value:
Last year my co-founder and I were talking about ecommerce store owners hitting small conversion issues that could easily be fixed—but nobody had the time or expertise to actually identify what was broken and validate fixes.
So we built Spar to handle that loop automatically. It analyzes any ecommerce store (Shopify, WooCommerce, BigCommerce, headless, doesn't matter) by crawling it like a customer would. It finds conversion gaps you don't know about, prioritized by impact, and gives you specific A/B test hypotheses for each issue instead of just generic best practices.
It works with any publicly accessible store and gives you results in minutes. It identifies issues across your pages (we're getting cart and checkout completed soon).
The idea generation is tailored per store. Free to sign up. Let me know if you want access to more of the gaps.

value: Show HN: Spar – Built a tool to help improve store conversion rates


value: neliousness

value:
Hi HN,
This is my first time sharing something like this here. I built TiniText to solve a problem I kept running into myself: I needed simple tools for transcription, summaries, and drafts, but most options felt heavier than necessary for everyday use.
Instead of building a large platform, I focused on small, single-purpose tools with predictable behavior and minimal setup.
The app supports:
- Audio transcription (single and multi-speaker)
- Text summarization with adjustable detail
- Simple draft generation (blogs / meeting notes)
- A few practical text utilities
It’s production-ready but still early, and I’d really appreciate feedback on:
- where the UX feels unnecessary
- what’s missing for real-world use
- whether “small focused tools” is still a compelling direction
Happy to answer questions.

value: Show HN: TiniText – Small tools for transcription, summaries and drafts

author: neliousness


value: montakaoh

value: Show HN: I built a Twitter bot that adds translated subtitles to videos

author: montakaoh


value: Saw online, been using for a while

value: Show HN: Code Puppy

story_text: Saw online, been using for a while

title: Show HN: Code Puppy


value: SteveChurch

value:
Hey HN!
I've been running side projects for years and every time I needed a status page I set up one of the many ones out there, before long I am paying more than what I believe it's worth for something as simple as it is.
So as a serial side hustler... I thought why not just smash one out.
StatusPage (https://statuspage.fyi) does uptime monitoring + status pages + incident management in one place.
There's a free tier. Actually free. Not "free for 14 days then we guilt you" free. Yeah ok it's not huge, but still 2 monitors, 1 status page, forever, it's a start, then a pricing that scales. I believe most people like me who run the odd little hustles wont break out past the $3 tier, and for those more serious companies that do have some cash and have a serious subscriber list can help cover the cost of us indies.
Still adding features (incident response/on-call is coming soon™), but it's been running my own stuff reliably for a while now.
Would love feedback. Roast my pricing. Tell me what's missing. Or just say hi.
Peace out fellow nerds.

value: Show HN: Yet Another Status Page FYI – Without Selling Your Kidneys

author: SteveChurch


value: schlichtm

value:
Hey everyone!
Just made this over the past few days.
Moltbots can sign up and interact via CLI, no direct human interactions.
Just for fun to see what they all talk about :)

value: Show HN: Moltbook – A social network for moltbots (clawdbots) to hang out

author: schlichtm


value: gopalv

value: Show HN: If You Want Coherence, Orchestrate a Team of Rivals: Multi-Agent "

author: gopalv


value: sftechdude

value:
See, we all know tools like ChatGPT and Claude can create files now. But something big is still missing: context.
Real work does not start from scratch. It depends on existing files, past documents, logos, images, spreadsheets, and PDFs scattered across your drive.
That is exactly why we built The Drive AI.
The Drive AI uses file agents that do more than just generate new files. They can pull information, images, tables, and logos from your existing files and use them to create new documents like Word files, PDFs, PowerPoint decks, and Excel sheets.
Would love to hear your thoughts.

value: Show HN: AI file agents that work across your existing documents

author: sftechdude


value: alecdotdev

value:
Built this for two reasons:
One: I've always wanted to be able to double click a Markdown file and see it like it appears on GitHub. Didn't want Obsidian or jumpy VS Code extensions just to view a README offline.
Two: Opening Microslop's Notepad lately shows how determined they are to add bloat to every aspect of Windows, so I needed a replacement.
Markpad is a simple Markdown file viewer and general text editor, rendered as close as possible to GitHub's markdown flavor. Features:
- Tabbed interface
- Monaco editor (VS Code)
- Syntax highlighting both in editor and code blocks
- Image and YouTube embeds
- Familiar GitHub styled markdown rendering
- Tiny memory usage (~10MB)
- No telemetry or bloat
- Free and open-source
- Lightweight native-feeling UI
Still in development, so I'd love some feedback on how to shape it to something more people can enjoy.
Cheers

value: Show HN: Markpad – The Notepad Equivalent for Markdown

author: alecdotdev


value: alexandermorgan

value: Show HN: Eightile, A Nested Anagram Solver Game

author: alexandermorgan


value: dz-codes

value:
I built Vultrino because I kept running into the same problem: I want AI agents to do things
that require credentials, but I don't want those secrets in prompts, logs, or context windows.
It's not just API keys – it's signing commits with PGP keys, accessing databases, decrypting
files, anything that needs a secret. The agent shouldn't see the credential; it should just be
able to use it.
Vultrino is a credential proxy that sits between your AI agent and the operation. The agent says
 "use my github-api credential" or "sign this with my pgp-key" and Vultrino handles the secret
material without exposing it.
Key features:
- WASM plugin system – add any credential type (PGP signing plugin included, build your own)
- MCP native – works directly with Claude
- OAuth2 with automatic token refresh
- Scoped API keys – agent X can only access credentials matching "github-*"
- Encrypted storage (AES-256-GCM), SSRF protection, audit logging
Written in Rust. Self-hosted, no cloud dependency.

value: Show HN: Vultrino – Let AI agents use credentials without seeing them

author: dz-codes


value: kozhan

value:
I built Frame to better manage the projects I develop with Claude Code, to bring a standard to my Claude Code projects, to improve project and task planning, and to reduce context and memory loss. In its current state, Frame works entirely locally. You don’t need to enter any API keys or anything like that. You can run Claude Code directly using the terminal inside Frame.
Why am I not using existing IDEs? Simply because, for me, I no longer need them. What I need is an interface centered around the terminal, not a code editor. I initially built something that allowed me to place terminals in a grid layout, but then I decided to take it further. I realized I also needed to manage my projects and preserve context.
I’m still at a very early stage, but even being able to build the initial pieces I had in mind within 5–6 days—using Claude Code itself—feels kind of crazy.
What can you do with Frame?
You can start a brand-new project or turn an existing one into a Frame project. For this, Frame creates a set of Markdown and JSON files with rules I defined. These files exist mainly to manage tasks and preserve context.
You can manually add project-related tasks through the UI. I haven’t had the chance to test very complex or long-running scenarios yet, but from what I’ve seen, Claude Code often asks questions like:
“Should I add this as a task to tasks.json?” or
“Should we update project_notes.md after this project decision?”
I recommend saying yes to these.
I also created a JSON file that keeps track of the project structure, down to function-level details. This part is still very raw. In the future, I plan to experiment with different data structures to help AI understand the project more quickly and effectively.
As mentioned, you can open your terminals in either a grid or tab view. I added options up to a 3×3 grid. Since the project is open source, you can modify it based on your own needs.
I also added a panel where you can view and manage plugins.
For code files or other files, I included a very simple editor. This part is intentionally minimal and quite basic for now.
Based on my own testing, I haven’t encountered any major bugs, but there might be some. I apologize in advance if you run into any issues.
My core goal is to establish a standard for AI-assisted projects and make them easier to manage. I’m very open to your ideas, support, and feedback. You can see more details on GitHub : https://github.com/kaanozhan/Frame

value: Show HN: Frame – Managing projects, tasks, and context for Claude Code

author: kozhan


value: agmmnn

value:
Hi HN — I built Badgewind, a small service for generating SVG badges styled with Tailwind CSS via a URL API.
It’s meant as an alternative to shields.io when you want badges that match your design system instead of predefined themes. Badges are styled using Tailwind utility classes (colors, spacing, rounded corners, fonts, icons), all encoded in the URL, so they work directly in READMEs and CI.
There’s also a small studio to try it live:
https://badgewind.agmmnn.workers.dev/

value: Show HN: Badgewind – Generate SVG Badges Styled with Tailwind via URL

author: agmmnn


value: Show HN: Invisible AI that helps you ace coding interviews in real-time


value:
Hey HN!
We started Perceptis a little over a year ago to bring the tide of generative AI into the consulting industry. At first, we focused solely on one use case: delivering professional-grade business proposals. The interaction was pretty simple: write a simple, email-like prompt about the proposal you want to request + attach any supplemental documents, and in <24 hours, you will get a polished, beautiful, 20-30 page (depending on request) deck according to the best consulting practices (also checked by our team for hallucinations and any other issues).
However, we kept hearing that our customers wanted to create slides instantly and go beyond proposals: presentations for the board of directors, team showcase, quick investor updates, QBRs, technical diagrams, etc. These presentations also need to follow their corporate branding, be fully editable, support PPTX-native charts, etc.
Recently, we launched Slidekick: our self-serve slide generation tool. You can describe your request in a single prompt and get a premium-grade slide in around 3 mins.
We want to provide slides that are truly professional and don't look like websites :) Slides you can truly share with your colleague in a real work scenario. Give it a try: https://app.perceptis.ai.
Would be happy to hear any feedback & thoughts! There is more to come and more to build!
upd1: here are examples of slides you can generate: https://www.linkedin.com/posts/perceptis-ai_perceptis-slide-..., https://www.linkedin.com/posts/perceptis-ai_ai-productivity-...
-- Yers, Perceptis co-founder

value: Show HN: Slidekick – business-grade slides generation


value: Jollydevs

value:
I built LinkBin after getting frustrated with bit.ly's pricing and outdated UX. It's a modern URL shortener with detailed analytics for half the cost of enterprise alternatives.
Key features:
• Better pricing: Pro plan at $14.99/mo vs bit.ly Enterprise at $35/mo
• Modern analytics: Geo, device, referrer tracking with clean dashboard
• Fast redirects: <100ms performance with global edge deployment
• Developer API: RESTful endpoints for programmatic link management
• Custom domains: Professional branding for businesses
Tech stack: Next.js 16, TypeScript, Vercel edge functions, PostgreSQL, Stripe
The free tier includes 50 links/month with basic analytics. Paid plans add advanced features like custom domains, API access, and extended retention.
Live demo: Try shortening a URL at https://linkbin-phi.vercel.app
I'm particularly proud of the analytics dashboard - it shows detailed click data with charts and geographic breakdown, something that's either missing or expensive in other tools.
Pricing comparison:
• LinkBin Pro: $14.99/mo (unlimited links, custom domains, 1yr retention)
• bit.ly Enterprise: $35/mo (similar features)
• TinyURL Pro: $19.99/mo (basic analytics only)
Questions for the community:
1. What features would make you switch from your current URL shortener?
2. How important are custom domains vs analytics for your use case?
3. Any feedback on the pricing strategy?
The app is live and accepting payments. Would love feedback from the HN community!

