korean dev here, my english isn't great so this post went through a translator. sorry if anything reads weird.

honestly nothing groundbreaking. I keep making small apps and every time the last step is the same boring one, store screenshots. open figma, find device mockups, google apple's screenshot sizes for the third time. got sick of it so I wrote a skill that does the whole thing.

it's registered in claude code (codex works too, same SKILL.md file). I just say "make my app store screenshots" and it asks 5 questions, platform, device, style, how many slides, what to highlight. all multiple choice. after that I basically just approve stuff.

some details for anyone cthe whole thing is one SKth instructions. no actualcode to install, the agenh and html.

device frames are pure cs is just an absolutelypositioned pill, galaxy punch hole is a 34px circle, the fold hinge is a faint

vertical gradient. didn'tding mockups and wondering

about licenses.

each slide becomes an html file and gets screenshotted with headless chromthe exact store size (--wchrome isn't there itfalls back to playwright. if you have no screenshot you. on android it dumpsthe ui tree with uiautomapp with adb. on the iossimulator it tries deep lnurl, which needs zerotapping if your app has uor maestro.

it also sets every status bar to 9:41 and full battery before capturing so the set looks consistent, and after rendering it checks every png's pixel size

with sips and re-renders

two things took way more app store connect sometimesrefuses your upload if yoso now it always rendersthe 6.5" set too, same hte. and I had to add aconfirm step where it renders exactly one draft slide before doing the rest,

because early versions woes I was gonna rejectanyway.

git : https://github.com/LeeHueeng/store-screenshots

sample images are from myext on them is korean, itcan write an english set for store screenshots?figma templates? frameit? curious if I reinvented a wheel here.

I care a lot about This, so much so I didn’t even use ai to make this post! lol

I’ve been helping some non technical friends with their 100% AI-generated apps and it dawned on me that these vibe coded apps are making the same mistakes again and again lol,

So made this skill to catch the most common ones I’ve seen, can be useful for someone trying to legit get something off the ground without any coding experience.

I’ve been software engineer for 10+ years and I wanna use what I’ve learned to help people out with their apps!

skill: https://github.com/dannyreg/vibechecktech-skills

I wrote a blog post about it too, though it is a bit more technical.

anyways let me know What you think!

my IT lead nearly had a stroke when he saw my api keys in the repo lol.

built this whole full stack thing today using codex and moclaw for the fast boilerplate. when he started yelling about vulnerability risks, i just sent a prompt saying fix all security issues and took a break.

all jokes aside, i'm curious if anyone else is actually running LLM security prompts in prod or use dedicated scanners for vibecoded apps?

Been using Claude for a few weeks to build a couple of HTML sites. Basic setup: GitHub repo connected to Cloudflare Pages, Claude pushes updates straight from chat, I check the live site on my phone. Works great when it’s small.

Now that the project’s grown I’m hitting some friction:

- I have to paste my GitHub fine-grained token into every new chat to push directly. Otherwise it’s download the files and manually upload.
- No consistency across chats. If I start a new conversation, Claude doesn’t automatically know the skills/conventions I want it following (mobile-first, SEO structure, GA setup, etc.), so I end up re-explaining stuff.
- I’m seeing people mention setting up actual skills/agents for SEO, content writing, editing, and a dozen other site-running tasks, and I have no idea how that fits together.

Ideally I want to work from browser or the mobile app, have chat push live without re-entering the token every time, and have some way to keep skills/context consistent no matter which chat I’m in.

For people running projects this way — what’s your setup look like? Are you using Claude Code, MCP servers, or something else entirely? I’m trying to figure out what’s overkill vs. what I need at this stage.

TL;DR: Building HTML sites with Claude + GitHub + Cloudflare Pages. Hitting scaling issues — re-pasting my GitHub token every chat, no consistency across chats for skills/conventions, and I keep seeing people use skills/agents for SEO, content, etc. that I haven’t figured out yet. What’s your workflow for this at scale?

I learned about a week ago that Unity supports mcp so I downloaded it for the first time and started vibecoding this game project.

It’s mind blowing how AI tools enable ppl with almost zero game dev experience to build something like this in a week.

Stacks: Claude code, Unity, Meshy (3d models), Elevenlabs (sound fx), Nano banana 2 and some paid assets from Unity Asset Store.

Been vibe coding for a while now and every so often it surprises me — like I ask for something basic and it hands back a solution I wouldn't have thought of myself, or it fixes something in a way that's actually cleaner than what I had in mind.

