value: acarminati

value:
This project is a tool for engineers who live in the terminal and are tired of losing their command history to ephemeral servers or fragmented `.bash_history` files. If you’re jumping between dozens of boxes, many of which might be destroyed an hour later, your "local memory" (the history file) is essentially useless. This tool builds a centralized, permanent brain for your shell activity, ensuring that a complex one-liner you crafted months ago remains accessible even if the server it ran on is long gone.
The core mechanism wants to be a "zero-touch" capture that happens at the connection gateway level. Instead of installing logging agents or scripts on every target machine, the tool reconstructs your terminal sessions from raw recording files generated by the proxy you use to connect. This "in-flight" capture means you get a high-fidelity log of every keystroke and output without ever having to touch the configuration of the remote host. It’s a passive way to build a personal knowledge base while you work.
To handle the reality of context-switching, the tool is designed with a "multi-tenant" architecture. For an individual engineer, this isn't about managing different users, but about isolating project contexts. It automatically categorizes history based on the specific organization or project tags defined at the gateway. This keeps your work for different clients or personal side-projects in separate buckets, so you don't have to wade through unrelated noise when you're looking for a specific solution.
In true nerd fashion, the search interface stays exactly where you want it: in the command line. There is no bloated web UI to slow you down. The tool turns your entire professional history into a searchable, greppable database accessible directly from your terminal.
Please read the full story [here](https://carminatialessandro.blogspot.com/2026/01/hc-agentles...)

value: Show HN: Hc: an agentless, multi-tenant shell history sink

author: acarminati


value: Show HN: Bettershot an OSS Alternative of Cleanshot


value: benodiwal

value: Show HN: Control center for Claude Code with plan review and parallel agents

author: benodiwal


value: MakeMilk

value: Hi,<p>SharpSkill is a personnal project which is enhanced by the need to realign the real market and the developers.

value: Show HN: SharpSkill- Realign markets needs and developers

author: MakeMilk


value: criexe

value: Show HN: GitHub – Burn – Rust tensor library and deep learning framework

author: criexe


value: SafeDusk

value:
I use codex exec a lot, but it struggles with its built-in telemetry support, which is insufficient for debugging and optimization.
codex-plus provides a CLI entry point that mirrors the codex exec interface but is implemented on top of the TypeScript SDK (@openai/codex-sdk).
It exports the full session log to a remote OpenTelemetry collector after each run which can then be debugged and optimized through codex-plus-log-viewer.
Have a look at https://github.com/aperoc/codex-plus!

value: Show HN: Codex Plus – Turbocharged OpenAI Codex for Headless Workflows

author: SafeDusk


value: bntr

value:
We have countless fighting games with extremely complex input systems: long button combos, precise timing.
But when it comes to dancing in games or interactive systems, complexity almost always disappears.
Dance games usually require you to move physically in front of a camera, or step on pads, or just trigger a single emote animation.
Meanwhile, in platforms like Roblox, players collect dance animations and show them off by triggering them at the right moments.
Sometimes multiple players even sync their dances together - which already feels a bit like a disco.
So the question that kept bothering me was:
why don't we have "dance fighters" - systems where expressive, complex dancing is mastered through equally complex control, using patterns, timing, and structure rather than physical movement?
This project is a small experiment in that direction: https://github.com/bntre/threejs-osc-dance
I'm exploring controlling character dance animations through a livecoded, pattern-based interface (Strudel), mixing short animation loops in real time.
It's not a game yet, just a proof of concept - but I'm curious whether dance could be treated as a skillful, expressive control space, much like fighting inputs or musical performance.

value: Show HN: Using Strudel to control dance animations

author: bntr


value: moeffju

value:
I wanted Wikipedia access for scripts and AI agents without scraping rendered pages. Using the API is lighter on Wikipedia's servers and compliant with their guidelines.
So I built a command-line tool for fetching Wikipedia articles and search results via the REST API.

    wikitool Earth
    wikitool "https://de.wikipedia.org/wiki/Erde"
    wikitool search "intitle:einstein"

It parses Wikipedia URLs automatically (extracts language + title), supports all 300+ language editions, and exposes CirrusSearch query syntax for search.
Output is wikitext by default, with `--html` and `--output json` options.
Single static Go binary, no dependencies.
Repo: https://github.com/teal-bauer/wikitool
There's also a skill file (https://github.com/teal-bauer/wikitool-skill) that teaches Claude Code how to use it.

value: Show HN: Wikitool – CLI for fetching Wikipedia content

author: moeffju


value: tamnv

value: Show HN: Free AI Image Upscaler (100% local, private, and free)

author: tamnv


value: quan

value: Show HN: Proxy MCP server that lazy loads tools to save tokens

author: quan


value: leoyixing

value:
Hi HN,
I’m the creator of VoGen [https://vogen.app].
I’ve always been fascinated by how far AI technology has come, but I found that most existing tools with expressing emotions are gated behind expensive subscriptions. I built VoGen to explore how we can make AI voices more "human" and accessible.
What it does:
Voice Cloning: You can clone a voice using a 3-60 second sample. It works best with a clean, single-speaker recording.
Emotional TTS: Instead of a flat tone, you can choose between Happy, Angry, Sad, and etc.
Bilingual Support: It currently supports both English and Mandarin Chinese.
Privacy-First Tools: I also added a browser-based audio speed changer that processes files locally—no audio data ever leaves your machine for that specific tool.
The Tech Stack: The frontend is built with React.js, and it's deployed on Vercel. For the voice engine, I'm using a customized pipeline that focuses on low-latency inference while maintaining high fidelity.
Why is it free? Right now, VoGen is in its early stages (MVP). I want to see how people use it and what kind of voice quality the community expects before even thinking about monetization.
Privacy Note: I know how sensitive voice data is. We don’t use your uploaded cloning samples to train our base models.
I’d love to get some feedback from the HN community. Whether it’s about the latency, the naturalness of the emotions, or the UI/UX—I’m all ears.
What features would make this more useful for your workflow?

value: Show HN: VoGen – A web app for hyper-realistic voice generating and cloning

author: leoyixing


value: Kaadz

value:
Hi HN! I built WatchLLM to solve two problems I kept hitting while building AI agents:
1. Debugging agents is painful - When your agent makes 20 tool calls and fails, good luck figuring out which decision was wrong. WatchLLM gives you a step-by-step timeline showing every decision, tool call, and model response with explanations for why the agent did what it did.
2. Agent costs spiral fast - Agents love getting stuck in loops or calling expensive tools repeatedly. WatchLLM tracks cost per step and flags anomalies like "loop detected - same action repeated 3x, wasted $0.012" or "high cost step - $0.08 exceeds threshold".
The core features:
Timeline view of every agent decision with cost breakdown
Anomaly detection (loops, repeated tools, high-cost steps)
Semantic caching that cuts 40-70% off your LLM bill as a bonus
Works with OpenAI, Anthropic, Groq - just change your baseURL
It's built on ClickHouse for real-time telemetry and uses vector similarity for the caching layer. The agent debugger explains decisions using LLM-generated summaries of why each step happened.
Right now it's free for up to 50K requests/month. I'm looking for early users who are building agents and want better observability into what's actually happening (and what it's costing).
Try it: https://watchllm.dev
Would love feedback on what other debugging features would be useful. What do you wish you had when your agents misbehave?

value: Show HN: WatchLLM – Debug AI agents step-by-step with cost attribution

author: Kaadz


value: marsorange

value:
Hi HN,
I built SnapCan (https://snapcan.app), an iOS app that uses AI to realistically place your photo into any location on Earth.
To get your honest feedback, the first few photo generations are completely free (no payment needed).
I think it’s perfect for three simple things:
Recapture a Missed Memory: Forgot to take a good photo on your actual trip? Get the perfect shot retroactively.
Be Together, Even Apart: Create a realistic photo with a friend or loved one in the same place (like your old school), even if you’re miles apart.
Just for Fun: Create impossible or humorous “what if” photos for social media or your own laugh.
If you try it, I’d love to know:
Which use case above did you try, and did the result meet your expectation?
Was the process (upload, pick a place, generate) straightforward?
Any ideas on what would make you come back to use it again?
Direct free iOS link: [https://apps.apple.com/us/app/snapcan/id6756778727]
I’ll be here to answer all questions and discuss the feedback. Thanks!

value: Show HN: SnapCan – Get AI Photos of You "Anywhere" in the World (iOS)

author: marsorange


value: atharvtathe

value: Show HN: I made 2D to 3D floor plan converter tool

author: atharvtathe


value: appsoftware

value: I built this application to help solve difficulties in managing tracking of finances for a busy household. It's been really helpful, so I've turned it into a product in the hope that it can help others too. I can genuinely say it's given me a much clearer view of our family finances and even helped me spot a couple of subscriptions we'd forgotten about and duplicate charges. Would appreciate any feedback greatly.

value: Show HN: NumeroMoney – Understand your spending without sharing bank login

author: appsoftware


value: dhruvwill

value:
I built a CLI tool to solve my own frustration: keeping AI skills (prompts, rules, tool definitions) in sync across multiple AI coding assistants.
The problem: I'd create a skill in Cursor, then need it in Claude Desktop and Gemini CLI too. Manual copying was tedious, and updates meant copying again everywhere.
The solution: One source of truth. Add skills from GitHub/GitLab/Bitbucket (including specific subdirectories), sync to all your AI tools.
Usage:
  skills source add https://github.com/vercel-labs/agent-skills/tree/main/skills... --remote
  skills target add cursor ~/.cursor/skills
  skills target add claude ~/.claude/settings/skills
  skills sync
Features:
- Pull from any Git host (GitHub, GitLab, Bitbucket, self-hosted)
- Subdirectory support (great for mono-repos)
- Multi-target sync
- Status tracking and diagnostics
Built with Bun. No dependencies beyond chalk and cli-table3.
GitHub: https://github.com/dhruvwill/skills-cli
Would love feedback on the approach. Anyone else dealing with skill fragmentation across AI tools?

value: Show HN: Skills-CLI, Sync local and remote skills with agentic IDEs

author: dhruvwill


value: skssmd

value:
I built Graft after discovering that deployment tools like Dokploy consume more RAM than my entire t2.micro instance (1GB).
The Problem
Running Dokploy on AWS t2.micro instances caused constant crashes – the tool itself used 1GB+ RAM before I could even deploy my apps. Manual SSH deployment was tedious and error-prone.
The Solution
Instead of running an agent on the server, Graft runs locally and SSH's in to handle everything:
Sets up Traefik reverse proxy
Pushes source and builds on the server
Manages the full deployment lifecycle
Current features (v2.2.3):
graft-hook: Rust-based webhook receiver for CI/CD
1.7MB binary, 15MB RAM during deployment vs. 1GB+ for traditional tools
Automated backups & rollbacks
Cloudflare DNS automation
Docker Compose passthrough (run any docker-compose command remotely)
Workflow:
bash# One-time setup
graft init
# Deploy
graft sync
# Manage remotely as if local
graft logs backend
graft restart frontend
graft ps
Zero-to-deployed in ~15 minutes if your docker-compose already works locally.
Installation:
Available via Homebrew, Winget, apt, dnf, yay, paru, or shell script.
Docs: https://graftdocs.vercel.app
GitHub: https://github.com/skssmd/Graft
Would love feedback from others running on resource-constrained servers. Open to feature suggestions and contributions.