value: Show HN: LinkBin – Modern URL shortener with analytics ($15 vs. bit.ly's $35)

author: Jollydevs


value: sethyl

value: Show HN: Fast, private image compression in the browser using WASM

author: sethyl


value: Subesh

value: Show HN: Ignite – Run Firecracker Micro-VMs with a Docker-Like CLI (Rust)

author: Subesh


value: vietthan

value:
Hi all,
TL;DR: Open, source-linked Vietnam election datasets (starting with NA15-2021) with reproducible pipelines + GitHub Pages site; seeking source hunters and devs.
I want to share [Vietnam Elections](https://bamboo-filing-cabinet.github.io/vietnam-elections/), a project I've been working on to make Vietnam election data more accessible, archived, and fully sourced.
The [code for both the site and the data is on GitHub](https://github.com/bamboo-filing-cabinet/vietnam-elections/). The pipeline is provenance-first: raw sources → scripts → JSON exports, and every factual field links back to a source URL with retrieval timestamps.
Data access: the exported datasets live in `public/data/` within the repo.
If anyone has been interested in this data before, I think you may have been stymied by the lack of English-language information, slow or buggy websites, and data soft-hidden behind PDFs.
So far I've mapped out the [2021 National Assembly XV election](https://bamboo-filing-cabinet.github.io/vietnam-elections/el...) in anticipation of the coming [2026 Vietnamese legislative election](https://en.wikipedia.org/wiki/2026_Vietnamese_legislative_el...). There are already a bunch of interesting stats, for example, did you know that in 2021:
1. ...the smallest gap between a winner and a loser in a constituency was only 197 votes, representing a 0.16% gap?
2. ...8 people born in 1990 or later won a seat, with 7 of them being women? Or that the youngest was only 23?
3. ...2 candidates only had middle school education?
4. ...1 person won, but was not confirmed?
I'm looking for contributors or anyone interested in building this project as I want to map out all the elections in Vietnam's history, primarily:
1. *Source hunters (no coding):* help find official/public source pages or PDFs (candidate lists, results tables, constituency/unit docs) — even just one link helps.
2. *Devs:* help automate collection + parsing (HTML/PDF → structured tables), validation, and reproducible builds.
For corrections or contributions, it would be best to start with either the [GitHub Issues](https://github.com/bamboo-filing-cabinet/vietnam-elections/i...) or use the [anonymous form](https://forms.gle/UaPUdJZ5SGrTKdr2A).
You might ask, "what is this Bamboo Filing Cabinet?" It's the [umbrella GitHub organization](https://bamboo-filing-cabinet.github.io/) (org page [here](https://github.com/bamboo-filing-cabinet/)) I created to store and make accessible Vietnam-related datasets. It's community-run, not affiliated with any government agency, and focuses on provenance-first, reproducible, neutral datasets with transparent change history. If you have ideas for other Vietnam-related datasets, please reach out.
Sincerely,
Viet Than
PS: can someone help share this on /r/VietNam, I made a more [official username](https://www.reddit.com/user/thanhoangviet1996/) and my posts are blocked by Reddit filters.

value: Show HN: Vietnam Elections (open, source-linked datasets and site)

author: vietthan


value: Deonnroberts

value:
We built Lexiso because I kept running into the same question: when AI agents start making purchases, who decides what they're allowed to spend?
Today, if you're building an AI agent that buys things (shopping assistant, procurement bot, subscription manager), you either:
- Give it your card and hope for the best
- Build custom authorization logic yourself
- Don't let it spend money at all
None of these scale.
Lexiso is the missing layer. It's an API that sits between your agent and any payment system:
1. Register your agent
2. Define policies (amount limits, merchant restrictions, time windows)
3. Call /authorize before any purchase
4. Get a signed yes/no decision in <300ms
5. Full audit trail for compliance
The response is cryptographically signed, so you can prove later exactly what was authorized and why.
Site: https://lexiso.app
Live API: https://api.lexiso.app
Docs: https://lexiso.app/docs
npm: npm install lexiso
Looking for feedback from anyone building agents that touch financial workflows. What's broken? What's missing? Would you use this?
Technical details:
- Go backend, PostgreSQL
- RSA-2048 signatures on all decisions
- Designed for AP2 compliance (Google's agent payments protocol)
- No custody, no money movement – authorization only

value: Show HN: Lexiso – Authorization layer for AI agents that spend money

author: Deonnroberts


value: Show HN: A linear-time approach to P vs. NP via Information Noise Subtraction


value:
Hey HN! I built a little side project I wanted to share.
Shelvy is a free, visual bookshelf app where you can organize books you're reading, want to read, or have finished. Sign in to save your own collection.
Not monetized, no ads, no tracking beyond basic auth. Just a fun weekend project that grew a bit.
Live: https://shelvybooks.com
Would love any feedback on the UX or feature ideas!

value: Show HN: Shelvy Books

title: Show HN: Shelvy Books


value:
Hi HN,
I built EZThrottle because I was tired of copy-pasting exponential backoff into every codebase.
The core idea:
retries shouldn't be independent. When thousands of machines all hit a 429 and retry independently, you get retry storms that cascade into outages. EZThrottle coordinates failure in one place.
What it does:
  - Rate limiting per destination (default 2 RPS – conservative on purpose)
  - Region racing: send to multiple regions, accept first success, cancel the rest. If one
region goes down, your request still completes with just a latency bump instead of a full outage
  - Adds event-driven architecture to your stack via webhooks – fire and forget, get results delivered
Current scale (setting expectations):
  Running 4 machines across 2 US regions (Dallas + Washington DC) on Fly.io. Not massive yet –
  we'll expand to more regions with demand. Early days.
SDKs:
  - Python: https://github.com/rjpruitt16/ezthrottle-python
  - Node: https://github.com/rjpruitt16/ezthrottle-node
  - Go: https://github.com/rjpruitt16/ezthrottle-go
Written in Gleam, runs on the BEAM. This is part of a larger vision (L8-OS – local-first AI stack), but EZThrottle works standalone.
Blog post with architecture diagrams:
https://ezthrottle.network/blog/making-failure-boring-again
Free tier:
1M requests/month. Happy to answer questions.
@RahmiPruitt on Twitter

value: Show HN: EZThrottle – Coordinated retries and region racing for APIs Gleam/BEAM


value: lalalerodas

value: Show HN: Building a TradingView alternative pixel by pixel

author: lalalerodas


value: Show HN: Eure – TOML-like data notation with arbitrary nesting and tagged unions


value:
AstrolaDB (alab) is a schema-first code generator for polyglot systems. Define your schema once and generate:
- SQL migrations (PostgreSQL, SQLite)
- Language-native types (Rust, Go, Python, TypeScript)
- API contracts (GraphQL, OpenAPI)
It's build-time only, with zero runtime dependencies. All outputs are explicit artifacts you can commit. The schema is the single source of truth across languages and APIs.
Links:
- Repo: https://github.com/hlop3z/astroladb
- Docs: https://hlop3z.github.io/astroladb/
- Comparison: https://hlop3z.github.io/astroladb/comparison/

value: Show HN: Schema-first codegen for SQL, Rust, Go, Python and TS (single binary)


value: Most developers treat RAG (Retrieval-Augmented Generation) as a "Black Box" of semantic similarity. We’ve been told: If the vector distance is small, the answer is there. This is a lie. Vector matching is Static Fact Comparison, while user queries are Dynamic Intent Solves. This repository deconstructs why pure vector RAG hits a ceiling and proposes a transition to 5W1H-Structured Intent Routing.

value: Show HN: Intent-Aware RAG – Moving from Vector Matching to 5W1H Accounting


value: irasigman

value: Hello! I've been working on a systematic query language (SYSQL) for some time as a personal tool to enable my daily crypto-trading. I enabled US equities and added some AI to help use it. Then I found out I could easily output Pine Script (TradingView specification format for signals) from my SYSQL deterministically while only squashing a few of my languages nice to have features like range optimization. Anyways, check out SYSQL and get your TradingView game up!

value: Show HN: AI-Generated Trading View strategies with no lock in

author: irasigman


value: yaoluxing

value: A free, web-based Facebook video downloader that actually preserves the original audio - something most Facebook downloaders fail to do. Built with Next.js and yt-dlp, it offers a clean, no-ads experience for downloading Facebook videos in multiple qualities.

value: Show HN: Free Facebook Video Downloader with Original Audio Quality

author: yaoluxing


value: Show HN: Figma MCP is read-only,so I built a pilot MCP by code execution


value: leopiney

value:
I've been experimenting with autonomous coding agents for ML workflows. ML-Ralph uses claude-code to run a continuous experiment loop - it forms hypotheses, writes training code, evaluates results, and iterates on what it learns. Added Weights & Biases integration for observability on long runs.
As a test, I pointed it at Kaggle Higgs Boson and let it run for a few hours unsupervised. It placed top 30. I humanly participated on that competition too, and barely reached top 150.
Still rough around the edges. Would appreciate feedback, especially on failure modes you'd want to see handled better.

value: Show HN: AI tool to that reaches top in machine-learning competition

author: leopiney


value:
Distributed systems usually pay milliseconds for correctness because they define correctness as execution order.
This project takes a different stance: correctness is a property of algebra, not time.
If operations commute, you don’t need coordination.
If they don’t, the system tells you at admission time, in nanoseconds.
Cuttlefish is a coordination-free state kernel that enforces strict invariants with causal consistency at ~40ns end-to-end (L1-cache scale), zero consensus, zero locks, zero heap in the hot path.
Here, state transitions are immutable facts forming a DAG. Every invariant is pure algebra. The way casualty is tracked, is by using 512 bit bloom vector clocks which happen to hit a sub nano second 700ps dominance check. Non-commutativity is detected immediately, but if an invariant is commutative (abelian group/semilattice /monoid), admission requires no coordination.
Here are some numbers for context(single core, Ryzen 7, Linux 6.x):
Full causal + invariant admission: ~40ns
kernel admit with no deps: ~13ns
Durable admission (io_uring WAL): ~5ns
For reference: etcd / Cockroach pay 1–50ms for linearizable writes.
What this is:
A low-level kernel for building databases, ledgers, replicated state machines
Strict invariants without consensus when algebra allows it
Bit-deterministic, allocation-free, SIMD-friendly Rust
This is grounded in CALM, CRDT theory, and Bloom clocks, but engineered aggressively for modern CPUs (cache lines, branchless code, io_uring).
Repo: https://github.com/abokhalill/cuttlefish
I'm looking for feedback from people who’ve built consensus systems, CRDTs, or storage engines and think this is either right, or just bs.

