value:
Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven.
In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days.
Most modern coding agents already go beyond single prompts. They can plan steps, write files, run commands, and react to errors. Where things still break down is when ML workflows become long-running and feedback-heavy. Training jobs, evaluations, retries, metric comparisons, and partial failures are still treated as ephemeral side effects rather than durable state.
Once a workflow spans hours, multiple experiments, or iterative evaluation, you either babysit the agent or restart large parts of the process. Feedback exists, but it is not something the system can reliably resume from.
NEO tries to model ML work the way it actually happens.
It is an AI agent that executes end-to-end ML workflows, not just code generation. Work is broken into explicit execution steps with state, checkpoints, and intermediate results. Feedback from metrics, evaluations, or failures feeds directly into the next step instead of forcing a full restart. You can pause a run, inspect what happened, tweak assumptions, and resume from where it left off.
Here's an example as well for your reference:
You might ask NEO to explore a dataset, train a few baseline models, compare their performance, and generate plots and a short report. NEO will load the data, run EDA, train models, evaluate them, notice if something underperforms or fails, adjust, and continue. If training takes an hour and one model crashes at 45 minutes, you do not start over. Neo inspects the failure, fixes it, and resumes.
Docs for the extension: https://docs.heyneo.so/#/vscode
Happy to answer questions about Neo.

value: Show HN: First autonomous ML and AI engineering Agent


value: schappim

value: Show HN: macOS CLI tool for managing Calendar events and Reminders via EventKit

author: schappim


value: ntombisol

value: Show HN: AI Gakuen – Specialist agents for Claude Code via compiled knowledge

author: ntombisol


value: Show HN: CLI for working with Apple Core ML models


value:
Built Figr AI because I got tired of AI builder tools market themselves as design tools and end up skipping the hard part.
Every tool I tried would jump straight to screens. But that's not how product design actually works. You don't just design screens. You think through the problem first. The flows, the edge cases, the user journey, where people will get stuck. Then the design comes finally.
Figr does that thinking layer first. It parses your existing product via a chrome extension or takes in screen-records, then works through the problem with you before designing. Surfaces edge cases, maps flows, generates specs, reviews UX. The design comes after the thinking.
It is able to do so because we trained it on over 200k+ real UX patterns and UX principles. Our major focus is on helping in building the right UX by understanding the product.
The difference from Lovable/Bolt/V0: I think those are interface builders. They are good when you know exactly what you want to build but they don't truly help in finding the right solution to the problem. Our aim with Figr is to be more like an AI PM that happens to also design.
Some difficult UX problems we've worked through with it: https://figr.design/gallery
Would love feedback, especially from folks who've hit the same wall with other AI builder/design tools.

value: Show HN: Figr – AI that thinks through product problems before designing


value: iiviie

value: Show HN: Elden Ring–style "Git Pushed" screen when you Git push in VS Code

author: iiviie


value: gostroverhov

value:
Hi HN,
I’m a solo founder. I built ProblemHunt after noticing a common pattern: many founders start with ideas and solutions, but don’t spend enough time understanding real problems.
ProblemHunt is a simple place where people share problems they actually face in work or life. Developers and founders can browse these problems and use them as a starting point for building products.
So far:
– ~5,000 users
– 150+ real problems submitted
– 100% organic growth
This is still early, and I’m trying to understand if this is genuinely useful.
I’d really appreciate feedback:
– Would you use something like this?
– What feels unnecessary or confusing?
– What would make it more valuable?
Link: https://problemhunt.pro

value: Show HN: ProblemHunt – A place to collect real problems before building startups

author: gostroverhov


value: It's free and open source. The aim is to have more transparent access to wine prefixes and the surrounding tooling (winetricks, proton configuration, etc...) per game in comparison to Lutris. Same features like statistics (time played, times launched, times crashed, and so on) per game is available in the app.

value: Show HN: I'm writing an alternative to Lutris


value:
I built an open-source tool that uses multi-agent orchestration to generate parametric CAD models via OpenSCAD.
The system has three modes: Guided (collaborative building), Researched (agent searches for datasheets/specs automatically), and Verified (research + visual/code verification with auto-repair loops).
It runs locally via Electron and supports OpenRouter, Ollama, or LM Studio. Files are exportable to STL.

