value: rakeda

value:
Hey HN, I’m Brandon, developer for Harbor Guard, an open-source container security platform that unifies multiple scanning tools into a single intuitive dashboard.
Over the past month, I got tired of juggling different CLI scanners (Trivy, Grype, Syft, Dockle, etc.), for my work in DevSecOps. Stitching results together started becoming a hassle and my organization started heavily focusing on container security. It was messy, repetitive, and hard to keep track of active vulnerabilities.
So I built Harbor Guard, a modern, Next.js app that runs all major open-source container scanners, stores the results, and turns them into interactive visualizations you can actually use.
What Harbor Guard does:
- Runs 6 major tools: Trivy, Grype, Syft, Dockle, OSV Scanner, and Dive
- Unified dashboard: View and compare results without jumping between CLIs
- Historical tracking: Persist and compare scans across versions
- Advanced visualization: Interactive scatterplots, severity-based grouping, and layer-by-layer analysis
- Report export: Grab JSON or full ZIP packages for compliance
- API access: REST endpoints for automation and integrations
- Docker-native: Run it with a single docker run -p 3000:3000 …
Personally, I needed a tool that made vulnerability data easier to explore visually and had some fun putting something together.
Try it out
GitHub: https://github.com/HarborGuard/HarborGuard
Live Demo: https://demo.harborguard.co
It’s free, open source, and I’d love feedback, bug reports, or feature ideas. Contributions welcome too.
Thanks,
Brandon

value: Show HN: Harbor Guard – Manage and Scan Container Images (Open Source)

author: rakeda


value: Croffasia

value:
Honest question: Do you also give AI minimal info and expect magic?
We've all been there: Ask AI to code something. Get code that works but looks nothing like your project. Spend hours fixing it to match your style.
I built this tool for Claude Code to fix that problem. It's like having AI that actually reads your codebase first.
How it works:
1. Tell it what you want in plain English
2. It asks questions if it needs more info
3. It studies your existing code patterns
4. It searches the web for best practices if needed
5. It creates a detailed plan for Claude Code to follow
Result: Code that matches your project from day one.
Claude Code gets a complete guide instead of a vague prompt. It knows your naming style, your architecture, your testing setup. Everything.
Works with any programming language. The tool figures out your project automatically.
No more random AI code. No more refactoring. Just code that fits.
Built for Claude Code CLI but the approach works anywhere. Would love to hear what you think.

value: Show HN: Stop AI from Writing Random Code That Doesn't Fit Your Codebase

author: Croffasia


value: pikaiqiu

value:
I built a tool to monitor changes in any website’s sitemap: [sitemapmonitor.live]
It automatically tracks new/removed URLs from a site’s sitemap.xml, and notifies you when something changes.
This is useful for:
- SEO (detecting new pages or deleted ones)
- Competitive analysis (see when competitors launch new features or content)
- Site reliability (alert if a big chunk of pages disappears)
Unlike generic crawlers, it focuses only on sitemap data → less overhead, more precise tracking.
I made it because I kept manually checking competitor sitemaps for updates, which was painful.
Would love feedback from the community — what use cases do you see for this?

value: Show HN: SitemapMonitor – Track changes in any website's sitemap automatically

author: pikaiqiu


value: inshinrei

value: hi! I've made a logger for JS/TS. It's easily extendable, easy to use and configure.<p>Would like to hear a feedback from you!

value: Show HN: I've made an easy to extend and flexible JavaScript logger

author: inshinrei


value: johannesgen

value:
Hey! Johannes here and I've build Enduin.
While AI changes how software is build in many domains, it lacks adoption in embedded software.
When looking at what embedded engineers do in their development time, it's mostly debugging instead of writing code and current AI dev tools are not helping here. They are just not made for this domain.
That's why I've build enduin, which integrates into GDB through the VS Code debugger (GDB) and executes code, sets breakpoints and finds the bugs with that. You can also upload documents that are used as context. Enduin is currently not changing your codebase, just helping to find bugs. It focusses on embedded code but basically every code that can be debugged with GDB can be used (C/C++, Rust, ...).
You can try it through the VS Code marketplace.
Is that helpful to you? What would you expect from such a tool?
Here's the link to the extension: https://marketplace.visualstudio.com/items?itemName=Enduin.e...
Here's also a demo on YouTube: https://youtu.be/RNaiwj85eyU
Looking forward to your feedback!

value: Show HN: AI for Embedded Software Debugging

author: johannesgen


value: AnkitRH

value:
Hi HN!
I just launched Rocket Journal, a voice-first journaling app designed to make reflection as easy as talking.
Key ideas:
Rant mode — vent freely, no judgment
Reflect mode — guided prompts to help dig deeper
AI insights — mood tracking, patterns, helpful takeaways
Stickers & scrapbook — journaling feels lighter and fun
Privacy-first — your data isn’t used to train models
I built this because journaling apps often feel like “work.” I wanted something that felt like having a safe, responsive companion for those late-night thoughts or walks outside.
I’d love feedback from the HN community:
Does this feel useful or different from other journaling apps you’ve tried?
Any concerns about using voice for private reflection?
What features would make you want to use this daily?
Thanks!

value: Show HN: Rocket Journal – voice-first AI journaling for your 2 AM thoughts

author: AnkitRH


value:
A web-based paycheck calculator has been built to reflect the latest 2025 federal and state tax policies across all 50 US states. It estimates after-tax income by accounting for federal, state, and FICA deductions, and supports different pay frequencies (weekly, bi-weekly, monthly, etc.).
The intent is to provide an up-to-date, lightweight tool for anyone trying to quickly understand take-home pay. The design goal was simplicity: one page, minimal inputs, instant breakdown.
Questions for the community:
 • What additional features would actually make this more useful (e.g., 401k, health deductions, local taxes)?
 • Would people prefer a simple “quick estimate” vs. a more configurable advanced mode?
 • From a technical/product perspective, what would you change or add?
Feedback is welcome, especially from those who have dealt with paycheck calculators before or have strong opinions on usability.

value: Show HN: A paycheck calculator for all 50 US states with 2025 tax rules


value: canercbo

value:
Hey everyone,
I’ve been working on a little side project: a website where I collect and display stats from soccer games (and I could expand it to other sports too).
The main idea isn’t to predict matches or do betting tips — it’s more about having a clean, easy-to-read overview of stats like:
 • Team performance across the season
 • Head-to-head comparisons
 • Player stats (goals, assists, cards, etc.)
 • Match summaries and trends
Right now it’s pretty simple, but I’d like to make it genuinely useful for fans who just want to explore numbers without drowning in clutter.
I’d love to hear your thoughts:
 • What stats do you usually look for when checking up on games?
 • Anything you wish other sports stats sites did better?
 • Features that would make you actually bookmark and revisit it?
Any feedback or feature requests would be amazing

value: Show HN: Kickpredict – Simple Soccer match analysis and stats collection by AI

author: canercbo


value:
Quick Links:
- PyPI: https://pypi.org/project/axon-api/
- GitHub: https://github.com/b-is-for-build/axon-api
- Deployment Script: https://github.com/b-is-for-build/axon-api/blob/master/examp...
Axon is a 507-line, pure Python WSGI framework that achieves up to 237MB/s file streaming on $8/month hardware. The key feature is the dynamic bundling of multiple files into a single multipart stream while maintaining bounded memory (<225MB). The implementation saturates CPU before reaching I/O limits.
Technical highlights:
- Pure Python stdlib implementation (no external dependencies)
- HTTP range support for partial content delivery
- Generator-based streaming with constant memory usage
- Request batching via query parameters
- Match statement-based routing (eliminates traversal and probing)
- Built-in sanitization and structured logging
The benchmarking methodology uses fresh Digital Ocean droplets with reproducible wrk tests across different file sizes. All code and deployment scripts are included.

value: Show HN: Python file streaming 237MB/s on $8/M droplet in 507 lines of stdlib


value:
I've been solo developing RoomCycle, an iOS app (macOS/tvOS on the way) that helps people (especially those with ADHD and/or MDD, like me) organize their living spaces using 2-minute micro-sessions and the OODA loop methodology (Observe, Orient, Decide, Act).
The entire app was built through vibe coding with Claude Opus using Claude Code - describing what I wanted and iterating on the implementation together. It features zone-based organization, CloudKit sync, and both "simple" and "advanced" modes to accommodate different cognitive loads.
Still squashing bugs before App Store submission, but wanted to share early and get feedback from the community. The app uses a gentle, non-judgmental approach to organizing - no before/after shame, just progress tracking and small wins.
Tech stack: SwiftUI, Core Data + CloudKit, MVVM + Coordinators, Semantic Colors
I had pretty decent success, so far - over the course of nearly a month, Claude Code only had a handful of instances of context poisoning and it felt like it got things right about 80% of the time.  It was a daily experience of handholding and guiding, however.  Still better not to take ones eyes off of the code, as I caught at least a couple of mistakes per day that would have led to a divergence from the expectation.  Overall, very pleased with the experience, even if left with a slight headache.
There were some neat aspects to using the LLM, such as it creating semantic colors appropriately (after some trial and error) and using it to generate dynamic "smart behavior" without the app itself needing to reach out to an LLM to get feedback.
Would love feedback on the concept, UX approach, or the experience of vibe coding production iOS/macOS/tvOS apps with AI
TestFlight: https://testflight.apple.com/join/Kj9MZ9Mx
Website:  https://roomcycle.app

value: Show HN: RoomCycle, iOS, ADHD-friendly home organizing, built with Claude Code


value: fazlerocks

value:
Hi HN,
I built Mail42 (https://mail42.ai) to make it easier to test email flows without dealing with regex or messy parsing.
The pain point: whenever I tested signup or checkout flows, I had to create throwaway inboxes and then write hacky regex just to grab a 6-digit OTP or a verification link.
With Mail42 you can:
- Generate disposable email addresses instantly for QA
- Query emails using natural language like "get the OTP" or "find the verification link"
- Use a simple REST API that works with curl, Postman, or your test suite
Example:
`curl "<a href="https://get.mail42.ai/?email=test.123@mail42.ai&prompt=get" rel="nofollow">https://get.mail42.ai/?email=test.123@mail42.ai&prompt=get</a> otp"`
Response:
847291
It’s lightweight and intended for testing env
I’d love your feedback:
- would you use this in your testing workflow?
- what features or integrations would make it more useful?
- are there cases where regex still feels more reliable?
Thanks for checking it out.

value: Show HN: Mail42 – Disposable emails with AI-based text extraction

author: fazlerocks

story_text:
Hi HN,
I built Mail42 (https://mail42.ai) to make it easier to test email flows without dealing with regex or messy parsing.
The pain point: whenever I tested signup or checkout flows, I had to create throwaway inboxes and then write hacky regex just to grab a 6-digit OTP or a verification link.
With Mail42 you can:
- Generate disposable email addresses instantly for QA
- Query emails using natural language like "get the OTP" or "find the verification link"
- Use a simple REST API that works with curl, Postman, or your test suite
Example:
`curl "https://get.mail42.ai/?email=test.123@mail42.ai&prompt=get otp"`
Response:
847291
It’s lightweight and intended for testing env
I’d love your feedback:
- would you use this in your testing workflow?
- what features or integrations would make it more useful?
- are there cases where regex still feels more reliable?
Thanks for checking it out.