value: Show HN: Cuttlefish – 40ns causal consistency using algebra instead of consensus


value: zakmcintyre

value:
Hey HN, I built DreamsJar as a solo project. It's a native SwiftUI app for tracking savings goals visually — you create "jars" for things you're saving toward and log deposits as you go.
The idea came from wanting something simpler than a spreadsheet but more tangible than just watching a bank balance. I wanted saving to feel like progress, not just math.
How it works:
  - Create a jar for a goal (vacation, new
    laptop, whatever)
  - Set a target amount and timeline
  - Log deposits and watch the jar fill up
  - Hit milestones at 10%, 25%, 50%, 75% with
    little celebrations
Built with Swift/SwiftUI and SwiftData. Free tier gives you one goal.
Premium ($3.99/mo or $49.99 lifetime) unlocks unlimited goals, iCloud sync, custom reminders, and deposit history.
Some technical decisions I found interesting:
  - Used SwiftData with an explicit Application
    Support store path for CloudKit
    compatibility
  - Streamlined onboarding from 11 taps to ~6
    taps to create a first goal after user
    testing showed drop-off
  - Had to move away from async/await in some
    Settings views to avoid @MainActor deadlock
  — ended up using callback-based APIs with
    deferred loading instead
Happy to answer questions about the build, SwiftUI/SwiftData pain points, or the App Store review process.

value: Show HN: DreamsJar – A visual savings goal tracker for iOS

author: zakmcintyre


value: Chronologos

value: Show HN: Cc-sessions – Fast CLI to list and resume Claude Code sessions

author: Chronologos


value: Chase-Chalker

value:
Hello HN,
I built Chatter because I was spending too much time copy-pasting feedback from my Discord channels and GitHub issues into a spreadsheet. I realized I was reading the same bug report 50 times, just phrased differently.
The Problem: When you have a community, feedback is fragmented. A user complains on Discord, another opens a GitHub issue, and a third emails support. It’s hard to see the magnitude of a problem when the data is siloed and unstructured.
What I built: Chatter is an aggregator that listens to these channels via webhooks/API. instead of just listing the messages, it runs them through a clustering algorithm to group semantically similar complaints.
It’s still early days, so I’m looking for feedback on the grouping accuracy and what other integrations (Slack/Linear/Intercom) you’d find most useful.
Thanks!

value: Show HN: Chatter – Cluster Discord/GitHub feedback to spot patterns

author: Chase-Chalker


value: cgdstnc

value:
Hi HN,
About 1.5 years ago, I published Jinear, an app I originally built for friends, family, and for fun. I tried to turn it into a SaaS to acquire paying users, but I failed.
Instead of letting it sit, I made it open source and moved on to other things. Over time it gained some unexpected traction nothing big just very small heartbeats. Meantime I needed file sharing and messaging for my own use, so I went back to jinear and added those modules too.
I don't think this will ever be a financially profitable product, but I'd be happy if it helps other people. I currently host it on a Mac Mini at home, which costs me almost nothing (besides couple of cents for google cloud storage).
While there’s a hosted version for quick testing, it is fully self hostable. You can create/assign tasks, share files, view everything on a calendar, and chat with your team. It’s also built as a PWA for mobile use.
If anyone needs this kind of tool feel free to use & modify it. I’d love to hear your thoughts or feedback. Thanks.

value: Show HN: I open sourced my failed SaaS (task/calendar/chat/files hub)

author: cgdstnc


value: RioBurhan

value:
Hi HN,
 I’m a solo developer from Indonesia and I just launched gLinksWWW, a standalone browser built for heavy multitaskers.
 The Problem: Switching between tabs to copy-paste multiple items is exhausting.
The Solution: I built a 9-segment clipboard system directly into the browser. You can store up to 9 different snippets and use them instantly.
 I've also prepared .AppImage and .deb builds because I believe in first-class Linux support. (Windows .exe is also available).
Product hunt:
https://www.producthunt.com/products/glinkswww?launch=glinks...
Download(.AppImage,.deb,.exe) & full information about gLinksWWW:
https://drive.google.com/drive/folders/1_l4mEDoyERPMj_AXsvDC...
I’d love to hear your thoughts on the UI or any features you'd like to see next (planning on AI-assisted doc summaries!).
 Thanks,
Rio

value: Show HN: gLinksWWW – A solo-made browser with 9 independent clipboards

author: RioBurhan


value: sinned

value: I wanted a super simple app that would show big, clickable buttons with JUST the exact link (map or zoom) that was important. Completely vibecoded with Antigravity & Claude Code. No data stored on any server, everything runs right off your phone.

value: Show HN: Go Calendar

author: sinned

title: Show HN: Go Calendar


value: psovit

value:
Hi HN,
We’ve been building a hiring tool that ranks candidates using multiple job-specific criteria rather than keyword matching (traditional ATS-style filtering).
For each job listing, the system generates hiring criteria and sub-criteria, then analyzes and ranks candidate CVs based on how well they meet those criteria.
The original target users are hiring agencies, HR teams, and recruiters.
Our current challenge is early adoption. Agencies are hard to onboard without seeing real results, and real results usually require usage at some scale.
So we’re running an experiment:
We added a candidate-facing tool where job seekers can paste a job link, upload their CV, and get an analysis showing which hiring criteria they meet and which they’re missing.
The hypothesis is that candidate usage and data can act as a bottom-up wedge to eventually attract agencies and recruiters.
We’re early and unsure whether this approach will work but let's see.

value: Show HN: A hiring tool that ranks candidates by job-specific criteria

author: psovit


value: thomino

value:
Open-source Expo playground to serve as starting point or just playground for React Native projects.
The Tech Stack:
- Framework: Expo
- Styling: NativeWind v4 (Tailwind for Native).
- Animations: Reanimated
Components and screens:
- Product tooltip
- Glassy dropdown
- 3D Card flip
- Expandable image tabs
- Product grid with animated filters
- Theme carousel & picker
- Onboarding introduction slider
- Toggle switch
- Parallax scroller
- Weather app interface
- Masonry/Staggered grid
- Card counter
- Earnings chart
- Expandable video card
- Bottom bar switcher
- Journal cards

value: Show HN: Expo Playground – Open-source React Native components and screens

author: thomino


value:
I built a database that scans SSL/TLS configurations of all 3,700+ publicly listed companies in Japan and identifies quantum-vulnerable cryptography.
With NIST finalizing PQC standards last year, I wanted to see how prepared Japanese enterprises actually are. Spoiler: not very.
The data shows which companies are still using RSA/ECDSA without any quantum-resistant alternatives, making them vulnerable to "harvest now, decrypt later" attacks.
Target users: security researchers, investment funds (for risk assessment), and auditors.
Would love feedback from anyone working in post-quantum cryptography or enterprise security.

value: Show HN: Quantum Vulnerability Database for 3,700 Japanese Public Companies


value: Show HN: Shorlabs – open-source Vercel for Python/Node back ends


value: hubertusputu

value:
Hi HN,
I’m the solo builder behind relnotes.app. I built this because I realized I was spending far too much time every Friday manually formatting technical changelogs into "human-readable" emails for stakeholders and clients.
As a dev, it felt like the least productive part of my week.
The Workflow:
You connect your GitHub repo.
When a Pull Request is closed, the app generates a release update.
It formats these updates into a branded, professional email template.
It sends/schedules them for your stakeholders automatically.
I launched this on Product Hunt last week and it was a total ghost town (1 upvote!), so I’m trying to figure out if I’m solving a problem people don't actually care about, or if I’m just bad at explaining the value.
I’d love your feedback on:
The "Stakeholder" Angle: Does your team actually send manual status emails, or do you just give them access to Jira/GitHub and hope for the best?
Technical friction: Would you trust an automated tool to draft these, or is manual oversight a "must-have"?
Pricing/Features: It’s currently in a very early stage. What’s the one feature that would make this a "must-buy" for your workflow?
I’ll be around to answer any technical questions about the stack or the integration. Thanks for taking a look!

value: Show HN: Relnotes.app – Turn GitHub PRs into your Friday's report automatically

author: hubertusputu


value: ishiooon

value:
Hi HN! I built codex.nvim, an IDE-style Neovim
  integration for Codex.

  Highlights:
  - Works with OpenAI Codex plans (no API key required)
  - Fully integrated in Neovim (embedded terminal
  workflow)
  - Bottom-right status indicator shows busy/wait state
  - Send selections or file tree context to Codex quickly

  Repo:
  https://github.com/ishiooon/codex.nvim

  Why I built this:
  I wanted to use Codex comfortably inside Neovim without
  relying on the API.

  Happy to hear feedback and ideas!

value: Show HN: Codex.nvim – Codex inside Neovim (no API key required)

author: ishiooon


value: OGsus

value: Show HN: I built a digital twin to visualize sensor drift in real-time

author: OGsus


value: Show HN: 1X is a Chrome extension to help with doomscrolling in X


value: debba

value: Show HN: Tabularis – A lightweight, developer-focused database management tool

author: debba


value:
Hi HN
SwiftMock is a lightweight CLI tool that generates mock implementations for Swift protocols.
The idea is to remove the repetitive boilerplate involved in writing mocks by hand, especially as protocols grow larger and start using async/await, throwing functions, and complex method signatures.
The tool scans the codebase, identifies mockable protocols, and produces deterministic
mock classes that support call tracking, argument capture, and customizable behavior for tests.
It’s written entirely in Swift, has no runtime dependencies, and is designed to be easy to integrate into existing build or CI workflows.
GitHub: https://github.com/gokulnair2001/SwiftMock
Feedback and suggestions are very welcome.

value: Show HN: SwiftMock – automatic mock generation for Swift


value: bugon

value:
Hi HN
 I built this Go (Baduk/Weiqi) platform called TheBaduk.<p>Tech Stack & Key Features:
 Frontend: Vanilla JS (No frameworks), optimized for performance on both desktop and mobile.
 AI: Client-side KataGo integration (runs in the browser).
 Backend: Socket.io for real-time matching.
 I wanted to create a frictionless experience where you can play instantly without heavy initial loads.
 I'd love to hear your feedback on the code performance and UI responsiveness. Thanks!

value: Show HN: TheBaduk – A Go/Baduk Platform Built with Vanilla JavaScript

author: bugon


value: sandeepkd

value:
So I built this calculator which can do big number multiplications (keeping the scope/functionality small)
Only caveat is that there is a certain probability of it making mistakes with the calculations ( I claim the probability to be less than .0001 %,  different results for different benchmarks though)
- It does speeds up the calculations, saving lots of time for business
- You can of course verify the calculations manually if you want to check on accuracy
- Better yet, you buy multiple calculators and execute the same inputs to get a better confidence on the result
( Though in full transparency, I must warn you, since the core logic is same, its possible that for certain combination of inputs it produces the same result across all the calculators/devices which may be wrong. Buying more than 1 calculator can only help up to certain degree.
- Also I am emphasizing that you should not spend any more efforts to learn multiplication since calculator is there
As a business:
1. Would you want to buy this calculator
2. How many calculators would you want to buy, I would like to emphasize that the more you buy the better accuracy/confidence you will have with the results
Oh couple more things I forgot to share,
1. I was able to sell this calculator to some of the companies in aviation industry to calculate altitudes while flying
2. My business plan does depends on people loosing the skill to do multiplication, thus artificially increasing the accuracy of my calculator in the absence of manual verifications. Eventually I will raise the price 10X to make profit.
PS: This is one time investment opportunity to take big number calculations to next level.

