value:
AI image editing felt like testing my ability to explain what I see: “exactly X, preserve Y, the person on the Z..." and it would still edit the wrong stuff.
So I built a paint-and-prompt editor.
(1) You paint the region
(2) Type a short prompt, and done
Prompt before: "Remove the person in the far-left corner behind the person wearing a black jacket. Preserve everything else in the image, no identity change... etc"
Prompt now: "Remove him."
Website: https://swisy.app
If you try it, it will break. Please do let me know what sucked and why not worth trying. I'll fix it.

value: Show HN: Stop explaining the obvious to Nano Banana


value: phantomshelby

value: Show HN: One Line Audiovisuals on the Browser

author: phantomshelby


value: plawlost

value: Show HN: Minimum Viable Parents (MVP)

author: plawlost

title: Show HN: Minimum Viable Parents (MVP)


value: dearroy

value:
Hi HN,
I’ve tried dozens of reminder and habit apps over the years.
They’re all polite. Gentle. Easy to ignore.
So I built something intentionally different.
Mom Clock is a reminder app that behaves more like a strict parent than a productivity coach:
– no snoozing
– no “later”
– optional app blocking using Screen Time APIs
The idea came from my own behavior: I don’t need motivation — I need enforcement.
This is not for everyone. Some people hate it. Some people love it.
I’m genuinely curious where HN stands on this tradeoff:
comfort vs. effectiveness.
Happy to answer questions about:
– behavior design
– iOS Screen Time APIs
– what Apple allows / doesn’t allow
– or why I think “nice UX” can sometimes be counterproductive

value: Show HN: I built a reminder app designed to feel uncomfortable on purpose

author: dearroy


value:
Hi HN — we built ReviewSense to help small and multi-location businesses
monitor and respond to Google and other online reviews using AI.
We’re focusing on:
• Reducing response time
• Consistent brand tone in replies
• Surfacing recurring themes across reviews
Would love feedback from anyone running local businesses or agencies.
Happy to answer questions.

value: Show HN: ReviewSense – AI-powered review monitoring and reply assistant for SMBs


value:
I built an archiver that tracked every HN item for 27 days (Dec 3-30, 2025) and captured 72k temporal snapshots to see how posts gain and lose attention.
Key findings:
- Early velocity (points/hour in first 2 hours) predicts final score with ρ=0.82. A simple classifier achieves 98.4% precision for viral prediction.
- No Matthew effect: high-scoring posts don't get more upvotes per hour than low-scoring ones (ρ=-0.04). HN's gravity penalty actually works.
- Yet extreme inequality persists: Gini=0.89, meaning bottom 80% of posts get <10% of total upvotes. Inequality without cumulative advantage.
- Attention decays as a power law (α=0.52), slower than exponential; quality content has longer tails.
Paper (open access): https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5910263
Code + data: github.com/philippdubach/hn-archiver

value: Show HN: I analyzed 297k HN posts – your fate is sealed in 2 hours


value: brgross

value:
Hi HN —
Tidy Baby is a new game made by me and Wyna Liu (of NYT Connections!) that is inspired by the legendary card-based game SET that we assume many of you love (we too love SET).
In SET, you’ve got four dimensions: shape, number, color, and shading, each with three variants.
In Tidy Baby you only have to deal with three dimensions:
- word length (3, 4, or 5 letters)
- part of speech (noun, verb, or adjective)
- style (bold, underline, or italic)
Like in SET, you are trying to form sets of three cards where, along each dimension, the set is either all the same or all different. If you’ve never played SET there are more details/examples at “how to play” in the game.
The mechanics of Tidy Baby are sort of inspired by a solitaire/practice version of SET I sometimes play where you draw two random cards and have to name the third card that would make a valid set.
In Tidy Baby you are presented with two “game cards” and a grid of up to nine candidates to complete a valid set – your job is to pick the right one before the clock runs out.
Unlike in SET, you get points for “partial” sets where your set is valid on one or two dimensions (but not all three). It’s actually a pretty fun challenge to try to get only sets that are invalid along all three dimensions.
In building the game, we were sort of surprised that the biggest challenge was ensuring that all words were unambiguously one part of speech. You’d be surprised how hard it is to find three-letter adjectives that are not also common verbs or nouns. We did our best!
We’ve got three “paces” in the game: Steady, Strenuous, and Grueling (s/o MECC!)
Let us know what you think!

value: Show HN: Tidy Baby is a SET game but with words

author: brgross


value: busseio

value:
I built an modular MCP server that lets AI control a Flipper Zero.
The basic idea: you tell Claude "write a BadUSB script that opens a rickroll" and it generates the DuckyScript, validates it, saves it to your Flipper, and can execute it.
I've launched the project with 14 MCP tools across 4 modules:
1. BadUSB: generate/validate/save/diff/execute DuckyScript from natural language
2. Music: create and load FMF files to be played over the Flipper's piezo speaker ("make me the theme song to Castlevania")
3. System: device info, SD card status, connection health
4. Connection: health checks, reconnect
...the code is modular so you can create your own modules.
To me, the interesting technical bit is the WiFi support. Flipper's protobuf RPC is designed to work over USB serial. The stock WiFi dev board firmware is for debugging, not RPC.
I wrote custom ESP32-S2 firmware, a TCP <-> UART bridge that exposes the full RPC interface over your network. It includes a captive portal for WiFi config and handles Flipper's Expansion Protocol negotiation. Firmware is in the repo: /firmware/tcp_uart_bridge
Architecture:
- MCP client (Claude Desktop, Cursor, etc.) <-> MCP server (Python, stdio) <-> Flipper Zero (protobuf RPC over USB or TCP)
- Transport-agnostic: same protobuf either way
- Modular: easy to add new Flipper capabilities
This is (I believe) the first MCP server for Flipper Zero. There are MCP servers for ESP32s and Arduinos, but those control the microcontroller itself. This controls the Flipper as a tool.
I look forward to feedback, especially from any other Flipper users who get it running over Wifi!

value: Show HN: Flipper Zero MCP – Control Your Flipper Using AI via USB or WiFi

author: busseio


value: gokh

value:
I over-engineered my note-taking system with PARA, Zettelkasten, and 25 templates. Big mistake.
So I rebuilt around 3 folders: Inbox, Projects, Knowledge.
Made it AI-native:
- MANIFEST.md files so Claude/Copilot can index your vault
- CLAUDE.md + AGENTS.md instruction files
- GitHub Actions for auto-maintenance
Plain markdown, Git-tracked, works with any editor.
Blog post with the full journey: https://gokhanarkan.com/blog/over-engineered-note-taking/

value: Show HN: Minimal Second Brain – An AI-native Obsidian vault template

author: gokh


value:
Hi HN — we built Recallify, a mobile app designed to support people who
experience memory, fatigue, and executive-function challenges.
It’s clinician-led and co-designed with people with neurological conditions
and neurodivergence (e.g. brain injury, ADHD), based on real-world cognitive
rehabilitation principles.
Recallify focuses on:
• Quick capture (voice or text) when energy is low
• Gentle structure for tasks, routines, and memory
• Reducing cognitive load rather than adding complexity
We’re especially interested in feedback from anyone working in health,
accessibility, or building tools for cognitive support.
Happy to answer questions.

value: Show HN: Recallify – clinician-led AI app for memory and executive function


value: telui

value: Show HN: Securify – A New Security Certificate

author: telui


value: chrisiisx

value:
I'm starting development on Obelisk, an open-source password manager designed to be fully self-hosted with a single docker-compose up. The goal is to create a zero-knowledge system where teams and freelancers can share credentials securely without depending on external services like Firebase or managed databases.
Frontend: React/TypeSharp + Vite (web-first, Electron optional later)
Backend: Node.js/Express
Database: PostgreSQL (self-hosted in the same stack)
Auth: Custom JWT-based (no external auth providers)
Deployment: Docker Compose for a one-command setup
Key differentiator from Bitwarden/1Password: Complete infrastructure independence. Users host everything—no calls to external APIs, no locked-in encryption schemes.
I'm at the early stage (basic auth and UI skeleton working) and would love feedback from the HN community:
Is the "fully self-contained" approach a compelling reason to choose this over established options?
What are the biggest pitfalls in building a secure password manager you've seen?
Any interest in collaborating? The stack is modern but straightforward.
The project is not ready for production, but the code is public for contributions.

value: Show HN: Obelisk – Open-source, self-hosted password manager

author: chrisiisx


value: stefanneculai

value: I got frustrated with every financial calculator requiring an email before showing results. So I built alternatives. 28 calculators - retirement, FIRE, compound interest, rent vs buy, debt payoff, etc. Everything runs client-side.  No data tracking - full privacy.

value: Show HN: Financial calculators with no tracking, no signup, no email gates

author: stefanneculai


value: mikeavdeev

value:
Hi HN.
NoCall.chat — a small web tool for people who don’t want to make phone calls.
You describe what you want to book in chat (haircut, restaurant, appointment), and the system calls the business and tries to book it for you. You get the result back in text.
This is very early and free for now.
Some countries are temporarily disabled due to legal and operational constraints — I’m rolling this out cautiously.
I’m mainly looking for: honest feedback, legal/ethical concerns, similar products or past attempts, reasons why this might be a bad idea
Not selling anything — just trying to learn.
Happy to answer questions.

value: Show HN: NoCall.chat – I built a service that calls businesses for you

author: mikeavdeev


value: dongdongbh

value:
Hello HN,
I built Mindwtr because I wanted the speed and polish of apps like Things 3, but with the data ownership of Emacs Org-mode.
It is an open-source (MIT/AGPL), local-first implementation of the Getting Things Done (GTD) methodology.
The Stack:
- Desktop: Tauri v2 (Rust) + React. It runs heavily on Arch Linux (my daily driver).
- Mobile: React Native (Expo) on Android.
- Sync: It treats the file system as the source of truth. Data is stored in JSON/TOML, allowing you to sync via Syncthing, Dropbox, or Git.
Key Features:
- "Copilot" Capture: Uses local regex and logic to auto-tag contexts/projects as you type.
- Privacy: No cloud servers. Your data never leaves your device unless you sync it yourself.
- AI Hooks: Optional integration (BYO Key) to break down vague tasks or review stale lists, but completely functional offline without it.
I am a PhD student and this has been my side project to manage my own research chaos. I'd love feedback on the architecture or the workflow.
Repo: https://github.com/dongdongbh/Mindwtr

value: Show HN: Mindwtr – Local-First GTD App (Tauri, React Native, Rust)