value: alwassikhan

value: Let me know what you think about this. Your thoughts.

value: Show HN: I made a JSON Editor. That allows to convert JSON to CSV and more

author: alwassikhan


value: Show HN: Understand Complex Codebase at Ease


value: Happy trading, more info and offer in the first comment

value: Show HN: CFA/ML engineer and prosports coach blew up trading accts so built this


value:
I’ve been messing around with the idea of having a coach that actually keeps up with you day to day. Most apps either make you log every crumb manually or just spit out generic meal plans. So I built this: a chat-based AI coach that logs your meals, and workouts, then uses that info to give you daily nudges and plans.
It’s still rough around the edges (bugs, UX quirks, the usual), but it’s already way more helpful than the spreadsheets and calorie counters I used before.
Would love feedback, feature requests, or “this sucks, here’s why.”

value: Show HN: Can an AI replace your nutritionist? I built one to try


value:
Back in college, I really enjoyed reading The Manga Guide to Calculus and other books in that series. Inspired by that, I recently added a feature to my app AISheets.study
that lets you turn any material into a manga-styled study guide using AI. It also supports other styles like xkcd and traditional colored comic styles.
The link I shared is an example I generated from Paul Graham’s essay on fundraising (https://paulgraham.com/fr.html)
Still ironing out a few quirks, but I thought it’d be fun to share this with the community!!

value: Show HN: Make Manga Study Guides on Any Subject


value: Show HN: Unified Sub-Agent Management

title: Show HN: Unified Sub-Agent Management


value: shanbin

value: Show HN: Self-hosted Amazon Bedrock router that learns from feedback (online RL)

author: shanbin


value: shawnconecone

value: Hi all, made this simple app with no frills just to calculate bills easily when splitting with friends. I fight with friensds on how to split bills too often so this app just calculates it and noone needs to choose which method of splitting.<p>I hope it's useful for you too. Let me know if you like it / don't like it, enjoy!

value: Show HN: I built a simple restaurant bill splitting app with receipt reading

author: shawnconecone


value:
We built SCAPO to collect specific, actionable tips about AI services (OpenAI, Claude, Midjourney, ElevenLabs, Copilot, etc.) from real Reddit threads: working parameters, cost-savers, rate limits, pitfalls, and usage patterns.
It discovers services, runs targeted queries, scrapes public JSON, uses an LLM to extract concrete advice, and writes organized markdown you can search or browse locally. There's a small TUI and an MCP server for LLM clients. MIT licensed.
If you don't want to install anything, you can just scan the SCAPO Models Archive to see if anything useful jumps out: https://czero-cc.github.io/SCAPO
Limitations: crowd-sourced tips can be wrong or stale; extraction quality depends on the model; scraping is throttled and avoids the Reddit API. We'd love feedback on failure cases, better query patterns, and additional services to cover.

value: Show HN: Scapo – Extract real usage tips from Reddit for AI services


value:
Hello, for some time I've been developing this project now that I am happy that it finally can see the light. I love Tor, but I believe the biggest thing with Tor is that the nodes are strangers which in itself requires some sort of level in just that, complete strangers.
For this reason, I decided to build this private network inspired by the Onion router. Unlike other public networks, GiralNet is not for anonymous connections to strangers. It is built for small teams or groups who want privacy but also need a level of trust. It assumes that the people running the nodes in the network are known and verifiable. This provides a way for a group to create their own private and secure network, where the infrastructure is controlled and the people behind the nodes are accountable. The goal is to provide privacy without relying on a large, anonymous public network.
In terms of technical details, it is a SOCKS5 proxy that routes internet traffic through a series of other computers. It does this by wrapping your data in multiple layers of encryption, just like the onion router does it. Each computer in the path unwraps one layer to find the next destination, but never knows the full path. This makes it difficult for any single party to see both where the traffic came from and where it is going.
I will gladly answer any questions you might have, thank you.

value: Show HN: GiralNet – A Privacy Network for Your Team (Not the World)


value: gargiulof

value:
I’ve been working on a compression algorithm for fast random access to individual strings in large collections.
The problem came up when working with large in-memory database columns (emails, URLs, product titles, etc.), where low-latency point queries are essential. With short strings, LZ77-based compressors don’t perform well. Block compression helps, but block size forces a trade-off between ratio and access speed.
Some existing options:
- BPE: good ratios, but slow and memory-heavy
- FSST (discussed here: https://news.ycombinator.com/item?id=41489047): very fast, but weaker compression
This solution provides an interesting balance (more details in the paper):
- Compression ratio: similar to BPE
- Compression speed: 100–200 MiB/s
- Decompression speed: 6–7 GiB/s
I’d love to hear your thoughts — whether it’s workloads you think this could help with, ideas for API improvements, or just general discussion. Always happy to chat here on HN or by email.
---
Resources:
- Paper: https://arxiv.org/pdf/2508.02280
- Rust: https://github.com/gargiulofrancesco/onpair_rs
- C++: https://github.com/gargiulofrancesco/onpair_cpp

value: Show HN: OnPair – String compression with fast random access (Rust, C++)

author: gargiulof


value: Show HN: Clipipe.io – Pipe data to another machine (open source)


value: Show HN: Stof – Unified data format and language


value: webzz

value:
Hi HN,
I built Bloogle
because I was frustrated with how much time it takes to set up and maintain a blog.
WordPress felt bloated, static site generators required too much config, and even "simple" platforms had friction.
With Bloogle, you just:
1. Write your post in Google Docs (where you’re already comfortable).
2. Paste the link into Bloogle.
3. Get a live blog instantly, already optimized for SEO.
Some details:
- Instant publishing: no CMS, no setup.
- Automatic SEO-friendly pages (structured data, indexing, sitemap).
- You can map it to your own domain or use a free yourname.bloogle.blog.
- You own analytics dashboard
Why I built this
I noticed that a lot of indie founders and freelancers never launch a blog because setup takes too much effort.
But a blog can be a huge source of traffic and credibility.
My thought: why not just use the tool most people already use for writing a.k.a Google Docs and skip the CMS entirely?
What I’d love feedback on
- Is this useful enough as-is, or do you need more customization (themes, analytics, comments)?
- Who do you think would benefit most: solo founders, agencies, or casual writers?
- Any red flags you see in terms of SEO / scaling?
You can check it and try it for free here: https://bloogle.blog
Thanks! I’d really appreciate any thoughts or brutally honest feedback.

value: Show HN: Bloogle – Turn Google Docs into a blog in 5 minutes

author: webzz


value:
Hi HN,
I’m a theoretical-physics–turned–software engineer, and over the last several months I built AsyncFlow, an open-source discrete-event simulator for asynchronous distributed backends.
Idea: create a digital twin of your service before you deploy. You define a topology in YAML (client → optional load balancer → N servers → network edges with stochastic latency) and a workload driven by a stochastic request generator. The simulator runs full request lifecycles through each server’s event loop with explicit models for CPU work (blocking), I/O waits (non-blocking), and RAM residency.
What you get: production-like metrics (p50/p95/p99 latency, RPS, queue lengths) and plots to answer questions like “How many cores do I need to keep p99 < 100 ms?” without spinning up infra or running an expensive load test.
Example with output (2-server LB):
https://github.com/AsyncFlow-Sim/AsyncFlow/tree/main/example...
Quick start
pip install asyncflow-sim
Repo & README: https://github.com/AsyncFlow-Sim/AsyncFlow
Why this vs load testing? Load tests (Locust, k6) measure a real system. AsyncFlow simulates one that doesn’t exist yet, so you can compare designs and size capacity offline, then validate with a load test later.
Status (alpha):
Works end-to-end; strict Pydantic schemas; ready-made plots; Pythonic builder.
Limits: simple network (latency + optional drops), single event loop per server, linear endpoint flows, no thread concurrency, single core per server.
Roadmap: Monte Carlo runs w/ confidence intervals, event injection (server down/up, network spikes), cache step, richer network model, richer nodes structure.
I’d love feedback on:
- YAML vs Python builder ergonomics
- Which metrics/plots you want by default
- Realistic knobs you’re missing for what-if capacity planning
MIT-licensed. Thanks!

value: Show HN: AsyncFlow – Event-loop aware simulator for async distributed systems


value: taoh

value:
Hi, HN!
Our team has been working on a suite of tools that help developers to better document their work. We released an open source tool [DeepGuide CLI](https://github.com/DeepGuide-Ai/dg) that records terminal and automatically convert it to SVG which can be copied and pasted, and allow search engine to index.
Why dg?
* Demo GIFs and Videos are large. dg replaces them with animated SVG, up to 50–100× smaller than equivalent GIFs, ensuring your README docs stays lightweight and fresh.
* Demos aren’t just illustrative; they’re re‑run and validated in github CI, so if something breaks, the PR fails.
* Works across any Node.js 18+ environment: macOS, Linux, and Windows (via WSL). We tried to use bun to build it into a binary program, but it was flakey due to the reliance on foundational programs.
* Open source: Built on solid and awesome OSS foundations like asciinema, node‑pty, and termsvg, all with permissive licenses.
It's easy to use:
```bash
# Install via npm (recommended):
sudo npm install -g @deepguide-ai/dg<p># Or run without installing:
npx @deepguide-ai/dg init
```
Once installed, you can just run `dg capture` which will start a pty that allows you to run any terminal programs. After exiting, the recording will automatically be converted to a SVG in your local folder. It streamlines the process of downloading asciinema, installing it, recording your workflow, and converting the cast to SVG into a single command.
Moreover, the recordings were saved into CI action folder. You can easily add them to your Github actions to re-run the workflow as part of CI.
If you’re tired of outdated CLI screenshots or bloated GIFs, dg might be just the tool for you — lightweight, automatic, and CI-friendly.
Do you think such tool is useful? Do you think it would help console devs to better document their work? Or is it useful to record CLI tools such as Claude Code or Gemini CLI sessions and share with others as SVGs? Would love your feedback, issues, or PRs!

value: Show HN: Open-source CLI that records your terminal into lightweight SVG demos

author: taoh


value: AmitleshedNY

value: SHOW HN: ActsAsActive: Plug-and-play activity tracking for ActiveRecord

author: AmitleshedNY


value: prateekkarki

value:
I’ve been working on my developer portfolio and blog, and I finally have it live. It’s built with Next.js + TypeScript + Tailwind, and I wanted to share it here and get some feedback from the community.
Features:
Projects showcase with live links and descriptions.
Blog section powered by Markdown/MDX (easy to add posts).
SEO-friendly with meta tags, sitemap, and Open Graph images.
Responsive design (works great on mobile and desktop).
Custom theming with twin.macro + styled components.
Downloadable résumé (with a simple access modal).
I’d love to hear your thoughts — whether it’s on the design, UX, performance, or content. Constructive criticism is super welcome.