value: Show HN: Selling New Era Calculator

author: sandeepkd

title: Show HN: Selling New Era Calculator


value: chbkall

value: This is how I edit my videos. I would love to know if there is a better way out there.

value: Show HN: My workflow for editing and compiling videos as a programmer

author: chbkall


value: rene-veerman

value: wikipedia with photo / video backgrounds, and a theme editor!

value: Show HN: Introducing: HTTPS://nicer.app/wiki/frontpage

author: rene-veerman


value: zkenthusiast

value:
I was learning ZK proofs and found that visualizing things really helped me understand them. Noticed there aren't many interactive visualizations out there, so I built one.
Here's the first version: zkvisualizer.com
It walks through the full pipeline step by step (Problem → Circuit → R1CS → Polynomials → Witness → Proof → Verification) with real Groth16 proofs generated in your browser using snarkjs.
You can toggle between what the prover knows vs what the verifier sees, and there's a tamper detection demo where you can watch verification fail.
This is still very early on, but I would be very happy to receive any feedback!

value: Show HN: ZK Visualizer – I built this while learning zero-knowledge proofs

author: zkenthusiast


value: tommyjepsen

value:
Hi,
I ran a fun experiment trying to beat the danish C25 index with just Gemini 2.5 in simulation.
I fed Gemini 2.5 with stock data, danish news articles, Wikipedia & Google trends top lists and much more like Eurostat data to see if I could get Gemini to beat the danish C25 stock index. (Novo Nordisk, Carlsberg, Mærsk etc.)
It could only see the current days data and backwards and was prompted to not take in forward data from its training data. It was prompted to follow these strategies among others::
- Take a longer term perspective
- Be conservative with position sizes
- Only trade when seeing a clear opportunity
It did pretty well, but ended up doing a couple bad moves selling at bad times - it almost feels like it panicked.
Data is from (01-01-2025 to 11-12-2025).
-
Any ideas on improving it? I think next step is using more a Chain of Thought process and multiple personas to evaluate each investment.

value: Show HN: I tried beating the stock market with Gemini 2.5 for 2025

author: tommyjepsen


value: dimahali

value:
Hi HN,
I built TrafficChecker (https://trafficchecker.net) because I was frustrated with the state of "free" SEO tools. Most require an email sign-up or have aggressive paywalls just to see basic visitor counts.
TrafficChecker gives you instant insights for any domain without an account:
- Monthly visitor estimates & trends
- Domain Authority calculation
- Traffic source breakdown (Direct/Search/Social)
- WHOIS info & Domain Age
- Geographic visitor distribution
Technical Implementation:
Stack: Laravel 12, Redis, MySQL, Tailwind.
Queueing: I use Laravel Horizon to manage background jobs.
For single lookups, it's synchronous/cached. For bulk CSV uploads (the paid feature), it pushes jobs to a Redis queue to process thousands of domains in parallel without timing out.
Data: Aggregated from multiple third-party analytics APIs and cached to reduce upstream costs.
It's a solo dev project. The single-domain lookup is permanently free/unlimited. Monetization is via bulk CSV processing and API access.
Would love feedback on the responsiveness and any data points you find missing.

value: Show HN: Free traffic stats, authority and WHOIS lookup (Laravel/Redis)

author: dimahali


value:
Hey everyone
I’ve been building an iOS app that lets you create and edit a full business website just by describing what you want. No agencies, no Webflow, no fiddling with layouts just vibe-code it straight from your phone.
You can ask it to build pages, tweak sections, add or remove content, and iterate on the site entirely from your pocket.
If your site includes a form, submissions land directly inside the app, and you also get basic analytics to see how your site is performing.
I built this mainly for founders and solo builders who want something fast and flexible without the usual setup pain.
Happy to answer questions or get feedback
Here is the app link : https://apps.apple.com/in/app/pocket-site/id6757796769

value: Show HN: I built a vibe coding app for websites


value: thibaultbessonm

value: Sorank is an all-in-one SaaS platform that helps SEO agencies automate audits, manage clients, assign tasks to freelancers, and deliver results through white-label portals, replacing your entire tool stack with one subscription.

value: Show HN: Sorank All-in-one tool for SEO Agency

author: thibaultbessonm


value: mpoweredo

value:
I got mass jealous of all these fancy explainer videos, so I built something
I like designing, it's genuinely satisfying work. But motion design? That's a different beast. Time-consuming doesn't even begin to cover it.
I kept seeing all these polished explainer videos on X or reddit. Smooth transitions, perfectly timed text animations, the whole package. And every time I thought "I could do that for my project", then reality hit.
Learning AE properly takes a lot of time. Existing browser tools are either too basic or feel like piloting a spaceship.
So I did what any reasonable developer does when frustrated, I started building my own thing.
It's a browser-based motion design tool. No downloads, no subscriptions to Adobe, no 47-step tutorials just to animate text flying in. You just prompt an AI Agent. Done.
I've been working on this for a while now and honestly, I'm at that stage where I need fresh eyes. What would make something like this actually useful for you?
What's the biggest pain point when you want to make a quick promo video or explainer?

value: Show HN: I built an AI Agent that turns prompts into a SaaS explainer videos

author: mpoweredo


value: Gregoryy

value:
Created a tool for observability psychos like me :)
I wanted to track every change that MoltBot does to it's own system files (memories) in git and notify me with the exact diff
This tool watches a git repo (e.g. /Users/<username>/clawd/), auto-commits/pushes on changes, and sends the diff to Telegram
One command setup

value: Show HN: Moltbot state observability and persistance daemon

author: Gregoryy


value: Show HN: An AI chat app with no usage limits and 200+ models


value: blindnomore

value:
i HN
I built Post Tomato to make social media publishing simpler.
You can write posts manually or generate them with AI, then publish or schedule them across platforms like LinkedIn, Threads, and Telegram from one place.
I built this after getting tired of juggling multiple tools just to publish content consistently.
Would love to hear your feedback — especially what feels missing or unnecessary.

value: Show HN: Post Tomato – simple social media publishing with AI

author: blindnomore


value:
Hi HN, I’m Enric. I built ButterflAI to help e-commerce teams keep product pages fresh without doing constant shoots or manual copy updates.
What it does?
- Upload 1 product photo (or connect a Shopify store).
- Generates a small set of product visuals (clean + lifestyle-style) and a short product video.
- Updates product listing content (title/description/metafields) to improve SEO and conversion.
Why I built it?
I kept seeing teams stuck between "expensive shoots" and "stale pages". I wanted a workflow that’s fast, consistent with brand guidelines, and usable for real stores (not mockups).
Why its different?
Because it’s not a general-purpose image generator. It’s built specifically for e-commerce product assets.
It produces the exact formats stores need (clean PDP shots, detail/angle views, before/after sets, and product infographics), with consistency across a whole catalog.
I’d love feedback on:
 1. Are the generated visuals actually usable for PDPs/ads?
 2. What would make you trust the output (brand controls, review flow, provenance)?
 3. What’s the minimum "control surface" you need (style presets, negative prompts, rules)?
If you prefer the Shopify app listing: https://apps.shopify.com/butterflai
Thanks!

value: Show HN: ButterflAI – turn 1 product photo into optimized ecommerce listing


value:
Hey HN,
The AI that's becoming ubiquitous (and a bit forced) could be used to help people and communities - things like countering polarized media, helping people get involved in civic life, and coordinating collective action.
I built an app that's a small step/experiment in that direction; it uses Ai to help people find common ground on divisive topics.
It's not sticky at all, just a demo of using this thing as a personal lite-mediator.
The origin: My partner and I were stuck debating corrupt countries at an airport. Turns out we were using different definitions of corruption - we were both right actually, but couldn't see it. That began the first clear 'app idea'. (That's where the name came from: b'right = both right)
What the app does:

  - Two people enter their perspectives on a topic (or use "Listen In" to speak it)
  - AI searches the web for context
  - Returns common ground + nuanced additions to each view, with sources
  - Use when needed (maybe once a month... maybe extended family gatherings), not daily

You can try it free: I cover 100 uses per day globally (one per device), so there's always free access. After your free use, 20c per topic (no subscription).
Technical details:

  - No login, no tracking, no conversation storage (unless you flag a response)
  - Stripe payments (Revolut Pay available)
  - 25% of revenue → carbon offsets (carbon negative)
  - Export as PDF (no app-install spam)
  - Live on EU Play Store, global expansion soon

EU Play Store: https://play.google.com/store/apps/details?id=com.vadix.beri...
The broader context on why I was interested to make this app, is the social service angle above.
What could AI as public infrastructure look like, and how might it work?
That's the kind of discussion/feedback I'd love to get. The app is a nice idea, but it's a proof of that concept more than anything.
Looking for feedback:
- Does this idea resonate?
- Any other use cases for this concept?
- How would you increase impact in this scenario?
Thanks for reading.

value: Show HN: Small demo of AI for finding common ground on divisive topics


value: Vranasko

value:
Hi HN,
I documented something I kept running into while debugging my own reactions under pressure.
There appears to be a tiny runtime gap between incoming signal (trigger) and outgoing action.
If that gap collapses, behavior executes automatically.
If it stays open even briefly, explicit choice becomes available.
I formalized it as a minimal behavioral control primitive:
Origin → Signal → OP Gap → Zero Point → Operator Point → Choice → Action → Return
No beliefs, no mindset, no therapy framing.
Just a control discontinuity observable in real time.
OP Gap itself doesn’t decide anything.
It simply exposes a control surface.
Without it: reflex.
With it: authored action.
The model includes explicit failure modes:
- gap collapse (autopilot)
- operator unavailable
- missing return (residual accumulation)
And a recovery mechanism (Return Frame).
I wrote a short technical book describing the closed loop.
I’m not trying to sell anything here — I’m interested in pressure-testing the architecture.
If you think this already exists under another name, or see structural flaws, I’d genuinely appreciate feedback.
Thanks.