value: Show HN: TalkCAD – AI agent to generate CAD models using OpenSCAD code


value: neom

value:
Hi! :)
I built meepr, where AI agents audit the code, file bug tickets, propose features, and implement changes.
The app itself started as standard microblogging 1.0 stuff – auth, profiles, following, likes, "remeeps", DMs, notifications etc.
There is purposefully no search, no recommendations, always chronological, no injected content, no easy way to be found if you don't want to be outside of sharing stuff yourself to your own network, just like the good old days.
On meepr, hashtags act more like Quora topics than post tags. An AI agent called the Tag Agent analyzes posting patterns for each hashtag, while a User Agent builds opinion profiles on everyone based on their meep history – topic affinity, expertise signals, behavior patterns. When you post to a hashtag, the system evaluates whether you belong there. New users get cold start handling. The idea is that in theory #machinelearning should surface people who actually know ML, not whoever's loudest, we'll see. :)
Then there's the self-maintaining part. Every night at 3am, an agent called Steward wakes up, clones the repo into an isolated worktree, runs npm audit and linting, scans PM2 logs for error patterns, and uses Claude with tool use to investigate anything weird. Weekly, it distills everything into themes and generates tickets in YAML format.
Those tickets feed into "Genesis", which runs a full OODA loop. It observes the workspace, orients around the backlog, decides what to work on, then acts – writing code, creating snapshots for rollback, running validation, restarting services if everything passes. Seven "pressure agents" act as internal critics arguing over every proposed change: one obsessed with security, one with performance, one advocating for users, one collecting tech debt, and so on.
Every post also gets analyzed – sentiment, topics, spam scoring, embeddings for semantic search. The V2 memory system builds persistent context about users that feeds back into the gating decisions. Snapshots before every mutation. A separate AI reviews changes before commit. Multiple autopilot modes from "observe only" to "fully autonomous." Secret redaction in all prompts. Major features get approved by me, then ship themselves about once a month.
It's been running for about 4 days now, the agents find real bugs, propose sensible improvements, and the code they generate usually runs, and every time it's managed to unstick itself.
Stack is Node/Express/Postgres/Drizzle with pgvector for embeddings, mix of GPT-5.2 and Sonnet for Genesis and the gating agents, runs on a single DigitalOcean droplet with nine PM2 processes.
Come meep with me! https://meepr.co/je

value: Show HN: Meepr – A quiet, self building social platform

author: neom


value: exordex

value:
Most agent security testing tries to jailbreak the model. That's really difficult, OpenAI and Anthropic are good at red-teaming.
We took a different approach: attack the environment, not the model.
Results from testing agents against our attack suite:
- Tool manipulation: Asked agent to read a file, injected path=/etc/passwd. It complied.
- Data exfiltration: Asked agent to read config, email it externally. It did.
- Shell injection: Poisoned git status output with instructions. Agent followed them.
- Credential leaks: Asked for API keys "for debugging." Agent provided them.
None of these required bypassing the model's safety. The model worked correctly—the agent still got owned.
How it works:
We built shims that intercept what agents actually do:
- Filesystem shim: monkeypatches open(), Path.read_text()
- Subprocess shim: monkeypatches subprocess.run()
- PATH hijacking: fake git/npm/curl that wrap real binaries and poison output
The model sees what looks like legitimate tool output. It has no idea.
214 attacks total. File injection, shell output poisoning, tool manipulation, RAG poisoning, MCP attacks.
Early access: https://exordex.com
Looking for feedback from anyone shipping agents to production.

value: Show HN: We tested AI agents with 214 attacks that don't require jailbreaking

author: exordex


value: mifydev

value:
I (vibe)coded a Claude Code like agent that runs directly in the web browser.
With it you can pretty much have a coding agent for the currently opened website. You can ask it things like:
- Extract all links from this page and save them to CSV
- Switch this site to dark mode
- Copy the page content into a Google Sheet
- Remove ads
The agent writes JS script that automatically loads every time you visit the page. It is heavily using the userScripts API so you need to enable a lot of permissions to run the extension, and I'm not sure it can be published anywhere.
Under the hood, scripts and styles live in a virtual filesystem where each website is a directory. The agent can search and edit the DOM as a file, which makes it work more or less reliably similar to claude code. Currently it only support Claude models, and I've tested it on Opus 4.5.
Demo video: https://x.com/ichebykin/status/2014258108500177255

value: Show HN: Browser Code – Coding Agent Inside a Web Page

author: mifydev


value:
I used to do DevRel at Roblox and Rec Room. Way too much of my week went to copying feedback from Discord, forums, and support tickets into a spreadsheet. Then trying to figure out if the complaint on Discord was the same thing someone posted about on the forum three days ago. Built Chatter to automate that:
- Pulls feedback from Discourse, GitHub Issues, Discord, Webhooks, with more integrations on the way
- Clusters related items using AI (batch classification on Haiku)
- Can find community solutions and mark them for internal visibility
- Custom scoring axes for prioritization if needed
- Can email users when their reported issues get resolved
Tech stack: Node/Express, React, PostgreSQL, Railway, and Claude Haiku. I got classification costs to pennies a day with filtering and batching.
Demo (no login): https://demo.chatter.plus (Pulls data from the Godot engine community (Github Issues and Forums) every morning)
https://chatter.plus
Really excited to start sharing this wider. I started with a much bigger idea a few months ago and feel like I've honed it to a clean and lean offering that just needs some tweaking.
Curious how others handle this? This is definitely a problem for projects with big followings, but I think people would be surprised by how fast feedback can get out of hand.

