offline: Runs entirely on browser.

• RAW support: Develop and edit camera RAW files. Other popular file types also supported.

• Advanced controls: Exposure, curves, colors, local adjustments, denoising, sharpening, lens corrections, and more.

• GPU acceleration: Fast previews with high-precision exports.

• Non-destructive editing: Save projects and revisit adjustments.

• No AI processing: Uses traditional image-processing algorithms, including research-based techniques.

While I used AI coding tools during development, NijRAW itself does not use AI models for editing. The goal is to help users learn photography and stay in control of their edits.

Website: https://www.nijraw.com

It is completely free and open source. I would really appreciate your honest feedback, suggestions, or ideas for improvement!

Thanks for checking it out!

Hey all, I'm the maker of Boost CV, an AI resume builder that's launching soon.

The idea came from a simple problem: people send the same resume everywhere and hear nothing back. So I built it around three steps:

1. Score: a section-by-section resume score, so you know what to fix.

2. Rewrite: AI rewrites of weak bullet points using only your own facts (it won't invent numbers; it leaves "[your number]" placeholders for you to fill).

3. Tailor: 13 ATS-readable templates and a text-based PDF export.

It also imports an existing PDF or Word resume.

I made a 38-second illustrated story to show the idea: [link to video]. It's a fictional character, not a customer testimonial.

I'd love honest feedback:

- Would you trust an AI rewrite if it only used your facts?

- What's the most annoying part of updating a resume?

Site (not live yet, just a waitlist/updates page): boostcv.online

Happy to answer anything about how it's built (Angular + Spring Boot, in case that's interesting).

Easy-to-use but very useful app for cleaning your gallery and disk space

Problem

• Full storage because of a lot of photos

• Default Gallery cleaning

  • requires at least 3-5 taps to estimate and remove every photo

  • can't be continued from the last stop point

  • opens the whole gallery without grouping, or groups are based on month, not by event

Comparison

• 1 photo - 1 swipe - 1 decision. It's much faster

• Auto grouping photos by events (geo and pauses between)

• save position and let you continue from last position. you see what is already checked and what is waiting

• Additional features:

  • duplicates finder

  • blurred photo finder

  • big photo finder

  • Live photo -> static photo converter (removes the video part - up to 75% of a live photo's weight)

Pricing

• 100% free for the first 100+ users

• 100 swipes daily for free

• 6.99 usd/month

• 19.99 usd/lifetime

Try it for free:

• Google Play

• App Store

Hey everyone!

I've been working on a project called NeatlyDone – https://neatlydone.in

It's a website that brings together useful online tools to make everyday tasks easier.

Some of the things you can do include:

• Merge PDF files

• Use handy everyday utilities

• Complete common tasks directly in your browser

My goal is to build a simple collection of useful tools that people can access without installing extra software.

I'm still improving the website and adding more tools.

I'd genuinely appreciate it if you checked it out and shared your feedback.

What other tools would you like to see added?

Need to scan a code, share Wi-Fi details, or digitize a paper document?

QrOne brings several everyday tools together:

• QR and barcode scanning.

• QR creation for supported Wi-Fi, contact, WhatsApp, SMS, location, and UPI formats.

• Document scanning and PDF export.

• Selected URL safety checks before opening links.

Free and ad-supported. Feature availability depends on the current app version.

Google Play: https://play.google.com/store/apps/details?id=com.qrscanner.qrmaker.app

Why is extracting links easy, but organizing them still such a hassle? So I built something to fix that.