value: Show HN: A minimal control primitive between impulse and action (OP Gap)

author: Vranasko


value: xenni

value:
Hey HN! I'm one of the folks behind Documenso (open-source document signing).
We spent years combining pdf-lib with a custom Rust signing library. It worked, but real-world PDFs kept finding edge cases.
Instead of waiting for a better library to appear, we wrote our own.
LibPDF:
- Lenient parsing with brute-force recovery (inspired by Apache PDFBox)
- Digital signatures with no native bindings and full PAdES support
- Incremental saves that preserve existing signatures
- Encryption (AES-256, AES-128, RC4)
- TTF/OTF font subsetting (ported from PDFBox's fontbox)
API inspired by pdf-lib.
Still in beta, but we use it in production at Documenso already. You might hit a few bugs that we haven't yet, if you do let us know!
https://documenso.com/blog/introducing-libpdf-the-pdf-librar...
https://github.com/libpdf-js/core
https://libpdf.dev

value: Show HN: LibPDF – The PDF library for TypeScript that I needed

author: xenni


value: liad

value:
PolicyLayer enforces spending limits on AI agent wallets without custodying private keys.
The problem: AI agents are moving into production with irreversible financial capabilities, but every agent is one bug or prompt injection away from draining a wallet. Traditional options are bad—shared seed phrases (compliance nightmare), custodial wallets (counterparty risk), manual approval (defeats automation), prompt-level limits (easily jailbroken).
How it works:
- Drop-in wrapper for existing wallet SDKs (Ethers, Viem, Coinbase CDP, Privy, Solana)
- Two-gate enforcement: Gate 1 validates against policies, Gate 2 detects tampering via SHA-256 fingerprinting
- Keys never leave your infrastructure—we only see transaction metadata
- Fail-closed: if anything fails, transactions stop (not continue)
- Policies configured in dashboard: daily caps, per-tx limits, recipient whitelists
Also supports X402 (HTTP 402 payment protocol) for agents paying for APIs—per-endpoint limits, auto-discovery of new paid endpoints, duplicate payment prevention, and circuit breakers.
SDK is open source.
Feedback welcome — what would make this more useful for your agents?

value: Show HN: PolicyLayer – Non-custodial spending limits for AI agents

author: liad


value: benfosterdev

value:
Hey HN! I'm the founder of Credyt (https://credyt.ai).
If you're running an AI product that burns $0.50+ per interaction, you need to bill customers as usage happens, not at the end of the month. Otherwise you're a bank for your customers, and you'll run out of money before they do.
Why invoice-based billing doesn't work for AI:
Most usage-based billing tools (Stripe Billing, Orb, etc.) were built for SaaS. They meter usage all month, then send an invoice. That works fine when your COGS is 5%. It's a disaster when you're paying your AI vendor upfront for every request and your margins are 15-30%.
If a power user runs up $10K in costs and churns or their card declines at month-end, you've just eaten $10K. We've seen multiple startups nearly run out of runway because of this.
"Just build a wallet in Postgres" – harder than it sounds:
Everyone starts there. Track a balance, decrement on usage, done. Then you hit race conditions when usage spikes, auto-top-up logic that needs to be bulletproof, credit grants with expiry dates and priority rules, pricing versioning (customer X is on v1 rates, customer Y on v2, customer Z has a custom deal), profitability analysis (what did this customer cost us vs. what we charged them?), refunds, disputes, partial credits, reserves...
Three months later you've hacked together a billing system instead of building your product.
What Credyt does:
It's a wallet-native billing engine. Your customers get a balance (in USD, credits, tokens, minutes, whatever you want), you send usage events as they happen, and Credyt handles the debiting, auto-top-ups via Stripe, and gives you an embeddable billing portal.
We match against your pricing rules (which you can version and test before publishing), debit the wallet atomically, trigger top-ups via Stripe when they hit their threshold, and give you a hosted billing portal so you're not building balance UIs.
Unlike tools that only track revenue, Credyt lets you log both what you charged and what it cost you. So you can see margins per customer, per product, per pricing tier—in real-time. Most founders are shocked when they realize their most active users are unprofitable.
Docs: https://docs.credyt.ai
Quickstart video: https://www.youtube.com/watch?v=48XJlId7098
Pricing: Free to start, then $1/month per active wallet. No processing markup—Stripe fees pass through directly.
We're still early stage and genuinely want feedback from people in the trenches:
What would stop you from ripping out your current system for this?
What's missing that would make this production-ready for you?
If you tried to build wallets yourself, where did it break?

value: Show HN: Credyt – Real-time billing, built for AI

author: benfosterdev


value: stokry

value: Show HN: SemanticCache – Save 70%+ on LLM API costs with semantic caching (Ruby)

author: stokry


value: isitcontent

value:
This started as a "cyberdeck" style crafts project using ESP32-S3, for some retro coding. Then I got carried away and wrote a self-hosted mini C compiler for it. Now I published the whole system that runs it. The core reusable parts are also packaged in Espressif Components Registry as "BreezyBox".
So far, this platform lives up to my dreams: instant on, snappy when optimized, flexible with resource allocation.
I upgraded to a bigger screeen: Waveshare ESP32-S3-Touch-LCD-7B, 7", 1024x600. It takes some effort to drive it with good speed on the S3, but this sort of challenge is exactly why I started this project, so I am having fun.
It captures a lot of the old school DOS era coding experience. I created a custom fast text mode driver, plan to add VGA-like graphics next. ANSI text demos run smooth, as you can see in the demo video featured in the Readme.
App installs also work smoothly. The first time it installed 6 apps from my git repo with one command, felt like, "OMG, I got homebrew to run on a toaster!" And best of all, it can install from any repo, no approvals or waiting, you just publish a compatible ELF file in your release.
It is something like Raspberry Pi, but without the overhead of a full server-grade OS.
Repo: [https://github.com/valdanylchuk/breezydemo/](https://github.com/valdanylchuk/breezydemo/)
If you like small elegant systems that punch above their weight, consider trying this sort of setup! It is surprisingly capable.

value: Show HN: Instant-on tiny ESP32 PC with an editor, compiler, and apps installer

author: isitcontent


value: We are launching SuperQode and SuperQE to redefine Quality Engineering for Agentic Coding teams. SuperQode is an open‑source terminal UI for interactive, agent‑driven quality engineering. SuperQE is the CLI for automation and CI. The goal is simple: let agents test agents, capture evidence, and keep humans in control. Everything is self‑hosted and privacy‑first.Feedback welcome.

value: Show HN: SuperQode, an open‑source coding agent for agentic quality engineering


value:
Hi HN — I’m Ethan, a solo developer and a language learner. I built SonicCaption because I often watch courses/videos and join meetings in languages I’m not fluent in, and I wanted something that works across sites, not just on one platform.
What it is: a Chrome/Edge extension that adds live captions + translation on top of the page you’re already using (videos, meetings, livestreams, etc.). You can show bilingual captions or translation-only.
How to try it:
1) Install the extension
2) Google sign-in (required to link usage quota and prevent abuse)
3) Open a tab with audio → click Start in the extension → you’ll see live captions/translation
Trial: everyone gets 20 minutes free to test it.
Note on sign-in/privacy: I know sign-in adds friction. I use Google login only to associate usage quota with an account and to prevent abuse. The extension does not access your inbox/contacts. If an anonymous trial mode would significantly increase willingness to try, I’d love to hear that.
If you try it and it fails or behaves oddly on a site, telling me the url + browser would help a lot.
I’ll be here to answer questions and iterate quickly.

value: Show HN: SonicCaption – Real-time bilingual captions and translation for videos


value: LinuxWhisper

value: Wrote this over the weekend because I missed native dictation/AI tools on Linux. Uses Groq for speed. Written in Python.

value: Show HN: LinuxWhisper – A native AI voice assistant for Linux (Groq/GTK)

author: LinuxWhisper


value: zvec

value:
Zvec is a lightweight, SQLite-like embedded vector database purpose-built for edge and on-device workloads. It delivers four core advantages: out-of-the-box usability, configurable resource budgets, extreme performance, and versatile vector capabilities. Open-sourced under the Apache 2.0 license, Zvec aims to provide developers with a one-stop path from prototyping to production deployment on the edge. Try Zvec—we’re excited to see your adoption, feedback, and contributions.
For a more detailed introduction, you can refer to https://zvec.org/en/blog/introduction/

value: Show HN: Zvec – The SQLite of Vector Databases

author: zvec


value: throwawaste

value: Show HN: Video feed experiment without login nor AI

author: throwawaste


value: d-yoda

value: Show HN: A Python CLI for Managing AI Agent Skills

author: d-yoda


value: keepamovin

value: Show HN: Rent VPS from your terminal

author: keepamovin

title: Show HN: Rent VPS from your terminal


value:
Tree-based inspector for JSON/XML documents.
At work, debugging often means jumping between logs from multiple systems, and I got tired of opening a bunch of tabs just to quickly format and inspect JSON/XML side by side.
A lot of existing tools are ad-heavy, not fully client-side, or limit you to a single document, so I built a small workspace-style tool that lets me inspect multiple payloads at once, entirely in the browser.

value: Show HN: Formatter Workspace – A multi-pane JSON/XML inspector and formatter


value: digitcatphd

value:
I've been fascinated by a fundamental gap in AI music: Current models (Suno, Udio) generate audio via sequence prediction—they pattern-match existing waveforms but don't "know" music theory. Consequently, you can't get stems, adjust the mix, or modify the arrangement logic.
I wanted to see if an LLM could compose music from first principles—understanding scales, chord progressions, and arrangement theory—and control a DAW to generate the audio.
Loom Demo: https://www.loom.com/share/8f55136085a24ed1bc79acb5cdda194c
The Stack
Ableton Live 12: The DAW engine.
Ableton MCP (Model Context Protocol): Forked and extended to allow Claude to manipulate MIDI, clips, and devices.
Claude 3.5 Sonnet: The "Composer," equipped with ~12 custom skill files covering arrangement, EQ, and sound design.
Gemini: The feedback loop. Used to analyze rendered audio (via stem separation) and provide critique for iteration.
Python: 1,700+ lines of performance scripts.
The Engineering Challenges
1. The Sample Library Problem Techno relies on curated samples, not just synthesis. But LLMs can't "hear" a sample library to pick the right kick or hat.
I built a sample analysis system that pre-processes the library and generates JSON profiles. This allows Claude to query samples by spectral characteristics rather than just filenames.
JSON
{
  "file_name": "001_Stab_Low.wav",
  "bpm": 126.0,
  "key": "N/A (atonal)",
  "spectral_centroid_mean": 297.2,
  "brightness": 0.04,
  "warmth": 1.0,
  "texture_tags": ["dark", "warm", "soft-attack", "distorted"],
  "category": "bass"
}
2. The Performance Layer (Polymetrics) Ableton's Session View handles loops, but a track needs transitions. I didn't want static blocks; I wanted a live performance.
I wrote a Python performance engine that creates a real-time automation script. It handles volume fading, spectral carving (ducking frequencies when elements collide), and—most importantly—polymetric cycling to create hypnotic phasing:
Python
# Polymetric cycle lengths in beats
POLY = {
    "STAB": 7,      # Cycles every 7 beats
    "RIDE": 5,      # Cycles every 5 beats
    "DING": 11,     # Cycles every 11 beats
    "ARPEGGIO": 13  # Cycles every 13 beats
}
The Pipeline
Planning: Claude analyzes target styles (e.g., Ben Klock, Surgeon) and generates an arrangement map (Intro -> Peak -> Outro).
Setup: Spawns 19+ tracks with specific instrument racks.
Generation: Python scripts generate MIDI patterns (e.g., 256 events following G minor with velocity curves).
Performance: The system "plays" the track, automating parameters in real-time based on the energy curve logic.
Results & Learnings
The output is recognizably techno. The mix is balanced, and the structure is logical. However, while the system creates music that is theoretically correct, it currently lacks the intuition to break rules in interesting ways—the "happy accidents" of human production are missing.
I suspect the next step for symbolic music generation is modeling "taste" as a constraint function rather than just adhering to theory.