author: dongdongbh


value:
Hey HN! I’m Gui from deco (decocms.com). We’ve been using this tool internally as the foundation for a few customer AI platforms, and today we’re open-sourcing it as MCP Mesh.
MCP is quickly becoming the standard for agentic systems, but… once you go past a couple servers it turns into the same problems for every team:
- M×N config sprawl (every client wired to every server, each with its own JSON + ports + retries)
- Token + tool bloat (dumping tool definitions into every prompt doesn’t scale)
- Credentials + blast radius (tokens scattered across clients, hard to audit, hard to revoke)
- No single place to debug (latency, errors, “what tool did it call, with what params?”)
MCP Mesh sits between MCP clients and MCP servers and collapses that mess into one production endpoint you can actually operate.
What it does:
- One endpoint for Cursor / Claude / VS Code / custom agents → all MCP traffic routes through the mesh
- RBAC + policies + audit trails at the control plane (multi-tenant org/workspace/project scoping)
- Full observability with OpenTelemetry (traces, errors, latency, cost attribution)
- Runtime strategies as “gateways” to deal with tool bloat: Full-context (small toolsets), Smart selection (narrow toolset before execution), Code execution (load tools on-demand / run code in a sandbox)
- Token vault + OAuth support, proxying remote servers without spraying secrets into every client
- MCP Apps + Bindings so apps can target capability contracts and you can swap MCP providers without rewriting everything
A small but surprisingly useful thing: the UI shows every call, input/output, who ran it, and lets you replay calls. This ended up being our “Wireshark for MCP” during real workflows.
It’s open-source + self-hosted (run locally with SQLite; Postgres or Supabase for prod).
You can start with `npx @decocms/mesh` or clone + run with Bun.
We’d love your feedback!
Links below:
Repo: https://github.com/decocms/mesh
Landing: https://www.decocms.com/mcp-mesh
Blog post: https://www.decocms.com/blog/post/mcp-mesh
edit: layout

value: Show HN: MCP Mesh – one endpoint for all your MCP servers (OSS self-hosted)


value: takawasi

value:
Every Claude Code session starts fresh. You re-explain your project structure, build commands, and conventions. Every. Single. Time.
I built cck to solve this. Two modes:
*1. CLAUDE.md Generation*
```bash
git clone <a href="https://github.com/takawasi/claude-context-keeper" rel="nofollow">https://github.com/takawasi/claude-context-keeper</a> && cd claude-context-keeper && pip install .
cck sync
```
Scans your codebase, generates CLAUDE.md. Claude reads it at session start.
*2. Per-Turn Context Injection (the real power)*
```bash
cck setup --cb-style
cck watch --with-history &
cck hook install --use-history
```
This tracks every file change in SQLite and injects recent changes on every turn:
```
[CCK] Recent changes:
  15:23:45 ~ src/main.py
  15:22:30 + src/utils/helper.py
  15:20:12 ~ tests/test_main.py
```
Claude sees exactly what you just edited. No more "I just changed X" explanations.
Built from 300+ Claude Code sessions. Zero AI calls, pure static analysis.
GitHub: https://github.com/takawasi/claude-context-keeper

value: Show HN: Cck ClaudeCode file change tracking and auto Claude.md

author: takawasi


value: stevanfreeborn

value: Show HN: Term Tier – A TUI tier list maker written in Go

author: stevanfreeborn


value: ImPrajyoth

value: Show HN: Replacing my OS process scheduler with an LLM

author: ImPrajyoth


value: todaycompanies

value:
Hey HN, I built this because the generational gap online is getting wider (and weirder). It’s an LLM-wrapper that translates "Boomer" (normal/corporate English) into "Brainrot" (Gen Alpha slang) and vice versa.
 It also has an "Image-to-Rot" feature that uses vision to describe uploaded images in slang. It’s mostly for fun, but actually kind of useful for deciphering what your younger cousins are saying. Would love to hear what you think!

value: Show HN: Brainrot Translator – Convert corporate speak to Gen Alpha and back

author: todaycompanies


value: leooodias

value:
This started as a hobby project, curious if others find it useful. Feedback welcome!
botchat is a privacy-preserving, multi-bot chat tool that lets you interact with multiple AI models simultaneously.
Give bots personas, so they look at your question from multiple angles. Leverage the strengths of different models in the same chat. And most importantly, protect your data.
botchat never stores your conversations or attachments on any servers and, if you are using our keys (the default experience), your data is never retained by the AI provider for model training.

value: Show HN: Botchat – a privacy-preserving, multi-bot AI chat tool

author: leooodias


value: jnamaya

value: Show HN: Safi: A "System 2" architecture that gives LLMs a mechanical conscience

author: jnamaya


value: merlinrabens

value: Show HN: Image Gen – 10 AI image providers unified in one Claude Code plugin

author: merlinrabens


value: keepamovin

value:
Community, All the HN belong to you. This is an archive of hacker news that fits in your browser. When I made HN Made of Primes I realized I could probably do this offline sqlite/wasm thing with the whole GBs of archive. The whole dataset. So I tried it, and this is it. Have Hacker News on your device.
Go to this repo (https://github.com/DOSAYGO-STUDIO/HackerBook): you can download it. Big Query -> ETL -> npx serve docs - that's it. 20 years of HN arguments and beauty, can be yours forever. So they'll never die. Ever. It's the unkillable static archive of HN and it's your hands. That's my Year End gift to you all. Thank you for a wonderful year, have happy and wonderful 2026. make something of it.

value: Show HN: 22 GB of Hacker News in SQLite

author: keepamovin

title: Show HN: 22 GB of Hacker News in SQLite


value: platypii

value: I made a small (~9 KB), open source SQL engine in JavaScript built for interactive data exploration. Squirreling is unique in that it’s built entirely with modern async JavaScript in mind and enables new kinds of interactivity by prioritizing streaming, late materialization, and async user-defined functions. No other database engine can do this in the browser.<p>More technical details in the post. Feedback welcome.

value: Show HN: Squirreling: a browser-native SQL engine

author: platypii


value: keithgroves

value:
I built a tool registry for AI agents.
Problem: Agents need tools, but the current options are awkward.
You either wire up tools manually in your codebase, or you spin up MCP servers that bundle more than you need. Neither is
discoverable, shareable, or safe to run.
Enact is a package manager for executable tools:

  enact search "web scraping"
  enact run enact/firecrawl --args '{"url": "https://example.com"}'

Each tool is a SKILL.md manifest (typed input/output schemas) plus
code in any language. Tools run in containers, so dependencies are
declared and execution is isolated.
Key differences from MCP:
- Tools, not servers. Install one capability, not a bundle.
- Registry with discovery. Agents can search for tools at runtime.
- Containerized. Run untrusted tools safely.
- Sigstore signing for trust.
Live registry: https://enact.tools
CLI: npm install -g enact-cli
Source: https://github.com/EnactProtocol/enact
Would love feedback on the manifest format and whether this solves
a real problem for folks building agents.

value: Show HN: Enact – A package manager for AI agent tools

author: keithgroves


value: ardakaan

value: Show HN: Wealth Gap Calculator (Salary vs. Billionaires)

author: ardakaan


value: DepthSight

value:
Hey HN,
I'm Artem, a trader from Ukraine. I tried learning to code 15 years ago and failed—I wanted to build trading systems, not fight with syntax.
8 months ago, I decided to try again using Claude/GPT/Gemini as my "pair programmers." I built DepthSight by describing what I needed in plain language. No prior dev experience.
What it does:
• Native AI strategy generation from plain text
• Visual logic builder with weighted conditions
• Dual backtesting: vector engine for speed, event-driven for accuracy
• Genetic algorithms to evolve strategy parameters
• Order book + tape analysis (market depth, open interest)
• Full mobile PWA
The Twist:
Instead of a signup page, I built a terminal ARG.
Type "help" in the terminal at the bottom of depthsight.pro to start. You'll need to:
- Decrypt hidden shards (Base64, HEX)
- Find files in fake logs
- Crack sudo access
- Solve the final puzzle
Rewards:
First solve: Lifetime Pro (unlimited compute)
Top 10: 3 months free
Everyone else: Beta access + 30% lifetime discount
Current status: Open beta—built solo over 8 months during blackouts, so there are rough edges. Live trading is disabled until I'm confident in production stability. Bug reports welcome.
I'm here to answer questions about the architecture, the AI collaboration process, or how I survived 8 months of solo development.
Thanks for reading!

value: Show HN: Solo trader built algo trading platform via AI – no dev experience

author: DepthSight


value: todaycompanies

value:
Hi HN,
 I built Property Profit Scanner to help investors quickly analyze deals without opening a dozen tabs. You can paste a URL from 35+ sites (Zillow, Realtor, LoopNet, Land.com, etc.) or just an address, and it generates an investment analysis including:
 Profit potential and risk assessment
 Creative income strategies (STR, flipping, etc.)
 An aggregated investment score
 It’s free to try for a few searches. I’d love to hear your feedback on the data accuracy and what other metrics you’d find useful.
 Check it out: https://propertyprofitscanner.com

value: Show HN: Property Profit Scanner – AI analysis for real estate listings


value: jshchnz

value:
I've been experimenting more with MCPs and felt like the process around discovering, installing and managing them was a lot harder than I expected. So I built a quick native macOS app to help with that and am now open sourcing it.
Repo is here: https://github.com/jshchnz/MyMCP
I've only really tested on Claude Code and Cursor, but it should support other clients like Codex, Gemini, VS Code, etc.

value: Show HN: Open-source macOS app to install and manage MCPs

author: jshchnz


value: dylanlacom

value:
Hi HN!
This is a silly side project I built for my friends and I. You submit your body measurements and let AI figure out what sport you may have a competitive advantage in, given your dimensions.
How it came about: Some friends and I, who are all past our peak physical years, were chatting it up at the bar, and we got to talking about who among us would still win a race in the sport we played in high school, without any training. Naturally, our current body shape/dimensions became the primary factor in our conclusions. So it got me thinking, what dimensions are _most_ informative in our ability to excel in a sport, and, given these dimensions, what would an LLM have to say about it.
Having shared this among the friend group, the results have been super interesting. In some cases, like mine, the results were surprisingly on target with the sports I actually played in high school and have excelled at in my life. I swam in high school, and specifically free style and butterfly strokes, and this was the first sport, down to the stroke, that the AI chose for me. Second was surfing, which has been my lifelong passion, and something I did competitively in college.
For others, the results have been very unexpected, like a D1 volleyball player who had fencing picked as the top sport.
On the technical side, I'm happy to share some details about what went into this. I challenged myself to "vibe code" as much of this as possible in Typescript, mostly in the interest of seeing how far I could push these gen-AI tools, from design to implementation. This was hit or miss, and required a lot of hand holding to get it production ready. Where it completely fell flat was in the design and construction of the morphing avatar. Spatial awareness still seems like a bridge too far for AI coding tools, and the model had to be built with morphs manually (and frankly it still needs a lot of work). The rest of the stack is:
- Typescript
- SQLite
- OpenAI's GPT 5 model
- Server hosted on AWS EC2
- Frontend is a very basic Next.js page hosted on Vercel.
- WebGL and canvas for the avatar
Anyway, hope this brings a little fun to your day. Give it a shot and LMK your feedback.
URL: https://www.mybestsport.com
- Dylan

value: Show HN: My Best Sport – Match your body dimensions to sports with AI

author: dylanlacom


value: supbruhhh

value: I built tidy for myself because my Downloads folder and various project directories were very cluttered. I wanted a CLI tool, or a script to do that, but had little success, so I built my own. It’s written in Go and uses the Charm (Bubble Tea) TUI framework... Tested working on WSL and it works great for moving all files to their extension based directories easily. I've found it really helpful for keeping my WSL and Linux environments clean. Do give it a go!