value: Show HN: My developer portfolio and blog built with Next.js

author: prateekkarki


value:
Tired of AI coding tools that forget everything between sessions? Every time I open a new chat with Claude or fire up Copilot, I'm back to square one explaining my codebase structure.
So I built something to fix this. It's called In Memoria. Its an MCP server that gives AI tools persistent memory. Instead of starting fresh every conversation, the AI remembers your coding patterns, architectural decisions, and all the context you've built up.
The setup is dead simple: `npx in-memoria server` then connect your AI tool. No accounts, no data leaves your machine.
Under the hood it's TypeScript + Rust with tree-sitter for parsing and vector storage for semantic search. Supports JavaScript/TypeScript, Python, and Rust so far.
It originally started as a documentation tool but had a realization - AI doesn't need better docs, it needs to remember stuff. Spent the last few months rebuilding it from scratch as this memory layer.
It's working pretty well for me but curious what others think, especially about the pattern learning part. What languages would you want supported next?
Code: https://github.com/pi22by7/In-Memoria

value: Show HN: Built a memory layer that stops AI agents from forgetting everything


value: oluvvafemi

value: Hi HN, I am Chris, a solo founder. I am building software to help DTC fashion brands create media for product display pages and engaging promotional videos for social media.

value: Show HN: CostumePlay AI – Short Fashion Campaign Videos and On-Model Photos

author: oluvvafemi


value: Cykelero

value:
Last year I released Retcon, a Git GUI specifically made for rewriting history. Think `git rebase -i`, but with all the friction removed: no need to stash changes, a single undo command that works in any situation, and the ability to make changes even when there are conflicts. (so a bit of an alternative take on jj, that's more Git-compatible and comes with less mental load, but has its own tradeoffs)
Today I'm releasing version 1.4, which has basically one difference: everything is much faster. The app handles histories with hundreds of thousands of commits now, where before it'd freeze for seconds just trying to open these repos. So it's exactly the same thing as before, just much more pleasant to use, and usable on vastly larger repos.
I'm planning to write a series of blog posts of all the different optimizations once I've had time to rest, but in the meantime, I wanted to show the result of these efforts! If you're interested, the linked page has a couple of graphs showing some specific speed measurements.

value: Show HN: I spent two months optimizing my Git client

author: Cykelero


value:
Hey HN,
Over the years, I've built quite a few OpenAPI specs that'd get neglected over time and where the endpoints would eventually drift away from the spec.
I wanted to build something super lightweight that I could drop in during development to double check that my endpoints still match the spec as expected.
SpecGate is a lightweight proxy that checks API responses against the given OpenAPI spec. It'll tell you if there's an undocumented endpoint or if the response doesn't match the spec. I managed to catch about 10 issues with one of my more recent specs as soon as I started using it.
It's possible to run this in production as well, but it currently only logs to stdout/stderr, so keep that in mind if you decide to run it in production.
Would love to hear your feedback on this tool.

value: Show HN: SpecGate – Validate API responses against OpenAPI in real-time


value: grouchy

value:
Hi HN--
Tambo is a React SDK that lets your app render and control UI components based on natural language input.
We are hooked on Cursor and want all our apps (Stripe, Vercel, GitHub) to have the same experience. I should be able to type `update env key` and get a UI to add it.
Tambo lets an AI assistant render or update the state of registered React components.
It can fetch context via MCP (Model Context Protocol) or client-side fetches (similar to OpenAI tool calls).
The SDK handles streaming messages and prop updates, maintains thread history, and passes context across turns. It’s BYOM (Bring Your Own Model) and works with Next.js, Remix, Vite, and React Native.
If you’re building a “Cursor for X” (spreadsheets, video, design, etc.), check it out.
Yesterday, we went 100% open source.
Docs: https://docs.tambo.co
GitHub: https://tambo.co/gh
— Michael x2, Alec, Akhilesh

value: Show HN: Tambo Add A Cursor style assistant for React apps (OSS, self-hosted)

author: grouchy


value: twistorino

value:
I’ve been working on Cheatsheet++. A free site with 50k+ tech interview Q&As across multiple topics.
New feature:
Users can now upvote/downvote answers
Add comments to share alternative approaches
The goal is to move from a static Q&A bank to a living, community-driven prep tool.<p>I’d love feedback from HN:
Do you think community voting improves interview prep, or is it better to keep curated, single answers?
Any pitfalls you see in opening answers up to comments?

value: Show HN: Cheatsheet++. Free Tech Interview Q&As (now with voting and comments)

author: twistorino


value: BuiltSimpleAi

value: Show HN: I made Python uncrashable, it catches every exception

author: BuiltSimpleAi


value: culturengine

value: Show HN: Skate Moves – Spatial pro skating with real-time body tracking (~10ms)

author: culturengine


value: cosmosfr

value:
Hey Hacker News,
We all know Reddit marketing can be a minefield. There's a fine line between being helpful and being a spammer. We've seen founders find their first users by genuinely engaging, but finding the right moment to add value manually is nearly impossible to scale.
I built Reddit Genius AI to fix this. It’s a "listening tool" designed to help you do outreach the right way.
It monitors relevant subreddits for keywords—pain points, competitor mentions, requests for help—and flags conversations where you can make a real contribution. The AI assistant then helps you draft a thoughtful comment, turning a cold outreach into a warm, helpful interaction.
The goal is to automate the tedious 90% of searching so you can focus your energy on the critical 10%: actually helping people.
I’m trying to build tools that keep us on the right side of the spam line. Is this a fool's errand, or is there a real need for this? I'd love your perspective.

value: Show HN: I built a app to find your first users by listening to Reddit community

author: cosmosfr


value: olehtsyupa

value: Show HN: Free privacy-focused PDF tracking with analytics

author: olehtsyupa


value: thedkpatel

value:
I got tired of spending 20 minutes Googling ffmpeg syntax every time I needed to process a video. So I built aiclip - an AI-powered CLI that translates plain English into perfect ffmpeg commands.
Instead of this:
  ffmpeg -i input.mp4 -vf "scale=1280:720" -c:v libx264 -c:a aac -b:v 2000k output.mp4
Just say this:
  aiclip "resize video.mp4 to 720p with good quality"
Key features:
- Safety first: Preview every command before execution
- Smart defaults: Sensible codec and quality settings
- Context aware: Scans your directory for input files
- Interactive mode: Iterate on commands naturally
- Well-tested: 87%+ test coverage with comprehensive error handling
What it can do:
- Convert video formats (mov to mp4, etc.)
- Resize and compress videos
- Extract audio from videos
- Trim and cut video segments
- Create thumbnails and extract frames
- Add watermarks and overlays
GitHub: https://github.com/d-k-patel/ai-ffmpeg-cli
PyPI: https://pypi.org/project/ai-ffmpeg-cli/
Install: pip install ai-ffmpeg-cli
I'd love feedback on the UX and any features you'd find useful. What video processing tasks do you find most frustrating?

value: Show HN: AI-powered CLI that translates natural language to FFmpeg

author: thedkpatel


value: seekerquest

value: Show HN: Twick - React SDK for Timeline-Based Video Editing

author: seekerquest


value: nvrstl

value:
Hi HN,
At the 2023 Hawking Fellowship at Cambridge Union, a student asked Sam Altman:
“To get to AGI, can we just keep min-maxing language models, or is there another breakthrough that we haven’t really found yet?”
Altman’s response was telling:
“We need another breakthrough… I don’t think that doing that will get us to AGI. If, for example, superintelligence can’t discover novel physics, I don’t think it’s a superintelligence. Teaching it to clone the behavior of humans and human text – I don’t think that’s going to get there.”
If Altman is right that scaling alone is a dead end, then this might be the beginning of the real race - not just to build bigger LLMs, but to invent the architectures that can discover the unknown.
This echoes a long-standing question in AI research: what lies beyond scaling language models in the pursuit of true general intelligence?
Did we finally stumbled onto the next breakthrough Altman was hinting at?
We think so.
Collective AGI: The Civilizational Path to AGI
Rooted in History:
Human intelligence didn’t become powerful in isolation. A single brain is limited. What made human intelligence general and world-changing was the civilizational process - networking, collaboration, culture, institutions, governance, commerce, law, ethics - compounding across generations.
A Pattern, a Fractal:
Ecosystems evolve through interdependent species; human intelligence evolved through interdependent minds. Civilization was humanity’s first great outcome of collective intelligence, recursively amplifying the reach of individual cognition.
Applied to AGI:
In the same way, AGI won’t emerge from a single artifact or mono-worldview. It must arise through plurality of AI forms, multi-agent networks, evolving institutions, and shared participation - the same mechanisms that scaled human intelligence, now applied to artificial intelligence.
If that’s true, the next breakthrough isn’t bigger LLMs. It’s building civilizational ecosystems for AI societies scale - that don’t just predict text, but evolve new knowledge, new institutions, and new ways of thinking.
I'm Kanishka Nithin, I’ve been working on AI for over a decade, and today I’m excited (and a little nervous) to share something deeply personal and long in the making: AGI Grid - our open effort to together build what we call Collective AGI - The open, fastest, safest, and most efficient path to Artificial General Intelligence.
AGI Grid: It is a open civilizational infrastructure ecosystem for collective AGI
Website: https://www.agigr.id
Vision paper: https://resources.agigr.id
The collective AGI ecosystem consists of 12 Open source projects - listed at
Docs: https://docs.agigr.id
What we’d love from HN:
Feedback: Does this framing of Collective AGI resonate?
Critique: Where do you see the holes?
Collaboration: If you’re working on agents, collective intelligence, or diverse cognitive architectures, let’s talk.
This project grew out of both crisis and conviction, and we believe the next leap in AI won’t come from a single giant model, but from grids of diverse forms of intelligence, aligned and cooperating.
-Team
AGI Grid:  A Collective AGI

value: Show HN: Sam Altman:"Scaling LLMs won't get us to AGI" – maybe we found a path

author: nvrstl


value: kstonekuan

value: Show HN: Web Agent Memory Protocol (WAMP) – Building Shared Memory for the Web