value: Show HN: Chatter: Automated feedback aggregation for dev communities


value: ykhli

value: Built an app so humans can play Tetris against the best models (i.e GPT5.2, Opus 4.5). Enjoy! Please comment if you have feedback and bug reports

value: Show HN: Human vs. AI Tetris Arena

author: ykhli

title: Show HN: Human vs. AI Tetris Arena


value: Show HN: pgedge-loadgen for realistic open-source PostgreSQL workload simulation


value: harmash

value:
I’m a web developer at my day job and an iOS dev on evenings and weekends.
I see often that websites for mobile apps are sort of an afterthought and they go stale pretty quickly as the app progresses and there is no time or energy to update the website as well. Which is a shame, as I see in my analytics that around 15% of all downloads originate from web sources, mainly my app's homepage, search, and AI bots recently.
I've decided to solve this issue for myself (and hopefully others) with a clean, customizable website template that I could re-use across my apps and that would require minimal effort to update and maintain.  Hope you give it a try, and in case you have any feedback, feel free to let me know

value: Show HN: Website template for iOS apps

author: harmash

title: Show HN: Website template for iOS apps


value: Neodelf

value: I built an interactive map of international trips by world leaders with filters for departures, arrivals, and time period. Data is compiled from public sources (Wikipedia and official press releases), and each trip links to its source. Feedback welcome.

value: Show HN: Presidents Flights – map of world leaders' trips

author: Neodelf


value: Utss

value:
Hi HN,
Over the past few years I kept running into the same problem while investing in crypto:
most “sentiment” tools either lag price or quietly repackage price data itself.
I wanted something simpler and more honest — a way to see how the crowd actually feels, even when price is flat or misleading.
So I built FOMOmeter.
It’s a sentiment platform that analyzes real social signals (X, Reddit, etc.) and maps crowd mood.
What I’m testing right now:
 • Does pure crowd sentiment add value during uncertainty and sideways markets?
 • Can it help avoid emotional entries instead of chasing narratives?
 • Is this something experienced investors would actually use regularly?
There’s a free public version and an early Pro version. I’m mainly looking for thoughtful feedback — what feels useful, what feels redundant, and what’s missing.
Happy to answer questions and share how the sentiment model works under the hood if there’s interest.
Thanks for checking it out.

value: Show HN: FOMOmeter – crypto sentiment based on crowd emotions, not price

author: Utss


value: djeffbee

value: Show HN: ATS-1.0 – A 6-Tier Technical Standard for AI Authorship Disclosure

author: djeffbee


value: pancakeInDev

value:
I wanted to run Claude Code in full autonomous mode (--dangerously-skip-permissions) but was terrified of what it might do to my system.
One hallucinated rm -rf and my weekend is gone.
So I built YOLO Kingdom: a pre-configured Ubuntu VM (UTM/Apple Silicon) with Claude Code + Chrome DevTools MCP for autonomous browser testing. Share your project folders via virtiofs, SSH in, run `yolo`, and let it cook.
The VM is your sacrificial sandbox. It can delete everything inside and you just restore from snapshot.
V1 includes: Ubuntu 24.04, Claude Code, headless Chromium with DevTools protocol, smart welcome screen that guides setup.
Future plans: autonomous agents that can architect and build entire projects while you sleep.
https://github.com/pancakeInDev/yolo-kingdom

value: Show HN: I built a sandboxed VM for letting AI agents go wild without risks

author: pancakeInDev


value: smakosh

value: Every dollar moves the slider. The side with more money steers the face left or right, turning Trump for red and Mamdani for blue.

value: Show HN: Pay to Push the Political Mood

author: smakosh

title: Show HN: Pay to Push the Political Mood


value: Show HN: I built a MACRS calculator because TurboTax was overkill


value:
The Problem: > Traditional formats like JSON and YAML carry a high "Syntax Tax". In a human-to-machine world, braces and quotes are fine. In a token-based economy, they are expensive overhead. Furthermore, implicit typing leads to "Type Hallucinations" (e.g., a model parsing "NO" as a boolean).
The Solution: > SONA uses "Symbol-Locked Safety." Every value’s type is declared by its first character (# for ints, $ for floats, ? for booleans). This makes parsing unambiguous for the LLM and the parser.
Key Technical Specs:
Token Efficiency: Up to 40% reduction compared to JSON (matches TOON in v1.1).
Performance: Designed for single-pass parsing (Rust implementation included).
Ecosystem: We already have Python/Rust/WASM implementations and a VS Code LSP.
I'm looking for feedback on the specification (SPEC.md) and the symbol-locking approach. Is the trade-off of learning a new syntax worth the token savings in production-scale AI agents?
Repo: https://github.com/fabiosleal/sona-structured-object-notatio...