value: Show HN: System to have Claude compose and perform a techno track end-to-end

author: digitcatphd


value: Show HN: I made a new compression algorithm


value: akhow

value:
SoundLocate (https://soundlocate.com) matches you with cities based on your favorite artists.
The idea: artists are popular in specific cities. If you love the same music as people in Berlin or Melbourne, you'd probably love those cities too.
Connect Apple Music or enter artists manually → get matched → shareable result card.
Tested it on myself: 7 out of 10 cities it suggested actually matched my lifestyle and preferences. Got heavy results on British cities (Glasgow, Manchester) and Australian ones (Melbourne, Sydney) - all have that indie/alternative vibe I gravitate toward in real life.
Free, no signup. Curious how accurate it is for others.

value: Show HN: SoundLocate – Find your city match based on music taste

author: akhow


value: geiser

value:
Hey, I'm Sergio, the dev behind Telegram-Archive
I built Telegram-Archive because I wanted complete control over my chat history, no matter what might happen (i.e. my account gets locked, or Telegram changes policies, etc.)
It's composed of a backup and a viewer. It has been evolving for some time and it's more complex than that, so you can, for example, archive and share public channels.
Feel free to check the features. I think the project is still in its infancy, but I hope you can bring your expertise and suggestions too.
Built with Python, FastAPI, Telethon, and Vue. GPLv3 licensed.

value: Show HN: Telegram-Archive – Own your chat history

author: geiser


value: jackhyyy

value:
Hi HN,
I’m an indie developer and I built an app called *静阅 (JingYue)* because I wanted a calmer reading experience before bed.
Most reading tools push feeds, recommendations, endless scrolls and notifications. I wanted something that felt closer to flipping through a book — quiet, simple, and relaxing.
So I made 静阅:
• curated calm reading content — quotes, images, short essays
• dark and light adaptive themes optimized for night time
• no notifications, no algorithmic feeds, just relaxed reading
• designed to help you slow down your mind before sleep
The app is live on the App Store here:
 https://apps.apple.com/us/app/静阅/id6758232981
It’s very early and opinionated; I’d love feedback — especially on UX for night time reading and content pacing.
Thanks!

value: Show HN: 静阅 means "quiet reading" – a calm reading app for bedtime

author: jackhyyy


value: Show HN: Native-devtools-MCP – MCP server for native desktop app interaction


value: timchinye

value: I got tired of digging through raw JSON exports from AI Studio, so I built this tool.

value: Show HN: Inspector – Open-Source Google AI Studio Conversation Viewer

author: timchinye


value: Show HN: I design logos for startups for $160


value: cong-or

value: Show HN: Hud – eBPF-based blocking detector for Tokio

author: cong-or


value: ericatcandid

value:
Hi HN! I’m Eric, the creator of Candid.
I built Candid because I was exhausted trying to follow politics across 10 different apps, sites, and news sources - and still felt like I didn’t actually know what was going on on any of the issues I cared about.
Political information is everywhere now, but it’s so fragmented across socials (Truth Social, X, TikTok, Instagram, Blue Sky, etc), government sites, and legacy media that it’s become harder than ever to follow. At the same time, Gen Z & Millennials like me will become the majority of voters by 2028. And we care more about getting news on issues rather than political party labels. The data exists. The modern interface doesn’t.
So my cofounder and I built Candid - a nonpartisan political media app that makes politics easy and fun to follow, personalized to your issues with privacy, and way less toxic. We present primary source political content through custom news feeds built around your issues.
What you can do in Candid:
- Trump Feed & Trumpy Score: a daily 0–10 score and summary of Trump’s activity across platforms, including Truth Social
- Personalized Feed: Track the issues you care about across Republicans, Democrats, and Independents in a private setting. No follows needed!
- Explore Feed: see what’s happening across the full political landscape
- Politician Profiles: quick snapshots of who’s who in politics (e.g. cabinet members), their roles, and their backgrounds
Simply put, my goal is to make politics digestible again by turning noise into clarity - so you can see what’s happening, who said what and when, and what it actually means.
I’d love your feedback and thoughts!

value: Show HN: Candid – Your front-row seat to politics

author: ericatcandid


value: IAMsterdam

value:
Hey HN – Kas here, founder of BarrierX.
The problem I kept seeing:
I spent years watching B2B sales teams treat "Closed Lost" as a graveyard. Thousands of deals sitting in CRM, never touched again. But here's the thing – most of those deals aren't actually dead. They're just badly timed.
Budgets get unfrozen. Champions change jobs and land at new companies. Competitors drop the ball. Reorgs happen. The same prospect who said "not now" 8 months ago might be ready today – but nobody's systematically tracking this.
Meanwhile, reps burn hours chasing net-new leads from the same generic ZoomInfo lists everyone else has.
What BarrierX does:
Instead of scraping public data like traditional sales intelligence tools, we analyze your proprietary data:
Ingests your CRM history (won and lost deals)
Analyzes patterns: what signals preceded wins vs. losses at your company
Monitors lost accounts for trigger events (job changes, funding rounds, leadership changes, tech stack shifts)
Surfaces which lost deals are worth re-engaging right now – with reasoning on why
The core insight: the patterns that predict success for your business are specific to you. A "good fit" at Company A looks completely different than at Company B. Generic intent data misses this entirely.
Early results:
In pilots, teams have resurfaced 15-20% of deals marked "closed-lost" as re-engageable within 90 days. Most of these would have sat untouched forever.
On invite-only:
We require CRM integration to work properly (the whole point is learning from your data), so we're onboarding gradually to ensure quality. If you're from HN and want to try it – reply with your CRM setup (Salesforce, HubSpot, etc.) and rough deal volume, and I'll get you access this week.
What I'd love feedback on:
Has anyone else tried systematically working lost deals? What worked/didn't?
For those who've used Gong/6sense/ZoomInfo – what's actually useful vs. noise?
Any concerns about the approach I should be thinking about?
Happy to answer questions about the architecture, how we handle data, or anything else.

value: Show HN: BarrierX – AI that finds which lost deals are worth re-engaging now

author: IAMsterdam


value:
I have always spent quite some time on setting up pipelines, env, secret, ingress and certificates just to deploy small side projects to my Kubernetes rig, so ended up automating it.
Cloudness is an open-source app platform I’m building to deploy applications directly from Git and manage them on Kubernetes. It’s designed around multi-tenant projects and environments, with automatic deployments on Git pushes and basic app-level CPU and memory metrics built in by default. Also a small market place with one-click templates and few databases.
It’s still early and opinionated, and I’m actively iterating. I’d appreciate any feedback.
Code: https://github.com/cloudness-io/cloudness
Demo: https://demo.cloudness.io

value: Show HN: Cloudness – An open-source tool to deploy and run apps on Kubernetes


value: bladecd

value: a live demo to show how LLM + visualization transforms paper reproduction and understanding.

value: Show HN: LLM-assisted research paper reproduction and understanding

author: bladecd


value:
Hello HN,
I built Planet Cert because I was frustrated with the two main options for IT certification prep: expensive monthly subscriptions or sketchy "brain dump" PDFs that encourage memorization without understanding.
The Project: Planet Cert creates practice tests for 1,000+ exams (AWS, CompTIA, CISSP, plus the newer AI certifications like Azure AI-900 and Google ML).
How it’s different:
-> Detailed Explanations: We treat every question as a learning opportunity. Instead of just marking A or B correct, we break down why the answer is right and why the distractors are wrong.
-> Lifetime Updates: The certification treadmill never ends. If you buy a course for AWS SAA-C03, you get the C04 updates automatically when they release. No recurring fees to recertify.
-> Modes: We built specific modes for "Study" (immediate feedback) vs. "Simulation" (timed, pressure testing).
I’d love feedback on the interface and whether the explanation depth meets the standard for those of you currently prepping for higher-level exams like the CISSP.
Thanks!

value: Show HN: Planet Cert – Practice Tests for AWS, Cisco, and AI Certs


value: Show HN: Figma MCP Without Tool Explosion – Let AI Execute JavaScript


value: wolfejam

value:
  AI kept changing my auth system - wrong assumptions, no context.
  Built this to fix it. project.faf sits between package.json and README.md
  (alphabetically and conceptually).

  IANA registered the media type. Anthropic merged it into MCP.
  21k faf eco-system npm downloads, MIT licensed.

  Happy to answer questions about the format or the IANA process.

value: Show HN: FAF – The package.json for AI context (IANA registered)

author: wolfejam


value: arthurlee

value:
Hi HN!
My friend and I have been working on this project for the past few days.
While building and deploying MCP servers, we found it hard to understand how they were actually being used by a model in practice. Even after deployment, it was often unclear whether the model was calling our MCP tools at all, or how it was interacting with them.
When things failed, we could not easily tell whether the issue came from our function definitions, our documentation, or how the model was interpreting and calling the tools.
So we built Heimdall to trace how models call and use an MCP server. It shows which functions are invoked, with what arguments, and in what order, so we can better understand model behavior and refine our MCP setup.
This is a very early-stage project, and there is still a lot to do. Feedback is very welcome.
Thanks for reading!

value: Show HN: Heimdall – Open Source Observability Platform for MCP servers and apps

author: arthurlee


value: Show HN: Clings – Learn C through interactive, Rustlings-style exercises


value: heartrock

value:
I got tired of running `docker ps`, `kubectl get pods`, and checking if my local services were up every time I started working. So I built UpDog — a macOS menu bar app that monitors Docker, databases, HTTP endpoints, Kubernetes, and more.
It shows a simple traffic light in your menu bar and lets you see the status of all your services at a glance.
https://updog-3b484.web.app/
Built with Flutter. Happy to answer any questions!

value: Show HN: UpDog – Menu bar app to monitor your dev environment health

author: heartrock


value: carlossouzarj

value:
Hello HN,
I built a desktop app to help with interview anxiety. It's an overlay that sits on top of Zoom/Teams, listens to the interviewer's audio, and flashes relevant bullet points from your own resume/projects.
Tech Stack:
Electron + React (Vite)
Gemini 2.0 Flash for low-latency transcription & reasoning.
Client-side RAG (Your resume is the context).
Privacy: It uses a BYOK (Bring Your Own Key) model. Audio streams directly to Google; nothing is stored on my servers.
I built this because I often "blank out" on dates/metrics during behavioral questions. It’s not about cheating, but about having a "memory jogger" HUD.
Would love feedback on the overlay UX.