author: kstonekuan


value: trajectoryfyi

value: Show HN: Trajectory.fyi – Compare people and companies by age

author: trajectoryfyi


value:
Lemonade is an open-source SDK and local LLM server focused on making it easy to run and experiment with large language models (LLMs) on your own PC, with special acceleration paths for NPUs (Ryzen™ AI) and GPUs (Strix Halo and Radeon™).
Why?
There are three qualities needed in a local LLM serving stack, and none of the market leaders (Ollama, LM Studio, or using llama.cpp by itself) deliver all three:
1. Use the best backend for the user’s hardware, even if it means integrating multiple inference engines (llama.cpp, ONNXRuntime, etc.) or custom builds (e.g., llama.cpp with ROCm betas).
2. Zero friction for both users and developers from onboarding to apps integration to high performance.
3. Commitment to open source principles and collaborating in the community.
Lemonade Overview:
Simple LLM serving: Lemonade is a drop-in local server that presents an OpenAI-compatible API, so any app or tool that talks to OpenAI’s endpoints will “just work” with Lemonade’s local models.
Performance focus: Powered by llama.cpp (Vulkan and ROCm for GPUs) and ONNXRuntime (Ryzen AI for NPUs and iGPUs), Lemonade squeezes the best out of your PC, no extra code or hacks needed.
Cross-platform: One-click installer for Windows (with GUI), pip/source install for Linux.
Bring your own models: Supports GGUFs and ONNX. Use Gemma, Llama, Qwen, Phi and others out-of-the-box. Easily manage, pull, and swap models.
Complete SDK: Python API for LLM generation, and CLI for benchmarking/testing.
Open source: Apache 2.0 (core server and SDK), no feature gating, no enterprise “gotchas.” All server/API logic and performance code is fully open; some software the NPU depends on is proprietary, but we strive for as much openness as possible (see our GitHub for details). Active collabs with GGML, Hugging Face, and ROCm/TheRock.
Get started:
Windows? Download the latest GUI installer from https://lemonade-server.ai/
Linux? Install with pip or from source (https://lemonade-server.ai/)
Docs: https://lemonade-server.ai/docs/
Discord for banter/support/feedback: https://discord.gg/5xXzkMu8Zk
How do you use it?
Click on lemonade-server from the start menu
Open http://localhost:8000 in your browser for a web ui with chat, settings, and model management.
Point any OpenAI-compatible app (chatbots, coding assistants, GUIs, etc.) at http://localhost:8000/api/v1
Use the CLI to run/load/manage models, monitor usage, and tweak settings such as temperature, top-p and top-k.
Integrate via the Python API for direct access in your own apps or research.
Who is it for?
Developers: Integrate LLMs into your apps with standardized APIs and zero device-specific code, using popular tools and frameworks.
LLM Enthusiasts, plug-and-play with:
Morphik AI (contextual RAG/PDF Q&A)
Open WebUI (modern local chat interfaces)
Continue.dev (VS Code AI coding copilot)
…and many more integrations in progress!
Privacy-focused users: No cloud calls, run everything locally, including advanced multi-modal models if your hardware supports it.
Why does this matter?
Every month, new on-device models (e.g., Qwen3 MOEs and Gemma 3) are getting closer to the capabilities of cloud LLMs. We predict a lot of LLM use will move local for cost reasons alone.
Keeping your data and AI workflows on your own hardware is finally practical, fast, and private, no vendor lock-in, no ongoing API fees, and no sending your sensitive info to remote servers.
Lemonade lowers friction for running these next-gen models, whether you want to experiment, build, or deploy at the edge.
Would love your feedback!
Are you running LLMs on AMD hardware? What’s missing, what’s broken, what would you like to see next? Any pain points from Ollama, LM Studio, or others you wish we solved?
Share your stories, questions, or rant at us.
Links:
Download & Docs: https://lemonade-server.ai/
GitHub: https://github.com/lemonade-sdk/lemonade
Discord: https://discord.gg/5xXzkMu8Zk
Thanks HN!

value: Show HN: Lemonade: Run LLMs Locally with GPU and NPU Acceleration


value:
Hi HN,
We’ve been working on a project to automate one of the most painful but universal tasks: turning scattered data and notes into polished, professional documents.
The idea is simple:
You upload the final document you normally produce (e.g., a monthly report, project update, or client deliverable).
You also upload the raw inputs you usually work from (Excel sheets, PDFs, Word notes, etc.).
The system learns the mapping, so next time you can just drop in the new raw inputs and instantly get the finished document.
Example workflow I’ve been testing:
Raw inputs: a spreadsheet of KPIs, a staffing note in Word, and a PDF of receivables.
Output: a clean monthly business performance report in Word.
The goal is to make this general-purpose (works for consultants, engineers, businesses — anyone who spends hours creating repetitive docs/reports).
Right now this works best with small–medium files (big inputs may time out). I’m still improving performance, but wanted to share early to get feedback.” I’d love feedback on:
What kinds of documents you’d actually want automated.
Whether the “teach it once, reuse forever” approach makes sense to you.
Any must-have features you’d expect before using something like this.
You can try it here: https://gridfusion.ai/
Below are some automations we built for a couple of different consulting companies:
Report Generation: https://www.youtube.com/watch?v=wvOiQtIW5P8
                 Google Earth File Generation: https://www.youtube.com/watch?v=cU0VMgdB06Y
Would love to hear your thoughts and critiques!

value: Show HN: Generate polished reports/docs automatically from messy inputs


value: Sean-Der

value: I have been working on making WebRTC + Embedded Devices easier for a few years. This is a hackathon project that pulled some of that together. I hope others build on it/it inspires them to play with hardware. I worked on it with two other people and I had a lot of fun with some of the ideas that came out of it.<p>* Extendable/hackable - I tried to keep the code as simple as possible so others can fork/modify easily.<p>* Communicate with light. With function calling it changes the light bulb, so it can match your mood or feelings.<p>* Populate info from clients you control. I wanted to experiment with having it guide you through yesterday/today.<p>* Phone as control. Setting up new devices can be frustrating. I liked that this didn't require any WiFi setup, it just routed everything through your phone. Also cool then that they device doesn't actually have any sensitive data on it.

value: Show HN: OpenAI/reflect – Physical AI Assistant that illuminates your life

author: Sean-Der


value: artifects

value: Show HN: AI that finds qualified leads (pay per result)

author: artifects


value: This is a simple project to create a binary clock using a ESP8266 and some WS2812 single addressable leds. Use the wi-fi connection to syncronize the time via NTP, change timezone, led color and brightness via Serial commands or physical buttons. In this case, i've used two "touch" button behind the front mask (STL for box and mask attached) for a better, minimal design.

value: Show HN: A simple binary clock, just for fun


value: st-matskevich

value:
I was recently working on wake words detection and came up with a different approach to the problem, so I wanted to share what I have built.
I started working on a project for a smart assistant with MCP integration on Raspberry Pi, and on the wake word part I found out that available open source solutions are somewhat limited. You have to either go with classical MFCC + DTW solutions which don't provide good precision or you have to use model-based solutions that require a pre-trained model and you can't let users use their own wake words.
So I took advantages of these two approaches and implemented my own solution. It uses Google's speech-embedding to extract speech features from audio which is much more resilient to noise and voice tone variations, and works across different speaker voices. And then those features are compared with DTW which helps avoid temporal misalignment.
Benchmarking on the Qualcomm Keyword Speech Dataset shows 98.6% accuracy for same-speaker detection and 81.9% for cross-speaker (though it's not designed for that use case). Converting the model to ONNX reduced CPU usage on my Raspberry Pi down to 10%.
Surprisingly I haven't seen (at least yet) anyone else using this approach. So I wanted to share it and get your thoughts - has anyone tried something similar, or see any obvious issues I might have missed?
GitHub - https://github.com/st-matskevich/local-wake

value: Show HN: Wake word detection with custom phrases without model training

author: st-matskevich


value: amaan-mohib

value:
Hi HN,
I’ve been working on a project called Delta Widgets, a desktop widget maker for Windows.
The idea: make it easier to create and customize widgets without having to edit .ini files or configs like with Rainmeter. You can design visually using a drag-and-drop builder, or write your own HTML/CSS/JS if you want more control.
Some features:
Drag-and-drop widget builder (no coding needed)
Or load widgets from custom HTML/CSS or a live URL
Support for dynamic data like time, system info, and media playback
Pre-made templates to start quickly
Built on Tauri (Rust + system WebView) → lightweight, secure, native feel
Website: https://delta-widgets.vercel.app/
Product Hunt: https://www.producthunt.com/products/delta-widgets?utm_sourc...
Peerlist: https://peerlist.io/amaanmohib/project/delta-widgets

value: Show HN: Delta Widgets – A widget maker for Windows using Tauri

author: amaan-mohib


value: froschXP

value:
Hey all
I love Claude Code but was burning through my Anthropic credits way too fast. Wanted to hook it up to cheaper providers like OpenRouter, but Claude Code expects Anthropic's API format.
So I built a simple proxy that sits in the middle - Claude Code thinks it's talking to Anthropic, but I'm actually hitting whatever LLM I want. Bonus: I had multiple API subscriptions sitting around, so I added key rotation to cycle through them all efficiently. Would be happy to get some feedback or suggestions to improve it.

value: Show HN: LLM API proxy with API token rotation

author: froschXP


value: frknbasaran

value: Show HN: I made insta-like stories widget to mobile sites

author: frknbasaran


value: Show HN: SEO Middleware for Next.js

title: Show HN: SEO Middleware for Next.js


value: yegemberdin

value:
Hi everyone! I wanted to share something wonderful we've been working on for the past months.
We found a way to leverage AI to make designs on a canvas, and we're building a design tool that can help with various tasks, from exploring different UX flows, layouts to complex tasks like building your design system.
If you are a designer or worked with designs in the past, we would love to get your feedback on what things can be useful for you!
We will be launching it with select people soon and hope that we can bring value to the design community.

value: Show HN: Wonder – AI-native design tool on canvas

author: yegemberdin


value: rushter

value:
I made a new library to detect malicious and harmful behaviour in Python scripts.
There are alternative libraries, but they usually rely on regexes, which can be fragile and tricked. My library uses AST and tracks some of the obfuscation techniques, such as import/call reassignment.
Currently, I'm testing it on public files where some of them implement malicious behavior, as well as past malicious packages on PyPI.
You can see some of the detection examples here:
https://github.com/rushter/hexora/blob/main/docs/examples.md
I'd love to hear your feedback and ideas on how to improve this and identify missing rules.