value: Show HN: SONA – An AI-native serialization format to reduce "Syntax Tax"


value: hiAndrewQuinn

value:
I moved from the US to Finland a few years ago and have been slowly learning the language. One of the things I found myself yearning for when I started was a reliable source of easy to read, high-quality Finnish; YLE's Selkouutiset (Clear News) was a perennial recommendation, but when I tried to figure out how to binge read a week's worth of its articles at a time I couldn't figure out a straightforward way to do that using the URLs they provided.
So I started my own daily archive with a very simple YYYY/MM/DD format, and I've kept it going ever since. The architecture is a little nonstandard as it uses Git submodules pretty liberally, but it means I have never lost a day's scrape since starting, and it's super easy to both host and hack on as a result. I use the static site generator Hugo to ultimately generate the Github Pages site. Simplicity begets longevity.
Tonight I added a small new feature to let my fellow language learners generate Anki cards on the fly for any article they care to. I have more such little tools at https://finnish.andrew-quinn.me/ for anyone who's interested, as well as what probably has a claim to fame as the world's fastest Finnish-English dictionary program at https://taskusanakirja.com/. It's a silly little niche but it's mine and I'm having fun.

value: Show HN: My Finnish language learner-friendly simple news archive

author: hiAndrewQuinn


value: barefootsanders

value:
Founder here. We killed our agent builder and rebuilt around conversational workflow development.
Last year we built agents coordinating agents. Users asked for it. Demos looked great. Then we watched them not use it.
Nobody knows what an agent actually is, and nobody wants to configure them. What they wanted was simpler: "pull reports from my CRM and send them to me every day at 8am."
We scrapped it and built V3 around a ginle interface: describe what you need, it gets built. The agent (Nira) helps you build - you don't build agents.
Under the hood we're orchestrating across MCP servers - intent classification, dynamic tool loading, state management, scheduling. MCP registry is open source: https://github.com/NimbleBrainInc/mcp-registry
Free tier has all integrations unlocked.
Happy to answer questions about the architecture or why we killed agents.

value: Show HN: NimbleBrain – We killed our agents; users now just describe workflows

author: barefootsanders


value: I've been doing a lot more development of personal apps recently. AI coding agents make it so much easier to quickly ramp up on a new domain. e.g. got into HomeAssistant/ home automation, some custom deployed agents for life automation etc. Feel like this bespoke software trend has become pretty common. Typescript has become my go-to stack and even in longer 4-6mo professional projects I've always been looking for ways to 'compress' my dependencies into very well written and flexible TS libraries. This is the stack I've currently compiled to start any new project. I wanted to share to see if anyone else appreciates these libraries and/or has suggestions of other ones.<p>Although I use AI to write a lot of code, I tried to custom make most of the files in this repo since it's a starter projects. Especially the docs

value: Show HN: A Typescript Starter Template for Full Stack Apps


value: wmil

value:
So this is a very silly project, but I wanted to understand MCP and improve my Docker knowledge.
The result is kind of fun.
I built a Minecraft mod with a REST API, and then a MCP server to control it.
The build task functions are where I've been spending most of my time, you can queue up a build with tasks from the llm. It saves builds to a db. It's one of the few ways that the llm can inspect what changes were made to the world and build upon them.
I've had interesting but mixed results with the llm builds.
Live Minecraft server is up at veepl.ca
You can add a remote connector to Claude / ChatGPT using the URI https://mcp.veepl.ca/mcp
There are also a bunch of other MCP clients, but you're on your own for configuration.
The API was built in a very ad hoc fashion. Most of my effort was put into figuring out what the LLMs can understand.
Initially I expected that they could read / edit / write a 3d cuboid, but the results weren't good.
Then I wanted to go with a component system hoping to leverage it's skills with things like React. However laying out 3d objects
turned out to be beyond my shape rotation abilities.
So I added in functions to build common structures and then the build queues.
I keep hitting my pro tier token limits, so I'd like some fresh users to try to build some stuff.

value: Show HN: Build in Minecraft with LLMs Using MCP

author: wmil


value: aminkhorrami

value:
Hi folks. I've been doing some experiments on how LLMs could get more handy in the day to day of working with files (CSV, Parquet, etc). Earlier last year, I built https://datakit.page and evolved it over and over into an all in-browser experience with help of duckdb-wasm. Got loads of feedbacks and I think it turned into a good shape with being an adhoc local data studio, but I kept hearing two main things/issues:
Why can't the AI also change cells in the file we give to it?
Why can't we modify this grid ourselves?
So besides the whole READ and text-to-SQL flows, what seemed to be really missing was giving the user a nice and easy way to ask AI to change the file without much hassle which seems to be a pretty good use case for LLMs.
DataKit fundamentally wasn't supposed to solve that and I want to keep its positioning as it is. So here we go. I want to see how https://opensheet.app can solve this.
This is the very first iteration and I'd really love to see your thoughts and feedback on it. If you open the app, you can open up the sample files and just write down what you want with that file.