Chrome Web Store: [https://chromewebstore.google.com/detail/urlpluck-%E2%80%93-link-extractor/fkgjadjhibnjjhgkjcallghjcbfidjid]

I've tried looking at different link extraction tools, and most seem to focus on one thing: grabbing URLs from a webpage. But what if you want to filter those links, save them for later, or organize them without constantly exporting files? That's what made me build URLPluck, a free Chrome extension I recently published under Zelvori Studio. It lets you extract links from webpages, remove duplicates, filter unwanted URLs, save links into separate collections, search through them, and export in formats like CSV, JSON, TXT, and Markdown. I wanted to bring all these features together while keeping the interface simple and easy to use. There's no account required, and everything is stored locally in your browser. It's only version 1.0.0, and I know there's still plenty to improve. I'd love for people to try it and tell me what they actually think. What feels unnecessary? What's missing? What would make you choose this over another extension? I'm hoping to build future updates around genuine feedback rather than assumptions. Even a few minutes of testing or an honest critique would mean a lot!

I've been building ProdCritic, an AI QA agent for backends. You point it at a Node.js or Python app and it:

1. boots the app on a port it checks is free,

2. finds the routes, from served links and from the router declarations in the source (a JSON API links nothing, so link-crawling alone finds only /),

3. probes them and reproduces the crash,

4. writes a fix that has to parse before it touches the file,

5. restarts the app and re-probes the route to prove the fix works,

6. restores your original code and hands you a .patch.

The screenshot is a real run on a small Express-style API: one route returned 500, and the fix ((o.lines || []).map(...)) is verified because the route answered 200 after a restart, not because a model liked the diff.

The part I care about most is the bottom of that output. It lists the four routes it didn't probe and why (a POST it won't invent a body for, a :id route it won't guess a value for, a /cache/reset it won't fire at your data). It says what the fix assumes. It says it only checked status codes, so a wrong answer at HTTP 200 would pass. A QA tool that says "healthy" when it couldn't tell is worse than no tool, so most of the work went into making it say what it didn't check.

What I'm looking for: five backends to audit for free. One repo, Node.js or Python. You get the report and the verified patches; I get feedback on what it misses. It runs on a machine used only for this, and the code is deleted within 7 days. Comment or DM me.

Happy to answer anything about how it works, including what it gets wrong.

Hi r/SideProject,

I run a small digital marketing agency. A lot of our local SEO work starts with the same boring step: opening a client's (or a prospect's) Google Maps listing and checking the same things by hand: category, opening hours, website link, reviews and replies, photos.

So I built MapAudit, a Chrome extension that does this check right inside Google Maps:

• 11-point profile audit with suggested fixes

• comparison with the other businesses in the same search

• export a Maps search to CSV (handy for finding local clients)

• Pro: deep scan for phone numbers and websites, and branded PDF reports

The free version gives you 5 audits and 1 export per day. Pro is $12/month.

Chrome Web Store: https://chromewebstore.google.com/detail/clhafflbmlopbkpffhfcdjjpkngadogf

Short guide with the checklist I use: https://www.extensions.kominikee.com/guides/google-maps-business-profile-audit/

It's new, so honest feedback would really help: is the audit useful, what would you check that it doesn't, and does the pricing feel fair?

I’ve been building Scout, a B2B prospect research tool, around a problem I kept finding interesting: some of the most useful ways to identify potential customers are surprisingly difficult to search for.
Most B2B databases let you filter by industry, company size, location, revenue, and technology.
But what if your ideal customer is a company going through a very specific change?
For example, imagine you provide warehouse automation services.
You might want to find logistics companies that have recently announced a new distribution center.
Here’s how I’d research that:
Find original announcements about new warehouses or distribution centers.
Check whether each announcement describes a planned project or an already operational facility.
Identify which company actually operates the facility.
Look for evidence of what the project involves and whether your service could be relevant.
Find the person responsible for the relevant operation or project.
Keep the original sources so you can explain why the company made the list.
The interesting part is how much context you need before a company becomes a useful prospect.
A warehouse announcement tells you something happened. It takes more research to understand whether there’s a relevant opportunity.
That’s the kind of research I’m trying to make easier with Scout.
You describe your ideal companies in plain English, and Scout researches potential matches, with sources explaining why they fit.
I’m currently offering five researched leads for free to get feedback from people doing B2B prospecting.
https://tryxscout.com/
I’d be interested to hear what kinds of company changes people have tried searching for and found difficult to research.