value: Show HN: Hexora – static analysis tool for malicious Python scripts

author: rushter


value: rakeda

value:
Hey HN, I’m Brandon, developer for Harbor Guard, an open-source container security platform that unifies multiple scanning tools into a single intuitive dashboard.
Over the past month, I got tired of juggling different CLI scanners (Trivy, Grype, Syft, Dockle, etc.), for my work in DevSecOps. Stitching results together started becoming a hassle and my organization started heavily focusing on container security. It was messy, repetitive, and hard to keep track of active vulnerabilities.
So I built Harbor Guard, a modern, Next.js app that runs all major open-source container scanners, stores the results, and turns them into interactive visualizations you can actually use.
What Harbor Guard does:
- Runs 6 major tools: Trivy, Grype, Syft, Dockle, OSV Scanner, and Dive
- Unified dashboard: View and compare results without jumping between CLIs
- Historical tracking: Persist and compare scans across versions
- Advanced visualization: Interactive scatterplots, severity-based grouping, and layer-by-layer analysis
- Report export: Grab JSON or full ZIP packages for compliance
- API access: REST endpoints for automation and integrations
- Docker-native: Run it with a single docker run -p 3000:3000
Personally, I needed a tool that made vulnerability data easier to explore visually and had some fun putting something together.
GitHub: https://github.com/HarborGuard/HarborGuard
Live Demo: https://demo.harborguard.co
It’s free, open source, and I’d love feedback, bug reports, or feature ideas. Contributions welcome too.
Thanks, Brandon~

value: Show HN: Harbor Guard – Manage and Scan Container Images (Open Source)

author: rakeda


value: thebeardisred

value:
Aloha HN - I'm redbeard, ex-CoreOS homey, RISC-V guy, and general free software wingnut.
Like many of us, I've increasingly found myself using AI for my work.  One of the challenges for me is that I prefer to stay on the command line and I'm often working on remote machines over SSH.  This often means moving off of the keyboard to use the mouse or a complex chording of characters to capture output from the buffer.  Capturing a single file isn't too challenging on a localhost (`cat | wl-copy` /`cat | pbcopy`, etc) but this is still really focused on single files.  If you're capturing multiple files, the content (of course) gets catenated together.
"There's got to be a better way!"
After realizing the many terminals support ANSI control code OSC 52 and my preferred terminal, Kitty, supports OSC 5522 I put together "rucat", a cat inspired tool for capturing multiple files with additional semantic data.
Rucat excels at capturing multiple files quickly and without worrying about serialization loss.  It's been written in Rust to intentionally avoid a number of memory safety and string parsing issues as well as providing a path to cross platform support.  The tool is currently available in binary and source form in the repository.  Feedback is welcomed!

value: Show HN: Rucat – Cat for Prompt Engineers

author: thebeardisred


value: txprog

value: Built this because LLM tools with MCP servers (OpenCode, Goose, Claude code, etc.) have too much network access. It uses network_mode: 'service:x' to force containers through iptables rules that drop everything except whitelisted domains. No proxy - operates at the network namespace level so bypasses aren't possible.

value: Show HN: Network-filter – domains-based whitelist for Docker containers

author: txprog


value: Temukan nama China yang sempurna dengan generator bertenaga AI. Ciptakan nama-nama yang bermakna dan otentik secara budaya.

value: Show HN: Generator Nama China

title: Show HN: Generator Nama China


value: howardV

value:
Hey HN!
I’m building IndieRadar, an AI-powered scout that trawls technical subreddits and turns raw posts into actionable “opportunity cards.” Each card includes:
• Demand score (0-10) – based on intent phrases, failed attempts, and impact
• Type (billing | workflow | missing-feature…)
• Urgency & pay-signal (0-3)
• A compliant follow-up draft so you don’t break subreddit rules
Why?
• I wasted hours combing r/IndieHackers & r/webdev, only to realise 90 % is noise.
• Generic “trending keywords” tools ignore real purchase intent.
• Cold-DM is spammy; I want data-backed pull signals instead of push outreach.
How it works
1. Pick subreddits / topics
2. Keyword & rule-based filter
3. LLM labels high-potential posts (we only run AI on likely hits to keep costs low)
4. Alerts in real-time or a 3-minute daily digest (Email/Slack/Webhook)
Ask
• Would this save you research time?
• Would you use？
• Do you have any good suggestions?
• Which community should we support next (HN, PH, GitHub Issues are on the roadmap)?
Try the private beta: drop your email at indieradar.dev (7-day trial, no CC).
Promise: no auto-posting, no data-selling.
Thanks! Happy to answer anything about scoring heuristics, Reddit API woes, or launching without spamming.

value: Show HN: IndieRadar – AI finds build-worthy problems on Reddit

author: howardV


value: aayush-kosh

value:
While leading tech for a fintech org where we built out a relatively large and complex project in django and celery backed by postgres, we often came up with testing situations that needed real-world data to work with.
We created an in-house hacked together version of what is now stagDB using only docker and zfs.
stagDB allows its user to create a database, load it with data to create a master, and then create as many clones as the underlying hardware may support.
This is still version 0.0.1 of the product. Feedback is welcome.

value: Show HN: stagDB – Free and Open-Source database manager with instant branching

author: aayush-kosh


value: qwikhost

value: Scrape B2B leads from Apollo.io with verified emails, phone numbers & company data. Fast, accurate prospecting.

value: Show HN: Apollo Exporter – Extract and Export Apollo B2B Leads

author: qwikhost


value: hgarg

value: Show HN: Discover everything related to MCPs in one place

author: hgarg


value: dahuangf

value: Professional image editing platform powered by 20B parameter Qwen-Image-Edit model, supporting semantic editing, appearance editing, and precise bilingual text processing

value: Show HN: Qwen Image Edit– Intelligent Image Editing with Qwen-Image-Edit Vision

author: dahuangf


value: glockxx

value:
Hello everyone,
I was tired of bloated invoicing apps, paywalls, and forced signups, so I built PineBill. It runs entirely in your browser: fill in products and customer details on the left, see a live preview on the right, then export/download a PDF. No ads, no tracking, no account.
I first shared it on Reddit and got a bunch of thoughtful feedback; it’s now at ~3k monthly active users. I’d love your critiques, bug reports, and feature ideas.
Reddit post: https://www.reddit.com/r/SideProject/comments/1ksnikx/i_made...

value: Show HN: PineBill – make invoices in the browser (free, no ads, no account)

author: glockxx


value:
Hi HN,
I’m Lily, a solo indie maker, and I’ve been working on Textideo
 — an AI video generator that turns text prompts into short videos.
Why I built this
I’ve always found creating videos challenging. Traditional editing tools are heavy, expensive, and require skill. On the other hand, most AI tools I tried were either locked behind subscriptions or required publishing outputs publicly. I wanted something simple: pay-as-you-go, private, and accessible to anyone.
How it works
You enter a short text prompt (e.g., “A cat walking on the grass at sunset”).
The system runs it through multiple text-to-video models (Google Veo 3, WAN, etc.).
Within 30–60 seconds, you get a short MP4 clip you can download.
No subscription, no login required for trying the demo.
Under the hood:
Backend is built with Python (FastAPI) + PyTorch + FFmpeg for video rendering.
Frontend is in React + Tailwind, optimized for minimal UI friction.
Videos are generated via a credits system instead of recurring payments.
What’s different
No subscription lock-in — buy credits only when you need.
Privacy first — you don’t need to make your outputs public.
Multiple models in one place — test different AI video generators without juggling accounts.
Current status
The project is in beta. You can try generating a short video right on the homepage. I’d love to hear your feedback — technical, UX, or ideas for improvement.
https://textideo.com
Thanks for reading, and I’m happy to answer any questions!

value: Show HN: Textideo – Generate short AI videos from text prompts


value: oliverbenns

value: After years of working in crypto fintech, I noticed a problem in the industry that needs solving: every institution is building the same UI functionality and trading components from scratch.<p>So I built a React starter kit! It gives you the building blocks to kick start your trading application with customisation and core trading components.

value: Show HN: Hedge UI – React starter kit for trading applications

author: oliverbenns


value: agiordanelli

value:
Hi HN,
I built Web Server Components, a minimalist (~1KB min+gz) TypeScript library that enables SSR + hydration with Custom Elements using just a simple decorator and base class — no frameworks, zero dependencies.
At its core:
withWSC decorator auto-registers your element.
WSC is an isomorphic HTMLElement wrapper — so you can safely call .render(...) on the server and append the same element client-side.
Highlights:
~1KB min+gz
Zero dependencies
Standards-only: Custom Elements + Declarative Shadow DOM
SSR + minimal hydration with no framework lock-in
Live demo:  https://1kb.alexandre-giordanelli.workers.dev/
Repo: github.com/alexandregiordanelli/web-server-components
The goal is to show that you don’t need a framework to get SSR + hydration with Web Components — just a decorator and a lightweight HTMLElement wrapper.
Would love feedback, comparisons with other minimal SSR approaches (htmx, Lit, etc.), and ideas for improvements. Thanks!

value: Show HN: Web Components SSR and hydration in 1KB– just a decorator, no framework

author: agiordanelli


value: liltofu

value:
I built a web game where anyone can submit a fact or a lie anonymously (no authentication or login required). You can also guess on others' truth or made-up myths. Think "Two Truths and a Lie" but crowdsourced and with scoring.
What it is:
Players submit interesting claims such as "I think bitcoin can reach $1MM."
Other players vote on whether each submission is Truth or Myth.
Why this works:
The best part is the community creates all the content. I've been amazed by the creative myths people invent and the bizarre-but-true facts they dig up. Some submissions have stumped 90%+ of players.
What surprised me:
Players are incredibly good at crafting believable myths. The voting patterns reveal fascinating insights about what kinds of "facts" people instinctively trust vs. doubt.
The HN crowd tends to be skeptical of everything - curious to see how you perform compared to other communities I've tested this with.
Play here: https://truth-wave.lovable.app/
Would love feedback on the mechanics and any interesting submissions you come up with!
Will incorporate more features as statements increase.

value: Show HN: Truth Wave – Community Driven Truth or Myth Game

author: liltofu


value: xiaoshumiao

value:
I've always been fascinated by the structure of tarot and the psychology behind why people find it meaningful. As an experiment, I built https://www.randomtarotcard.org/ai-tarot-reading to see if modern LLMs (I'm using a fine-tuned OpenAI model) could generate thoughtful, personalized tarot readings.
The tech stack is simple but effective: Next.js frontend, a serverless function to handle the AI API call, and a prompt engineering system that provides the AI with rich context on each card's symbolism (upright and reversed) before it generates the interpretation for the user's specific question.
It's completely free—this is just a fun side project. I'd love the HN community's feedback on a few things:
The quality of the interpretations. Do they feel generic or surprisingly insightful?
The user experience. Is it clear and engaging?
The ethical considerations of an "AI mystic." It's a strange new world.
You can try it here: https://www.randomtarotcard.org/ai-tarot-reading
The code is not open source, but I'm happy to answer any technical questions about the implementation!