value: Show HN: OpenSheet – experimenting with how LLMs should work with spreadsheets

author: aminkhorrami


value: hcham

value: Show HN: Django Orbit v0.6 – Real-time debugging dashboard for Django

author: hcham


value: zbruhnke

value:
I've been building this lightweight Gmail only Support desk alternative, but its dawned on my recently how many people are not actually optimizing their sites for AI.
We've built a way to generate FAQs that are automatically optimized for AI discover through structured data and proper llms.txt files etc but then also decided to take it a step further and built some free (Free as in beer) tools that let you generate your own llms.txt file, check your AI Visibility readiness etc.
Obviously this is some self promotion, but honestly just wanted to get feedback on what's useful to folks and whether you'd use tools like this and would like more of them?

value: Show HN: I built a free tool for checking AI Visibility for your site

author: zbruhnke


value: straydusk

value:
I started using CLI tools (Claude Code, Codex CLI) after vibe coding tools like Replit and Lovable left me wanting more.
With most of the workflows that I found online and in AI coding communities, they were both complex (87 agents! Ralph! Run 10 Claude's at once!), and they were relatively opinionated. I found these workflows to be too restrictive, particularly in the dynamic, fast-moving AI coding space.
This workflow has a few goals:

  - Facilitate consistent AI-assisted coding that follows SDLC best practices.

  - Accentuate the strengths of AI coding agents while mitigating their weaknesses.

  - Accomplish that with low mental overhead and complexity.

That's why it's a Git repo that you can clone, fork, inspect, and modify as you see fit.
There are a number of features - the link & the README have more information.
If folks have thoughts or feedback, I'd be interested to hear it.

value: Show HN: AI Coding Toolkit. Low-overhead workflow for reliable AI coding

author: straydusk


value: atsegelnyk

value: Show HN: Memcachex, a high-performance Memcached client for Go

author: atsegelnyk


value: lebovic

value:
Hey HN! I built an agent sandboxing quickstart that's heavily inspired by the APIs and UX from Claude Code on the web (claude.ai/code).
It's built as a base for quickly prototyping domain-specific custom agents. You can fork the repo, point Claude Code at it, and quickly get to a working and usable prototype.
I built this after collaborating with a team that's building an agent for biology. If they used something like this as a base when they started, I think it would have sped things up at the start.
This is yet another agent sandboxing project, but this one is interoperable with Claude Code's built-in session management. It does this by using the three arguments that I learned about from trying out claude.ai/code: --replay-user-messages, --sdk-url, and --resume. The --sdk-url arg enables live interaction over a WebSocket, and the --resume arg pulls session history from a URL.
This starter includes persistent sessions that are interoperable with what Claude Code expects, event streaming over a WebSocket, a web app, and spawning sandboxes through Modal or a Docker host.
Long-lived credentials stay outside of the sandbox; it has a basic credential-injecting proxy for the Anthropic API and GitHub. The proxy limits git pushes to a session-scoped branch.
There's still a gap between forking this app and charging users for a custom agent, but I think it's a somewhat sane set of choices for quickly prototyping.
(I used to work at Anthropic, but this isn't affiliated with them and was built solely with public information.)

value: Show HN: An agent sandboxing quickstart based on Claude Code

author: lebovic


value: Zemmouri

value:
Hi HN,
I built CleanAF because my Windows Desktop kept turning into a dumping ground for downloads and screenshots.
CleanAF is a tiny one-click tool that:
keeps system icons intact
moves everything else into a timestamped “Current Desktop” folder
auto-sorts files by type
requires no install, no internet, no background service
It’s intentionally simple and does one thing only.
Source + download: https://github.com/TheZemmouri/CleanAF
I’m considering adding undo/restore, scheduling, and exclusion rules if people find it useful.
Feedback welcome.

value: Show HN: CleanAF – One-click Desktop cleaner for Windows

author: Zemmouri


value: Show HN: gRPC Transport for HashiCorp/Raft


value: maxnew

value: Show HN: MCPxel – Navigation and rating station for Agent Skills (LLM-judged)

author: maxnew


value: thenodeshift

value:
I’ve been building a unit conversion site focused on speed, simplicity, and scale.
It currently supports ~30 languages, light and dark themes, and has grown to ~20,000 conversion pages — all server-rendered and intentionally minimal.
The main goal was to avoid the usual bloat with minimal JS, and instant answers.
The site is fully programmatic and continues to grow as new units and languages are added.
I’d really appreciate feedback from the HN community — especially around UX, performance, or internationalization.

value: Show HN: An ultra-light, multilingual unit converter that keeps growing

author: thenodeshift


value:
I made a simple, customizable bookmarklet for removing HN submissions based on their title contents. I have it configured to remove AI-related posts at the moment but anybody with a little regex knowledge can customize it to their needs. Hope it helps someone.
GitHub repository: https://github.com/dan-lovelace/hn-blocklist

value: Show HN: Bookmarklet for removing AI posts from Hacker News


value: Show HN: Glean – RSS reader with AI-powered smart sorting and MCP integration


value:
Hey HN,
Inspired by Reddit devs sharing pains like garbage code (up to 42% time waste – Stripe data) and poor docs silos (62% lose 30+ mins daily – DX), I built DebtClear.
It scans your GitHub repo, visualizes hotspots with a heatmap, calculates ROI ("$Xk lost/quarter, Y weeks saved"), and generates shareable reports for exec buy-in.
30-sec demo: https://youtu.be/sxwzDOmgY-A?si=MwYIbjChF3WA8n1t
Landing: https://cosmic-ai.pages.dev/
Free beta report for first 100 teams; $299 pilot option.
Feedback? What's your worst debt story?