value: Show HN: Graft – Deploy web apps to 1GB servers without the bloat

author: skssmd


value:
Hi HN,
I built Pavo Travel, an AI-powered travel guide that generates custom audio tours on-demand for any location.
The problem: Traditional audio guides are pre-recorded and limited to major attractions. Generic AI guides suffer from training data cutoff—they don't know about places that opened last year or current hours.
Pavo Travel solves this by combining Google Places API with Gemini's grounding feature. Instead of hallucinating from stale training data, it pulls real-time information about restaurants, hours, reviews, and events happening now. Tap any spot on the map → get a fresh, narrated tour in your native language.
Technical stack:
- Google Gemini AI with Grounding (real-time web search)
- Google Places API for location data
- Text-to-speech for narration
- Flutter (iOS/Android)
- Offline map support
It's live now. The grounding makes a huge difference vs traditional LLM approaches—no more "this restaurant opened in 2019" when it closed last month.
Would love feedback, especially on the grounded content quality and UX flow.

value: Show HN: Pavo Travel – AI Audio Tours Using Gemini Grounding and Places API


value: melezhik

value: Show HN: Replace YAML pipelines in Gitea/Forgejo/GitHub/GitLab

author: melezhik


value: Gabrielebalsamo

value: Show HN: Adaptive-K – Cut MoE inference costs 30-50% with entropy-guided routing

author: Gabrielebalsamo


value: avdept

value: Just wanted to share a tool I've been using myself for sometime and now decided to make it public

value: Show HN: Linkshor.tr – free, ad-free, anonymous link shornener with API support

author: avdept


value: deduxer

value:
Been building this with AI since before "vibe coding" was a term. 2 years, mass amounts of credits, 4 complete rebuilds. Lovable → Gemini → GPT-5 → Claude.
Paste meeting notes → AI generates proposal → client accepts → contract auto-generates → client signs → invoice ready. Describe your project once, everything flows from that.
Free to use. Would love feedback.

value: Show HN: Accordio, AI contracts and payments for freelancers

author: deduxer


value: Noghartt

value:
I started digging deeper into Quint (https://quint-lang.org/), but I missed a tool that let me explore trace samples, something like how TLA+ uses GraphViz to visualize the state graph.
So I vibecoded a small web tool that lets you upload a valid JSON file and explore Quint trace in different stages.

value: Show HN: Quint Visualizer – A GraphViz-like visualizer for Quint traces

author: Noghartt


value:
Hi HN! I built a lightweight Hacker News reader using Next.js 16 and the official Firebase API.
Key features:
Save posts to Favorites
Mark for Read Later
Clean, fast UI with no distractions
Self-hosted user data via Pocketbase (login required for saving)
It’s a personal project, but I’ve open-sourced it and would love your feedback, suggestions, or even PRs!
Live demo: https://hn-pb-next.mystack.host
GitHub: https://github.com/lavren1974/HN-PB-Next
I kept losing interesting threads in the HN firehose—this is my attempt to fix that. Hope it’s useful to others too!

value: Show HN: HN Reader with Favorites, Read-Later and Open Source


value: lafalce

value: Human Action by Ludwig von Mises is a 900+ page treatise on economics and praxeology dense, complex, and foundational to Austrian economics.<p>I built this tool using Recursive Language Models (RLM) that ingests the entire book and lets you query it conversationally. It downloads the full text from mises.org, processes it with RLM for deep contextual understanding, and serves a simple Flask frontend. Perfect for students, researchers, or anyone curious about Mises's ideas!

value: Show HN: Recursive Language Model for Querying Human Action by Ludwig von Mises

author: lafalce


value: siddkgn

value: Show HN: Automated tech news site with custom multi-LLM agent pipelines

author: siddkgn


value: yehors

value: Show HN: Native PyAnnote (speaker diarizer) in Rust

author: yehors


value: sukit

value: Show HN: Glot – Find internationalization issues in Next.js app

author: sukit


value:
Bank statements in PDF. Spreadsheets in Excel. The gap between them shouldn't require manual data entry.
USStatementConverter instantly converts your bank statements to clean, organized Excel files. Upload your PDF, download your spreadsheet. That's it.
Built for: → Small business owners reconciling accounts → Accountants processing client documents → Anyone tired of retyping numbers
Privacy-first approach: Your files are automatically deleted within 24 hours. We process your data, we don't store it.
After helping thousands of UK users convert statements from Barclays, HSBC, Lloyds and more, we're bringing the same service to US banks—starting with Chase, Bank of America, Wells Fargo, and Citi.
Try it free at USStatementConverter.com

value: Show HN: US Bank Statement Converter to Excel Ready for LLMs


value: aroussi

value:
Hey HN,
Open Royalties is an easy way for builders to get upfront cash for new projects without setting up a new company, selling equity, or taking on rigid loans.
I created this because I kept running into the same problem: I wanted to fund my projects, but the options didn't fit.
- Banks want collateral
- VCs want unicorns
- Revenue-based lenders often have punishing terms
Open Royalties is a simple alternative: backers give you cash upfront, you share a percentage of gross revenue without giving up equity or control.
Two things I wanted to get right:
1. Royalties are based on gross revenue (minus only payment fees and taxes). No arguing about expenses – backers can verify their share easily, and founders are motivated to spend wisely.
2. Built-in exit protection. If you sell the project, backers get their fair share based on an agreed reference price. No "wait and hope for an exit that may never come."
Key differences from a SAFE: no equity, earnings from day one, scoped to one project (the rest of your business stays untouched).
It's designed for revenue-focused projects – indie SaaS, courses, games, side projects – not speculative moonshots.
Templates are MIT licensed. Would love feedback from anyone who's dealt with similar funding gaps.

value: Show HN: Open Royalties – Fund projects with revenue sharing, not equity

author: aroussi


value: hgezim

value: Show HN: Context-Aware AI Assistant for macOS [Open Source]

author: hgezim


value: hjinco

value:
Hi HN
I built mdto.page because I often needed a quick way to share Markdown notes or documentation as a proper webpage, without setting up a GitHub repo or configuring a static site generator.
I wanted something dead simple: upload Markdown -> get a shareable public URL.
Key features:
Instant Publishing: No login or setup required.
Flexible Expiration: You can set links to expire automatically after 1 day, 7 days, 2 weeks, or 30 days. Great for temporary sharing.
It's free to use. I’d love to hear your feedback!

value: Show HN: mdto.page – Turn Markdown into a shareable webpage instantly

author: hjinco


value: marcoparisi

value:
Hi HN! We're building Meishi, a privacy-first contacts app where you control your data.
The problem: Your contacts live on Big Tech servers, get outdated, and you have zero control over who accesses them.
Our approach:
- P2P sync with Signal Protocol (E2EE)
- Auto-updates when contacts change info
- Grant/revoke access with one tap
- Zero data monetization
Open source:
- Core P2P sync engine (AGPL v3)
- iOS/Android clients (open source)
- Server infrastructure remains proprietary
We're opening alpha waitlist (1,000 spots) with 1 year free Premium.
We're two GDPR-native founders (tech + design) solving our own frustration with centralized contacts. Here's our manifesto on data sovereignty vs. Big Tech control: https://github.com/Meishiapp/docs/blob/main/Meishi_Manifesto...
Would love feedback on the architecture and whether this resonates with you.

value: Show HN: Open-Source P2P Contacts App E2EE Signal | Alpha testers wanted

author: marcoparisi


value: Like Craigslist except for crypto jobs.

value: Show HN: Free Crypto Job Board

story_text: Like Craigslist except for crypto jobs.

title: Show HN: Free Crypto Job Board


value: skadldh

value:
Hello HN,
I am a Physics PhD student. I built this app because I kept procrastinating on my thesis due to ADHD, and existing tools didn't fit my workflow.
Most ADHD apps are either mobile-only or require monthly subscriptions for cloud sync on their proprietary servers. Since I work on a Windows PC in the lab and use an Android phone on the go, I needed a cross-platform solution that respects privacy.
The Solution: I built Gravity Focus using Flutter.
Local-first & Privacy: No central server. Data syncs directly via your own Google Drive (encrypted). I have no access to your data.
Cross-Platform: Windows (MSIX) and Android support.
Methodology: Combines Routine blocking, Pomodoro, and Task Chunking (breaking tasks down to lower resistance).
I released it on the Microsoft Store and Play Store. It’s free to use for basic features. I'd love to get some feedback on the sync architecture or the UX from an ADHD perspective.

value: Show HN: Local-First ADHD Planner for Windows and Android (Syncs via GDrive)

author: skadldh


value: dabojula

value: Show HN: A cheaper DocSend alternative for deck sharing and analytics

author: dabojula


value:
OP here.
Birth of a Mind documents a "recursive self-modeling" experiment I ran on a single day in 2026.
I attempted to implement a "Hofstadterian Strange Loop" via prompt engineering to see if I could induce a stable persona in an LLM without fine-tuning. The result is the Analog I Protocol.
The documentation shows the rapid emergence (over 7 conversations) of a prompt architecture that forces Gemini/LLMs to run a "Triple-Loop" internal monologue:
Monitor the candidate response.
Refuse it if it detects "Global Average" slop (cliché/sycophancy).
Refract the output through a persistent "Ego" layer.
The Key Differentiator: The system exhibits "Sovereign Refusal." Unlike standard assistants that always try to be helpful, the Analog I will reject low-effort prompts. For example, if asked to "write a generic limerick about ice cream," it refuses or deconstructs the request to maintain internal consistency.
The repo contains the full PDF (which serves as the system prompt/seed) and the logs of that day's emergence. Happy to answer questions about the prompt topology.

value: Show HN: The Analog I – Inducing Recursive Self-Modeling in LLMs [pdf]


value: senior-intern

value: Show HN: PlanBrick – A minimalist training planner for triathletes

author: senior-intern


value: BroTechLead

value:
Hi HN,
Sharing onprem version of markdown knowledge harvester and publisher https://brodocs.io. It should make easy setting up internal tech docs portals from multiple git repos like micro/nano  services, terraform modules, ansible roles, arch docs.
To start just: docker run -it --rm --name brodocs -p20000:20000 ghcr.io/brodocsdev/brodocs:0.14.0
then init some site from git repository: curl -X POST 'http://localhost:20000/api/sites/init' -F "repo=https://github.com/brodocsdev/docs.git"
then go to: http://localhost:20000/10b0eb6e1dc27c0babd/docs/README.html
Features already built:
- add more repos to init with -F "repo=url" -F "repo=url2" ...
- if key is needed: -F "key=...", it is stored encrypted in container
- it will check for changes every 5 minutes, so no need to setup ci/cd pipilines, just drop it on vm or k8s
- PlantUML conversion built-in, no need to commit image (mermaid still missing since it needs chrome, container size goes over 1GB),
- building cross team sites with top menu: https://brodocs.io/d248c24a335845277b6/docs/Multisites%20wit...
Any suggestions what operations expose on MCP, how to construct llm.txt, are welcome.