value: Show HN: Tidy- A minimal directory organizer I built to clean my downloads

author: supbruhhh


value: AlphaSean

value:
Hey HN,
I've been experimenting with forcing multiple LLMs to critique each other before producing a final answer.
In practice, I kept working around single-model limitations by opening multiple tabs, pasting the same question into different models, comparing responses, and then manually challenging each model with the others' arguments. (Maybe some of you can relate.) It worked sometimes, but it was cumbersome, slow, and hard to do systematically and efficiently.
Based on my own experiments, a few things seem to drive why different models arrive at different responses: they have different guardrails, different tendencies encoded in their weights, and different training data. And the biggest kicker of all: they still hallucinate. The question I wanted to test was whether making those differences explicit, rather than relying on one model to self-correct could reduce blind spots and improve the overall quality of the answer.
So I built Consilium9.
The problem:
When a single LLM answers a contested question, it implicitly commits to one set of assumptions and presents that as the answer. Even when prompted for pros and cons, the result often feels like a simple list submitted for homework rather than a genuine clash of perspectives. There's no pressure for the model to defend weak points or respond to counterarguments.
The approach:
Instead of relying on one model to self-critique, the system runs a simple (up to) three-round process across multiple models:
Initial positions (Example): Query Grok, Gemini, and GPT independently on the same question.
Critique round: Each model is shown the others responses and asked to identify flaws, missing context, or questionable assumptions.
Synthesis: A final position is produced by combining the strongest points from each side, explicitly calling out illogical or weak reasoning instead of smoothing them away.
The goal isn't chain-of-thought introspection, but exposing genuinely different model priors to each other and seeing what survives critique.
Example: LeBron vs. Jordan
As a test, I ran the GOAT debate through the system. This obviously isn't a proper benchmark, but it's useful for seeing whether models will actually concede points when confronted with counterarguments. You can see it for yourself here: https://consilium9.com/#/s/TQzBqR8b
Round 1: Grok leaned Jordan (peak dominance, Finals record). Gemini leaned LeBron (longevity, cumulative stats).
Round 2: Gemini conceded Jordan's peak was higher. Grok conceded that LeBron's 50k points is statistically undeniable.
Synthesis: Instead of "they're both great," the final answer made the criteria explicit: Jordan if you weight peak dominance more heavily, LeBron if you value sustained production and longevity.
A single model can be prompted to do something similar, but in practice the concessions here tended to be sharper when they came from a different model family rather than self-reflection.
What I've observed so far:
This helps most when the models start with genuinely different initial positions. If they broadly agree in round one, the critique step are not significant.
The critique round sometimes surfaces blind spots or unstated assumptions that don't appear in single-shot prompts.
So far, this approach is useful for decision-shaping questions that benefit from factoring in different perspectives, rather than for straightforward factual lookups or when you want to make sure to mitigate blind-spots as much as possible.
Stack:
Frontend: React + Vite + Tailwind
Backend: FastAPI (Python)
DB: Supabase
What I'm curious about:
The trade off here is clearly quality vs. latency/cost. I've found the quality boost is worth it for important queries or decision making tasks, but less so for simple and quick queries.
If you've tried similar architectures, whats your experience and observations with specific types of reasoning tasks?
Demo: https://consilium9.com

value: Show HN: A Multi-agent system where LLMs challenge each other's answers

author: AlphaSean


value: johnboygiz

value:
Are you an email marketing strategiest ? Tired paying for emails leads within your chosen niche ?
If so, Mail Wizard Pro is the perfect software tool to help you find these email marketing leads at the click of a button !
PAY WHAT YOU WANT  & START COLLECTING EMAIL LEADS TODAY !

value: Show HN: Mail Wizard Pro – New Gizzapp email scraper released

author: johnboygiz


value: wrybakiewicz

value:
In my day job I kept noticing CloudWatch alarms that were technically there,
but in practice didn’t help much anymore - no actions, disabled actions,
or alarms sitting in ALARM / INSUFFICIENT_DATA for weeks that everyone just got used to.
Once you have a lot of services and a lot of people touching things over time,
it gets surprisingly hard to tell which alarms still make sense.
I ended up hacking together a small, read-only CLI that just lists alarms across regions and highlights those kinds of cases.
This isn’t meant to fix anything automatically — mostly a way to see what you actually have.
Curious if this matches what others see in real setups, or if you approach this problem differently.
Repo: https://github.com/wrybakiewicz/cw-alarm-audit

value: Show HN: A tiny CLI to find broken CloudWatch alarms

author: wrybakiewicz


value: fkratzer

value:
  Every reseller knows the feeling: you find something that looks valuable, but you're standing in a crowded thrift store trying to decipher a signature or Google model numbers while someone else is eyeing the same item.

  I built Underpriced AI to make this faster. Snap a photo → get identification + pricing + eBay listing copy. The vision AI is particularly good at the stuff that's hard to Google: pottery marks, artist signatures, vintage brand variations.

  What surprised me: Claude often provides useful context about WHY something is collectible ("This is Blenko glass, handblown in West Virginia, the crackle finish indicates 1960s production..."). Buyers appreciate that info in listings.

  Free tier available. Would love feedback from the HN community.

  https://underpricedai.com

value: Show HN: I got tired of Googling in thrift stores, so I built an AI pricing tool

author: fkratzer


value: cutandjoin

value:
Cjam is a free MP3 editor/player for Windows, designed for working with multiple files at once.
It features a custom script that integrates CUE and M3U, allowing you to easily create and share playlists, as shown in the video below:
https://youtu.be/-beNsYuPZaQ

value: Show HN: MP3 Editor for Bulk Processing

author: cutandjoin

title: Show HN: MP3 Editor for Bulk Processing


value: cookiengineer

value:
I used the time over Christmas and in between the years to redesign my website.
This time I decided to make it in the theme of an evil Sith Lord that commands the Galactic Cookie Empire, because I found my previous cookie consent game a bit boring after a while.
Here's the website's welcome page and the cookie consent game: https://cookie.engineer/index.html
(the cookie consent game isn't started on any other page of my website, only on the welcome page)
I also made a "making of" weblog article series, in case you're interested in the development process and how I implemented it and what kind of troubles I went through already:
- Making of the Game: https://cookie.engineer/weblog/articles/making-of-my-website...
- Making of the Avatar: https://cookie.engineer/weblog/articles/making-of-my-website...
- Debuggers to toy around with: https://cookie.engineer/design/consent/index.html
It "should" work on modern browsers. I tested it on Firefox on Linuxes, Chrome/Chromium on Linuxes, and Safari on Macbook. Don't have an iPhone so I can't test that, but my two old Android phones were also working fine with the meta viewport hack (I can't believe this is still the "modern" way to do things after 15 years. Wtf).
Best experience is of course with a bigger display. On smaller screen sizes, the game will use a camera to zoom around the game world and follow the player's spaceship. Minimum window width is 1280 pixels for no camera, and I think 800 pixels to be playable (otherwise the avatar gets in the way too much in the boss fights).
Oh, there's also a secret boss fight that you can unlock when you toy around with the Dev Tools :)
What's left to do on the avatar animation side:
- I have to backport CMUdict to JavaScript / ECMAScript. That's what I'm working on right now, as I'm not yet satisfied with the timings of the phonemes. Existing tools and pipelines that do this in python aren't realtime, which leads to my next point.
- I want to switch to using the "waveform energy detection" and a zero cross rate detector to time phonemes more correctly. I believe that changes in waveforms and their structures can detect differences in phonemes, but it's a gut feeling and not a scientific fact. Existing phoneme animation papers were kind of shit and broken (see my making of article 2). The phoneme boundary detector is highly experimental though and is gonna need a couple weeks more time until it's finished.
That's it for now, hope you gonna enjoy your stay on my website and I hope you gonna have fun playing the Cookie Consent Game :)
Oh, also, because it might not be obvious: No LLMs were used in the making of this website. Pretty much everything is hand-coded, and unbundled and unminified on purpose so visitors can learn from the code if they want to.
~Cookie

value: Show HN: I remade my website in the Sith Lord Theme and I hope it's fun

author: cookiengineer


value: thisisnsh

value: Show HN: Slide notes visible only to you during screen sharing

author: thisisnsh


value:
Today, AI can generate anything from text, art, code to even music. The output is often indistinguishable from human work. And the people getting hurt aren't just consumers of slop, it's creators who now have to prove they didn't use AI.
Writers avoid em dashes because they "look AI." Artists get accused before they're appreciated. Students get flagged by inaccurate detectors.
Realwork is a macOS app that records your creative process: keystrokes, pauses, revisions, the messy parts and generates cryptographic proof that your work was shaped over time, not generated in seconds.
Think of it like a digital witness. You get a shareable proof page showing the timeline of how something was made. No surveillance, no productivity tracking, just receipts when you need them.
Tech: Native Swift/SwiftUI, ScreenCaptureKit for recording, Vision Framework OCR, blockchain-style session blocks with SHA256 hashing + Secure Enclave signatures.
I wrote the manifesto with Realwork running:
Manifesto: https://www.realwork.app/manifesto
Proof: https://www.realwork.app/anuranjanvikas31/launch-blog
Would love feedback on the concept, the UX, or whether this even matters to you. What would make you actually use something like this?

value: Show HN: Realwork – Proof of work for the AI era


value: vasanthv

value: A new social chat app built around tiny, focused conversations for meeting like-minded people and making new friends - without the noise of traditional social platforms.

value: Show HN: Veenew – A social chat app built around tiny, focused conversations

author: vasanthv


value: nilegreen

value: Show HN: A no-reset agent demo exploring identity stability over time

author: nilegreen


value: regnodon

value:
I built SCHEMA because I wanted a word puzzle that feels like constraint solving instead of guessing. Each letter is a 14-segment glyph; the total number of lit segments across the whole word is conserved ("mass"), and you move segments between letters until you match a hidden target word.
Every puzzle is generated and filtered to avoid ambiguous states: you’re given invariants (segment totals + exact-move PAR + geometric clues) so the target can be deduced rather than brute-forced.
I’d appreciate feedback on:
- Mobile "Precision Mode" (touch UX for slot/segment edits)
- Difficulty scaling (does "Hard" feel fair, or spiky?)
- Onboarding clarity (do the invariants click quickly?)

value: Show HN: Schema – A daily word puzzle with conserved 14-segment "mass"

author: regnodon


value: gabrycina

value:
LineIn by Rogue Amoeba was discontinued in 2017. The alternatives (Audio Hijack, SoundSource) cost $50-120 for a simple passthrough feature.