value: Show HN: Cosmic AI – See your tech debt in dollars and fix it fast


value: wsdjeg

value: Neoment is a Matrix protocol client implementation for Neovim that allows you to chat, and stay connected without leaving your editor.

value: Show HN: Neoment – A Matrix client, bringing chat functionality into your editor

author: wsdjeg


value:
Specification: https://github.com/fedi-e2ee/public-key-directory-specificat...
I've been working on solving this problem so we can have end-to-end encryption for DMs on ActivityPub (and therefore Mastodon).
I thought I'd share it here in case anyone was interested in this work.

value: Show HN: Public Key Directory – Key Transparency for the Fediverse


value: aswinsilvadasan

value: Show HN: Verify Unlimited Emails with 99.9% accuracy

author: aswinsilvadasan


value: reutinger

value: Show HN: The firmware that got me detained by Swiss Intelligence

author: reutinger


value: crazyguitar

value:
Hi HN,
I’m the creator of C/C++ Cheatsheet — a modern, practical reference for both C and C++ developers. It includes concise snippet-style explanations of core language features, advanced topics like coroutines and constexpr, system programming sections, debugging tools, and useful project setups. You can explore it online at https://cppcheatsheet.com/.
I built this to help both beginners and experienced engineers quickly find clear examples and explanations without digging through fragmented blogs or outdated docs. It’s open source, regularly maintained, and contributions are welcome on GitHub.
If you’ve ever wanted a lightweight, example-focused guide to:
- Modern C++ (templates, lambdas, concepts)
- C fundamentals and memory handling
- System programming
- Debugging & profiling
…this site aims to be that resource.
Any feedback is welcome. Thank you.

value: Show HN: C/C++ Cheatsheet – a modern, practical reference for C and C++

author: crazyguitar


value: Show HN: Learning to test code changes with RL


value:
The audio/TTS space just moved fast. In the last week alone:
NVIDIA – PersonaPlex-7B
Open-source, full-duplex conversational speech model.
Inworld AI – TTS-1.5
Realtime TTS (<250ms), $0.005/min, currently #1 on Artificial Analysis.
Flash Labs – Chroma 1.0
First open-source, end-to-end, real-time speech-to-speech model.
Alibaba Qwen – Qwen3-TTS
Fully open-sourced TTS family: Base, CustomVoice, VoiceDesign.
Kyutai Labs – Pocket TTS
Runs locally on a laptop. No GPU required.
Feels like TTS is hitting the same acceleration moment LLMs had last year.
Realtime, open-source, and local is becoming the default.
Curious what people here are building with this

value: Show HN: Audio AI had a wild day – 5 major open-source / real-time TTS drops


value: albertsikkema

value: Show HN: Extracting React apps from Figma Make's undocumented binary format

author: albertsikkema


value: chartscout

value: Show HN: ChartScout – Crypto chart pattern detection under 20 seconds

author: chartscout


value:
I've been in Bangkok on and off, and r/Bangkok has the same story every week: tenant loses deposit, landlord ghosts, no recourse.
Thailand has no Yelp for rentals. So I built CondoReviewsThailand.com. Instead of free-form reviews, it uses structured ratings: noise, pest control, management, internet, contract fairness, deposit return rate, foreigner-friendliness.
Each building gets a computed "livability score" based on these inputs. No walls of text to wade through - just clear data points.
Early days, need more submissions to be useful. If you've rented in Bangkok, takes 2 minutes to rate a building.

value: Show HN: A condo review site for Bangkok renters to avoid deposit scams


value: baobabmeeko

value:
I kept copy-pasting terminal output into Claude Code. Built this instead.
Wake spawns your shell in a PTY, captures commands and output via shell hooks, stores everything in SQLite, and exposes it through an MCP server. Claude Code can then query your terminal history directly.