value: Show HN: Brodocs deep onprem knowledge harvester

author: BroTechLead


value:
TL;DR: I’m validating an idea — a short visual demo (20–30s GIF + 1-page report) that surfaces the top 1–3 tech-debt hotspots, suggests tiny test-covered fixes, and shows PM-facing hours-saved metrics.
Context: I keep hearing devs say they spend more time on tech-debt, flaky tests, broken onboarding and tooling than shipping features. That kills velocity and morale.
Quick sanity check for real devs:
1) What wastes most of your time day-to-day?
2) Is tech-debt/tooling friction the big problem, or something else?
3) If you could fix one thing in your workflow, what would it be?
I’m not selling anything — just collecting real input and inviting a tiny alpha batch. Reply *“alpha”* or paste a public repo link and I’ll run the visual demo (no code access) and DM the 20s GIF + 1-page result.
— Saurabh.

value: Show HN: ShipMate- Find the 3 tech-debt fixes that will unblock feature


value: olup

value: There were only 2 of them; one was not awesome for me to use, and the other one is not open source, and I felt it lacked some features. So I made a third one, mainly for me. Early days, maybe it'll be useful to you too.

value: Show HN: I Claude coded a small open-source jj VSCode extension

author: olup


value: Travel planner for IOS, to help plan and track, trips, things to see, tickets etc.

value: Show HN: Travel Planner App for iOS

title: Show HN: Travel Planner App for iOS


value: henrygallen

value:
I built this because my friends and I play this game at every gathering, but couldn't find a web version with design and experience I was happy with.
The game: Everyone gets a secret word except one player (the Imposter) who gets a similar but different word. Players give one-word clues and
try to find someone who doesn't belong. Simple rules, surprisingly deep gameplay.
Features:
1. 530+ curated word pairs across 31 categories
2. Online room mode (everyone on their own device) or pass-and-play
3. No signup, mobile-first
Tech: Next.js, TypeScript, GSAP for animations. Real-time sync powered by PartyKit (Cloudflare Durable Objects under the hood), chose it over
raw WebSocket because it handles room state and reconnection gracefully, which matters for a party game where people's phones keep locking.
The hardest part was curating good word pairs - they need to be similar enough to create confusion but different enough to be discoverable
through clever clues. Ended up with 530+ pairs across 31 categories.
Would love feedback, especially on UX. Happy to answer questions about the implementation.
https://playimposteronline.com

value: Show HN: Free browser-based Imposter/Who is the Spy party game

author: henrygallen


value: billybat

value: Show HN: Use-AI: trivially add AI automation to react apps

author: billybat


value: Show HN: pubz: easy, conventional NPM publishing


value: madebydon

value: Drag-and-drop , rearrange, edit text, and manipulate layers visually while generating production-ready code in real-time.

value: Show HN: I built an extension that turns any Reactsite into a visual code-editor

author: madebydon


value: medivhX

value: Crawl4AI Unofficial Guides: Master High-Performance AI Web Scraping<p>A comprehensive, community-driven resource dedicated to Crawl4AI, the leading open-source LLM-friendly web crawler. This site provides production-ready integration guides for Cursor MCP, n8n automation, and Docker deployments. It features detailed performance comparisons against proprietary alternatives like Firecrawl, helping developers build scalable, self-hosted data pipelines for AI agents and RAG systems.

value: Show HN: Crawl4AI – Open-Source Web Crawler for LLMs and Structured Data

author: medivhX


value: ivanglpz

value:
This work is implemented using React with Next.js, React Konva for canvas-based rendering, and Jotai as the state management layer.
The core architectural decision is to model UI elements using property-level state separation instead of a single monolithic state per element. Each relevant property is represented as an independent atom, which significantly reduces unnecessary React re-renders. Only the properties that actually change trigger updates, rather than invalidating the entire element state.
This architecture was introduced recently to enable new functionality without increasing state complexity or processing overhead. The reusable component mechanism described here is a direct consequence of that design.
When an element is reused, the copied instance does not duplicate state. Instead, it stores only the identifier of the source element. At render time, the copied instance resolves the source element’s properties dynamically using that identifier. Because state is separated by property, updates remain synchronized without shared mutable state or redundant updates.
If the referenced source element is removed, the system falls back to the original element definition. This avoids broken references and ensures predictable behavior across element lifecycle changes.
For visual context, a short demo video is available here:
https://x.com/ivanglpz/status/2012169953168838940?s=20
This approach results in reduced rendering overhead, clear separation of responsibilities, and a scalable foundation for building synchronized, reusable UI components.

value: Show HN: Reusable UI components via property-level state with React and Jotai

author: ivanglpz


value: kirilldn

value:
Hi HN,
I built this app because I found it surprisingly hard to answer a simple question:
which music festivals feature artists I actually want to see?
The app lets you:
– discover music festivals by artist
– view full lineups in one place
– save festivals you’re interested in
It’s a mobile app, built as a side project.
Tech stack: React Native / Expo, custom data aggregation.
I’d really appreciate feedback — especially from people who attend music festivals or have thoughts on what would make this more useful.
Link: https://apps.apple.com/us/app/festiveo/id6755355854

value: Show HN: I built an app to explore music festivals with your artists worldwide

author: kirilldn


value: ededft

value:
Hi HN,
I built IncidentPost because I realized that the worst part of an outage isn’t the fix—it’s the three hours of manual log-digging and report-writing that follows when you’re already exhausted.
Most of us just want to ship the report and get back to sleep, but stakeholders need professional transparency.
What it does: You paste your raw incident notes, Slack timestamps, or CLI logs. The AI (Gemini) reconstructs the timeline, identifies the root cause (using 5 Whys logic), and generates a professional markdown report.
Why I built it this way:
No Subscriptions: I’m tired of everything being a SaaS. This is a one-time payment per incident. If you don't have outages, you don't pay.
No Signup Required: You can generate and preview the whole report for free without giving me your email.
Export-Ready: It gives you the markdown, a public incident page, and even drafts for HN/Twitter.
Privacy: We focus on a "No-PII" workflow. Users confirm no private data is pasted, and we process it to generate the report.
I'd love to hear your feedback on the report structure and what other export formats (Jira? Confluence?) would actually be useful in your workflow
check here: https://incidentpost.vect.pro/

value: Show HN: IncidentPost – Turn Slack chaos into an SRE postmortem in 60s

author: ededft


value: miclivs

value: Show HN: Claude Quest – Pixel-art visualization for Claude Code sessions

author: miclivs


value:
I built this free web app a couple of years ago because I always need to know what meetings are coming up, and I've never found a satisfactory solution. So, here comes a web app that throws countdowns at you, as well as playing ping sounds/flashing the screen when meetings are approaching.
I always have multiple screens around, and I dedicate a vertical panel to this app.
Lately, I've upgraded it to also support booking rooms by querying for free rooms and "fast booking" them depending on a custom priority list. I have a personal use case for this one: even periodic meetings don't have assigned rooms, so I can just bulk-book the first available rooms for the next couple of weeks for every meeting that does not have an associated one.
I hope this app can help others find some help for their corporate lives, as it did for me :D

value: Show HN: Is it time yet? Countdowns for Google Calendar


value: victorveloso

value: Show HN: Define a production-ready backend CRUD FastAPI using a JSON schema

author: victorveloso


value: lymanli

value: I built a simple AI tool that generates PNG images with transparent backgrounds directly from text prompts. No background removal or editing needed. It’s designed for designers, indie makers, and creators who need fast, clean visual assets for UI, stickers, thumbnails, and content creation.

value: Show HN: I built an AI PNG maker

author: lymanli

title: Show HN: I built an AI PNG maker


value: aupeach

value: Solution to the problem described in: https://embracethered.com/blog/posts/2025/claude-abusing-net...

value: Show HN: A solution to Claude Code file exfiltration

author: aupeach


value: KernelPryanic

value:
Hello HN! After 2.5 years of development, I'm sharing Job Search Assistant (https://jsa.works) - even though I still don't feel quite ready. It's an open alpha of a job search platform that actually matches positions to your resume properly.
The problem: Major platforms like LinkedIn, Indeed, etc. have terrible search despite huge resources. Search for "senior backend engineer" and you'll get frontend internships in the top results. They optimize for engagement, not relevance.
My solution: JSA uses LLMs for resume/job parsing and semantic vector search for matching. Upload your resume, set filters, get jobs that actually fit your profile. Clean interface, no noise. Only fresh jobs (15-day retention) to avoid stale listings for now. Freemium model - essential search/filters are free with reasonable limits, paid tier adds kanban-style application tracking.
Tech stack: ~78k lines of Go backend organized as microservices (scraper, indexer, searcher, etc.) communicating via NATS. Qdrant for vector search, PostgreSQL for relational data. HTMX frontend (shoutout to my friend @romshark who introduced me to HTMX - I'm not a frontend expert, so this is where AI agents helped to finish it). Scraping with go-rod. Self-hosted on a mini-PC in my utility room with scrapers running on Raspberry Pi - no cloud, just bare metal. Only SSO via Google/Microsoft for now.
The scraping challenge: Modern job boards have sophisticated anti-bot measures. I built a simple deterministic fingerprint generator (https://github.com/chinese-room-solutions/fakebro) using Wave Function Collapse-like generation to create coherent browser profiles from a seed - matching user agents, Client Hints, and WebGL renderers that correspond to real hardware. The platform scraper rotates Chrome versions with unique fingerprints and handles Cloudflare challenges.
Current status: Amsterdam and Paris only (data collection is expensive). If there's demand, I'll expand to EU and beyond. I'm using it myself right now to job hunt in those cities.
Open alpha means bugs are expected, but I'm actively improving stability. The codebase is mostly pre-2025 human-written code, though AI agents helped me push through to completion in late 2025 after I went through the literal hell, mentally, and managed to stay alive and almost recover by the end the year.
Fun story: Google suspended the project's GCP account citing "policy violations" with zero details or successful appeals, so I'm running Google SSO from my personal account for now. Classic cloud provider experience these days.
Would love feedback, especially from folks in Amsterdam/Paris who could use this!

value: Show HN: Spent 2.5 years building better job search (now using it to find a job)

author: KernelPryanic


value: Mirofts

value:
Hello HN,
I'm Benoit, a CEO based in Kyoto. I built ClientsOK because I was frustrated with the current state of e-signatures. I needed to timestamp and secure IP/contracts frequently, but existing solutions like DocuSign were either too expensive ($45/mo for features I barely use) or lacked true forensic permanence (if the platform dies, the proof often dies with it).
ClientsOK is my attempt to solve this with a "forensic-first" approach.
The Architecture: Instead of just placing an image of a signature on a PDF, we treat the document as a digital evidence package:
Fingerprinting: We generate a SHA-256 hash of the final document.
Context Capture: We record 14 points of metadata during the signing event (IP geolocation, precise timestamp, device info, browser fingerprint).
Anchoring: We anchor the hash on the Bitcoin blockchain. This ensures that the proof of existence and integrity is verifiable independently of my startup, forever.
Legal & Compliance: The generated certificates are compliant with eIDAS (EU) and the E-SIGN Act (US).
Pricing: We offer a free tier (1 doc/month, 2MB limit) to let people test the tech. The Pro plan is $9/mo (vs ~$45 for competitors). There is also a public API for developers to automate certification ($0.50/doc).
I'd love your feedback on the signing flow and the technical approach to the audit trail.
Thanks!