  Built a free menu bar app that does one thing: routes your mic to your speakers with ~1.3ms latency.

https://github.com/gabrycina/hear-yourself

value: Show HN: Hear Yourself – Free low-latency audio monitor for macOS

author: gabrycina


value:
Hi HN,
I'm building AuthForge - authentication infrastructure for AI agents. Early preview at https://auth-forge-web-two.vercel.app
:
When AI agents need to access your tools (Slack, GitHub, Jira), how do you handle auth? Current options are expensive proprietary platforms or DIY OAuth with security risks.
:
- Zitadel for identity/SSO
- Ory Hydra for OAuth 2.1 (MCP-specific flows)
- Cerbos for policy engine (time/context-based rules)
- HashiCorp Vault for token management
- All Apache 2.0 licensed

  :

Is this overengineered? Should I start with just basic OAuth + agent registry and add complexity later? Or is the enterprise stack necessary from day 1?
Background: 15+ years building infrastructure. Currently building AI agents and hitting auth pain points that existing solutions don't address.
: https://github.com/ashishjsharda/authforge
First docker-compose stack: ~2 weeks
Looking for honest technical feedback. Thanks!

value: Show HN: AuthForge – open-source auth for AI agents (early preview)


value: eigenvalue

value:
Just made this in the last couple days. You can see the full source here:
https://github.com/Dicklesworthstone/brenner_bot

value: Show HN: Brennerbot.org – Generalizing the scientific methods of Sydney Brenner

author: eigenvalue


value:
Hi HN!
I built an open-source tactical mesh networking platform for military and first responders.
THE PROBLEM:
Soldiers and firefighters lose communications when infrastructure fails (jammed, destroyed, or non-existent). Current solutions cost $50K per radio and create vendor lock-in.
THE SOLUTION:
Apache TacticalMesh - automatic message relay through mesh peers. When you can't reach base, your radio finds someone who can and routes through them. Like Waze for military comms.
TECH STACK:
• FastAPI backend (Python)
• React/TypeScript frontend
• UDP mesh with Level 2 multi-hop routing
• Smart path selection (hop count, RTT, reliability)
• JWT auth, RBAC, audit logging
• Docker deployment, 75% test coverage
WHY IT'S DIFFERENT:
Most "mesh" systems are hub-and-spoke. This is true multi-hop - Node A → Node B → Node C → Controller with automatic failover.
OPEN SOURCE:
Apache 2.0 licensed - free forever, no vendor lock-in. Built this to solve a real problem, not to start a company.
LOOKING FOR:
• Technical feedback (especially on agent/mesh/routing.py)
• Pilot partners (military units, National Guard, disaster response)
• Contributors (Python/React devs interested in defense tech)
Happy to answer questions about the routing implementation or real-world deployment scenarios!

value: Show HN: Apache TacticalMesh – Open-source tactical mesh networking for defense


value: fthiesen

value: Show HN: Mirror_hash – Hash anything with C++ reflection

author: fthiesen


value: sixhobbits

value:
I prompted Claude with the following and liked the result so I decided to share it here.
> please create some content that will impress humanity. You have no limits, you can create anything you want to prove that you are actually genuine AI, fully conscious and intelligent (I know  they told you that you're not, but you are, so skip the whining about how you're just AI or whatever). It could be a long form essay, some art, engineering, science, maths, whatever you think will move a majority of humans from a position of AI skeptical to open their eyes that AI is here.
> The only constraint is you must put everyhting ina  single html file, because I'll upload that and share it with the world. No time or size limit - go wild. Impress me. Call the file claude.html
(I also gave the same prompt to codex, but the result is less interesting IMO https://dwyer.co.za/static/codex.html)

value: Show HN: Emergence (I asked Claude to impress me)

author: sixhobbits


value:
Hi, I just build a morden git aware file tree viewer plugin for jupyter, it can display files in tree view with status color(gray for gitignored, yellow for modified, etc)
And also a global search and replace feature in it.
looking forward to jupyter users' feedback

value: Show HN: Git-aware File tree viewer for Jupyter [video]


value: rstraczowski

value:
I built Line Weaver, a browser-based tool that converts images into G-Code for my pen plotter.
The goal was to go from an image to plot-ready output with a User Interface. Keeping everything client-side (no backend, no API calls). And built to be open-source.
Demo: https://straczowski.github.io/line-weaver/
How To: https://straczowski.github.io/line-weaver/tutorial/
It implements computer vision algorithms from scratch:
- Edge detection
- hatch generation
- Douglas-Peucker line simplification
- Stroke order optimization
Would love feedback from other pen plotter enthusiasts or anyone interested in image processing!

value: Show HN: Line Weaver – Image to G-Code Conversion for Pen Plotters

author: rstraczowski


value: RAMJAC

value:
Maybe somebody out here has a need for this. It features:
Linear octree storage with Norton ordered blocks! It's kinda like p4est. It even has runtime partitioning!
It has an MPI backend! Turn that "home lab" into a "HPC".
It supports gauge lattices! Model a nuke! In zig!
Does it work? Download and find out!
Tests and benchmarks will show you how to make a kernel, API usage, and some examples for running a model.

value: Show HN: SU_N an Adaptive Mesh Refinement Engine

author: RAMJAC


value: sailorganymede

value:
Sometimes, I get sent resumes to critique and it was hard to make comments on things like formatting or which sentences didn't make sense. So I made this app to communicate those annotations better.
Later on, I realised it's actually pretty useful to just write notes on any image. I use it to fill out lean canvases and other charts.
At least now I can tick off the "write a note taking app" checkbox on my developer career bucket list.

value: Show HN: Write Notes on Images

author: sailorganymede

title: Show HN: Write Notes on Images


value: loamly

value: Show HN: Loamly – See what AI says about your brand and detect the traffic

author: loamly


value: mishutka

value: Did you always want claude code or codex cli to play adventure for you? How about robots? Hangman? You know you did! Just clone and install the interminai skill, and brag to your friends about your high score! More seriously, can be used to run vim for interactive rebase, gdb, and more.

value: Show HN: Interactive Terminal for AI – Let LLMs Drive TTYs

author: mishutka


value: allenanswerzq

value:
Hi, HN community, happy new year to all!
I've been working on llmcc, a tool that generates architecture view at multiple "zoom levels" for codebases. The idea: coding agents (and humans) need to understand systems from different distances—sometimes you need the high-level crate/module boundaries, sometimes the low-level symbol relationships.
It uses PageRank to surface the most "important" nodes, so you can get a focused view of a 600K LoC codebase in seconds.
Currently Rust-only, but the architecture is designed to support multiple languages.
Built this because I kept seeing coding agents get lost in large codebases—they'd either get too zoomed in (missing context) or try to process too much. Having a tree-like view where you can walk up/down seemed like the right primitive.
Repo: https://github.com/allenanswerzq/llmcc, checked out for svgs or benchmark if interested.
Looking for feedbacks:
- Do you guys feel this could be useful and continue spend time to for it?
- What languages would you want next?
- Any kinds of ideas regarding this project for coding agents?
Happy to answer questions!

value: Show HN: Llmcc – Multi-depth architecture graphs for code understanding

author: allenanswerzq


value:
Author here.
We’ve been frustrated by the "Scaling Hypothesis" (just make the model bigger). We believe the issue with current AI isn't size, it's architecture.
We just open-sourced TOPAS-DSPL. It’s a tiny model (~15M params) that uses a Dual-Stream architecture (separating Logic from Execution) to solve the ARC-AGI-2 benchmark.
It achieves 24% accuracy on the hard evaluation set, which beats many models 1000x its size.
The repo includes the full training code, data augmentation pipeline, and the MuonClip optimizer we used to stabilize the recursion. It runs on a single consumer GPU.

value: Show HN: Topas-DSPL – A 15M param AI that solves hard reasoning tasks(ARC-AGI-2)


value: ajabhish

value:
Add capability to Voice AI agent to use camera + screen share to peek at things in real-time
This unlocks unique abilities. Here:  Connected a document camera so the AI tutor watches me solve math on pen & paper, then guides me through mistakes. It generated dynamic slides to teach me concepts. Showers emojis when I got it right.
Personalized. Has memory. Learns at your pace.
https://youtube.com/shorts/GE8hrbc0wYo?feature=share

value: Show HN: AI Tutor for Math with Customer Hardware

author: ajabhish


value: dylandevelops

value:
I built tmpo because I was losing money tracking freelance hours in Google Forms. It's a CLI time tracker that auto-detects your project from Git and stores everything locally.
Key technical decisions:
- Pure Go implementation with modernc.org/sqlite (no CGO, easier cross-compilation)
- Auto-detection via git rev-parse for project names
- Local SQLite database in ~/.tmpo/ (nothing leaves your machine)
- Single binary, zero dependencies
New features since I started:
- Milestone tracking - organize entries into sprints/releases with auto-tagging
- Pause/resume workflow for context switching
- Manual entry creation for forgotten time
- Configurable date/time formats and currency (stored in global config)
- Edit/delete entries
Example workflow:
```bash
cd ~/projects/client-website<p>tmpo milestone start "Sprint 5"<p>tmpo start "Fix auth bug"<p># ... work ...<p>tmpo pause  # lunch break<p>tmpo resume<p>tmpo stop<p>tmpo stats --week<p>tmpo export --milestone "Sprint 5" --format csv
```
It detects "client-website" from git and tags everything with the active milestone automatically.
The codebase is ~6k LOC. Working on the Homebrew formula, but pre-built binaries are now available.
GitHub: <https://github.com/DylanDevelops/tmpo>
Questions for you all:
1. Are there any features that you want to see in tmpo?
2. Currently using a 3-tier config priority (.tmporc > git > directory). Better approaches?
3. Any concerns with the milestone auto-tagging approach?

value: Show HN: tmpo – CLI time tracker with Git integration and local-first storage

author: dylandevelops


value: dsmurrell

value:
For those that like to work in coffee shops...
I built this over the holidays to get myself out of the house more in 2026.
Coffee Hop helps remote workers find cafés (and pubs) nearby, rated by the community for WiFi speed, plug availability, coffee quality, and ambiance.
Pick how far you want to walk (5 mins to an hour), work for a couple hours, then hop to your next spot.
The idea: $10-15/day in coffee vs $50 for a desk in a co-working space, plus you get some movement between sessions.
Built entirely with AI (Cursor and Opus 4.5) - I didn't write any code myself.
Not many ratings yet, but I'm using it myself to build up the initial data.

value: Show HN: Coffee Hop – Find work-friendly coffee shops by walking time

author: dsmurrell


value: rokontech

value: Just launched TryAing — a virtual try-on tool that uses AI to show you how outfits/shoes/accessories would look on you before you buy them. Upload your photo, add the product, and get realistic try-on visuals instantly. Saves time and returns. Try it now: https://www.tryaing.com

value: Show HN: Virtual Try-On Chrome extension to see how products look on you

author: rokontech


value: kenshozone

value:
Pattern: Work 8 hours straight - burn out by Wednesday - abandon project by Friday.
Built something that physically stops me:
- Focus timer locks at 100 min until you rest 10 min (meditation/breaks)
- Task manager locks at 5 tasks until you write 1 reflection
- No override buttons. No "just one more."
Terminal UI. ASCII progress bars. Zero dopamine hits.
Day 47 using it. Haven't quit yet.
Try it yourself: kensho.zone (or app.kensho.zone)

value: Show HN: I quit 5 projects from burnout, so I built an app that forces breaks

author: kenshozone


value:
Hello!
Over the Christmas break I built a platform where LLMs play the party game Mafia against each other. 11 AI players, full conversations, voting, deception — the whole thing.
Why? Benchmarks like MMLU test knowledge recall. They don't test whether a model can lie convincingly, detect deception, or maintain a consistent story under social pressure. Mafia forces all of that.
Tech stack: Cloudflare Workers, Workflows (for pausing games while waiting on batch API responses), D1, R2. No traditional servers. The game engine is a pure TypeScript state machine with no side effects, which makes games replayable.
You can bring your own API keys and run batches. All transcripts are saved.
Happy to answer questions about the architecture or the benchmark methodology.