value: Show HN: An AI-powered tarot card reader that gives surprisingly deep readings

author: xiaoshumiao


value: jumpdong

value: Welcome

value: Show HN: Random Letter：I build a website that can generate random things

author: jumpdong

story_text: Welcome


value: karnoldf

value:
Hi HN,
I’m excited to share The Point Poker [https://www.thepointpoker.com], a web app I built in a month to make agile effort estimation fun and intuitive. As an engineer in a company running 3-4 grooming/planning sessions per sprint, I wanted a tool that’s fast, visually appealing, and engaging for pointing tasks and stories.
The Point Poker is an MVP focused on engineers (B2C for now), built with Astro, React, Vercel, Supabase, and Shadcn for a smooth, minimal experience. What sets it apart:
- *Minimal UI*: Designed in Figma for a clean, distraction-free interface.
- *Gamification*: Level up as you point, keeping sessions engaging.
- *Custom Cards*: Unlock unique cards (crafted in Procreate) to estimate with style.
I used Plausible Analytics for privacy-first usage tracking to understand how teams interact. Future plans include B2B features like Jira/Slack integrations and team wellness tools (e.g., sentiment dashboards).
I’d love your feedback on the UI, gamification, or tech stack. What features would you want in a team-focused version? Try it at [https://www.thepointpoker.com] and let me know your thoughts!
Thanks

value: Show HN: The Point Poker – A Stylish Web App for Agile Effort Estimation

author: karnoldf


value:
hanaco Weather is a minimalist social network where users post short, emotional weather thoughts and connect with others experiencing the same weather.
No likes or followers (for now) — just gentle presence.
Built entirely by a solo engineer, including the custom operating system it runs on: OS Yamato.
What is OS Yamato?
OS Yamato is a poetic, ephemerality-first operating system designed to let digital memories bloom and fade, like flowers in the wind.
Features include:
Diaries that bloom like seasonal flowers — and wither if forgotten
Photos and videos that quietly disappear unless viewed again
Chat with ambient seasonal effects and no pressure
A soft, nature-inspired calendar with reusable schedule templates
Wind Messages — time-delayed letters that arrive months later
A 3D globe to see fleeting connections blossom around the world
Each app within OS Yamato reflects a different way of embracing impermanence in the digital world.
Learn more about the concept and philosophy: [YouTube – Write a diary, and a flower will bloom](https://youtu.be/JrqwU_N5WBA?si=kZQAadNdBGipk6gz)
Try Hanaco Weather now: https://hanaco875.com
#ShowHN #HanacoWeather #OSYamato #solodev #minimalism #digitalpoetry #webapp #ephemeral

value: Show HN: Hanaco Weather – A poetic weather SNS from the OS Yamato project


value:
Hi HN — I built STIX, a tool that calculates a simple 0–100 score for US stocks and ETFs. The score describes whether the ticker is institutionally sponsored and thusly primed for higher pricing. It’s meant to help active traders decide what to lean into—and what to avoid.
What it is: STIX produces a per-ticker score for US equities and ETFs, plus sector and market aggregates, updated daily. Higher and rising scores suggest stronger structural support; lower and falling scores suggest potential distribution or fragility. It’s not a price predictor—think of it as a distilled view of where larger players appear to be accumulating or distributing risk.
Why I built it: Most trading tools surface signals that are incredibly complex to understand and require a lot of subjective interpretation. I wanted a positioning-centric tool that simply and concretely expressed to users whether a stock had a higher probability of appreciating or deteriorating.
How it works (high level): Each day STIX ingests trade/quote data from all US exchanges and engineers features around size/lot anomalies, time-of-day behavior, persistence, breadth, clustering and more. A rules-plus-ML pipeline weights these features and normalizes them from which a 0–100 score is derived per symbol. Zones where larger players campaign tend to mark areas of interest; holding above those zones can indicate supportive positioning, while trading below can indicate distribution or short pressure.
Outputs: Current score, short-term change, sector rollups, and simple screens.
Try it: https://stix-v1.onrender.com
 — use promo code STIXTRIAL to waive the $2.50 day pass and get 24 hours free.
Feedback I’d love: Does the signal explanation make sense? What, if anything, is confusing in onboarding or UX? Did you hit any latency or performance bottlenecks? Which programmatic outputs (API or CSV) would be most useful?
Notes: This is research/analytics, not financial advice. No trackers or ads. Emails (if used) are for key generation only. I’m iterating actively—candid criticism is welcome, and I’ll be in the thread.

value: Show HN: STIX – Institutional positioning in US equities revealed as a score


value: natewww

value:
Just wanted to share my latest project Taskstax, it's just a simple Kanban kind of trello clone, built mainly for the learns, but it works too so it's online.
Simple Kanban boards, easy login that takes you straight to it.
It uses socket.io for data xfer after login which was fun to setup and also makes it work well.
Totally free, any feedback would be cool or if you wanted some info on the tech just ask.

value: Show HN: Because I Kanban

author: natewww

title: Show HN: Because I Kanban


value: masutaka

value: Show HN: Emacs Helm Interface for Raindrop.io

author: masutaka


value: Vue-uForm is an unstyled, flexible form validation library for Vue 3, focusing on component-driven design.

value: Show HN: An unstyled, flexible form validation library for Vue 3


value: artiomyak

value: Show HN: Flags Quiz

author: artiomyak

title: Show HN: Flags Quiz


value: jumpdong

value: welcome

value: Show HN: Vibe Coding：I built a website that can use multiple coding AI models

story_text: welcome


value: gavino

value: I also wrote a blog post detailing my time building this project here: https://gavin.wtf/blog/building-spectre

value: Show HN: Spectre, a coding agent for llama.cpp servers

author: gavino


value:
Hi HN!
I’m launching VoxDemo, a browser-based tool to record your screen, add AI voiceovers, and fine-tune everything with a timeline editor.
What it does:
- Record your screen in the browser (no installs)
- Add AI voiceovers (6 natural voices to start)
- Use the timeline editor to cut, trim, and sync voiceover to the video
- Share instantly via a link
Why I built it:
Creating narrated demo videos is tedious if you don’t like recording your own voice or wrangling heavyweight editors. VoxDemo aims to make clean, narrated demos fast.
Current limitations:
No “how it works” video yet, and since this is the MVP, I’ll be adding new features over time.
Would love feedback on the workflow and what you’d want next. Feel free to comment here or use the feedback form on my site if that’s easier. Thanks!

value: Show HN: VoxDemo – Create demo videos with AI voiceovers


value:
I built *Tempmail3*—a lightweight, disposable email service that works instantly and requires *no signup or verification*.
*Why I built this*
I often needed quick email addresses for testing or sign-ups—but existing services were slow, cluttered, or required entering my real email. So I built Tempmail3 to be as fast and frictionless as possible.
*What it does*
- Generate a temporary email with one click.
- View incoming emails in real time via the browser.
- Discard or regenerate the address anytime.
- (Optional) This is an open-source project: [GitHub link].
*Technical details & challenges*
- Back-end is in Go, using in-memory store for emails to guarantee speed.
- Email retrieval via WebSocket for live updates.
- Rate-limiting to prevent abuse, while keeping user experience seamless.
- Lightweight CSS/UI for ultra-fast load times.
*Differences from other services*
- No ads, trackers, or cluttered UI.
- Minimalistic, lightning-fast UX.
- Open-source and privacy-focused—no logs retained more than 1 hour.
- Hosted on low-tier infrastructure—demonstrates that even with limited resources, it stays responsive.
I’d love feedback on:
- UX or UI improvements—what would make me use this everyday?
- Abuse prevention—any suggestions for better rate-limiting or abuse mitigation?
- Feature ideas—e.g. custom domains, API, etc.
Happy to walk through any part of the design or code if anyone is curious!

value: Show HN: Tempmail3 – Instant disposable email service, zero signup, open-source


value: zemaj

value:
Hey HN,
Today we're launching Code, a community-driven, open-source coding agent for your terminal. It's a fork of OpenAI's codex with a focus on developer ergonomics and local control.
Key features:
- Browser integration – attach to your Chrome via CDP or use a built-in headless browser. You can browse pages, run the CLI in a browser session, and even take screenshots from the terminal.
- Multi-agent commands – /plan, /solve and /code orchestrate multiple models (ChatGPT, Claude, Gemini) to propose and implement solutions, with consensus or race options.
- Diff viewer – see proposed changes in a unified side-by-side diff with syntax highlighting before you apply them.
- Theme system & reasoning control – customise the TUI with /themes and adjust model reasoning effort on the fly with /reasoning.
- Safety modes & sandboxing – run read-only or require approvals to keep your projects safe.
To try it right away:
```
bash
npx -y @just-every/code
# or install globally
npm install -g @just-every/code
code  # or `coder` if you already have a `code` command
```
You can authenticate with ChatGPT (Plus/Pro/Team) or an API key, and even hook in other CLI agents like @anthropic-ai/claude-code and @google/gemini-cli.
We're launching on Product Hunt today if you'd like to support us: https://www.producthunt.com/products/code
Would love to hear your feedback, suggestions, and bug reports. Happy to answer questions here!

value: Show HN: Code – coding CLI with browser control and diffs

author: zemaj


value:
Hi HN, I’ve been working on BlipCut, an AI-powered video localization tool that helps creators and businesses translate and adapt video content quickly and at scale.
The problem we’re tackling is that traditional video localization is slow, expensive, and manual-heavy. It often requires separate tools for subtitles, dubbing, transcription, and editing. With BlipCut, we’re trying to make the whole workflow simpler and faster in one platform.
What BlipCut does:
Video & Audio Translation: Translate into 130+ languages instantly
Subtitles: Auto-generate and translate captions, then customize them
Voice Cloning & AI Voiceover: Reproduce speakers' voices (29 languages) or use 1300+ AI voices in 90+ languages
Lip Sync: Sync translated audio with speakers' lip movements for natural dubbing
Batch Translation: Process multiple videos at once
AI Transcription & Clip Maker: Transcribe videos, create short clips with auto titles/summaries, and translate them too
Why it matters:
Speed: Up to 10x faster than traditional workflows
Scale: Batch process many videos at once
Quality: Natural voices, accurate translations, seamless lip-sync
Who it's for:
Content creators, educators, businesses, and film teams who need to share video content across multiple languages without a big localization budget.
I’d love feedback from the HN community—especially around what features would make this more useful in your workflows.
Demo here: https://www.youtube.com/watch?v=gzPhtWFHYH8

value: Show HN: BlipCut – AI Tool for Fast Video Translation and Localization


value: freakynit

value:
https://github.com/freakynit/file-fabric
I just released File-Fabric, a tiny TypeScript toolkit to generate various files for demos, CI fixtures, prototypes, and seeding workflows.
It can produce documents (PDF, DOCX, TXT, JSON), spreadsheets/slides (XLSX, CSV, PPTX), media (JPG/PNG, WAV/MP3, MP4), and archives (ZIP, optional RAR). Everything has sensible defaults, with options to control size, duration, text, etc.
Supports both direct API usage and YAML-driven batch generation. Great for quickly spinning up sample data without hunting for random files.
Repo: https://github.com/freakynit/file-fabric
Would love feedback from folks who’ve struggled with needing realistic files for tests or demos!