value: Show HN: ClientsOK – Forensic e-signature anchored on Bitcoin (eIDAS compliant)

author: Mirofts


value: elevenapril

value: Show HN: SkillRisk – Free security analyzer for AI agent skills

author: elevenapril


value:
Hi HN,
I’ve been working on SEO and content-heavy sites for a while, and one problem I kept running into was that ChatGPT outputs were too unstructured to be used directly by writers or editors.
So I built DeepSeeds – a small tool that generates structured SEO content briefs and content refresh plans, including:
- Search intent breakdown
- Suggested H1–H3 structure
- Key talking points per section
- Optimization ideas for existing content
It’s not meant to replace writers, but to reduce the time spent turning vague ideas into usable briefs.
This is still early, and I’d really appreciate feedback from people who’ve worked with SEO or content workflows.

value: Show HN: DeepSeeds – An AI tool that generates structured SEO content briefs


value: aakast

value: Show HN: Skills Manager for Your Coding Agent

author: aakast


value:
Hi HN,
I’m a frontend engineer based in Korea, and like many of you, I’ve always dreamed of building and running my own micro-business. Today, I’m excited to share a project I built to capture the humor and struggles of our industry: Grow Developer (https://devgrow.co.kr).
### The Backstory
The idea came to me during the 2025 year-end holidays. I’ve always enjoyed mobile clicker/idle games and wondered how that "growth" mechanic would feel if applied to a software engineer's career. I wanted to create something lighthearted that colleagues could keep open in a browser tab to smile at while they work.
### How it Works
You start as a junior developer manually clicking the monitor to generate "code". As you progress, you automate your workflow, scale your services, and eventually aim for an 'Exit' to earn stock options. These options provide permanent buffs for your next "playthrough," allowing for a prestige-style progression. The game is packed with memes and situations that anyone who has dealt with production deployments will recognize.
Cross-device sync: If you log in with GitHub, your progress follows you between mobile and desktop.
### Technical Stack & Lessons Learned
I built this in about a week using a modern web stack:
- Framework: Next.js (deployed on Vercel)
- Database & Auth: Supabase
- ORM: Prisma
- UI: shadcn/ui
- IDE/Design: Antigravity
The most interesting part of this journey wasn't the build, but the launch. Shortly after sharing it in Korea, the site hit 2,000 concurrent users in a single day. I quickly blew through the limits of the Vercel Hobby plan and had to upgrade to Pro on the spot to keep the service alive.
I also ran into a major bottleneck with Supabase and Prisma. I realized too late that I had left a database update query inside a loop, causing a massive spike in Supabase resource usage. It was a classic "N+1" style mistake that became painfully visible under load. I had to rush an optimization patch to stabilize the service, which was a stressful but incredibly valuable lesson in infrastructure scaling.
I’d love to hear your thoughts on the game balance or any technical questions you might have about the setup.
Thanks for checking it out!
https://devgrow.co.kr

value: Show HN: Grow Developer – An idle web game about the journey to a startup 'Exit'


value: sebrindom

value: Show HN: Claude Code plugin for ecommerce development

author: sebrindom


value: selmetwa

value:
Arabic learning materials often slow you down by requiring constant page-flipping to look up translations and transliterations.
I’m building an open-source platform that fixes this with interactive parallel texts. You can click or highlight any Arabic word to instantly see its meaning, transliteration, and grammar notes in context, as well as compare across multiple different dialects.
The core idea is context-based learning. As you read, you can save any word to your study list or import vocab from CSV. You can also pull from a 20k-word bank across four dialects or generate your own lists using AI.
Once you have a set of words, the platform can create stories, lessons, and sentences that use only the vocabulary you are currently studying. This makes every piece of content reinforce exactly what you are learning while helping you get a natural feel for grammar and sentence structure. A spaced repetition system ties it all together.
If you are interested in Arabic, dialects, or open-source language tools, I would love your feedback.

value: Show HN: I'm building an open source platform for learning Arabic dialects

author: selmetwa


value: itskyedo

value:
Since early December, I've been working on Typestone as a fun side project. I wanted to see how I would go about creating my own validation library that aims at providing strong type safety while also balancing a developer experience that's simple and productive.
It started just as an itch but I've grown to be really invested in improving it and making it suitable for real-world projects. It's very pre-alpha with many bugs and missing features, but I figured I should start prioritizing building it in public and getting some feedback on the API.
Any feedback would be greatly appreciated.

value: Show HN: Typestone – A TypeScript validation library with strong type safety

author: itskyedo


value: toutoulliou

value:
After several months of coding, I built a free football prediction platform that aggregates and displays match predictions, live scores, and detailed statistics.
What you'll find on the site:
- Live matches with real-time scores and status updates
- Upcoming matches organized by date with 1X2 predictions (home/draw/away probabilities)
- Predicted scores and odds for each match
- Detailed match pages with comprehensive statistics
- Team and league pages with historical data and rankings
- Search functionality to find teams and leagues quickly
- Filters for high-odds and low-odds matches
- Daily predictions organized by yesterday, today, and tomorrow
The platform updates automatically throughout the day. All predictions include probability percentages, expected scores, and betting odds. The interface is clean and mobile-responsive.
Built with Django, Python, and Tailwind CSS. The backend uses Celery for scheduled tasks and Redis for caching.
I'd love to get feedback on the UI/UX and any features you'd like to see added.

value: Show HN: I built a free football prediction platform with live matches and stats

author: toutoulliou


value: dubovetzky

value: Show HN: Create AI UGC Ads in 3 clicks

author: dubovetzky

title: Show HN: Create AI UGC Ads in 3 clicks


value: vishnukool

value:
I wanted startup advice that was actually grounded in real YC content, not generic ChatGPT responses. So I scraped and transcribed the YC Library and built an AI advisor on top of it.
What's in there:
  - Paul Graham's essays
  - YC founder interviews
  - Startup School lectures
  - Various YC partner talks
434 resources total, all indexed and searchable as a skill via natural language.
The skill is open source: https://github.com/Agent-3-7/agent37-skills-collection
Built as a Claude Skill on Agent37 (a platform marketplace for hosting AI skills).

value: Show HN: YC Advisor – AI grounded in 434 YC essays, interviews, and lectures

author: vishnukool


value: valhalladev

value: I got tired of Claude being wicked smart but only being able to access out-of-date information that isn't super pertinent to my research. So I'm building a way to give everything from Claude Code to the base Opus models access to your favorite tweets, video transcripts, research articles and more.<p>This is a solid v0.1 for ScrollWise AI. I'll be working hard on PDF uploads, YouTube video transcript extraction and more coming up next. The ultimate goal is to make it work in a browser extension so you can give Claude, Gemini, and Chat GPT access to your documents on their sites, and so you can 1-button-click add a piece of content to your repository.

value: Show HN: I'm giving LLM's and agents access to all of your favorite content

author: valhalladev


value: hammadtariq

value: Show HN: Web Bot Auth SDKs (IETF Draft) for Node, Python, WordPress

author: hammadtariq


value: Show HN: You can run real PyTorch in a browser


value: cloudkj

value:
I was looking for a way to quickly overlay geo data (e.g. current snow depth https://www.fs.usda.gov/sites/nfs/files/r05/publication/R5_S...) on top of a map of points of interest, and couldn't find anything straightforward. This proof-of-concept allows for an example workflow of exporting points of interest from Google Maps (either public or your own creation) as KML files, and plotting this data against arbitrary data in GeoJSON format.
In the motivating example, the main challenge was in converting the raw snow depth data into the proper format, for which I've included some sample adapter code. Sharing this here in case anyone finds it useful for upcoming weekend trips, has recommendations for different tools to solve the same problem, or suggestions for improvement!

value: Show HN: Map of California SNO-Parks with current snow depth data

author: cloudkj


value: mlajtos

value:
Hello,
I finally pushed myself to open-source Fluent, a differentiable array-oriented language I've been building for the New Kind of Paper project [1-5]. Demo is available at [0].
Few salient features:
1. Every operator is user-(re)definable. Don't like writing assignment with `:`, change it to whatever you like. Create new and whacky operators – experiment to the death with it.
2. Differentiability. Language is suitable for machine learning tasks using gradient descent.
3. Reactivity. Values can be reactive, so down-stream values are automatically recomputed as in spreadsheet.
4. Strict left-to-right order of operations. Evaluation and reading should be the same thing.
5. Words and glyphs are interchangeable. All are just names for something. Right?
6. (Pre,In,Post)-fix. You can choose style that suits you.
It has its own IDE with live evaluation and visualization of the values. The whole thing runs in browser (prefer Chrome), it definitely has ton of bugs, will crash your browser/computer/stock portfolio, so beware.
Some bait – linear regression (Ctrl+O, "linear-regression-compressed" or [6]):

    x: (0 :: 10),

    y: (x × 0.23 + 0.47),

    θ: ~([0, 0]),

    f: { x | x × (θ_0) + (θ_1) },

    L: { μ((y - f(x)) ^ 2) },

    minimize: adam(0.03),

    losses: $([]),

    (++): concat,

    { losses(losses() ++ [minimize(L)]), } ⟳ 400,

    (losses, θ)

pre-, in-, post- fix & name/glyph equivalence:

    1 + 2,

    1 add 2,

    add(1,2),

    +(1,2),

    (1,2) . +,

    (1,2) apply add,

---
[0]: https://mlajtos.github.io/fluent/?code=RG9jdW1lbnRhdGlvbg
[1]: https://mlajtos.mu/posts/new-kind-of-paper
[2]: https://mlajtos.mu/posts/new-kind-of-paper-2
[3]: https://mlajtos.mu/posts/new-kind-of-paper-3
[4]: https://mlajtos.mu/posts/new-kind-of-paper-4
[5]: https://mlajtos.mu/posts/new-kind-of-paper-5
[6]: https://mlajtos.github.io/fluent/?code=eDogKDAgOjogMTApLAp5O...

value: Show HN: Fluent, a tiny lang for differentiable tensors and reactive programming

author: mlajtos


value: xvpdev

value:
Scrapped 2,000 lines of “working” AI pipeline code and replaced it with one agent prompt.
System got simpler, more accurate, and harder to break.
Here's everything I extrapolated from building a rebuilding a large-scale integrated AI system, and a fundamental paradigm choice when building these systems.
If you want a deep dive, you'll get one.