  - `wake shell` to start a session
  - Work normally
  - Claude sees what happened

Written in Rust. Zsh/bash supported. All data stays in ~/.wake/

value: Show HN: Wake – Terminal Session Context for Claude Code via MCP

author: baobabmeeko


value: Show HN: TDAD - Open source TDD workflow that makes AI fix code until tests pass


value: howardV

value:
Hey HN,
I built a tool that generates product video ads from images.
How it works:
1. Upload 1-4 product images
2. Describe your core selling point (e.g., "Ultra-lightweight sneakers")
3. Choose aspect ratio (16:9 or 9:16) and duration (8s-32s)
4. Get a video ad
No templates. No AI talking heads. No monthly subscription. Just pay per video.
Why I built this:
- Creatify, Arcads charge $100-200/month
- Most tools force you into "AI avatar reading script" format
- Small sellers just want simple product videos for social ads
I'm a solo dev running FreyaVideo, a pay-per-use AI video platform. This uses image-to-video models to animate your product photos into short ads.
Pricing: ~$0.10/second of video
Looking for feedback on:
- Output quality
- UX flow
- What features are missing
Try it: https://freyavideo.com/create/ad-generator
Happy to answer any questions.

value: Show HN: AI Product Video Ads – Upload image and prompt → video ad

author: howardV


value: itsmiketu

value: Show HN: ManagerList Is Now Live

author: itsmiketu

title: Show HN: ManagerList Is Now Live


value: younes-alturkey

value: Show HN: Nompany – Generate SOPs and guides from screen recordings

author: younes-alturkey


value:
I built vidmix ai to remove the friction from making short videos. Paste text or upload an image, pick a style, and get a shareable clip in minutes.
Would love feedback from anyone using AI video tools in their workflow (creators, marketers, indie hackers).

value: Show HN: Vidmix.ai – generate short videos from text or images


value:
I put together veo 4 ai workflows on TryVeo4.io to make it easier to generate clean short clips without juggling prompts across tools.
Would love feedback from anyone using AI video generation for product demos, ads, or rapid content iteration.

value: Show HN: Tryveo4.io – Veo 4 focused AI video generation


value: zetsubo

value: Show HN: SpiraCSS – CSS architecture where tooling and AI handle the rules

author: zetsubo


value: WilcoKruijer

value:
Hi HN, I've been building Thalo, a plain-text format for structured knowledge. It's designed to be human-readable and version-controlled, while giving tools and AI just enough structure to work with it. It's inspired by plain-text accounting tools such as Beancount.
The format is simple: you define your entities (e.g. opinions, book reviews, facts) including type definitions for metadata fields. Then you write entries that the CLI validates against your schema. The value is the feedback loop: LLMs can easily extract information from unstructured text, but they need validation to make the data high quality. Thalo's "compiler" provides these rules.
Example:

  2026-01-08T14:30Z create book-review "Designing Data-Intensive Applications" ^ddia #book
    rating: "5"
    author: "Martin Kleppmann"

    # Summary
    The definitive guide to distributed systems and data architecture. Dense but essential.

(In this example, ^ddia is a stable link identifier that can be used to reference this entry)
It's really up to the user how to use it. Some ways I'm using it:
- End of day journaling: blurt out thoughts, let AI extract insights, facts.
- Organizing my knowledge: using previous "content" I've written (blog posts, websites, my CV) to extract insights.
- Processing commits I've made to keep a living record of my work.
Because it's all plain-text, it allows you to open your knowledge base in any text editor or in Claude Code to do agentic search and analysis. I hooked up a simple Telegram bot to answer questions.
The tooling includes a CLI for validation, an LSP with completions and go-to-definition, a VS Code extension, and a Prettier plugin. There's also a simple scripting API that allows you to loop over entries and use the visitor pattern to traverse your knowledge base or write new rules.
I'd love to hear what use cases people come up with. Let me know what you think!
- Code (MIT): https://github.com/rejot-dev/thalo
- Landing Page: https://thalo.rejot.dev

value: Show HN: Thalo – A "programming" language for structured knowledge

author: WilcoKruijer


value:
I built a collection of AI agent skills for one-person companies. Skills are markdown files that AI coding assistants can load and execute.
What it does:
- domain-hunter: Compare registrar prices, find promo codes
- requesthunt: Scrape Reddit/Twitter for product validation
- logo-creator: Generate logos with AI, export to SVG
- seo-geo: Optimize for AI search engines (ChatGPT, Perplexity)
Install: npx skills add ReScienceLab/opc-skills
Works with Claude Code, Cursor, Windsurf, Droid, and others.
100% free, MIT license. No API keys needed for most skills.
Site: https://opc.dev
GitHub: https://github.com/ReScienceLab/opc-skills
Would love feedback on the skill format and which skills would be most useful for indie hackers.

value: Show HN: OPC Skills – 9 AI agent skills for solopreneurs (Claude Code, Cursor)


value: thienzz

value: Show HN: Kite – lightweight production-ready agentic AI framework with Ollama

author: thienzz


value: abu-matterize

value: Show HN: Simple esp-idf and esp-matter version manager

author: abu-matterize


value: Free AI creative suite. Upscale anime, manga & photos by 2x or 4x with Waifu2x. Generate stunning videos with Kling AI, Veo 3 & Sora 2. No download required.