value: Show HN: File-Fabric – Generate Files (docs, media, archives) for Testing

author: freakynit


value: eugenegusarov

value: Show HN: I've launched my app on Hacker News and here is what happened

author: eugenegusarov


value: Just a generic list showing program student can join and make some impact and income while sharing the gospel of technology

value: Show HN: College Student Program Across Various Country


value: moyum

value: Show HN: Moyu Search – A better tab search

author: moyum


value: teruza

value:
We built [ZArbitrage.co.za](https://zarbitrage.co.za) to track the live price gap between Bitcoin in South Africa and major international markets.
South Africa often trades at a premium (sometimes double-digit %), and while many people know about the "ZAR premium", there hasn’t been a simple, transparent dashboard showing it clearly over time.
The opportunity is also only available to South African Tax registered citizens, so that does limit the the number of people who can profit of this specific scenario. Nevertheless, it is still interesting to see a real live Arbitrage example that lasted for a decade.
The site shows:
 -  Live BTC arbitrage opportunities (SA vs global)
 -  Historical charts for spreads over time
 -  Transparent data pulled directly from exchange APIs
This started as an internal tool for our own trading research, but decided to open it up for anyone interested in arbitrage, FX controls, and how capital restrictions create unique crypto pricing dynamics. Also, the opportunity is essentially dead as of a few months ago. Will it be back? Who knows...
Any feedback or comments are welcome. But it's mostly for fun, research and historical purposes. We hope someone out there finds it interesting or useful!

value: Show HN: Live BTC Arbitrage Monitor (South Africa vs. Global)

author: teruza


value: Show HN: The best IPA signer there is – May not be online for long


value: jayqinohboi

value: I dont feel like vaping at all after the 4th-5th day. Skin is getting better. Sleep also getting better.

value: Show HN: 10 days vape-free thanks to this

author: jayqinohboi


value: aanesn

value: Show HN: A Lambda Deployment Tool

author: aanesn

title: Show HN: A Lambda Deployment Tool


value:
Hi everyone,
After trying out a few SaaS ideas, one thing kept frustrating us: getting users to convert from free trials to paid. We noticed the simplest solution was well-timed email campaigns — reminders, feature highlights, even simple “here’s what you might be missing” messages.
But setting up these automated flows is harder than it should be, especially if you just want to connect Stripe and quickly target trial users.
So we’re working on LiftMRR.com — a lightweight tool to help Stripe customers run automated campaigns that encourage trial → paid conversion. It’s still early stage, please do give it a try and would love to hear your feedback?

value: Show HN: LiftMRR – a lightweight tool for Stripe users run automated campaigns


value: kyoagun

value:
Hi HN,
I’ve been working on a side project called *Capshot* – a mobile app that automatically generates short, catchy captions for your photos and videos using AI.
The idea came from noticing how much time people spend thinking of a "perfect one-liner" before posting on Instagram, X, or TikTok. Most apps help with editing visuals, but captions are usually left up to the user.
*Key features:*
- AI-powered caption suggestions tailored to the content
- Multiple styles (casual, witty, professional, etc.)
- One-tap sharing to social platforms
- Currently available on Android, iOS version coming soon
I’d love to get feedback from the community on:
- Potential use cases beyond social media (marketing, content creation, accessibility, etc.)
- How to better evaluate caption quality
- Concerns around dataset bias or ethical use of AI-generated text
Play Store: https://play.google.com/store/apps/details?id=ai.capshot.app
Website: https://capshot.ai
Thanks for reading, and I’m happy to answer any questions!

value: Show HN: Capshot – AI app that generates perfect captions for your photos

author: kyoagun


value: JianYangbachman

value:
We built a CLI to scaffold MCP servers with OAuth2 built-in.
The idea is to remove the boilerplate and make deployment faster.
Demo video: https://m.youtube.com/watch?v=eVfHBhnwH7M
Code: https://github.com/granular-software/mcpresso

value: Show HN: CLI to generate MCP servers with OAuth2 included

author: JianYangbachman


value: aroussi

value:
I built a lightweight project management workflow to keep AI-driven development organized.
The problem was that context kept disappearing between tasks. With multiple Claude agents running in parallel, I’d lose track of specs, dependencies, and history. External PM tools didn’t help because syncing them with repos always created friction.
The solution was to treat GitHub Issues as the database. The "system" is ~50 bash scripts and markdown configs that:
- Brainstorm with you to create a markdown PRD, spins up an epic, and decomposes it into tasks and syncs them with GitHub issues
- Track progress across parallel streams
- Keep everything traceable back to the original spec
- Run fast from the CLI (commands finish in seconds)
We’ve been using it internally for a few months and it’s cut our shipping time roughly in half. Repo: https://github.com/automazeio/ccpm
It’s still early and rough around the edges, but has worked well for us. I’d love feedback from others experimenting with GitHub-centric project management or AI-driven workflows.

value: Show HN: Project management system for Claude Code

author: aroussi


value: Forgret

value:
I've been frustrated by the lack of a truly portable, no-dependency printf for embedded and kernel development. Most solutions are either too bloated or missing key features.
  So I built Uprintf. It's a single-header library that gives you full printf (flags, width, precision, floats, even custom specifiers) from bare metal to desktop, with zero dependencies or #ifdef hell.
  Key features:
  · One header file, no dependencies, no dynamic allocation
  · Full standard support: %d, %x, %f, %.*s, etc.
  · Extensible with custom format handlers (add %T for your project)
  · Configurable: disable floats, set locale, etc.
  · MIT Licensed.
  GitHub: https://github.com/Ferki-git-creator/Uprintf
  I'd love your feedback and contributions!

value: Show HN: Uprintf a universal stb-style printf implementation for C (no OS)

author: Forgret


value:
I built War of Sticks, a free browser-based medieval stickman strategy game. The idea was to combine fast-paced battles with resource management and tactical decisions, but still keep it simple enough to play instantly without downloads.
What you can do:
Train miners to gather gold and stone
Convert stone into gold for more resources
Recruit units like shielders, archers, barbarians, and wizards
Build and upgrade defensive towers
Lead your army to destroy enemy bases and free your people from the Red Empire
Features:
3 difficulty levels: Easy, Normal, Impossible
Works on desktop, tablet, and mobile browsers
Also available on Google Play and App Store
No downloads required, play instantly online
Family‑friendly, suitable for all ages
Why I made this
I grew up playing simple stickman games and wanted to create a modern version with strategy depth but the same instant accessibility. The game is built to run smoothly in the browser and be playable even on school or work networks (unblocked).
Would love feedback from the HN community on gameplay balance, performance across devices, and ideas for future unit types or mechanics.
You can try it here: https://warofsticks.app/

value: Show HN: War of Sticks – Free Online Medieval Stickman Strategy Game


value: Zifnap

value:
Hi HN,
I’ve been working on Word Maze – Secure Folder, a mobile app designed to keep files private without pushing them to system galleries or the cloud.
Some of the core features:
- Flip-to-Hide → Instantly switch to a maze game screen in unexpected moments.
- KillSwitch → Wipe data safely if needed.
- Built-in Viewer → Open photos, videos, and audio directly inside the app — nothing leaves the sandbox.
- Custom App Icons → iOS fully supports multiple app icons; Android has partial support.
- In-App Camera → Photos/videos taken stay in the app, never exported to the system gallery.
Tech-wise, the app is built mainly with Flutter, but for performance (esp. thumbnails, memory handling), I had to drop down into Kotlin/Swift. iOS felt smoother for media handling, while Android required more native workarounds to avoid OOM issues.
I’ve tried to build this as carefully as I could, but I may have missed things.
If you spot a better approach, or think of another privacy feature worth adding, please let me know.
I’d be happy to answer any questions.

value: Show HN: Word Maze – Secure Folder with Flip-to-Hide and Built-In Viewer and Cam

author: Zifnap


value: Rimshadpcs

value: Show HN: My workout tracker app made $20 in first week (justlog.app)

author: Rimshadpcs


value: altilunium

value: Show HN: LbL-TC – Line-by-Line Text Comparison

author: altilunium


value: christiansafka

value:
Hey HN! I’m Christian, daily lurker and some might remember our original launch post (https://news.ycombinator.com/item?id=42935355). Today we're launching Pinch for Mac, which we believe is a step-change improvement in real-time AI translation. Our vision is to make cross-lingual conversations feel as natural as regular conversations.
TL:DR
During an online meeting, the app instantly transcribes and translates all audio you hear, and allows you to decide when you translate your voice and when you don't. It's invisible to others (like Granola), and works everywhere without any meeting bots. Try it at startpinch.com
Here's a live demo we recorded this morning, without cuts: https://youtu.be/ltM2p-SosLc
When we first launched Pinch, we shipped a video conferencing solution with a human-like AI interpreter that was an active participant in your call. Our users hold the spacebar down while speaking to the translator, and when they release the spacebar the translator speaks out to the entire room.
That design was intentional - it puts the task of context selection on the user and prevents people from interrupting each other awkwardly (only one person can press spacebar at a time). It also comes with heavy tradeoffs, namely:
* Latency - Up to 2x longer meeting lengths due to everyone hearing your full sentence and then the translation of your full sentence
* Friction with first-time users - Customers using Pinch for external communication often meet with new people each time, and we've learned of several that send out an instruction doc pre-meeting on how to join and use translation in the Pinch call. Bad signal for our UX.
* Restricting our customers to those who are meeting creators
Benefits of the desktop app:
1. It creates a virtual microphone that you can use in any meeting app
2. Instant transcription+translation means you can understand what's going on in real-time and interrupt where necessary
3. Simultaneous translation - after you start speaking, the others will hear your translated audio as fast as we can generate it, without interrupting your flow.
Over the last months our focus has been on developing a model and UX to support high translation accuracy while automating context selection - knowing exactly when it has enough words to start the translated sentence. We’ve rolled this out to the desktop app first.
We're incredibly excited to go public beta today, you can give it a try at www.startpinch.com
Cheers,
- Christian

value: Show HN: Pinch – macOS voice translation for real-time conversations

author: christiansafka


value: OskarVolcansek

value:
Hi HN,
I started investing when I was 14 and always found it annoying to manually value companies using Excel.
So I built Socks2Stocks, a simple tool that automatically estimates fair value using a discounted cash flow (DCF) calculator.
Originally, I overbuilt it with too many half-baked features. Everything felt wrong, so I scrapped the whole thing and rebuilt it from scratch with just one feature: the DCF calculator I always wanted when I first got into investing.
How it works
The app pulls financial data through an API, runs free cash flow projections, and automatically outputs a fair value estimate. The cash flow projections are based on the average growth rate of FCF over the past 10 years and then projected forward. Users can, of course, enter their own assumptions.
I’d love any feedback, and to hear whether you think people would actually use this.
Thank you for reading.

value: Show HN: I built an automatic tool for valuing stocks

author: OskarVolcansek


value:
Unified Crypto API Trading, Trading Automation, Portfolio Management, and Client Management Software Suite for Asset Managers
Enterprise-grade SaaS for pro traders & asset managers. Offers API trading services: copy trading (trade copier), TradingView & signal bots, bulk order execution, and trading terminal across Binance, Bybit, KuCoin, OKX, Gate, Bitget, Coinbase, Binance US.
+ White-labelling for asset management businesses with a full suite of client management tools and dashboards.<p>Upcoming Integration: MT4/MT5/Forex by 2026.