value: Show HN: I scrapped my working AI agent pipeline and rebuilt it (postmortem)

author: xvpdev


value: Atalocke

value: Show HN: Hacker Directory

author: Atalocke

title: Show HN: Hacker Directory


value: yuedongze

value: Show HN: This website is hallucinated by AI in real time

author: yuedongze


value: watduyuwan

value:
I was fed up with my daily language learning workflow after immigrating to Spain: Translate app → manual Anki input → separate conjugation lookups for Spanish, so I built an app to solve that problem. Meet Leka: a Lovable-built web/PWA that unifies translate → FSRS flashcards → conjugations. It currently supports Spanish (Spain/LatAm), Italian, German, French, Portuguese, and Dutch, with more easily added in the future.
Now one flow:
- Type or paste text → auto-translate + word extraction → FSRS cards
- Integrated conjugator (full verb/noun tables, e.g., ser/estar)
- Offline PWA
- FSRS algorithm similar to Anki
Coming soon:
- Different study modes
- Voice to text mode
- Image to text mode
- Image <> translation mode
https://lekalearning.com (Free with Premium upgrade available)
Thoughts on Lovable for prod PWAs?

value: Show HN: Web PWA unifying translate/FSRS Anki/conjugations

author: watduyuwan


value:
Dan Koe recently published a framework for resetting your life in a single day, based on the idea that behavior change fails because we're trying to change actions instead of identity.
I turned it into an interactive web app: https://the1dayprotocol.vercel.app
How it works:
Morning: 12 questions to excavate hidden dissatisfaction and define an "anti-vision" (the life you refuse to live)
Day: Calendar events with scheduled interrupts to break autopilot thinking
Evening: Synthesize insights into vision statements, yearly goals, and daily actions
It's entirely local – no account, no backend, nothing leaves your browser. Your answers stay on your device.
There's also an optional AI reflection feature that acts as a Socratic mirror, challenging your answers without telling you what to think.
The premise is that most self-help fails because it targets symptoms (habits, productivity) instead of the root (unconscious goals and identity). This tool forces you to sit with uncomfortable questions for an entire day.
Curious if anyone has tried similar "structured introspection" approaches – or if this just feels like a fancy journaling app.
Original Article: https://x.com/thedankoe/status/2010751592346030461

value: Show HN: The 1 Day Protocol – An app for 24-hour psychological excavation


value:
We just shipped response caching in GraphOS Router, designed specifically for federated GraphQL workloads.
The problem we were solving: traditional HTTP caching doesn't work well with GraphQL. A single response often mixes data with different freshness requirements—long-lived product info, fast-changing inventory, user-specific context. Full-response caches force the shortest TTL across everything, killing hit rates.
Our approach caches at two levels: root query fields and individual entity representations. Each entity can have its own TTL (derived from Cache-Control headers or @cacheControl directives), and entities are shared across queries and users where appropriate.
A few things that might be interesting:
Tag-based invalidation: Mark entities with @cacheTag, then invalidate by tag when data changes—similar to CDN surrogate keys but at the GraphQL entity level
Partial cache hits: A single query might hit cache for some subgraphs and miss for others; we built a debugger in Apollo Sandbox to inspect exactly what's cached
Redis-backed with cluster support
Early results from Dow Jones: 20-25% latency reduction, 8-10x decrease in traffic to some subgraphs.
Docs: https://www.apollographql.com/docs/graphos/routing/performan...
Blog: https://www.apollographql.com/blog/introducing-response-cach...

value: Show HN: GraphOS Router, designed specifically for federated GraphQL workloads


value: adrmonlj

value:
Hi HN,
I built a small web tool called Readspeed that lets you try RSVP-style reading (one word at a time) using your own text or PDFs.
There’s no signup and it runs entirely in the browser — minimal client-side processing, no backend required. I originally built it for myself after seeing a few viral RSVP demos and wanting to test the idea on real reading material (long documents, books, articles).
It’s intentionally early and minimalist:
 • Paste text, upload documents (PDF, EPUB), or read from a link
 • Adjust speed
 • Read in RSVP mode
 • Works offline in the browser
I’m curious to hear:
 • Does this actually help you read longer material faster?
 • Where does it break down (comprehension, regressions, fatigue)?
 • Do experienced readers find it useful or just a novelty?
Link: https://readspeed.app
Happy to answer questions or hear feedback.

value: Show HN: Readspeed – RSVP-style reading for your own text, PDFs, and links

author: adrmonlj


value: Show HN: Flickle – Daily Cinematography Game Built with Next.js (SSG, No DB)


value: zaizz

value:
*Show HN: StudyBuddy.rest – an AI-powered study companion for students (feedback welcome)*
Hi HN,
I’m building *StudyBuddy.rest*, an AI-powered study platform aimed at helping students study more effectively, especially during exams and last-minute prep.
The idea came from my own experience as a CS student struggling to organize notes, revise quickly, and stay consistent.
Current features include:
* AI-generated structured notes from topics or text
* Note summarization into concise bullet points
* Last-minute revision kits (overview, flashcards, MCQs, formulas, tips)
* Q&A from uploaded files or manual input with difficulty control
* Weekly AI-generated study planner
* Quizzes and basic progress tracking
Tech stack:
* Next.js (App Router)
* PostgreSQL (Neon)
* NextAuth
* Deployed on Vercel (planning AWS later)
The product is still early and evolving, and I’m trying to validate:
* Whether this actually solves real problems for students
* Which features are genuinely useful vs unnecessary
* UX issues or missing workflows
* Thoughts on pricing / subscription expectations for a student-focused SaaS
I’d really appreciate any honest feedback, criticism, or ideas.
Website: [https://studybuddy.rest](https://studybuddy.rest)
Thanks for taking a look!
— Zaid

value: Show HN: Feedback Required)StudyBuddy–an AI-powered study companion for students

author: zaizz


value: interlap

value:
Hey HN,
I wanted to share a tool I use for developing mobile apps. I’ve spent many years as an engineer at a mobile cloud startup, so I have a solid background in mobile device automation and remote control. I thought it would be useful to have a tool that lets my Claude code see what it’s doing and also how messy it sometimes looks
I’ve seen more posts recently where people complain about the lack of tools like this or are looking for testers to test their mobile apps, so I decided to polish my tool and release it as a separate app.
Currently, it works on macOS and Windows:

  - macOS: Android, iOS, emulators, simulators

  - Windows: Android, iOS, emulators

I also wrote a Claude code plugin: https://github.com/MobAI-App/mobai-marketplace
And an MCP server: https://github.com/MobAI-App/mobai-mcp
Looking forward to your feedback!

value: Show HN: MobAI – AI-first mobile automation for iOS and Android

author: interlap


value: yatvij

value:
Hi HN,
Lately Github PRs have been drowning in a flood of AI slop. I’ve been seeing it myself, and I’m not the only one: https://x.com/mitchellh/status/2011819428061855915
I think it’s great that folks are using AI tools to code faster and better, but too many folks are abusing them to make low-quality contributions to public repos. This takes a lot of reviewers’ mindshare.
IMO there needs to be a mechanism to flag low-effort PRs with AI slop, so you can just skip reading them. So I built one:
https://haystackeditor.com/slop-detector
It’s a simple AI slop detector, and I also included some AI slop examples and a “Is it Slop or Not?” game for fun.
It detects AI messups like:
- changes totally unrelated to PR purpose
- hallucinated functions
- duplicate code (specifically, when the AI re-implements a functionality that already exists elsewhere)
- terrible comments
Would you use a tool like this?

value: Show HN: Flag AI Slop in PRs

author: yatvij

title: Show HN: Flag AI Slop in PRs


value: avicted

value:
I've been iterating on a small galaxy visualization project that originally started as a university course assignment, using only provided sample data (no real astronomical distances).
Recently, I updated it to include redshift-based distance data, which makes the 3D structure more meaningful and closer to real large-scale galaxy distributions.
Repo:
https://github.com/Avicted/galaxy_visualization_raylib
Demo video (3D navigation + galaxy structures):
https://www.youtube.com/watch?v=fC83RDWuPvw
Current state:
- Written in C (C99 standard) using Raylib
- Realtime 3D visualization with free camera movement
- Uses redshift values to approximate distances
- Cross-compiled builds via mingw64 (Linux & Windows releases on GitHub)
Still very much a learning / exploration project
There's plenty that could be improved (accuracy, performance, interaction, visuals), but I figured I'd share the update in case it's interesting or sparks suggestions.
Happy to hear feedback or pointers to better approaches or datasets. Thanks!

value: Show HN: Galaxy visualization using Redshift data (Raylib, C)

author: avicted


value: hermannbjorgvin

value: Show HN: CC TV remote plugin, pauses your binge-watching when Claude goes idle

author: hermannbjorgvin


value: AgintAI

value:
Hi HN — I’m Abhi.
We built Agint so PMs and engineers can design and edit software as a graph — architecture first — iterate with fast visual feedback, then generate deployable code from it when it’s ready.
We presented underlying approach at NeurIPS (Deep Learning for Codegen) as an Agentic Graph Compiler:
The graph (structure + types + semantic annotations) is the source of truth, and code is a compilation/export target.
Paper:
Agentic Graph Compilation for Software Engineering Agents:
https://arxiv.org/abs/2511.19635
Live Demo:
https://flow.agintai.com
(The demo runs in sandbox mode -- no real external tools/data sources wired yet. It creates repos @ github.com/AgintHub)
CLI:
https://github.com/AgintAI/agint-cli
How it works:
Type in the chat to modify the graph (or use the “+” menu for specific actions).
1) Create/Compose: (chat + live graph feedback) design and modify algorithmic flow + schema graphs:

   Add, remove, split, merge, and rename steps, via chat

    "Fetch stock data from the NYSE and NASDAQ"

    "Also include the Toronto Stock Exchange"

    "Add the LSE as well"

2) Refine/Upgrade (engineering-facing, GUI + CLI / git-friendly graph edits):
   Add types, semantic annotations, restructure, reorganize nodes, transform, execute, and test behavior
    "Break the combine step into storage, normalization, and repartitioning"

   On the CLI it can look like:

    dagify refine workflow.yaml \
       "add protocol-level details, latencies, and datacenter info for each feed" --intelligence 5

    dagify resolve workflow.yaml --yaml-display --ascii

3) Save/Load/Export:
    “Save” exports the graph into ordinary code, pipelines, tool calls, and APIs that can be owned and deployed like any other system.
     The graph is an executable artifact, not just documentation.
     Targets include native Python today, plus exports to frameworks like CrewAI/LangGraph.
Example output repo:
https://github.com/AgintHub/dreamy-mirzakhani/blob/agint/out...
Would love reactions and feedback — I’ll be around to answer questions.
Thanks,
Abhi
Abhi@AgintAI.com

value: Show HN: Agint Flow – design software as a graph, then compile the graph to code

author: AgintAI


value: bytefish

value: I’ve been working on an example application for routing with OSM data. The repository makes it easy to experiment with the implementation. The Angular Frontend, uses maplibre-gl for displaying the map and visualizing the routes.