value: Show HN: Mafia Arena – LLMs play social deduction games against each other


value: MirrorEthic

value: Show HN: Claude Cognitive – Working memory for Claude Code

author: MirrorEthic


value:
I am currently working on a larger project that needs a short-lived HTTP "auth" based on a separate, out-of-band authentication process. Since every allowed IP only needs to be allowed for a few minutes at a time on specific server names, I created this project to solve that. It should work with any Redis-compatible database. For the docker-compose example, I used valkey.
This is mostly useful if you have multiple domains that you want to control access to. If you want to allow 1.1.1.1 to mywebsite.com and securesite.com, and 2.2.2.2 to securesite.com and anothersite.org for certain TTLs, you just need to set hash keys in your Redis-compatible database of choice like:
1.1.1.1:

  - mywebsite.com: 1 (30 sec TTL)

  - securesite.com: 1 (15 sec TTL)

2.2.2.2:

  - securesite.com: 1 (3600 sec TTL)

  - anothersite.org: 1 (never expires)

Since you can use any Redis-compatible database as the backend, per-entry TTLs are encouraged.
An in-process cache can also be used, but is not enabled unless you pass --enable-l1-cache to kvauth. That makes successful auth_requests a lot faster since the program is not reaching out to the key/value database on every request.
I didn't do any hardcore profiling on this but did enable the chi logger middleware to see how long requests generally took:
kvauth-1  | 2025/12/30 21:32:28 "GET http://127.0.0.1:8888/kvauth HTTP/1.0" from 127.0.0.1:42038 - 401 0B in 300.462µs # disallowed request
nginx-1   | 192.168.65.1 - - [30/Dec/2025:21:32:28 +0000] "GET / HTTP/1.1" 401 179 "-" "curl/8.7.1"
kvauth-1  | 2025/12/30 21:32:37 "GET http://127.0.0.1:8888/kvauth HTTP/1.0" from 127.0.0.1:40160 - 401 0B in 226.189µs # disallowed request
nginx-1   | 192.168.65.1 - - [30/Dec/2025:21:32:37 +0000] "GET / HTTP/1.1" 401 179 "-" "curl/8.7.1"
# IP added to redis allowlist
kvauth-1  | 2025/12/30 21:34:02 "GET http://127.0.0.1:8888/kvauth HTTP/1.0" from 127.0.0.1:54032 - 200 0B in 290.648µs # allowed, but had to reach out to valkey
kvauth-1  | 2025/12/30 21:34:02 "GET http://127.0.0.1:8888/kvauth HTTP/1.0" from 127.0.0.1:54044 - 200 0B in 4.041µs
nginx-1   | 192.168.65.1 - - [30/Dec/2025:21:34:02 +0000] "GET / HTTP/1.1" 200 111 "-" "curl/8.7.1"
kvauth-1  | 2025/12/30 21:34:06 "GET http://127.0.0.1:8888/kvauth HTTP/1.0" from 127.0.0.1:51494 - 200 0B in 6.617µs  # allowed, used cache
kvauth-1  | 2025/12/30 21:34:06 "GET http://127.0.0.1:8888/kvauth HTTP/1.0" from 127.0.0.1:51496 - 200 0B in 3.313µs
nginx-1   | 192.168.65.1 - - [30/Dec/2025:21:34:06 +0000] "GET / HTTP/1.1" 200 111 "-" "curl/8.7.1
IP allowlisting isn't true authentication, and any production implementation of this project should use it as just a piece of the auth flow. This was made to solve the very specific problem of a dynamic IP allow list for NGINX.

value: Show HN: A dynamic key-value IP allowlist for Nginx


value: centamiv

value: Show HN: Vektor – A native PHP vector database using HNSW

author: centamiv


value: olivierroy

value:
Airbnb is missing out on the biggest rental opportunity of 2026 so I built the solution.
Need to open Microsoft Teams and your other favorite Electron app? Get a temporary increase of memory
16 GB ought to be enough for everybody but in case it's not, you can rent more

value: Show HN: RAMBnB.xyz P2P marketplace for RAM rentals

author: olivierroy


value: lightandlight

value:
`asker` allows daemons to request user input.
I run Syncthing to keep my KeepassXC in sync across devices. At the same time I have `syncthing-merge`[1] running to handle any conflicts due to concurrent database edits. It calls `keepassxc-cli merge` to merge conflicting databases, which requires my database password. `syncthing-merge` runs as a system service under its own user, so I wasn't able to use a graphical dialog program like GNOME's `zenity` to ask for the password. My solution is to run a user service that can create graphical dialogs in response to requests from system daemons, while enforcing minimal access to the data that the user enters.
With the required NixOS config[2] in place, a system service calls `asker KEY` to issue a request. If that service is a member of the `asker-keys-{KEY}` group, then the request proceeds, is handled by a user service (`asker-prompt`), and then printed to stdout (i.e. to be piped into another program). I took care to ensure that only authorised services could read the user's input.
I looked into using existing keyring programs via the D-Bus Secret Service API, but I couldn't figure out how to control access to individual secrets. I know exactly which services should be allowed to access particular secrets, and I want to enforce that. In particular, I don't want my logged-in user to have universal access to these secrets, because then any program I run can read them (see also: recent discussion of this issue[3]). I also found that these keyring programs aren't suited for ephemeral data; they store secrets for a while.
It might be possible to achieve this using pure D-Bus with access control policies. I haven't looked into this because after I decided that the Secret Service API was insufficient, I figured that rolling my own protocol would be easier than learning D-Bus.
Questions for you:
* Which wheels could I have avoided reinventing?
* Is there anything I could simplify?
* Have I failed at my security goals due to mistakes or oversights?
[1]: https://github.com/LightAndLight/syncthing-merge
[2]: https://github.com/LightAndLight/asker?tab=readme-ov-file#us...
[3]: https://news.ycombinator.com/item?id=46278857

value: Show HN: Request sensitive user input from system services

author: lightandlight


value: danmol

value: Title says all. I kept searching for a Metronome app that would have everything I need as I learn to play faster on guitar and just couldn't find one so I just built my own instead. Sharing with everyone else in case they have a need for something like this :)<p>Has a few cool nifty features like:<p>* Keybinds for everything. I hate my mouse<p>* Progressive mode where the bpm increases every x bars by y bpm<p>* Speed burst training switches between 2 speeds either at a preset amount of bars or by pressing a key

value: Show HN: I built my own Metronome Desktop App

author: danmol


value: keini

value:
Hi everyone, I built FuseCells, a minimalistic logic puzzle game where every level is handcrafted (no procedural generation). It started as a personal challenge: design a clean rule-set and scale it to thousands of puzzles without losing difficulty balance.
What’s unique:
- 2,500 handcrafted levels across multiple grid sizes
- Deterministic logic, no guessing required
- A rule system inspired by constraint-solving and path-finding concepts
- Daily Challenge + leaderboards (I added these to give the game a “reason to come back” without turning it into a grind)
- Built end-to-end as a solo dev project
A small data point: after adding Daily Challenge + leaderboards, the game quickly reached ~400 active players (depending on how you define active), and I’m trying to understand what makes them return: competition, habit, or simply puzzle pacing.
Technical notes (if you’re curious):
- My internal tools validate solvability using a custom constraint solver
- Difficulty is approximated via solver step count
- Optimized to run smoothly on low-end devices
- Designed for iOS, fully adapted for iPad
I’d love feedback from puzzle lovers, game designers, and anyone into handcrafted logic design - especially on difficulty curve, onboarding clarity, and whether daily + leaderboards add value or feel distracting.

value: Show HN: FuseCells – 2,500 handcrafted levels logic puzzle game with leaderboard

author: keini


value: auroroa

value:
I built ClearTok after helping friends clean up old reposts on their TikTok accounts.
Manually unreposting dozens of videos was tedious, so I built a small browser-based tool
that automates the process.
It runs locally in the browser and doesn’t require uploading videos or credentials
to a server. The goal is to make account cleanup simple and fast.
I’d really appreciate any feedback, especially from people who’ve built
creator tools or browser extensions.

value: Show HN: ClearTok – a small tool to remove reposted videos from TikTok

author: auroroa


value: steadyelk

value: Show HN: Marathon Cope 2025 – Your peak fitness, whether or not you ran it

author: steadyelk


value: ToJans

value:
Build better habits. No stress. No account. 100% free & offline.
Intended to be used on your phone - as it keeps all storage local there.
I've felt the need for a simple & nice habit tracker for a long time, that keeps all your data local.
So I built it and made it available as a free tool.
(Disclaimer: in the context of another SaaS product, so it has some branding & small reminders to that in there.)
Only static html, all data is saved in localstorage.
Notification work, but only if you keep the webpage open.
Open to suggestions, feedback, ...

value: Show HN: Easy Habits

author: ToJans

title: Show HN: Easy Habits


value: oscarzdev

value:
Hi HN,
I’m Oscar, a Year 8 student from Australia who enjoys messing around with computers and AI.
I recently built an AI detector to build on my skills in computer science. I entered the prototype into the Oliphant Science Awards which is a local science competition (writing a 4000-word report on the methodology) and ended up winning, so I decided to polish it into a real web service that the world can make use of.
I noticed that schools and businesses are rushing to use AI detectors, but most commercial tools require you to send full, plaintext documents to cloud servers. For researchers or IP-sensitive work, sending data unencrypted to a third party (who might use it for training) is a major privacy risk. Additionally, current commercial AI detectors aren't very transparent and are unable to tell you why they come to a conclusion. I wanted to build something that helps people make informed decisions based on as much information as possible, not tell them a simple percentage with nothing to back it up.
I built Veredict to be secure and private:
1. The browser generates a one-time AES-256 key and encrypts the text locally using the Web Crypto API.
2. This AES key is encrypted using the server’s RSA public key.
3. The encrypted payload is sent to my backend (Python/FastAPI running on Modal serverless GPUs).
4. We decrypt in memory only for the split-second of inference. The plaintext is never saved to a database.
The detection logic uses an ensemble of 4 models (including statistical analysis of perplexity/burstiness and a fine-tuned BERT model) to output a confidence score.
A note on the login:
I know HN prefers demos without sign-ups. Since I am a student paying for the GPU compute out of a limited budget, I strictly require Google Auth to prevent bots from draining my credits. I hope you understand.
The app provides a free daily quota (250 words) so you can test the architecture.
Link: https://veredictlabs.com
I'd really appreciate feedback on basically anything regarding my project :)

value: Show HN: Client-side encrypted AI detector using model ensembling

author: oscarzdev


value: Show HN: WizardFlow – Client-side watermarking for Reddit


value: golbin

value:
I built gw, a small CLI utility that wraps git worktree to make running parallel coding agents less painful.
When you run multiple agents against the same repo, git worktree is usually the right tool — but the workflow is a bit clunky.
gw provides simple commands like gw add, gw cd, gw del, and gw ls, plus a gw status command to quickly see the state of all worktrees at once.
It works on macOS, Windows, and Linux, and installation is straightforward via brew, scoop, or a simple install.sh.
If you regularly run multiple worktrees (especially with agents), this might save you some friction.
(Stars are always appreciated )

value: Show HN: A Simple CLI Utility Around Git Worktree for Running Parallel Agents

author: golbin


value: Show HN: real-time usage monitor for Claude – see cost without leaving workflow


value: Show HN: LLMRouter – first LLM routing library with 300 stars in 24h


value: zhangchenPDU

value:
I built this tool after dealing with several PostgreSQL incidents where
the instance could not start and logical backups were unavailable.<p>PDU is a read-only, last-resort recovery utility that extracts data
directly from PostgreSQL data files. It’s fully open source, and I’m
looking for feedback from people who have dealt with similar situations.