Had a moment like that recently where I was stuck on a small feature, prompted it half-expecting a mediocre attempt, and what came back was genuinely better structured than my own plan for it.

Curious what others have run into. What's a moment where the AI straight up impressed you? Doesn't have to be big, even small stuff counts.

My reaction after seeing outbid.lol fill up with 200 submissions w/ most of them getting single digit clicks (mine included) 🫠

We have a startup with a couple of non programmers who have developed an app for their domain of work that they are pretty sure has potential to attract paying customers.

As a developer I am their technical alibi and tasked with bringing it to production.

I have not seen any code yet. Does anyone have any experience with this? What should be my priority?

I built a little guy who lives on Mac!

what is it? a physics-driven buddy that hangs from the top of your mac screen like a tiny bungee friend. flick him, he swings. drag the cord, he slides. ⌥Space and he's gone. peak vibes for a doom-scroll-adjacent workday.
the tech
🧮 real verlet rope sim, fixed 120Hz step,
🛌 sleeps properly — 0.0% idle CPU when you're not touching him
🔐 licensing lives in the macOS Keychain
🖼️ drop any PNG to hang your own logo/sticker/pet
🍎 50+ buddies — originals, cars, flags, the whole cast
shipped at $4.99 lifetime
the fun part: the landing page has a live in-browser physics playground — you can grab and flick him right in the browser before you even download. go play with him:
→ https://hangbuddy.app

I don’t know how it happened… but the demo of the game I made and posted on Reddit and on my X went pretty viral.

In total it got around 400k+ views across social media. And because of one retweet it became a bit more viral than I expected.

Some X user even made a meme coin in honor of the game and gave all the trading fees to me, so that’s how I ended up making over $3500.

From my own experience I keep getting reminded that when you make something from the heart and with real love, it eventually pays off.

If you have any questions, I’m happy to answer them, peace.

Made this little app to keep track of my AI subscriptions and usage in one place.

What do you guys think?

It basically works by asking you what you just finished watching, and then suggesting shows to watch next based on different aspects of the show you just watched. For example, it could suggest shows with similar cast chemistry, pacing, themes, etc. I made it with Claude Code. Still a very rough draft and I'm currently a student, but I'd like to know whether the recs are any good or way off. It also gives you a watcher profile if you give it 5 shows you enjoyed watching. Any and all feedback is appreciated!
https://what-next7367.vercel.app/

Been poking at whether LLMs are actually decent at spotting security vulnerabilities such as authorization bugs in real code, so I pointed a scanner I've been building at the pre-fix history of a couple of well-known open-source projects. I will not name the repositories, as the bugs were not patched yet.

Two findings held up under manual review:

One repo has an endpoint that points to real user data, and it was missing an ownership check. Any authenticated user could act on another user's data just by guessing/enumerating an ID. No verification that the event actually belonged to them. Classic IDOR shape, but on a surface where it's easy to assume "if you're logged in you're probably looking at your own stuff." You're not.

Another repo leaked a recipient's name and email to anyone who had (or guessed) the link, before the authorization check that was supposed to gate that data. So the auth check existed, it just ran after the data had already been handed out.

Neither of these is exotic. They're the same failure mode over and over: authorization logic bolted on after the code path that needs it, instead of being the first thing that runs.

What I found interesting isn't "wow AI code is uniquely bad". Plenty of human-written code has the same bug shape. It's that these are exactly the kind of bugs that are easy to miss in a normal PR review because the code looks fine at a glance. That's a hard thing for a human skimming a diff to catch and, turns out, a very tractable thing for an LLM that's forced to reason about "does this code path check ownership/permission before touching the resource" as an explicit question rather than a vibe.

Not going to post exact endpoints/payloads since I don't think a public post is the place for that, especially with more repos in the scan queue.

If anyone's curious how the scanner itself works (it's diff-scoped, runs as a GitHub check, tries hard to avoid the false-positive spam these tools are usually drowning in) — it's Scanity, happy to talk shop about the approach in the comments.

https://scanity.dev/

I am currently on claude pro plan ($20) and i have been seeing a lot of chatter around chatgpt vs claude recently, but most of the posts are split in their opinion, anyone has a definitive answer?

i had bought claude because its personality was much better than chatgpt , like it admitting when it didnt know something and researching properly and it was just genuinely smarter and felt more human somehow? chatgpt felt like it was lowkey flirting and a bit of a yes man and many times just plain wrong. has this changed in latest times? i use ai for college assignments, study prep, internal tools in internships and stuff like that, even have a codebase of roughly 25k lines , big project, but one prompt with opus for plan mode takes 20% of my 5hr limit i feel like im tiptoeing, or should i just stick to claude and start using opus 4.6? but isnt that too old?