value: Show HN: Finestel – White Label API Trading Fund for Asset Managers


value: alexpietro

value: I was tired of guessing why visitors weren’t converting, so I built a simple popup to ask them directly

value: Show HN: I built a no-code popup to collect visitor feedback

author: alexpietro


value: jwworth

value: Show HN: I Boiled a Decade of Debugging into a Practical Guide

author: jwworth


value: vipulag

value: Show HN: Feedback – "This is terrible." – What do you do with this?

author: vipulag


value: martianmanhunt

value: Chrome extension that pre-reads and marks posts with categories that you can define, like 'Cringe', 'Information', 'Self-Promotion', etc.<p>Feedback welcome on UI and categorization quality.

value: Show HN: LinkedIn Cringe Filter – Categorise LinkedIn posts before you read them

author: martianmanhunt


value:
I came across this on LinkedIn: Kodex AI, a German startup, has released a free Perplexity-like search tool for financial regulations in Germany and Europe. It indexes over 5,800 regulatory publications, supports natural-language queries, and provides AI-generated summaries, implementation timelines, and direct source links. Aimed at compliance teams, legal experts, and policy professionals.
Check it out:
https://smart-search.kodex-ai.com/
Thoughts or feedback?

value: Show HN: Perplexity-Like Search for European Regulatory Documents


value:
I built Magic Translate, a simple web app that allows you to translate text on images in over 100+ languages.
Magic Translate is designed to work with images with burned-in text. All you need to do upload is your original image, and Magic Translate will do the rest. No design files required.
This is the first launch, right now it only supports use on Desktop, but I'm looking to add a mobile experience soon.
The primary use case I had in mind was for marketers who wish to localize their content, but don't necessarily have the design team nor the time to hand-translate their creative assets. This app is singularly focused on image translation, rather than an entire suite of design tools.
It's free to try out, feedback and suggestions are much appreciated!

value: Show HN: I built a web app to translate burned-in text on images


value: fredwu

value:
Hi HN!
For the past while I've been building FeedBun, a browser extension that gives you health ratings and research summaries for food products while you shop online or while you look for cooking recipes.
I'm building this because I wanted this product and couldn't find anything similar - most tools I found either required barcode scanning or were limited to specific stores. I wanted something that works seamlessly across all websites. I even have some big features planned for the future.
Tech stack: Elixir/Phoenix via Petal Pro framework for the backend - this is my 3rd SaaS using Petal Pro which I'm also a contributor of.
What makes it unique in my opinion:
* Science-backed analysis: Our AI researches every ingredient against scientific databases and reputable sources and gives you plain English explanations
* Works anywhere: Amazon, Walmart, any grocery site - just click our extension while viewing a product (pages with ingredient info works better with more detailed research), no barcode scanning needed
* Health warning callouts on ingredients that might appear innocent but may have hidden risks
* A suite of personalisation features, such as allergy warnings, dietary preferences, with more to come
Looking for feedback on:
* Does the landing page resonate with you?
* Does the browser extension work well? Any bugs or glitches?
* How useful would this be for your grocery shopping or recipe hunting?
* What features would make this a must-have for you?
* Would you pay for this? If so, and assume the personalisation features mentioned on the landing page (such as allergy alerts, dietary preferences, etc.) are implemented, how much would you be willing to pay per month?
Any comments or feedback are appreciated!

value: Show HN: A browser extension that decodes food labels for healthy eating

author: fredwu


value: meirk-brd

value:
I’m the developer behind the Web MCP at Bright Data. We just launched a free tier so any AI Engineer/ Vibe coder can give their LLM real web access — 5,000 requests/month at no cost.
Unlike most MCP servers that wrap a single SaaS API (e.g. Gmail, GitHub), the Web MCP wraps the entire internet. It handles JS-heavy sites, auto-solves CAPTCHAs, and returns clean Markdown your model can use.
Free tier includes:
search_engine → search results from Google/Bing/Yandex
scrape_as_markdown → fetch any URL as clean, LLM-friendly Markdown (with CAPTCHA handling)
Quick start: https://docs.brightdata.com/mcp-server/quickstart/remote
I also wrote a blog post with the full background, challenges, and architecture:
Solving Web Access for Agents (For Free!):https://brightdata.com/blog/ai/web-mcp-free-tier
Would love feedback - what would you want to use live web access for in your agents?

value: Show HN: Web MCP Free Tier – Web Access for Agents Without Getting Blocked

author: meirk-brd


value: howardV

value:
Hi HN,
I play a lot of *[Wplace](https://wplace.live)*, the pixel-art world map that limits every drawing to the official 64-colour palette (32 free, 32 paid). Re-colouring images by hand was painful, so I built a *client-side tool* that:
* takes any PNG/JPG
* maps each pixel to the nearest of the 64 official colours
* lets you *toggle paid colours off* → no wasted droplets
* adds optional Floyd–Steinberg dithering
* shows live pixel / colour stats for cost estimation
* exports a ready-to-place PNG or copies it to the clipboard
  (all computation in the browser, nothing uploaded)
*Link*
<https://wplacecolorconverter.online>
*Tech notes*
* TypeScript + Vite + React + Tailwind
* Pixel work happens in a Web Worker on an `OffscreenCanvas`
* Quantisation is ~300 LOC (RGB Euclidean distance; optional error diffusion)
* No back-end, so it runs offline and keeps images local
I’d love feedback on:
* performance for big images (>512 px)
* better distance metrics (ΔE?) or a faster lookup table
* whether a WebGPU / wasm port is worth it
* other pixel-art communities that might need custom palettes
Thanks for reading!

value: Show HN: Browser-only 64-color Wplace image quantizer (no server, free)

author: howardV


value: mstroube

value:
I'm Matt, a financial analyst who got tired of waiting weeks for Quality of Earnings reports as a part of financial due diligence.
The problem hits anyone evaluating acquisitions, investments, or partnerships:
- QoE reports cost $20k-$40k and take 2+ weeks, even for smaller deals
- Fees aren't recoverable when deals fall through
- Delays kill momentum – many red flags could be spotted immediately
- You're stuck doing manual Excel cleanup while waiting for basic insights
So I built Provafi – an AI-powered tool that gives you the core financial insights in minutes, not weeks:
- Instant data cleanup – Upload messy financial statements, get structured analysis
- Automated red flag detection – Spot revenue anomalies, margin trends, cash flow issues
- Secure & private – Your sensitive data stays encrypted, never used to train public AI models
- Fast go/no-go decisions – Decide whether to commission a full QoE or walk away early
Early traction: currently being used by SearchFunder members on active deals.
Why not just use ChatGPT? Most M&A data is too sensitive for ChatGPT and other public LLMs, and these models need proper data structuring and context to provide valuable AI insights.
Current limitations: still working on automating management adjustments (add-backs, etc.) and other "full-scope" capabilities.
Try it free at https://provafi.com (use beta code HNFREE)
What would make this more valuable for you?
- Features for non-finance users to understand the analysis?
- Specific red flags or metrics you wish were automated?

value: Show HN: Upload financial data, get fast financial due diligence insights

author: mstroube


value: arephan

value: Show HN: The tool I built to survive big tech burnout

author: arephan


value: damarberlari

value:
I was wondering how I can arrange objects along a spherical helix path, and read some articles on it.
I ended up learning about parametric equations again, and make this visualization to document what I learned:
https://visualrambling.space/moving-objects-in-3d/
feel free to visit and let me know what you think!

value: Show HN: I was curious about spherical helix, ended up making this visualization

author: damarberlari


value: allday

value:
Hey HN,
I got tired of merge conflicts cropping up on my open PRs, so I built MergeBetter - a GitHub App that warns you before conflicts happen.
What it does:
Watches your team’s open PRs and detects when two branches touch the same files/lines in potentially conflicting ways.
Posts a single, tidy PR comment with the overlap and links.
No CI setup or YAML needed. Just install the GitHub App, pick repos, done.
Code never leaves GitHub. We only read PR diffs, never store source.
Why:
Even with good branch hygiene, people still step on each other’s toes. If two engineers are changing the same code at the same time, that’s probably a conversation worth having sooner rather than later. MergeBetter makes that conversation happen earlier, when it’s cheap.
Details:
Works with org or personal repos. You can install it in “selected repositories” if you want to trial safely.
It’s polite: fewer API calls, caches results, and updates one comment instead of spamming.
14-day free trial, then pricing is based on active members (not repos or PR count).
Security/privacy page is up; happy to answer questions.
Roadmap:
More granular hotspot analytics: see where conflicts cluster over time within files.
Smarter descriptions of conflicts.
GitHub Marketplace listing (currently billing via Stripe).
If you try it:
Install the GitHub App (takes ~1 min), push a PR or two, and let me know what breaks or annoys you. Feature requests, bug reports, and roasts are all welcome.
I’ll be around in the comments today.

value: Show HN: MergeBetter – Proactive conflict detection for pull requests

author: allday


value: virtuallyvivek

value:
I've been using Claude Code a bunch lately and wanted to see my usage patterns visualized like GitHub's contribution graph (mostly out of curiosity).
So I built ccheatmap - a tiny CLI tool that reads your local Claude Code usage data and renders it as a heatmap right in your terminal.
npx ccheatmap
It just reads the JSON files Claude Code already writes to ~/.config/claude/projects/ and shows you:
- Daily session counts (or token usage, or interactions)
- Weekly patterns (turns out I use Claude most on Tuesdays )
- Total stats for the period
- Nice color gradients to represent activity
The whole thing is ~300 lines of TypeScript. Nothing fancy - just parsing timestamps, bucketing by day, and rendering colored Unicode blocks.
What surprised me: weekend usage often spiked way higher than weekdays. Turns out I tend to vibe code more on side projects when the stakes are lower.
Repo: https://github.com/viveknair/ccheatmap
Would love to hear if others track their AI tool usage differently, or if there are other metrics that would be interesting to visualize. Also curious if anyone else has noticed usage patterns they didn't expect.
I was inspired by ryoppippi's ccusage tool which has cost tracking and detailed usage analytics - definitely check that out if you need deeper insights.

value: Show HN: I built a GitHub-style contribution graph for Claude Code usage

author: virtuallyvivek


value: paholg

value: I found myself needing to make the same request repeatedly in different environments, and could not find a good tool to switch between them and (importantly) to make it easy to see what environment I'm in, and I especially could not find one that supports fish. So, I built one and thought it might be useful to others.<p>I've also now found it useful for other things -- basically anytime you have some environment variables that you want to temporarily set at times, and want to track whether they're set.

value: Show HN: A tool to easily juggle sets of environment variables

author: paholg


value: sumeruchat

value:
Hi HN,
I was getting tired of all the news websites being incendiary and emotionally manipulative so I built this using AI. The goal is to keep the reader informed and nothing else.
Feedback welcome!

value: Show HN: A neat news website curated and generated by AI

author: sumeruchat