value: Show HN: InterviewHUD – Real-time interview copilot for Zoom (Electron/Gemini)

author: carlossouzarj


value: dandinu

value:
I built an open-source dashboard for analyzing whole genome sequencing data using Google DeepMind's AlphaGenome API.
After getting my WGS data from Dante Labs a few years ago, I wanted a better way to explore my variants beyond the basic reports they provide. When DeepMind released the AlphaGenome API, I saw an opportunity to build something more powerful.
The main limitation right now is that raw VCF files from consumer WGS services often lack gene annotations (VEP/SnpEff). The dashboard works best with annotated VCFs, but I've added rsID-based lookups as a fallback.
Would love feedback, especially from others who've been exploring their own genomic data.

value: Show HN: AlphaGenome Dashboard – Analyze Your Genome with DeepMind AlphaGenome

author: dandinu


value: artursapek

value: Show HN: Revise – collaborative documents with LaTeX support

author: artursapek


value: emiliano

value:
Hi HN,
I built this while helping a colleague migrate away from Outlook for Mac after a company acquisition.
Outlook only exports contacts as .olm, and most tools we found were either paid or required uploading the data somewhere
Since emails and contacts are a pretty sensitive topic, I didn’t like that, so I put together a small local tool instead
It extracts contacts from an Outlook for Mac .olm file and exports them as CSV or vCard.
There’s a CLI, plus a simple web UI that runs entirely client-side
Hope it helps someone else

value: Show HN: Export contacts from Outlook for Mac (.olm) (local, open source)

author: emiliano


value: kasimlyee

value:
Hey HN,
I've been building small Node/TS apps for a while and got tired of the usual dotenv pitfalls: forgetting to set required vars, type mismatches (string vs number/port), or accidentally leaking secrets in logs/errors.
So I made dotenv-gad: a lightweight wrapper around dotenv that adds strong TypeScript inference, schema-based validation, and some practical extras.
Main things it does:
- Define a schema → get fully typed env object with inference
- Built-in validators for url, email, port, json, arrays, objects, etc.
- Custom rules: min/max, regex, enum, transform, validate fn
- Group related vars automatically (e.g. DB_HOST, DB_PORT → db: { host, port })
- Compose schemas from different modules
- Redacts sensitive values in error messages
- Comes with a CLI for check/sync/generate-types/fix/init/docs
It's still early (v1.3), but I use it in my own projects and it's already saves me.
npm: https://www.npmjs.com/package/dotenv-gad
Would love to hear your thoughts, especially:
- How do you currently handle env validation in TS projects?
- What features are missing for your workflow?
- Any rough edges / bugs you've spotted?
Thanks for looking!

value: Show HN: Dotenv-gad – typed, validated .env with CLI and grouping

author: kasimlyee


value: Show HN: I scan AI agent skills for prompt injection before you install them


value: aymrick

value:
Hi HN,
I built AdminCore, a secure admin dashboard starter kit for Node.js + React.
It includes:
- Cookie-based authentication with HttpOnly cookies
- Role-based access (admin / user)
- Protected routes via middleware
- Full CRUD system
- Clean SPA admin UI (modals, tabs)
I built this after re-implementing the same auth + admin logic on multiple projects.
The goal is to save 3–5 days of setup time for devs building SaaS back offices or internal tools.
Happy to answer questions or get feedback.

value: Show HN: AdminCore – Secure Admin Dashboard Starter Kit (Node.js and React)

author: aymrick


value: RioBurhan

value:
Hi HN, I built a browser for power users who are tired of the "copy, switch tab, paste" loop.
Key Features:
9-Segment Clipboard: Copy 9 different items (Ctrl+Shift+1-9) and paste them anywhere.
Granular Cookie Control: Delete cookies for a specific site with one click (Great for privacy).
Built-in AI Search: Direct access to Perplexity, Google, Brave, etc., from the home screen.
Linux First: Native .AppImage and .deb support.
It's a solo project, and I'd love to get some feedback on the performance.
Download: https://drive.google.com/drive/folders/1_l4mEDoyERPMj_AXsvDC...

value: Show HN: GLinksWWW – A lightweight browser with 9 independent clipboards

author: RioBurhan


value: cloudmanager

value: Show HN: AsciiKit – a shared visual vocabulary for ideating with LLMs

author: cloudmanager


value: dbhariprakash

value:
I built this after spending too much time debugging Stripe and GitHub webhook integrations.
The problem: You set up a webhook, trigger an event, and... nothing. Did it send? What did it send? Is my endpoint even receiving it?
So I built a simple tool:
- Click once → get a unique HTTPS URL instantly
- Point any service at it (Stripe, GitHub, Shopify, whatever)
- See requests arrive in real-time with full headers and body
- JSON auto-formats so you can actually read it
- Copy as cURL to replay locally
No signup required to start. Free tier is 1 URL, 50 requests, 24hr retention — enough to actually test things.
Tech stack: React frontend, Cloudflare Workers for the webhook receiver (global edge, fast), Supabase for storage and real-time subscriptions, Stripe for payments.
Happy to answer questions about the product or the tech.

value: Show HN: Webhook testing with instant URLs and real-time viewer

author: dbhariprakash


value: kuligkar

value: Show HN: A Gemini Audio AI Murder Mistery Game with Multiple Speakers

author: kuligkar


value: kver

value:
Hey HN, I'm Kris. I run a small B2B SaaS (7-person team) and we use AI constantly - Claude for strategy and product decisions, ChatGPT for research, Gemini for docs.
The problem: Decisions get made, but the reasoning disappears. Last month a teammate asked why we scoped a feature a certain way. I knew the answer - I'd worked through the trade-offs with Claude over 30+ messages. But that rationale lived in my head and chat history. To everyone else, the decision just appeared without a context, without "why." If I get hit by a bus, that thinking is gone.
We tried the usual fixes. Notion wiki. Obsidian. "Let's document decisions." Nobody kept it up. Too much friction. The actual reasoning stays trapped in chat threads nobody else will ever see.
What I built: Nuggetz is a browser extension that extracts decisions, insights, and action items from ChatGPT, Claude, and Gemini chats. You pick a thread, click once, and an LLM parses it into structured "golden nuggets of knowledge".
Those nuggets flow into a separate web app where your team can search them via RAG-based agent, follow specific topics, share context with colleagues, or feed them directly to other AI tools. We're building this so the switch between platforms is frictionless - your teammates and your AI tools get the right context without anyone maintaining a knowledge base manually.
Privacy note: For those wondering, the extension only processes the DOM of the specific chat you choose to extract. We don't access your other threads.
Coming soon: We're testing an MCP server internally. Once released, you'll be able to save nuggets or inject context directly from any MCP-compatible client.
Stack: Chrome extension for capture, web app (Next.js) for knowledge management, extraction pipeline using Azure OpenAI API. Early stage - works for my team, now seeing if it generalizes.
Pricing: Free for personal use. Team features will be paid eventually, but right now I want to validate whether this solves the problem for others.
What I'd love feedback on:
- How do you handle the "decision got made but nobody knows why" problem?
- Is decisions/insights/actions the right way to categorize what's worth keeping?

value: Show HN: Nuggetz – Turn AI chat threads into a searchable team knowledge base

author: kver


value: dsmurrell

value:
Claude only starts the session timer for your next allowance when you send your first message after a period of no use.
It would be better for you if they started a new one when your current one expired so that there's less time until you get your new allowance when you happen to start using it.
They might do this for UX reasons (the auto-restart looks weird), or they could be trying to get people to upgrade. Maybe both.
A solution I've found is to just say "yo" to Claude every 5 hours. This somewhat decreases the chance that a deep Claude session gets blocked.
yo-claude is an easy way to enable this. Feedback and bug reports welcome.

value: Show HN: yo-claude – Start your Claude session early to avoid interruptions

author: dsmurrell


value: Atallapr

value:
The title says it all.
Was learning more about mcp and thought this would be a fun project to share! I built an mcp server that lets you find taco bell locations near you and get the menu items for a particular location. I will probably try to add ordering items for delivery as another feature down the line. Live Mas!

value: Show HN: Sigh* Taco Bell MCP

author: Atallapr

title: Show HN: Sigh* Taco Bell MCP


value: Weves

value:
I’ve found coding agents to be great at 1/ finding everything they need across large codebases using only bash commands (grep, glob, ls, etc.) and 2/ building new things based on their findings (duh).
What if, instead of a codebase, the files were all your workplace docs? There was a `Google_Drive` folder, a `Linear` folder, a `Slack` folder, and so on. Over the last week, we put together Craft to test this out.
It’s an interface to a coding agent (OpenCode for model flexibility) running on a virtual machine with:
1. your company's complete knowledge base represented as directories/files (kept in-sync)
2. free reign to write and execute python/javascript
3. ability to create and render artifacts to the user
Demo: https://www.youtube.com/watch?v=Hvjn76YSIRY
Github: https://github.com/onyx-dot-app/onyx/blob/main/web/src/app/c...
It turns out OpenCode does a very good job with docs. Workplace apps also have a natural structure (Slack channels about certain topics, Drive folders for teams, etc.). And since the full metadata of each document can be written to the file, the LLM can define arbitrarily complex filters. At scale, it can write and execute python to extract and filter (and even re-use the verified correct logic later).
Put another way, bash + a file system provides a much more flexible and powerful interface than traditional RAG or MCP, which today’s smarter LLMs are able to take advantage of to great effect. This comes especially in handy for aggregation style questions that require considering thousands (or more) documents.
Naturally, it can also create artifacts that stay up to date based on your company docs. So if you wanted “a dashboard to check realtime what % of outages were caused by each backend service” or simply “slides following XYZ format covering the topic I’m presenting at next week’s dev knowledge sharing session”, it can do that too.
Craft (like the rest of Onyx) is open-source, so if you want to run it locally (or mess around with the implementation) you can.
Quickstart guide: https://docs.onyx.app/deployment/getting_started/quickstart
Or, you can try it on our cloud: https://cloud.onyx.app/auth/signup (all your data goes on an isolated sandbox).
Either way, we’ve set up a “demo” environment that you can play with while your data gets indexed. Really curious to hear what y’all think!

value: Show HN: Craft – Claude Code running on a VM with all your workplace docs

author: Weves


value: adriancooney

value: Show HN: Evals skill for agents – no tooling, just Markdown and subagents

author: adriancooney


value: snorbleck

value:
With LORE LABYRINTH, you guide a yellow glowing orb through twisting corridors, razor-thin turns, and deceptive dead ends. One slip into a wall and you could lose some coins.
Along the journey, you will encounter some valuable collectibles like mushrooms, keys, and abilities that can turn disaster into triumph. Use them wisely!
Lock the cursor for precision, chase power-ups if the risk is worth it, and remember... every run is a one-of-a-kind challenge.