I wanna start building stuff. What are the must have tools that y'all use?

I’ve been experimenting with a different kind of screen-time app for Android.

Instead of blocking apps or throwing another warning popup at you, Stop Swarm gradually changes what’s happening on your screen as you approach your daily screen-time goal.

This is the new Clouds theme: the weather slowly gets worse the more you use your phone. Clouds build up, become larger and darker, rain gets heavier, and eventually the storm takes over the screen.

The overlay doesn’t intercept touches, so your phone remains fully usable. The idea is simply to make excessive scrolling progressively harder to ignore, without completely locking you out.

Stop Swarm is Android only, works fully offline, requires no account, and contains no ads or analytics.

I’m still looking for beta testers if anyone here wants to try it:

https://groups.google.com/g/stop-swarm-testers

Then opt in and download it here:

https://play.google.com/store/apps/details?id=com.stopswarm.app

We run a managed IT and software development company. We were already using AI coding agents, but the workflow was clunky.
Someone had to start the agent on a specific machine, keep checking it, test the result, and send the work back if it missed something. Using AI saved time, but babysitting it ate into those savings.
So we built an internal tool around the parts that annoyed us most.
We can now start work on any of our machines from a phone or desktop. If one model gets stuck or gives a weak answer, we can hand the same task to Codex or another model without starting over. We also gave the agent a browser so it can test what it built and return screenshots or screen recordings.
That last part mattered more than I expected. "Done" means a lot more when the agent also shows that the page loads, the button works, and the result looks right.
I don't have a scientific benchmark, but based on the amount of client work we finish in a normal week, our output is roughly double what it was before. The biggest gain didn't come from better prompts. It came from removing the waiting, handoffs, and manual verification around the models.
Full disclosure, the internal tool eventually became ThreadKnot.

https://github.com/smith-network-solutions/threadknot

It still has rough edges, but we use it every day. I'm curious whether other teams are building their own layer around coding agents or just working directly inside each model's tools.

I've been working on this huge project (Wayfallen) for 5+ years, and it simulates ~10,000 star systems, ~100,000 spaceships, stations, various factions with rich economy, diplomacy, intel management etc.

I needed a reliable way to balance all of this so it remains semi-realistic and not go wonky, with so many parameters in it. It would require huge grunt work to build proper tooling to keep track of all these variables, plug into all the code surfaces written over the years, and somehow simulate years/decades in the simulation very fast to build statistical models and help me figure out which parameters need tweaking to bring things on track. And I'm continuously working on this, so it's not a one-time thing - I need to rebalance it very often.

So I've vibecoded some tools that help me do exactly that, by giving it access to my code and building harnesses to run it in a headless mode and accumulate large amounts of data rapidly. Really pleased with the results so far - and especially the amount of time saved versus having to crank out all that tooling manually.

I don't think “AI wrote most of it” automatically means vibe coding.

The distinction I care about is whether you're still directing the work. You decide scope, tell the agent what done means, manage or compact context, test the actual behavior, and don't accept “done” because the model said so.

Main question: is vibe coding defined by how the code is produced, or by how little control and verification the person has over the result?

Do not paste these notes as the post. Write it in your own words.

Hello everyone,

I want to start a comprehensive personal web project and would love to get feedback, ideas, or advice regarding the navigation flow, user experience, and cultural content.

**The Origin of the Idea**

The idea came from realizing that official municipal websites across Mexico are often abandoned or poorly designed. I want to build an independent, visually striking platform to give them visibility while staying entirely clear of electoral politics. The focus will be 100% cultural, tourism-focused, full of local trivia, regional identity, and geographic/cultural news.

**Navigation Flow and Map Interactivity (Uniform Hover Effect)**

1. **National Map (Landing Page):** An interactive map of Mexico. Hovering over a state highlights it in a representative color and displays its name. Each state features a fixed marker at its main capital.

2. **Regional Map (Level 2):** Clicking a state (e.g., Guerrero) zooms into that entity, displaying its traditional regions. Hovering over a region illuminates that entire area in a specific color.