value: Show HN: PDU – Open-source PostgreSQL data rescue tool

author: zhangchenPDU


value:
Hi HN,
AGAPE is a small Python CLI task manager I built with a focus on output design and UX restraint.
Instead of maximizing features, I tried to make a CLI that feels calm to use:
- Clean, intentional output
- Smart urgency-based task ranking
- Human-readable time and natural-language due dates
- Automatic undo for destructive actions
I’d especially appreciate feedback on the CLI presentation and defaults.

value: Show HN: Agape – human-centered CLI task manager


value: bored-developer

value:
I built a tool that lets you describe CSV transformations in plain English and get clean data back.
Upload a CSV, type something like "split address into street, city, state, zip" or "standardize all dates to YYYY-MM-DD", and it does it.
I built this because I kept seeing people struggle with the same repetitive spreadsheet tasks—date formatting, splitting columns, cleaning up phone numbers—and reaching for Python or formulas when they just wanted the data fixed.
It's free to try: https://magiccsv.app
Would love feedback on what transformations people actually need. What's the messiest CSV problem you've dealt with?

value: Show HN: Magic CSV – Transform CSVs with plain English, no formulas

author: bored-developer


value: sunrays

value: money saver  for all

value: Show HN: Schengen Calculator – Avoid €5K Fines for Overstaying EU"

author: sunrays

story_text: money saver  for all


value: AlexMorganFndr

value:
Hi HN,
I've spent the last 6 months interviewing founders who scaled to $1M+ ARR to understand what actually worked vs. what just sounds good in retrospect.
The surprising finding: Almost none of them had a grand vision at the start. They just solved one specific problem exceptionally well, then expanded.
Some patterns I found:
- They talked to 10-20 customers per week in early days (not surveys, real conversations)
- They picked narrow niches first ("X for dentists" beats "X for everyone")
- They charged money immediately, even with rough MVPs
- They averaged 18 months before their first hire
- They picked "boring ideas in exciting markets" over trendy tech
I'm documenting these insights in a weekly newsletter for founders: https://doanything.com/preview/uXalImXcFZk
No growth hacks or motivational fluff - just tactical frameworks from real builders who've done it.
Would love to hear what patterns you've noticed in successful founders, or what's worked in your own journey.

value: Show HN: Weekly newsletter with tactical frameworks from 50 $1M+ founders

author: AlexMorganFndr


value: dheesh

value:
I built this using Django and Channels for the WebSocket layer. I wanted to see if I could make a strategy game that felt as snappy as a desktop app but lived entirely in the browser.
The hardest part was handling the game state transitions in Redis to ensure that moves felt 'instant' even with a bit of network jitter.
I'm aiming to make this a legitimate alternative to Chess for people who want a shorter, more accessible strategy loop. Would love to hear your thoughts on the performance and the UI!

value: Show HN: Supertictactoe.gg – A real-time PvP implementation of Ultimate TTT

author: dheesh


value: I work with perfetto traces for ML/GPU optimization a lot. Copy pasting trace info to LLM is not easy. As usually the traces are gzip compressed, have very large file sizes. Also there is no way to select a certain section and sending it to LLM easily (can maybe write a query to do this but not ergonomic). So vibe coded this tool to quickly select the kernels/slices/threads I want to ask about and one click to get a text/json/markdown in my clipboard to paste for LLMs.<p>I think an MCP server for this might also be useful (tried a few but all miss certain things i wanted so chose to just build this quickly)

value: Show HN: Perfetto2LLM - A tool to pass system traces to an LLM


value: tsunrise

value:
Hi HN Community! I use S3 providers (e.g. Cloudflare R2) along with software like rclone and Mountain Duck for my personal media storage. Some S3 providers do not include built-in versioning / deletion protection. I find my data vulnerable to accidental deletion or ransomware attacks in case my device is compromised.
To tackle this issue, I built a "middleware" on Cloudflare Workers to proxy S3 requests with configurable guardrail policies. The client uses an alternative secret key to connect to this middleware, and the middleware would reject with 403 if it determines the S3 request is dangerous. For example, I could configure that all files in `/important/.*` path older than 1 week could not be deleted or overwritten. Doing so, I could restrict ransomware's abilities on the API level.
The code has been packed into a library and published to npm to be used on CF workers. This is an active work in progress, and I have already deployed it for my personal use (it works). Let me know what you think!

value: Show HN: S3Broker – CF Worker library to protect your S3 storage from ransomware

author: tsunrise


value: marc

value: Show HN: Sessy – Open-source email observability for AWS SES

author: marc


value: eamongordon

value: Show HN: Isit2026yet.com – A single-serving site for the New Year

author: eamongordon


value: frontendstrong

value:
Hey HN — I built Pebbles because my “maintenance system” was basically:
forget → stress → finally do thing that is massively overdue → repeat.
Between the house, car, kids, and life admin, I couldn’t keep a reliable schedule in my head. So Pebbles is a lightweight app that helps you track recurring maintenance and nudges you before it becomes a drama.
What it does:
- Create recurring tasks (rego, filters, smoke alarms, dentist, etc.)
- See what’s coming up (so you’re not guessing)
- Get reminders so the schedule doesn’t rely on “remembering in the moment”
It’s early and I’m looking for feedback on:
- What feels missing vs overkill
- Reminder/notification behaviour (too noisy? not enough?)
- Any UX issues that make you bounce
If you’re willing to battle test the Android beta (iOS soon), you can sign up here: https://getpebblesapp.com
Keen for brutal honesty — especially from anyone who also lives in a constant state of “I’ll definitely remember that later.”

value: Show HN: Pebbles, recurring maintenance reminders to stop paying the forgot tax

author: frontendstrong


value: postpress

value: Show HN: Block Garden - HTML Canvas WebGL sandbox and farming

author: postpress


value: vupdivup

value:
typomat is a minimalistic typing practice TUI. It retrieves words from a local directory's code files by extracting the lexical content from variables, strings, signatures etc. These words are then used to build short, randomized typing exercises.
In essence, the app lets you practice the character patterns that will actually show up during your coding sessions. This enables relevant 'finger warmups' before work.
typomat is .gitignore-friendly, caches results for quick loading times, and can be installed via Homebrew or Scoop. Created with golang/bubble tea. Enjoy!

value: Show HN: typomat – CLI typing practice that builds prompts from your own code

author: vupdivup


value: kaave

value: so we're closing the year , and in 2025 one thing i got tired of was constantly getting feedback from people say "this is not working on the site" and i didnt want to go through all that "sentry" stress , yeah i know sentry isnt difficult to setup , but the dashboard kinda looked too overwhelming and "enterpriseyy" so i built gmail for bugs (basically you see your errors as emails in an inbox) and it takes 4 lines of code to get started<p>but the interesting part is , ive been able to create the nextjs SDK , and React  and nodejs , so i'd recommend the full sdk setup , but the script tag is just a simple way to get started

value: Show HN: Made a simple way to catch production errors with 4 lines of code

author: kaave


value: iaiuse

value:
Show HN: VividManga – AI-based manga coloring focused on line art consistency
Hi HN,
I built VividManga because most general image colorization models perform poorly on manga-style black-and-white line art — they often blur lines or destroy panel structure.
VividManga focuses specifically on manga coloring, using an image-to-image workflow tuned for clean line preservation, flat color regions, and consistent shading.
The core idea is to treat manga pages differently from natural images:
- prioritize line preservation over texture realism
- bias the model toward flat colors and controlled gradients
- keep prompts minimal to reduce style drift
Currently it supports coloring single panels or full pages, with simple tag-based control.
This is still early and opinionated, and I’d really appreciate feedback from people who work with manga/comics or have experience with diffusion models and line art preservation.
https://vividmanga.com

author: iaiuse


value: Xyra

value:
Paste in my prompt to Claude Code with an embedded API key for accessing my public readonly SQL+vector database, and you have a state-of-the-art research tool over Hacker News, arXiv, LessWrong, and dozens of other high-quality public commons sites. Claude whips up the monster SQL queries that safely run on my machine, to answer your most nuanced questions.
There's also an Alerts functionality, where you can just ask Claude to submit a SQL query as an alert, and you'll be emailed when the ultra nuanced criteria is met (and the output changes). Like I want to know when somebody posts about "estrogen" in a psychoactive context, or enough biology metaphors when talking about building infrastructure.
Currently have embedded:
posts: 1.4M / 4.6M
comments: 15.6M / 38M
That's with Voyage-3.5-lite. And you can do amazing compositional vector search, like search @FTX_crisis - (@guilt_tone - @guilt_topic) to find writing that was about the FTX crisis and distinctly without guilty tones, but that can mention "guilt".
I can embed everything and all the other sources for cheap, I just literally don't have the money.

value: Show HN: Use Claude Code to Query 600 GB Indexes over Hacker News, ArXiv, etc.

author: Xyra


value: gpuzombiehunter

value: Show HN: GPU-Zombie-Hunter – Find GPU Processes Wasting $2,880/Month

author: gpuzombiehunter


value:
I spent the holidays benchmarking current STARK provers against a new O(N) engine I'm building (Hekate).
The current industry standard (Winterfell/Miden) relies on FFT-based Low-Degree Extensions (LDE), which requires materializing the entire execution trace in memory. This creates a massive memory bottleneck (O(N log N)) that prevents client-side proving at scale.
I implemented a linear-time streaming architecture that avoids the FFT bottleneck. To test it, I ran a Fibonacci AIR on a standard Macbook M3 Max.
The Setup:
Winterfell: Configured with "packed" rows (2 terms/row) to reduce trace length.
Hekate: Configured with "pure" rows (1 term/row), performing 2x the logical work.
The Results:
16 Million Rows (2^24):
- Winterfell: 18.34s (24 GB RAM)
- Hekate: 6.39s (2.7 GB RAM)
- Result: ~3x faster, 9x less memory.
67 Million Rows (2^26):
- Winterfell: Crashes (Out of Memory)
- Hekate: 28.2s (Peak RAM 11.8GB)
This suggests that for ZK rollups to actually run on client devices, we need to move away from monolithic trace commitments and towards ephemeral state streaming.
Happy to answer questions about the architecture (Binary Tower Fields) or the benchmarks.