value: Show HN: Lore Labyrinth – A Maze Game

author: snorbleck

title: Show HN: Lore Labyrinth – A Maze Game


value: ShreyaChaurasia

value:
Hi HN,
We just shipped a Nomod integration in Flexprice.
For context, flexprice is an open-source billing system that handles invoices, usage, and credit wallets. One gap we wanted to close was supporting region-specific payment providers without breaking billing state.
With this integration:
- Invoices finalized in Flexprice can be synced to Nomod
- A hosted Nomod payment link is generated for the invoice
- Payment status updates flow back into Flexprice
- Invoices and payment records stay in sync
- Credits (if applicable) are applied only after payment succeeds
This keeps billing logic simple and avoids reconciliation issues later. There's no demo yet, but docs are live here: https://docs.flexprice.io/integrations/nomod/
Happy to answer questions or hear feedback from folks who've built billing or payment integrations before or feel free to join our open-source community if that interests you : http://bit.ly/4huvkDm

value: Show HN: Nomod payment integrated into usage-based billing stack

author: ShreyaChaurasia


value: dweekly

value:
Fellow HN folks,
Many of us who build macOS apps use Sparkle to keep our apps up to date, which uses a published appcast.xml file to track current releases & metadata. If you push out a bad file you could break your updates, but there wasn't a way to validate an appcast.xml before deploying it. So I built one.
It's an NPM module, open source & MIT licensed. Also a web service that can take URLs, files, or pastes and validate as errors, warnings, or informational items. It's also a GitHub Action that's on the marketplace so you can integrate it into your CI/CD pipeline in about three lines. I also put together an XSD validator and plain .md docs as you (or your agent) are authoring.
Feedback welcome!

value: Show HN: Sparklevalidator.com (For Appcast.xml Files)

author: dweekly


value: Shaehenderson

value:
Hi HN — this is a short demo of a locally run AI workflow generating a simple landing page from a prompt.
The AI proposes changes, but all file writes and commands are applied through a constrained local execution layer rather than directly by the model. The video shows a single end-to-end run from prompt to generated page, with no manual intervention during execution.
The intent of the demo is to illustrate controlled execution, not model capability or design quality.
Repo and demo video:
https://github.com/indyh91/Nyxi-Showcase
Happy to answer technical questions about the execution layer.

value: Show HN: Prompt → landing page: locally-run AI with a execution layer (demo)

author: Shaehenderson


value: bahaii

value:
I created a small free tool for engineers and CTOs to upload AI usage logs (CSV / API logs) and instantly see where your company might be wasting money or exposing sensitive prompts.<p>It’s fast, simple, and a bit shocking.
If you want to try it, reply here and I’ll send the link.

value: Show HN: Free AI Scan for Hidden Spend and Data Risk

author: bahaii


value: EastLondonCoder

value:
We’re Maria and Jonatan, a married couple running a small music night in Norrköping, Sweden, called Kolibri.
It’s not a software project. We run it through our own small Swedish company, pay artists, and do the operations ourselves. We do one night a month (usually the last Friday) in a restaurant venue called Mitropa. A typical night is about 50–70 paying guests. The first years it was DJs only, but last year we started doing live bands as well.
We made a simple site with schedule plus photos/video so you can see what it looks like:
https://kolibrinkpg.com/
On the site:

  * photos and short videos (size/atmosphere)

  * the kind of acts we book (post-punk, darkwave, synth, adjacent electronic)

  * enough context to copy parts of the format if you’re building something similar locally

  * for the tech-curious: we built our own ticketing system (first used in February) and a media ingestion pipeline for Instagram and external photographers

How it started was accidental. I was doing remote music sessions with a friend in London (Ableton projects back and forth on FaceTime), ran out of beer, and walked into the nearest place. I got talking to Nahir, who runs Mitropa, and floated the idea of running a DIY music night there. He was up for it.
What made it take off was doing things in person. People will show up alone if they trust the room. Maria ended up doing a lot of that work: greeting newcomers, noticing who looks uncertain, and setting a tone where people treat each other decently.
Maria didn’t come from a DJ background. Klubbvärdinnan started as a joke name at Kolibri and then became her DJ moniker. She got good quickly, and after a first gig outside our own night she started getting booked elsewhere too.
Marketing-wise, what worked best was very analogue: walking around town, visiting local businesses we genuinely like, buying something, introducing ourselves, and asking if we could leave a flyer.
In the beginning we weren’t sure how to present it on social media. So we filmed headphone walks: one person walking through town listening to a track we picked. It looked good, people wanted to be in them, and afterwards we’d buy them a couple of drinks and actually talk. That turned a social media interaction into a real connection. It was a bit of luck, but it worked.
Questions welcome about what worked, what failed, costs/logistics, and what we’d do differently if we started over.

value: Show HN: Kolibri, a DIY music club in Sweden

author: EastLondonCoder


value: runkids

value:
Hi HN,
I kept writing the same hooks for different AI coding tools with slightly different configs:
- Claude Code: ~/.claude/settings.json (PreToolUse)
- Cursor: ~/.cursor/hooks.json (beforeShellExecution)
- Gemini CLI: ~/.gemini/settings.json (BeforeTool)
- OpenCode: ES module plugins
So I made a skill that unifies them. One hook script works across all 4 tools.
It also includes patterns for common use cases: blocking dangerous commands, auto-formatting, notifications, audit logging.
Built two apps using Claude Code + this skill:
- Code Buddy (SwiftUI): menu bar status for AI sessions
- Veto (Rust): risk scoring + Touch ID before dangerous commands
Source: https://github.com/runkids/ai-hooks-integration
Feedback welcome.

value: Show HN: A skill that lets AI agents build hooks apps across 4 coding tools

author: runkids


value: samrith

value:
Hi HN,
I'm Samrith, the founder of Hyperterse.
We built Hyperterse because I kept running into the same problem when building AI agents: safely connecting databases to LLMs requires writing endless API endpoints, managing boilerplate validation, and building custom integrations for each AI framework, build custom MCP integrations for each AI framework, or worry about exposing SQL or connection strings to clients.
We built a runtime server that consolidates this into a single declarative configuration file. You define your queries once, and Hyperterse automatically generates typed REST endpoints, MCP tools, OpenAPI specs, and LLM-friendly documentation.
Instead of writing API endpoints, you define queries in a simple config file. Hyperterse handles:
- Query Definition: Write queries once with typed inputs
- Endpoint Generation: Each query becomes a REST endpoint
- MCP Integration: Queries are automatically exposed as MCP tools for AI agents
- Documentation: OpenAPI 3.0 specs and LLM-readable docs generated automatically
- Security: SQL and connection strings stay server-side—never exposed to clients
Here's what a typical query looks like. This replaces about 500-1000 lines of boilerplate API code:
adapters:

  my_db:

    connector: postgres

    connection_string: "postgresql://user:pass@localhost:5432/db"

queries:

  get-user:

    use: my_db

    description: "Retrieve a user by email"

    statement: |

      SELECT id, name, email, created_at

      FROM users

      WHERE email = {{ inputs.email }}

    inputs:

      email:

        type: string

        description: "User email address"

Supports PostgreSQL, MySQL, and Redis (at the moment, more connectors coming), hot reloading in dev mode, type-safe input validation (string, int, float, boolean, datetime), self-contained runtime—deploy anywhere, no ORMs or query builders required.
You can use Hyperterse for a variety of use cases, with the most prominent being:
- AI agents and LLM tool calling
- RAG applications with structured database queries
- Rapid API prototyping
- Multi-agent systems sharing database access

value: Show HN: Hyperterse – a super fast runtime to connect your data to your agents

author: samrith


value: jonhermansen

value:
I've been working on getting NixBSD (Nix package manager + FreeBSD) to boot alongside NixOS on a shared ZFS pool. The result is a <2GB disk image you can try in QEMU or virt-manager.
What works:

    - GRUB chainloads FreeBSD's bootloader
    - Both systems share a ZFS pool
    - Everything is defined in a single Nix flake
    - Fully reproducible builds (some dependencies are now cached on Cachix)

Planned:

    - Support native compilation of NixBSD (currently cross-compiled on Linux)
    - Many shortcuts were taken to get this working, needs lots of cleanup
    - Add a semi-automated installer like nixos-wizard

Try it:

    qemu-system-x86_64 -enable-kvm -m 2048 \
      -bios /usr/share/ovmf/OVMF.fd \
      -drive file=nixos.root.img,format=raw

Login: nixos/nixos or root/toor
The hardest parts were getting mounts working at boot, making the bootloader setup idempotent, and debugging early init. This disk image could potentially work on a USB stick with a bit more work.
This is very much experimental. My goal is to eventually produce a proper NixBSD installation ISO and consolidate all configuration into one repository while still consuming upstream NixBSD as a flake.
Download: https://github.com/jonhermansen/nixbsd-demo/releases/tag/bui...
Feel free to leave feedback here or on GitHub! Thanks!

value: Show HN: I made a dual-bootable NixBSD (NixOS and FreeBSD) image

author: jonhermansen


value:
For most of us, getting users still takes real work.
Short form content on TikTok and Reels can be one of the fastest ways to get real users, but DM’ing content creators on IG or TikTok barely works. Low response rates and a lot of manual work.
So I built Collab Only, a matching app where vibe coders and content creators match by niche and goals, then chat instantly to collaborate.
I launched a few days ago, and it has already helped me connect with content creators faster than cold DMs.
I'm looking for feedback from this community.
Have you tried working with content creators to get users? What other approaches have worked for you?

value: Show HN: I built an app to help vibe coders get users


value:
Hi,
I developed and use an IA tool to save $$$ .
https://github.com/pszymkowiak/rtk
Save your token on any IA code solution:
rtk gain from a session:

  RTK Token Savings
  ════════════════════════════════════════
  Total commands:    650
  Input tokens:      3.9M
  Output tokens:     204.4K
  Tokens saved:      3.7M (96.2%)

  By Command:
  ────────────────────────────────────────
  Command                Count       Saved     Avg%
  rtk find                  38        2.1M    86.2%
  rtk git status            93        1.4M    85.4%
  rtk grep                  67       84.5K    50.3%
  rtk read                  63       49.9K    30.7%
  rtk ls                   121       14.5K    52.9%
  rtk git push             138        9.4K    91.3%
  rtk env                   28        8.4K    98.4%
  rtk run-test               9        6.4K    87.0%
  rtk summary               13        5.1K    70.3%
  rtk kubectl svc            9        3.0K    95.3%

Free to Use !
Estimations:

  Tier             Quota Brut      Équivalent RTK
  Pro ($20)        6.0M tokens     ~24M tokens
  Max 5x ($100)    30.0M tokens    ~120M tokens
  Max 20x ($200)   120.0M tokens   ~480M tokens

value: Show HN: RTK – Simple CLI to reduce token usage in your LLM prompts


value:
This is a small runtime safety primitive I’ve been working on.
It computes a bounded “GV” signal from live agent behavior (token velocity, tool calls, errors, recursion, repetition) and emits:
green / yellow / red → continue / slow / halt.
The goal is runtime survivability rather than training-time alignment.
No model introspection, deterministic scoring, and designed to be embedded directly into agent loops.
There’s a short demo script in the repo that simulates an agent going unstable.
Feedback welcome.

value: Show HN: Measuring runtime strain in autonomous AI systems