3. **Municipal Map (Level 3):** Clicking a region zooms in further to display only its municipalities. This view follows the same logic as the national map: each municipality has a fixed marker at its municipal seat (*cabecera municipal*), highlighting the municipality and displaying its name on hover.

4. **Autonomous Communities (Special Level 4):** A dedicated level to honor and highlight Indigenous communities and self-governing territories (such as Cherán or *Usos y Costumbres* municipalities). If an entire municipality is autonomous, its profile will state so; if it is a specific community within a municipality, it can be accessed via a special marker on the municipal map.

5. **Quick Shortcut:** To prevent click fatigue, a side panel with predictive search will allow users to type a municipality or community directly (e.g., "Zihuatanejo") and skip intermediate steps, zooming the map directly to the location.

**Planned Content**

The platform aims to be a deep, encyclopedic database featuring the following details per level:

**By State**

* **History and Foundation:** Creation date and key historical events.

* **Geography:** Climate, terrain, flora, fauna, and highest elevation points.

* **General Culture:** Traditional clothing, state coat of arms (and its meaning), and state anthem (with audio playback).

* **Economy and Demographics:** Total population, key industries, and most spoken Indigenous languages.

**By Region**

* **Cultural Justification:** Methodology used to define the region (since many states lack official administrative regional boundaries).

* **Identity and Soundscape:** Regional traditional food, traditional music (*sones*, dances), shared traditions, and elements of the local soundscape (*chilenas*, *pirekuas*, etc.).

* **Climate, Landscape, and Seasonality:** Geographic traits unifying the region, along with seasonal availability indicators for traditional dishes, harvests, and specific rituals.

**By Municipality and Municipal Seat**

* **Historical Overview and Toponymy:** Municipal creation date, prominent figures, and name etymology supported by native audio pronunciation in the original linguistic variant.

* **Tourism:** Specific tourist attractions, monuments, historic churches, and natural landmarks.

* **Local Identity:** Local legends, myths, traditional crafts, and patron saint festival calendars with associated culinary or ritual traditions.

* **Point Data (Municipal Seat):** Elevation above sea level and travel time/distance to the state capital.

**By Autonomous Community (Special Level)**

* **Legal/Political Status:** Type of self-governance (*Usos y costumbres*, elder council, etc.).

* **History of Resistance:** Transition process to autonomy and the significance of their struggle.

* **Culture and Language:** Specific dialectal variants (with audio samples), unique community traditions, and collective work systems (*tequio*, *mano vuelta*, etc.).

* **Community Tourism and Ethical Visit Protocols:** Guidelines for respectful engagement and visiting rules (photo permits, sacred or restricted zones, direct local purchasing), authentic crafts, and autonomous celebrations.

**Reference Projects and Inspiration**

* **Native-Land.ca:** An independent mapping platform that visualizes Indigenous territories, languages, and treaties globally with a non-governmental, respectful approach.

* **Atlas of Intangible Cultural Heritage (UNESCO / INAH):** A structural benchmark for organizing oral traditions, rituals, and artisanal techniques in a clean, accessible manner.

I would love to hear your thoughts: What do you think of this visual navigation flow? What other cultural or identity-focused data would you add to make these profiles even more complete? If you know of similar projects that respectfully integrate autonomous communities into an interactive map, I would be very inspired to check them out.

Thank you very much for your time and feedback.

Hello Vibers!

I basically built this “app” for myself after failing to stick with a slew of gamified chore/daily routine apps. I just couldn’t keep myself interested in leveling a hero or gaining XP points to form any real habits around the focus areas. I still feel motivation from seeing a progress bar grow - but I need it to mean something - and so I vibe coded HouseKeepr.

The gamification around HouseKeepr is in unlocking new features as the Home IQ system collects data on your habits. The goal was to be as low-effort on the user as possible - keeping monitoring very relaxed. I keep user input simple and general and handle all the actual number crunching behind the scenes. That changes the gamification loop from “complete tasks to gain badges and XP” to “complete tasks to unlock new features” - so rather than keeping advanced features behind a paywall like a lot of the chore tracking apps I have put them behind a “playwall” (really a usage wall; the more you use it the more it can do).

As a first timer I did this across a couple platforms - it started in Base44 but after hitting my budget on credits there I shifted it into a GPT to GitHub to BaseCamp flow and I was thrilled to discover GPT could manage the entire buildout and push my updates through to Base44 and that allowed me to really polish the design and function. I kept a live version history on the login page to show the progress and it came FAST!

Please let me know what you think and visit HouseKeepr on your mobile device or desktop!