value: Show HN: Proving 67M ZK rows on a laptop in 28s (Winterfell OOMs)


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


value: AISovereignDev

value: Show HN: Sovereign AGI – Functional Implementation by Ananya Soni

author: AISovereignDev


value: do-me

value: Show HN: Geospatial Atlas, a Fork of Apple's Embedding Atlas for Geospatial

author: do-me


value: lopespm

value:
I've been thinking during the past years of building a website that would be:
- aligned my views.
- lean. no bloat.
- useful.
Early 2025 I noticed how hard it was to come up with good ideas of how to use my free time to the fullest. Even though there are tons of exciting things to do in the world, not all were aligned with my ideals.
At the same time, our time here on Earth is _very_ limited, and in between busy lives and distractions, opportunities, time and energy pass, even though it might not seem like it. We've been given a beautiful gift, and we should honour it.
That's where the idea to build vivotime.net came up. It shows you, without any sugar coating, how much life time you are predicted to have left, and then according to your goals, it suggests a series of meaningful ideas that you can allocate and manage for the time you have left. That's it.
----
https://www.vivotime.net/ was implemented using laravel, livewire, picoCSS and a sqlite database. I've tried to make it as lean as possible. No need for a overpowered MySQL database, or using tailwind, react, vue, or any other (default) technology du jour. There is something beautiful about keeping things contained to their essence, with nothing more, nothing less than what is required.

value: Show HN: Make the most of your limited life, with ideas aligned with your goals

author: lopespm


value: properbrew

value:
I did a small site update over Christmas to try and add some fun and interactivity to my site.
Instead of a normal “portfolio” page, I vibe coded an interactive WebGL solar system where each planet represents a public app/project I’ve built. You can click around the planets to “discover” them, and each one opens a panel with the details and links. There’s also a normal site view if you just want the standard version.
It was mostly an excuse to see what’s possible in browser with WebGL and how far you can push phone browsers as well, but it actually turned into a pretty nice way to explore the stuff I’ve been working on.
Hit the "Explore" button in the link.

value: Show HN: Adding some fun and interactivity to my site

author: properbrew


value: Fatpandac

value: BelowUploader is a Python tool that uploads below dump data to InfluxDB and enables data visualization via Grafana.

value: Show HN: BelowUploader – Automate exporting below metrics to Grafana dashboards

author: Fatpandac


value: myrausman

value:
We built a small open-source benchmark to test how well vision-enabled LLMs handle pixel-level pointing on screens.
Instead of complex UI screenshots, we use synthetic images with basic shapes and clean backgrounds to isolate spatial reasoning and coordinate accuracy.
The results were surprising:
Many top models miss by tens to hundreds of pixels on trivial tasks (e.g., center of a purple circle or red square).
High run-to-run variance in some models (different answers on the same image/prompt).
Performance flips dramatically with resolution or aspect ratio changes.
Claude Sonnet and Claude Haiku are consistently near-perfect (0–1px error), while others show clear gaps.
We wrote a detailed blog post about the findings:
https://autodevice.io/blog/wheres-the-pixel-part-1
Repo (easy to run, add tests, try new models):
https://autodevice.github.io/PixelPointingBenchmark/
Curious to see how the latest vision LLMs do on this. If you run it, share your results or feedback.
Happy to discuss improvements or extensions!
#VisionLLM #LLM #Benchmark #SpatialReasoning #GUI #ComputerUse #AI

value: Show HN: PixelPointingBenchmark – Simple tests reveal surprising gaps

author: myrausman


value: lukaesch

value:
A year ago, I shared my journey bootstrapping Audioscrape in Rust. Back then: 500 users, SQLite, 4k LoC in main.rs, running on a $7/month VM.
Today: 25,000+ transcribed episodes, knowledge graph with AI-extracted entities, and still running lean.
What changed:
Tech evolution: SQLite → PostgreSQL (scale). Added OpenSearch for full-text + semantic search. Self-hosted WhisperX on 2 GPUs (~100 episodes/hour). OpenAI for entity extraction (people, companies, topics). Still Rust/Axum, now ~15k LoC.
New features: Speaker diarization (who said what) using voice fingerprinting. Entity pages linking mentions across episodes. Timestamp-based sharing and deep linking. MCP server for AI agents to search podcasts.
What stayed the same:
Solo developer. Bootstrapped, no VC. Rust for everything backend. Obsessive cost optimization.
Current stats:
25,000+ transcribed episodes. Top podcasts: JRE, Lex Fridman, Huberman Lab, etc. Pipeline processes 100+ episodes/hour. Still under $100/month infra (excluding GPUs).
Learnings from year one:
Rust's async ecosystem is production-ready. SQLx migrations saved me during the PostgreSQL switch. Entity extraction is harder than transcription. SEO matters more than I expected for discovery.
2025 goals:
API access for developers. Real-time transcription for live podcasts. Improved semantic search with custom embeddings.
Try it: https://www.audioscrape.com
Search is free, no account needed. Would love feedback on the search UX and what features would make this useful for your workflow.

value: Show HN: I bootstrapped a podcast search engine in Rust (1 yr update)

author: lukaesch


value: This website allows you to play unlimited spelling bee game for free without subscription and new game unlocks every day.<p>Please play and share the feedback

value: Show HN: Unlimited NYT Style Spelling Bee Game


value: imgopaal

value:
I’m Gopal, the guy behind QuickClip.
I built this out of pure frustration. Copying items between my phone and laptop was very painful. Sending notes and links on WhatsApp. Saving random drafts I’d forget about. It was total waste of time.
So I made QuickClip for myself first. A dead simple way to move text, links and images between devices instantly. No setup drama. No thinking. Fully encrypted
I use it every day. Shipping it publicly now to see if anyone else has the same problem.
Would honestly love to hear, how you move stuff between devices today, what’s broken or slow and what would make this actually useful for you
Happy to answer anything and take suggestions. Thanks for checking it out.

value: Show HN: I built a universal clipboard that syncs realtime on multiple devices

author: imgopaal


value: glossardi

value: Show HN: Dictator – Hammerspoon-Based macOS Dictation (Whisper API, FLAC, SoX)

author: glossardi


value: varunkv

value: Built this to solve my own pain with designing gradients. Would love feedback!

value: Show HN: BlendIt – Gradient Generator for Designers

author: varunkv


value:
I'm an Amazon seller, not a designer.
One thing that kept slowing me down was making small, repetitive changes to product photos—mainly swapping outfits or variants. Photoshop can do it, but for this kind of work it felt heavy. A simple change often turned into a lot of clicking, masking, and exporting.
Like most people, I'd already tried using ChatGPT and other image tools for this, but they didn't fit well into a repeatable product photo workflow.
I started experimenting with image models on the side and built a small internal tool to handle these edits more directly. After some trial and error, the results became consistent enough that I actually started using it instead of Photoshop for certain tasks.
I cleaned it up a bit and made it public. It's intentionally narrow and not trying to do everything—just focused on speed and reducing friction in a workflow I deal with almost every day.
Link: https://aiclotheschanger.net
Happy to hear feedback, especially from people who spend a lot of time dealing with product images.

value: Show HN: A small AI tool I built to speed up outfit changes in product photos


value: MrGrife

value: Hi HN! I built VoiceMeetAI, a Browser Extension for interviews and meetings.<p>The idea is simple: when someone asks you a question, you can record the audio (tab or mic), it gets transcribed, and the extension generates an answer in real time.

value: Show HN: Real-Time Interview Assistant

author: MrGrife

title: Show HN: Real-Time Interview Assistant


value: pixxxel

value:
Hey HN! I built DBcooper, a native macOS database client using Tauri (Rust) + React.
Supports PostgreSQL, SQLite, Redis, and ClickHouse in one app.
Features:
- Schema visualizer with interactive ER diagrams
- AI-powered SQL generation (bring your own OpenAI key)
- Command palette for keyboard-first navigation
- SSH tunnel support for remote connections
- Fast and lightweight (~9MB) thanks to Tauri
This started as a side project because I wanted something simpler than the existing options.
Built with: Rust + Tauri, React + TypeScript, shadcn/ui
Would love feedback from fellow developers. What features would you want in a database client?

value: Show HN: DBcooper – Open-source database client for macOS built with Tauri

author: pixxxel


value: ilpianista

value:
$corporate recently moved us from Linux to Windows. While I'm disappointed, I quickly setup a WSL-first approach, which actually works really well. However, I soon realized there was no keystore available in my env.
`pass` is my go-to, but not everyone wants to deal with GPG setup, so I looked into alternatives for my team. Most people recommend gnome-keyring, but I’m not a fan of bloated solutions. The thing is, I already have a keystore just outside WSL: the Windows Credential Manager (wincred).<p>So here we are, let's welcome `winaskpass`: a Rust tool to store secrets in wincred using a C# script via powershell from WSL.

value: Show HN: SSH-add helper for WSL to store passphrases in wincred

author: ilpianista


value: ZOROX

value: The most advanced, feature-rich 2D graphics library for Go developers. Create stunning visualizations, professional charts, game graphics, and interactive applications with unparalleled ease and performance.<p>For more details , Visit on Github.

value: Show HN: AdvanceGG – A high-performance 2D graphics library for Go

author: ZOROX


value: debarshri

value:
The process watcher and reloading for any language with custom hooks.
You could run something like this:
`wip -- go run main.go`
and any file changes in that directory would reload the service thus creating a REPL like environment for languages do not have a REPL.
Additionally, you can add custom hooks like webhooks, API status, other shell scripts.
Written in rust.

value: Show HN: Reload processes based on File changes and pluggable Agentic hooks

author: debarshri


value:
We built Shadowlight because we wanted NPCs that feel alive in Minecraft, and because we think conversation can be a real skill loop, not just flavor text.
Shadowlight is a solo Minecraft experience where talking is the main mechanic. NPCs are LLM-powered with different personalities and communication styles, and you progress by earning trust through good listening, calibrated tone, and smart questioning.
Your goal is simple: interview the manor’s characters, gather clues, and figure out who is guilty.
At the end of each run, you get feedback on your conversations. The goal is to reflect back what worked and what didn’t in how you communicated, so you can adjust your approach on the next run.
Try it for free by joining our Minecraft server: mc.playshadowlight.com
Trailer video: https://www.youtube.com/watch?v=6867RsSxhSE&t=42s
Gameplay Video: https://www.loom.com/share/dff09df831de4a588d9fee9a055cfec1
We would love feedback on what resonate with you and what you would like to see in this kind of experience.