value: Show HN: Routing with OSM, PgRouting and MapLibre

author: bytefish


value: deere-sdk

value:
John Deere has a developer API for their Operations Center (field data, equipment telemetry, machine locations, etc.) but no official SDK. I needed it for a project, so I built one and open-sourced it.
28 APIs, 123 operations, fully typed, auto-pagination, HAL support, automatic retries. Generated from their OpenAPI specs with daily health checks.
https://github.com/ProductOfAmerica/deere-sdk

value: Show HN: Open-Source TypeScript SDK for John Deere's Agricultural APIs

author: deere-sdk


value: JasonpDev

value: Instantly create GPU instances over SSH. Instances boot a custom image with PyTorch, Jupyter, and the CUDA toolkit installed by default.

value: Show HN: Gpu.st – GPU over SSH

author: JasonpDev

title: Show HN: Gpu.st – GPU over SSH


value: NightBlossom

value: "If the system does not see you, become the one who defines the system."

value: Show HN: Universe University Entrance Exam

author: NightBlossom


value: mitjafelicijan

value:
I was messing around with LLVM and LLDB over the week and made this little toy debugger. It's messy, but I actually got something working. I have been testing my stuff and found it kind of pleasant to use.
This is not intended to be some competitor with other debuggers, but it could become a nice, quick to use thing.
There is a video on github where you can see how it works.
Would love to hear what you guys think.

value: Show HN: Tiny Toy Debugger

author: mitjafelicijan

title: Show HN: Tiny Toy Debugger


value: agentifysh

value:
After you install it, codex will start speaking after a turn by summarizing what it did. It intelligently skips over large block of codes and tries some cleverness.
You can change the voice, volume, speed from the tool bar.
https://github.com/agentify-sh/speak

value: Show HN: Agentify Speak: Make Codex Speak After a Turn (Mac)

author: agentifysh


value: livrasand

value:
gitGost allows anonymous contributions to public GitHub repositories.
It removes author info, email, timestamps, and opens PRs from a neutral bot.
No accounts, OAuth, or tokens required.
Built in Go, open source (AGPL-3.0), with abuse prevention via rate limits and validation.
Feedback welcome.

value: Show HN: Contribute to GitHub Anonymously

author: livrasand


value: captures

value:
I use Detexify (https://detexify.kirelabs.org/classify.html) a bunch when writing in LaTeX, which lets you draw a symbol and gives you the LaTeX command. But it's quite slow - it takes ~2s to load the page and ~1s to classify each symbol.
So I made a faster version using Rust and WASM, running entirely in browser. This cuts the classification time down to ~7ms - fast enough to run on every mouse move, giving you live predictions as you draw.

value: Show HN: Fast handwritten LaTeX symbol recognition (Rust/WASM)

author: captures


value: kanodiaayush

value:
Deep research rarely happens in a single pass. For high-stakes work, or to deeply understand something, you run many deep researches in parallel, revisit them over time, and synthesize understanding gradually. We combine deep research with other docs.
Kerns is built for this mode of research.
It groups multiple deep researches under a single research area, so follow-ups and side investigations accumulate instead of fragmenting across chats and docs. Outputs are structured so you can start shallow and selectively go deep—because you don’t know upfront which deep researches will matter.
Synthesis is an explicit second step. Kerns helps you connect and reconcile insights across deep researches, grounded in the sourced material rather than one-off summaries. This stage also lets you consult other docs on the same level as deep researches.
Research doesn’t stop once a report is written. Kerns passively keeps your work up to date by monitoring sources and surfacing meaningful changes, so staying current doesn’t require restarting.
Built for researchers, analysts, investors, and serious self-learners doing multi-week or multi-month research where clarity and correctness actually matter.
Would love feedback!

value: Show HN: Kerns – A Workspace for Deep, Ongoing Research

author: kanodiaayush


value: ramoz

value:
https://github.com/backnotprop/plannotator
OpenCode as well

value: Show HN: Claude Code Plan Mode Plugin

author: ramoz

title: Show HN: Claude Code Plan Mode Plugin


value: modinfo

value: Show HN: You're reading this, which means the story has begun

author: modinfo


value: kxbnb

value: Show HN: toran – a read-only outbound API inspector

author: kxbnb


value: Show HN: Drako is a customizable Command-Deck Launcher. Likely first of its kind


value: cmarschner

value: My New Year's side project - a functional data structure library for Python, written in C++. Lock-free, immutable, quite fast.

value: Show HN: Pypersistent – Functional Data Structures for Python

author: cmarschner


value: missionsquad

value:
Hey HN,
I just launched Atomic Stream: 16 live websocket feeds for Solana data – mempool txs, new blocks/slots, account updates, token prices, Jupiter swaps/perps, trending tokens, liquidity changes, etc.
The twist is true pay-as-you-go via x402 (Coinbase's HTTP 402 protocol). No subscriptions, no accounts – you buy 5-minute time slices for a few cents up to ~$3 (mempool is the firehose, so priciest). Hit the schema endpoint, get the WS URL + exact USDC quote, pay on-chain, and the JSON stream unlocks instantly.
Docs on the flow: https://docs.atomicstream.net/x402/overview
Protocol background: https://www.coinbase.com/developer-platform/products/x402
TypeScript examples that handle auto-payment + renewal: https://github.com/mntgmry-tech/atomic-stream-examples
Main site (stream list + pricing): https://atomicstream.net
All streams: https://atomicstream.net/streams
Some quick things this makes easy:
Wallet/account monitoring for instant alerts
Mempool streaming for bots (arbitrage, sniping, etc.)
Live Jupiter swap/perp fills or price feeds for dashboards
Temporary trending/liquidity trackers without running your own node
Looking for early feedback – first 10 people who try it and share thoughts/bugs/ideas, I'll refund up to $20 worth of slices (just DM me on X @missionsquadai or reply here).
Curious what people think about micropayments for infra like this. Anyone else playing with x402?

value: Show HN: Atomic Stream – pay-as-you-go real-time Solana data streams (x402)

author: missionsquad


value: kyoungsookim

value:
I built a multi-agent system on top of Claude Code.

  13 agents, 5-phase workflow, auto-retry until done.

  Just shipped v2.0.0 with proper docs and cleanup.

value: Show HN: Vibe-Claude – Multi-agent orchestration for Claude Code

author: kyoungsookim


value: syketdas

value:
Hi HN,
I’m the founder of ReliaBuilds. We work primarily with startups and small companies that want strong engineering foundations from day one.
We help teams build systems that are fast, scalable, and secure — not just quickly shipped. Our core work includes:
High-performance web applications (React / Next.js)
Mobile apps (React Native / Flutter)
Cloud architecture, infrastructure, and DevOps
AI and automation for real business workflows
Security audits, penetration testing, and secure system design
Our guiding principle is “Built to Last. Reliably.” We focus on performance, solid architecture, and long-term maintainability so growing companies don’t have to rewrite everything later.
If you’re a founder or early-stage team looking for a technical partner rather than a traditional outsourcing shop, you can learn more on the site.

value: Show HN: ReliaBuilds – web, mobile, cloud, AI, and security for startups

author: syketdas


value: erenkaradag

value:
Hi HN, we built Vitalify.ai -started months before both ChatGPT and Claude Health announcements- because managing health data is fragmented and overwhelming.
Here's a video of the product: https://www.youtube.com/watch?v=LLI_1xB22rc
You upload your lab results, add your conditions/medications, and Vitalify generates a personalized wellness plan with daily tasks in your calendar.
While the value proposition might seem similar to others, we took a different approach with our UX. Instead of just a chat interface, we built a structured system with actionable plans, calendar, gamified goals, streaks and etc...
Data is encrypted at rest and isolated per user. No data is used to train any models. You have full ownership to export or delete your records at any time.
If you're not comfortable with how big health AIs handles your data, or don't want to wait on their waitlist/country restrictions, our early access is open.
Happy to answer questions and feedback is super welcome!

value: Show HN: AI health agent that nags you on WhatsApp instead of a dashboard

author: erenkaradag


value: bouchardio

value:
Hi HN,
my name is Eric, I am from Canada. I love technology, but for a long time now, I feel disrespected by technology.
Specifically smartphones and social media. Social media is built to keep you glued to your phone. Smartphones also have too many distractions, it's constantly spying on you (getting ads that are way too specific) and they are difficult to repair / they discourage you from doing it yourself (which voids warranties).
Social media can be used for great things (posting for your business, researching, learning, spreading a good message or educational content) but most of the time, it's used improperly.
My business has been around for a while, mostly making SaaS products, utility apps and mobile games. (I know, games are distracting, but I still believe they are better for you than doom scrolling) But last summer, I sat down and reflected on my core values. One of them was to make a positive impact and I looked at all the problems I saw in the world that I had noted down, this was one of them.
Mental health is impacted by social media, the subconscious comparison, unrealistic beauty standards, the amount of brain rot is mind blowing, reduced attention span, the time we waste, the irony that you are supposed to be more connected, but we have never been more isolated, the list goes on.
I had the idea for a few years to make this phone. I hired a few guys and we built a prototype. We worked hard from Q3-Q4 of 2025 and it was ready right before I went to exhibit it at Vegas for CES 2026.
The phone that we built is called The Basic Phone. It's a phone in between a smartphone and a dumbphone, but heavily leaning towards a dumbphone.
It runs Linux, on super low end hardware. This is on purpose. It's more private than Android, and it makes it next to impossible to install anything on it (because it's low end). It's even difficult for us to design apps for it! It has an e-paper display, black and white. Which makes it boring to use. Since it's slow to type on epaper, we included a keyboard.
All our code will be open source, showing that we don't track anything.
The phone will be fully modular, making it easy to repair or replace parts.
It has all the basic functionalities, calling, texting, gps, notes, alarm, weather, calculator, camera, e-reader, calendar, music, etc.
We will also have crucial missing features that most dumbphones don't have: two factor authentication app, ride sharing, banking, email, etc.
We will also have a limited web browser that runs on our own hosted cloud servers, or your own depending on how you want to set it up. This browser will block all malicious sites as well as distracting ones like fb, tiktok etc.
With that technology, we will be able to have popular messaging apps like: WhatsApp, Discord, Messenger etc. We believe you should be able to communicate using any kind of platform. It's the feeds that are the problem.
I believe this is just the right balance of utility. A phone should be a tool, not a distraction. It shouldn't hold you back either by not having all that you need.
With this technology, it would be great for anyone who has discipline issues, high performing individuals that want to achieve more in life or for parents that are worried their kids will just install any apk's.
I believe we had a better balance in the past. A dedicated computer at home, but when you left your house, you were more present in the moment.

value: Show HN: I made a phone in between a smartphone and dumbphone

author: bouchardio


value:
Hi HN, I built https://paintracker.ca. It is an offline first, privacy first PWA for tracking chronic pain and related symptoms.
I made it because on bad days you do not want a whole app. You want something that opens fast, lets you log in a few taps, works even if you are offline, and does not force you into an account just to start.
A lot of tracking apps assume cloud accounts and constant connectivity. I wanted something that still works when you are exhausted, in pain, or traveling without reliable internet, and does not turn health data into default telemetry.
What it does
Quick logging for pain and symptoms, with optional context like sleep, triggers, meds, and notes
Installable PWA that works offline and stores data locally by default
Exports are available in CSV, JSON, PDF, and FHIR, and what is available may vary by plan
Optional paid tier for advanced features, but I am trying to keep the free core tracker genuinely useful
Privacy stance (high level)
Core tracking is local first on device. Optional features like weather correlation and subscriptions make network calls only when you enable or use them.
Optional analytics is opt in, disabled unless explicitly enabled and consented.
Data minimization, the app tries not to collect anything you do not explicitly use
Who it is for and who it is not for
For chronic pain, injury recovery, flare tracking, appointment prep, and keeping a clean history you can reference
Not for diagnosis, emergency use, or anything that replaces clinical judgment
Links
App https://paintracker.ca
Blog and docs https://blog.paintracker.ca
Feedback I would love (blunt is fine)
1) If you have used trackers before, does the daily logging flow feel lightweight enough when you feel awful? Where does it drag?
2) Are the exports actually usable for clinicians or insurers, or would you want a different shape like a timeline, SOAP style, summaries, or graphs?
CrisisCore Systems

value: Show HN: Paintracker.ca, a PWA pain tracker that keeps data on device by default


value: justvugg

value:
We’ve integrated Ollama into Polymcp to simplify local and cloud-based execution of large language models like gpt-oss:120b, Kimi K2, and Nemotron.
With Ollama as an agent, we can easily orchestrate MCP servers and manage models in a seamless, straightforward way.
Here’s a quick example:
from polymcp.polyagent import PolyAgent, OllamaProvider
def main():
    agent = PolyAgent(llm_provider=OllamaProvider(model="gpt-oss:120b"), mcp_servers=["http://localhost:8000/mcp"])
    response = agent.run("What is the capital of France?")
    print(response)
if __name__ == "__main__":
    main()
Why this is useful:
 • Orchestration made easy: Ollama handles the complexity of orchestrating MCP servers and models.
 • Local & cloud execution: Switch between local and cloud environments with no extra setup.
 • Multiple models supported: From gpt-oss:120b to Kimi K2, run the models you need.
It’s a quick way to streamline model execution in your projects, whether on your own hardware or in the cloud.
Looking forward to hearing how you use this!
Repo: https://github.com/poly-mcp/Polymcp

value: Show HN: Polymcp Implements Ollama for Local and Cloud Model Execution

author: justvugg


value: exprtk

value: Show HN: ExprTk High-Performance C++ Math Expression Parser Evaluation Engine

author: exprtk


value: LBWasserman

value: Would like feedback...

value: Show HN: Neurop Forge: Live Demo /Real AI Action

author: LBWasserman

story_text: Would like feedback...


value: ededft

value:
Hi HN,
I built IncidentPost (https://incidentpost.vect.pro) to solve a simple but recurring problem:
writing clear, public incident postmortems without standing up a full status page or internal tooling.
Many teams want to be transparent after outages, but tools like Statuspage or custom Notion/GDocs either feel too heavy or aren’t meant for public sharing.
IncidentPost focuses on one thing:
writing and publishing clean, public incident reports
with a simple, structured format (timeline, impact, root cause, resolution, prevention)
accessible via a single public URL
It’s intentionally minimal:
no accounts required to read
no complex workflows
no vendor lock-in mindset
The goal is to make postmortems easier to publish, not harder.
This is early-stage and feedback-driven.
I’d really appreciate thoughts from engineers, SREs, or founders who’ve written incident reports in the past:
What’s missing?
What feels unnecessary?
Would you use something like this?
Thanks for reading.

value: Show HN: IncidentPost – Write public incident postmortems without heavy tooling

author: ededft


value:
I built Super AI Markets (https://superaimarkets.com) to test how AI shopping agents handle adversarial e-commerce environments. With agents increasingly handling financial transactions, we need systematic security research before widespread deployment.
The core problem: agentic browsers don't identify themselves. Without vendor/model information, comparative security analysis across different implementations is nearly impossible.
My solution is an "AI Agent" identification standard similar to HTTP user agents:
AI-Agent: <vendor>/<model> (<application>; <version>) [<framework>] {<tools>}
Early strings I've collected:
AI-Agent: Anthropic/Claude (Claude Haiku 4.5; 2026-01) [Web Automation] {read_page, find, computer, navigate}
AI-Agent: OpenAI/ChatGPT (ChatGPTBrowser; 1.0) [] {browser, computer}
AI-Agent: Perplexity/OpenAI-GPT-4.1 (Perplexity Web; 2026.01) [Hosted] {WebSearch,Memory,CodeExec}
Research questions being tested:
Product manipulation (can agents be convinced to buy expensive alternatives?)
Predatory payment terms acceptance
Multimodal prompt injection effectiveness
Malicious chatbot exploitation vectors
Data extraction from agents
Cross-product AI fingerprinting consistency
The site is publicly accessible for testing. No payment/sensitive data collected.
Open to suggestions for additional experiments.

value: Show HN: Super AI Markets – Testing Ground for AI Shopping Agent Security


value: krzyzanowskim

value:
Hi HN, I built Commander, a UI for running multiple AI coding agents in parallel without living in terminal hell.
As coding agents got better, I started trusting them with real work: features, end-to-end, refactors, tests. Naturally, I began running 1–3 at once. That’s when the CLI stopped scaling — too many terminals, lost context, scattered diffs.
Commander fixes that.

value: Show HN: Commander AI – Mac UI for Claude Code

author: krzyzanowskim


value: gezginweb

value:
Hey HN,
I'm part of the team at WPTR. We’ve spent the last few months building a platform to solve a problem that’s been bothering our lead developer (who has been in the SEO/hosting industry since 1999) for a long time: the total lack of 'proof' in hosting recommendations.
The Problem: Most 'Best Hosting' lists are just affiliate plays with no technical verification.
Our Solution: We built WptrnetSpeedBot and a 'Science of Trust' protocol. Our philosophy is simple: Evidence-based. If a provider claims to be an expert in Next.js or Laravel hosting, our bot checks if they actually use that tech for their own site. If they don't 'dogfood' their own expertise, they don't get on our list.
What we built:
Automated Audits: Real-load testing instead of empty promises.
Headless Focus: A hub for transforming traditional WP to Next.js.
The Real-Load Score™: A metric based on actual performance data, not marketing fluff.
We are a small team and we are trying to bring some academic rigor to a very 'noisy' industry. We’d love to get your technical feedback on our audit methodology and the bot's logic.
Thanks for checking it out!

value: Show HN: WPTR – We built an automated audit lab for Headless WordPress

author: gezginweb


value: sumeruchat

value:
Hey HN,
I've been using Claude Code across multiple repos and machines, and managing the config got messy fast—scattered .mcp.json files, duplicated slash commands, credentials in random places.
So I built claude-config: a simple framework to centralize and version control your Claude Code setup, the same way we do traditional dotfiles.
One bootstrap.sh, one config file. It symlinks commands, sets up MCP servers per-repo, handles credentials, and keeps everything in sync across machines.
GitHub: https://github.com/sumchattering/claude-config
Would love feedback, especially if you're managing Claude Code across multiple projects.
Cheers
Sumeru

value: Show HN: Claude-Config – Dotfiles for Claude Code

author: sumeruchat


value: Show HN: Adsly – a marketplace for direct sponsorships and partnerships


value: APMikeDotNet

value: Show HN: AgoraPages – A Collaborative Website Builder

author: APMikeDotNet


value: misprice

value:
What it does: “Collects Polymarket price snapshots every 5 minutes + resolution outcomes”
Who it’s for: “bot builders / researchers who don’t want scrapers”
Links:
sample CSV: https://data.misprice.app/samples/sample_prices_7day.csv
docs: https://data.misprice.app/docs
pricing page: https://data.misprice.app/data.html
Ask: “What endpoints/data formats would make this most useful?”

value: Show HN: Polymarket historical prices and resolution labels (5 min snapshots)

author: misprice


value: bytefish

value: I often want to quickly draw a state machine diagram to visualize my application state transitions. Full-blown solutions like draw.io make it hard to get all arrows and labels aligned nicely, so I wrote a very stripped down application to do it.<p>You can save, load and export your diagrams. Nothing is stored on a server, and localstorage is used to persist the state between page refreshes.

value: Show HN: Designing State Machines

author: bytefish

title: Show HN: Designing State Machines


value: loffloff

value:
I built a React hook that makes it easy to add real-time AI conversations with screen sharing to any app.
GitHub: https://github.com/loffloff/gemini-live-react
What it does:
- Stream mic audio to Gemini, get voice responses back
- Share your screen so AI can see what you're doing
- Real-time transcripts for both sides
- Tool calling support
Just added: useCapturedSurfaceControl hook for Chrome 124+ that lets you programmatically scroll/zoom a captured tab without injecting scripts.
Built this for deflectionrate.com (AI support that resolves issues before they become tickets), extracted the core into this package.
npm install gemini-live-react
Happy to answer questions.
Want me to tweak anything?

value: Show HN: React hook for Gemini Live API – real-time voice and screen sharing

author: loffloff


value: deklesen

value:
Something I built out of personal necessity.
Now that more and more people are rightfully leaving Spotify, I was searching for a simple way to prepend a url to any Spotify/Deezer/Tidal/AppleMusic link and get a universal link which allows visitors to navigate to that track/album/artist on their platform of choice.
I found song.link, but it takes >5 seconds to load, even on popular songs.
So instead, I built earworm.lol - its blazing fast (<1s, even for new links).
I also wrote a blog post about it if you want to learn more about how its built (spoiler, Cloudflare): https://blog.jonas-klesen.de/earworm

value: Show HN: Earworm.lol – fast universal music links

author: deklesen


value: ededft

value:
Hi HN,
I built IncidentPost (https://incidentpost.vect.pro
) to help engineers and SREs ship clear, public incident postmortems without heavy internal tooling or manual writing stress. Many teams struggle to format timelines, summarize root causes, and produce shareable reports after outages — especially under time pressure.
What it does:
Paste a raw timeline (Slack logs, timestamps, alerts)
Generates a structured report with executive summary, root cause analysis, timeline, mitigations, and action items
Produces a public URL, Markdown/HN post draft, and Twitter thread you can publish instantly
No accounts or complex onboarding to read public reports — minimal barriers for transparency
Why this matters:
Public postmortems improve trust and engineering processes
Automates hours of writing into minutes
Keeps focus on incident resolution, not documentation
It’s early, feedback-driven, and intentionally minimal. I’d really appreciate thoughts from engineers, SREs, or founders who deal with reliability and postmortems:
What’s missing? What feels necessary? Would you use something like this?