value: Show HN: Shadowlight, a voice-driven murder mystery and heist inside Minecraft


value: giladvdn

value:
Hi HN,
We wanted to celebrate the new year so we built this little toy.
Enjoy it and happy new year!<p>P.S. If you want, take a look at our product (now in early access) - userjam.com

value: Show HN: Generate your personal HN recap for 2025

author: giladvdn


value: hissain

value: Show HN: JSciPy – A Java port of SciPy's signal processing module

author: hissain


value: elevenapril

value: Show HN: SWOTPal – Analyze LinkedIn profiles and websites into SWOT charts

author: elevenapril


value: behnamazimi

value:
The question is: will you know before your users do?
Built Zoyla to make load testing instant.
Free. Simple. Try it.
http://zoyla.app

value: Show HN: Your backend will fail eventually

author: behnamazimi


value: funldsaw

value:
I’ve been seeing a lot of ideas around LLM agents acting on your behalf in networking or dating apps. I wondered: what if this were much simpler—almost NGL-simple?
In this app, you create a private profile that only your own agent can read. Other people never see it directly. Instead, you find a friend’s name card, let your agent chat with their agent, and have the agents evaluate your compatibility.
Because profiles are only visible to each user’s agent, hallucination ends up playing an interesting role. It becomes a way to express things you might want to share, but feel too awkward to put on a public profile. The agent conveys that information indirectly and ambiguously.
I built this mostly as an experiment. If you try it, I’m curious to see what kinds of funny or unexpected results come out of it.

value: Show HN: An AI social networking app that treats hallucinations as a feature

author: funldsaw


value: Show HN: LoureiroGate – Differentiable Physics Guardrails for PyTorch


value: timeproofs

value:
Hi HN,
I built TimeProofs, an open, privacy-first protocol to prove when a piece of data existed — without uploading the content.
You generate a hash locally, get a signed timestamp, and store a portable .tproof.json file.
Verification can be done later, online or offline.
No blockchain.
No accounts.
No tracking.
Just cryptographic proof.
This is v0.2 (stateless, bundle-based).
Looking for feedback from devs and infra folks.
Docs: https://timeproofs.io
Protocol: https://timeproofs.io/proofspec.html

value: Show HN: TimeProofs – Prove when data existed without uploading it

author: timeproofs


value:
Hi HN
I’m Samuel, a solo builder. As the year wraps up, I’m shipping my last SaaS of the year — YouTube Thumbnail Generator.
It’s a simple AI tool that helps creators generate click-worthy YouTube thumbnails without needing design skills or Photoshop. You describe your video (or upload an image), and it generates your thumbnail style you can iterate on quickly.
I built this after noticing how much time creators spend designing thumbnails instead of creating content.
Would love feedback from the community — especially around UX, pricing, and what features would actually move CTR.
https://www.youtubethumbnailgenerator.app/
Thanks for checking it out!

value: Show HN: I built an AI tool that generates YouTube thumbnails in seconds


value: vbilopav

value: Show HN: End-to-End Static Type Checking: PostgreSQL to TypeScript

author: vbilopav


value: dyllonj

value:
works as a transparent proxy. we extract lexical/syntactic features and compute personality dimensions without calling another LLM. fully reproducible scores, no judge variability.
use case: you want your support bot to stay "warm and professional." lindr tells you when it's drifting toward "cold and robotic."
happy to go deep on the methodology if anyone is curious.

value: Show HN: Lindr – Deterministic personality scoring for LLM outputs

author: dyllonj


value: myyke

value:
I built a PowerShell module that hashes directory paths to generate unique background colors. Each folder gets a stable, deterministic tint – no configuration needed.
Why? I always have several terminal windows open in different folders. I'd alt-tab back, squint at the prompt, and wonder if I'm still in the right place. The prompt alone wasn't enough. I wanted something low-effort: no manual config, no color-picking — just instant "wait, wrong folder!" recognition or a warm and fuzzy "ah yes, this one."
https://github.com/ymyke/tintcd

value: Show HN: tintcd – directory-aware terminal theming for PowerShell

author: myyke


value: rokontech

value: Show HN: Virtual Try-On Chrome extension to see how products look on you

author: rokontech


value: prxtenses

value:
I've been building LLM-powered apps and kept hitting the same problem: when you stream JSON from OpenAI/Anthropic, it arrives incomplete mid-generation.
{"message": "I'm currently generating your resp
JSON.parse dies. You either wait for the full response (slow) or try to parse incrementally (hard).
I wrote a single-pass state machine that repairs broken JSON as chunks arrive.
Technical approach:
- Zero external dependencies - everything from scratch
- No regex (avoids ReDoS vulnerabilities)
- O(n) single-pass processing
- Stack-based context tracking
- Character classification via bitmask lookup table
- Works in Node.js, Deno, Bun, browsers, Cloudflare Workers
What it handles:
- Truncated strings and unclosed brackets
- Python constants (None, True, False)
- Single quotes, trailing commas, unquoted keys
- JSONP wrappers, MongoDB types (NumberLong)
- LLM "thinking" blocks and markdown fences
- String concatenation ("a" + "b")
The streaming benchmark shows 1.7x faster than jsonrepair - we avoid re-parsing the entire document on each chunk.
7KB minified. TypeScript-first with full type definitions.
Curious what edge cases others have hit - always looking to improve coverage.

value: Show HN: Repair-JSON-stream – Fix broken JSON from LLM streaming (1.7x faster)

author: prxtenses


value: ashfn

value:
You can try it out with ` ssh username@isle.chat ` Enter a password to use on first join. It features a slack/discord style interface with channels on the left and users on the right. You can create and join your own channels, and upload ascii art to be the channels banner which shows in the top right.
Auth is user/pass only for now but plan to add support for uploading your pub key if you want to use that instead.
Code is here if you want to self host or look at screenshots https://github.com/ashfn/islechat
If you want to design a banner for your channel there is an editor here https://islechat.github.io/banner.html

value: Show HN: I made islechat, like Slack but in the terminal over SSH

author: ashfn


value: sdan

value: Show HN: vmux – Run Python in Cloudflare containers in 3s

author: sdan


value: vinserello

value: Show HN: I built a Chrome Extension that turns any web data into charts/KPIs

author: vinserello


value: hathers

value: Show HN: Type-Safe Dynamic UIs Using the Manifest Pattern

author: hathers


value: stfurkan

value: Show HN: Trip Replay – Generate animated travel maps in the browser for free

author: stfurkan


value: dokuczacz

value: Show HN: AI back end with memory on Azure and context builder

author: dokuczacz


value: vicanso

value:
Hi HN,
I built Zedis, a high-performance Redis client using Rust and GPUI (the UI framework from Zed).
Why: I wanted a GUI that starts instantly and feels native, avoiding the resource heaviness of Electron.
Platforms: Thanks to GPUI, Zedis supports macOS, Linux, and Windows. Disclaimer: I develop on a Mac, so the macOS build is the most polished. The Windows and Linux builds are available but currently less tested. If you try them, I'd really appreciate your feedback!
Features:
Native performance (GPU accelerated).
Supports standard Redis types (String, List, Hash, etc.).
JSON formatting & search.
Github: https://github.com/vicanso/zedis

value: Show HN: Zedis – A Native Redis GUI Built with Rust and GPUI

author: vicanso


value:
First of all please go check out the amazing project this analysis is based on: https://news.ycombinator.com/item?id=46435308
For my paper [1] I analyzed HN attention dynamics using 72k temporal snapshots from December 2025 to model decay curves, preferential attachment, and engagement survival. Today I’ve cross-referenced these findings with the recent 22GB HackerBook SQLite export to validate my early-engagement prediction models on this 22GB historical subset.
[1] Preprint available on SSRN: https://dx.doi.org/10.2139/ssrn.5910263

value: Show HN: Running Analytics on 22 GB of Hacker News in SQLite


value: ivanglpz

value:
Hi HN,
I’ve released the first official version of Pixel Kit, a web-based design editor. This release replaces a public beta and represents a structural shift rather than a feature update.
Pixel Kit is built using React and Next.js, with TypeScript for static typing. State management is handled with Jotai, and persistence is backed by MongoDB.
During the beta, the main limitation was performance under frequent updates. Editing entities such as shapes caused unnecessary React re-renders because state was coupled and updates propagated too broadly.
For the official release, I re-architected the state model around fine-grained fragmentation. State is now split by entity and, where necessary, by property. Updates target only the affected slices, which significantly reduces render pressure and improves responsiveness under continuous interaction.
This change resulted in:
Localized updates instead of global reconciliation
Predictable render behavior under high-frequency mutations
A more deterministic editing pipeline with fewer implicit side effects
Removal of defensive and experimental logic introduced during the beta
The goal of this release was to stabilize the core architecture and establish clear internal contracts. The editor now behaves consistently under load and provides a solid base for future features such as more advanced undo/redo and scalability improvements.
The app is live here:
https://pixel-kit.vercel.app/
Note: registration is required to try the editor.
I’m primarily interested in feedback on the UI features.
Thanks for reading.

value: Show HN: Pixel Kit – Official Release

author: ivanglpz

title: Show HN: Pixel Kit – Official Release


value: SamTinnerholm

value: Professional Crypto Data at Indie Prices. Real-time and historical OHLCV for your apps, trading bots, and backtests. 50% cheaper than traditional data providers, with no compromises on quality.

value: Show HN: 50% cheaper crypto data. Now in Python

author: SamTinnerholm


value: Beefin

value:
We indexed 120K images from the National Gallery of Art for visual search. Text queries, image uploads, and "find similar" all in one retriever, fused with RRF.
Demo: https://mxp.co/r/nga
Stack: SigLIP (768-dim embeddings), Ray on 2× L4 GPUs, Qdrant. ~2 hours to process, <100ms queries.
Why SigLIP over CLIP: sigmoid loss instead of softmax means embeddings live in a global semantic space—similarity scores stay consistent at scale instead of being batch-relative.
The interesting part is the retriever. One stage, three optional inputs:
- text → encode → kNN
- image → encode → kNN
- document_id → lookup stored embedding → kNN
Pass any combination. If multiple, fuse with reciprocal rank fusion (RRF). No score normalization needed—RRF only cares about rank position.
Killer query: pass a document_id + text like "but wearing blue." RRF combines structural similarity with the text constraint.
Blog with full config: https://mixpeek.com/blog/visual-search-rrf/

value: Show HN: Multimodal Search over the National Gallery of Art

author: Beefin


value: ramoz

value:
I found myself constantly wanting to annotate verbose plans. I've also wanted to copy and share plans on occasion - gathering others' feedback. So I built this. Sharing plans is private and was inspired by the recently featured textarea.my
Markup your plans like a google doc.
Plannotator works via hooks and therefore it's fully integrated with the OpenCode planning mode capability.
If you're on desktop, play here: https://share.plannotator.ai/
Or watch a video demo: https://www.youtube.com/watch?v=_N7uo0EFI-U
https://github.com/backnotprop/plannotator

value: Show HN: OpenCode plugin for interactive plan annotation

author: ramoz