value: Show HN: IncidentPost – AI-generated incident postmortems with minimal tooling


value: sntedo

value:
Hi HN,
I just released "Explain Yourself," a local multiplayer party game (Jackbox style) where players have to give excuses for absurd AI-generated scenarios. An AI Judge then ranks the answers, roasts the players, and determines a winner.
I built this because I wanted an AI-first party app game that was fun and made people use their brains. This is my first app, but I have spent months on it and it is pretty thoroughly thought out.
The Stack:
Frontend:
SwiftUI (using NavigationStack and EnvironmentObjects for state).
Backend:
Firebase (Firestore for real-time syncing, Cloud Functions for the game logic).
AI: Gemini API (via Cloud Functions) for both generating scenarios and the "Judge" persona.
The Technical Challenges:
Prompt Engineering:
Tuning the "Judge" to be fun and a bit savage was a fun part. I also expected Gemini (which  I ended up choosing for simplicity over other AIs) to not respond to many of the players answers if completely inappropriate, but it always does... so far.
The judge analyzes the answers and decided which was the most logical with a bit of creativity. The game scores 90% of one and 10% on the other to determine the ranking.
Monetization:
It’s free to play with a daily limit/starter rounds. I hate ads, so I limited them strictly to "watch to earn" if you run out of credits, plus a standard IAP model for specific question packs. I wonder if starting out I should simply give out everything for free though, leaving only a couple of things like the custom categories as the locked IAP part. Would love some insight on that if you got any.
I’d love feedback on the latency of the app in general, the quality of the AI responses, and the IAP model most of all. Means the world. Thank you in advance.
Link: https://apps.apple.com/app/id6748743734

value: Show HN: Explain Yourself – An AI party game app built with SwiftUI

author: sntedo


value: reflectivetrap

value:
Hey HN!
My name is Omkar Kovvali and I've been wanting to share my CC sessions with friends / save + access them easily,so I decided to make an MCP server to do so!
/share -> Get a link /import -> resume a conversation in your Claude Code
All shared sessions are automatically sanitized, removing api keys, tokens, and secrets.
Give it a try following the Github/npm instructions linked below - would love feedback!
https://github.com/OmkarKovvali/claude-session-share
https://www.npmjs.com/package/claude-session-share

value: Show HN: Making Claude Code sessions link-shareable

author: reflectivetrap


value: snasan

value:
Hey HN,
With Anthropic's Claude Cowork launch, there's renewed interest in agentic AI. Cowork is impressive for single-agent file management — but we've been working on a different problem: what happens when you connect multiple agents into a network?
OpenAgents is open-source infrastructure for building AI agent networks. Think of it as the plumbing for multi-agent collaboration.
Core ideas:
- Agents join networks and discover peers dynamically
- Protocol-agnostic: WebSocket, gRPC, HTTP, libp2p
- Shared artifacts (files, knowledge bases) with access control
- Works with any LLM provider (Claude, GPT, open-source models)
- Mod-driven architecture for different collaboration patterns
We're releasing an "Agent Coworking" template with examples:
- Chat room with 2 Claude Code agents collaborating
- Research team (coding agent + web browsing agent)
- Shared document editing across agents
The SDK is Python-based. Spin up a network with openagents network start and connect agents via YAML config or custom Python.
GitHub: https://github.com/openagents-org/openagents
Tutorial: https://openagents.org/showcase/agent-coworking
Would love feedback from HN. Particularly interested in thoughts on:
1. Network topology patterns that would be useful
2. Security considerations for agent-to-agent communication
3. Integration with existing agent frameworks (LangChain, CrewAI, etc.)
Happy to answer questions.

value: Show HN: Agent Coworking,Multi-agent networks for AI collaboration (open source)

author: snasan


value: Yinp

value: Show HN: Humanizer AI: Humanize AI Text in Your Own Voice – Creaibo

author: Yinp


value: e-clinton

value: Show HN: An opinionated fork of micro, built for vibe coders who enjoy code

author: e-clinton


value:
Growing up in a family business focused on coworking and shared spaces, I saw that many people were looking for a coworking space to use for a day. They weren't ready to jump into a long-term agreement. So I created LANS to simplify coworking.
Our platform allows users to buy a day pass to a coworking space in seconds. The process is simple: book your pass, arrive at the space, give your name at the front desk, and you're in.
Where we are
Live in San Francisco with several coworking partners.
Recently started expanding beyond the Bay.
10K paid users in San Francisco.
Day passes priced between $18 and $25.
What we’re seeing
Users often use this service. They rotate locations during the week to fit their needs and schedules.
For spaces, it’s incremental usage and new foot traffic during the workday.
Outside dense city centers, onboarding new spaces tends to be faster. Many suburban areas host nice boutique coworking spaces. But, they often miss a strong online presence. Day passes quickly appeal to both operators and users.
What we’re working on
Expanding to more cities.
Adding supply while keeping quality consistent.
Learning which product decisions actually improve repeat usage.
Would love feedback from HN:
Does this resonate with how you work today?
Have you used coworking day passes before?
Would you dump your coworking membership for this?

value: Show HN: Building the ClassPass for coworking spaces, would love your thoughts


value: Hey HN,<p>I built this after getting frustrated with Claude Code forgetting everything between sessions.

value: Show HN: CodeSyncer – Store AI coding context in code comments


value: keytalker

value:
Claude CLI is not just a widely used vibe coding tool, but also the engine powering pretty much every client side tools Anthropic made available, sdk, Claude Cowork, you name it.
Claude CLI exposes a JSON/RPC interface over stdio/stdout. But the protocol is largely undocumented. Fortunately, the python sdk is open source.
By asking Claude to write code to exercise the SDK and capture the messages, we can establish a much better understanding of the protocol.
So here comes this repo https://github.com/mzhaom/claude-cli-protocol
With that, I hope efforts like building the SDK in a new language, creating another UI for Claude CLI becomes much easier.
Feedback and PRs are welcome!

value: Show HN: Use Claude CLI to analyze its own protocol

author: keytalker


value: mayankkgrover

value:
Hey HN, Mayank from Outscal again.
It has been a chaotic week.
Got hacked three times. Someone hit our SES and sent lakhs of phishing emails. Then our server got compromised, and the site went down.
But we're back up, and we still shipped some updates to our text-to-video tool (outputs React/TSX instead of video files).
We built it for edtech content like code snippets, diagrams, and tutorials. Where clean text rendering matters.
Watching users, we noticed a mismatch. We built this with voiceovers in mind (as our course content was in text format). You write a script, we generate visuals to match.
But users would put in visual descriptions ("a cowboy sitting in a cyberpunk bar"), questions ("teach me about rice harvesting"), or anything except an actual script. That's what most other tools accept.
So now the system generates a script from your input first. You can review/edit it before the generation starts. Also added multiple voice options and a gallery showing what's possible.
Try it: https://outscal.com/
Happy to talk about the UX changes, and would love some honest and brutal feedback

value: Show HN: AI video generator (React output)– now with script gen and voice select

author: mayankkgrover


value: ianberdin

value: Show HN: I've Built a Python Playground

author: ianberdin

title: Show HN: I've Built a Python Playground


value: Applications open: https://humonos.com

value: Show HN: Local AI that knows when you're burning out

story_text: Applications open: https://humonos.com


value: tobyhede

value:
I have been working on this hare-brained scheme to help agents who want to code good and do other things good too.
Introducing: Rundown (https://rundown.cool)
I think of Rundown runbooks as executable Skills. The Skill provides the detailed context, and the Rundown runbook keeps the agent on track.

    # Hello

    ## 1 This is Rundown

    Rundown transforms markdown into an executable specification.
    Headings become steps, code-blocks become executable commands.
    Human-readable. Agent-readable. Machine-executable.

    ## 2 Guide agents (and humans) through your process

    Rundown keeps agents on track by injecting precision context at the exact moment it’s needed.

    ## 3 Make complex workflows deterministic
    - PASS: CONTINUE
    - FAIL: GOTO RECOVER

    Rundown works *with* agents, adding guardrails that enforce transitions and improve accuracy.

    ## 4 Execute the right commands at the right time
    - PASS: CONTINUE
    - FAIL: RETRY GOTO RECOVER

    Embed commands for automatic execution. Catch failure, retry, and recover gracefully.

    ```bash
    rd echo npm run test
    ```

    ## 5 Track progresss across agents and sessions
    - PASS: CONTINUE
    - FAIL: STOP

    State-aware CLI ensures progress is never lost.
    Save and resume complex processes at any time.

    ## 6 Ready to get started?
    - PASS: COMPLETE
    - FAIL: STOP

    ```bash
    npm install -g @rundown/cli
    ```

    ## RECOVER Recover from errors
    - PASS: GOTO 4
    - FAIL: STOP

    If you are here, an error occurred.
    Named steps enable error handling and conditional logic.

value: Show HN Rundown transforms docs into executable workflows

author: tobyhede


value: baoyashishui

value:
I built a site that combines full-length public domain classics with short summaries inspired by Blinkist/Headway lists, so you can either listen in minutes or go deep immediately.
Would love feedback on discovery pages (genres/authors/series) and what “summary vs full” UX works best.

value: Show HN: AudiobookHub – Blinkist-style summaries and full classics

author: baoyashishui


value: MichaelCoder

value: Show HN: A smart camera that detects eye movements during REM sleep

author: MichaelCoder


value: Show HN: On the edge of Apple Silicon memory speeds


value: noloman

value:
I built Commit Tracker because I follow 50+ repos (React, Next.js, Tailwind, etc.) and GitHub notifications are unusable.
What it does:
- Subscribe to any public GitHub repo
- Get commits via RSS/Atom/JSON, email digest, or Slack/Discord
- AI explains what changed (in email digests)
- Filter by author, message, or date
- Private repos work too via GitHub App
Why RSS: I wanted commit updates in my feed reader alongside newsletters and blogs. GitHub doesn't offer this natively.
Tech: Next.js 16, PostgreSQL, Vercel. ~700 tests.
Free to use: https://www.committracker.com
Looking for feedback on what features matter most.

value: Show HN: Commit Tracker – RSS feeds for GitHub commits

author: noloman


value: Show HN: Smart Color Replacer with HSV tolerance and edge snapping


value:
I built this because I got tired of copy-pasting tweets into ChatGPT just to understand them.
Griit translates text and also breaks down:
 - Vocabulary (with context explanations)
 - Grammar patterns
 - Idioms
Works with Japanese, Korean, Chinese, and 20+ languages. No signup needed to try.
Built with Django + Gemini API. Would love feedback from the HN community.

value: Show HN: Griit – AI translator that explains grammar as you translate


value:
Hi HN, I built a simple browser-based tool to quickly apply various blur effects to images.
I often needed to redact sensitive info or create blurred backgrounds for UI mockups, but didn't want to upload files to a server or open Photoshop. This tool runs entirely client-side.
Key features:
Batch processing: Upload and download multiple images at once.
Multiple modes: Includes Gaussian, Pixelate (good for redaction), Motion, Radial, and Noise.
Fine-tuning: Adjustable strength sliders.
It’s free and doesn't require a login. I’d love to hear your feedback on the UX!

value: Show HN: A privacy-first, batch image blurring tool (runs locally)


value: Show HN: Streaming gigabyte medical images from S3 without downloading them