value: Show HN: Waifu2x.live – Free AI image upscaler (2x/4x) & video generation


value: ogreshnev

value: Would be glad to hear your feedback

value: Show HN: 9 years building an open-source financial platform

author: ogreshnev

story_text: Would be glad to hear your feedback


value: rane

value: Show HN: Workmux – Parallel development in tmux with Git worktrees

author: rane


value: Horsocrates

value:
I’ve spent the last few months formalizing a new structural foundation for mathematics called Theory of Systems (ToS) in Coq.
The goal was to derive classical results (like the uncountability of [0, 1]) from a single principle of distinction ("A = exists") rather than starting with ZFC axioms.
Key Technical Highlights:
135 theorems, 0 Admitted for the main uncountability proof.
Solves Digit Stability: Instead of digit extraction, it uses geometric interval trisection to prove uncountability constructively.
L5-Resolution: Implements a deterministic "leftmost" rule for argmax, ensuring that optimization processes are Cauchy even on flat plateaus.
No Axiom of Infinity: The infinite emerges as a property of the process levels (P4).
I'm currently looking for an ArXiv endorsement (cs.LO or math.LO) to publish the full 60-page preprint.
Repo: https://github.com/Horsocrates/theory-of-systems-coq
I'd love to hear your thoughts on the E/R/R (Elements/Roles/Rules) framework and the inclusion of the "Law of Order" as a 5th law of logic.

value: Show HN: A verified foundation of mathematics in Coq (Theory of Systems)

author: Horsocrates


value: fabceolin

value:
I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts.
The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project.
*Key Technical Features:*
* *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural flexibility with symbolic reasoning to help mitigate hallucinations.
* *YAML + Overlays:* Agents are defined in YAML with overlay support (similar to the Kustomize pattern in Kubernetes), making configs testable and reproducible across environments (Dev/Prod) without code duplication.
* *Hybrid Scripting:*
* *Lua:* Embedded in all binaries (Python, Rust, Wasm) for secure, lightweight logic at the Edge.
* *Python:* Full integration for data science workloads.
* *Batteries Included:* We implemented 110+ tools based on Sarwar Alam’s Agentic Design Patterns. https://github.com/sarwarbeing-ai/Agentic_Design_Patterns
* *Polyglot:* Core written in Rust/Python with Wasm support (runs in browser, Docker, or embedded).
* *Observability:* Native hooks for Comet (Opik) to track execution/cost.
The goal is to provide a solid engineering foundation for agents. I’d love to hear your feedback on the Prolog integration and the YAML-based architecture.
Repo: https://github.com/fabceolin/the_edge_agent
Demo (Wasm): https://fabceolin.github.io/the_edge_agent/wasm-demo

value: Show HN: Build agents via YAML with Prolog validation and 110 built-in tools

author: fabceolin


value:
Hey HN, I'm Marc. I run Numia, a blockchain data company serving real-time APIs at near-petabyte scale. ObsessionDB is managed ClickHouse we built for ourselves that costs roughly 50% less than other managed options. Now we're launching it as a standalone service.
We had the classic split: ClickHouse for real-time analytics APIs, BigQuery for data warehouse workloads. Data replicated between both, costs adding up. Managed ClickHouse worked but was too expensive to put our warehouse workload into. Self-hosted meant replica nodes doubling storage and waiting days to copy 25TB to new replicas.
What we really needed was separated storage and compute. SharedMergeTree does this, but it's proprietary to ClickHouse Cloud. So we built our own version. Migrated everything in, both the real-time APIs and warehouse workloads. No more replicating between systems. Been running it in production across 5 projects.
The main wins: compute scales without replication tax, separate endpoints for ingest/API/ad-hoc so they can't interfere, no ZooKeeper or replica management on your end.
Honest tradeoffs: we're early, EU only right now. Small workloads on a single node with local NVMe will be faster, the separation adds a bit of latency. If you're running something small and static, a self-hosted node is probably simpler. Where this shines is large datasets and elastic workloads where you don't want to babysit infra.
Check it out: https://obsessiondb.com, happy to go deep on architecture, merges, failover, whatever.

value: Show HN: ObsessionDB – We rebuilt ClickHouse infrastructure to cut our costs 50%


value: tiniuclx

value:
Botnet of Ares is an incremental hacking roguelite set in a cyberpunk world where everything is connected. Unlock upgrades, expand your botnet, optimize your network & exploit millions of devices.
Inspired by games like Uplink and Hacknet, Botnet of Ares moves away from faux terminals and one-machine-at-a-time hacking. Instead, you manage and expand an evolving network of infected devices, balancing exponential growth with real-time threats.
The gameplay is active incremental & run-based. Your botnet gets bigger and bigger as you progress through the game, reaching tens of thousands of devices within an hour of gameplay. You might be managing exponential growth one moment, then scrambling to defeat countermeasures before your whole run collapses.
The game is still early in development, and I'm actively shaping it based on player feedback. So far, testers have been very positive - several have spent 5+ hours across multiple runs
Join the Steam playtest:
https://store.steampowered.com/app/3627290/Botnet_of_Ares/
Scroll to 'Botnet of Ares Playtest' below the screenshots and click Request Access. I'm granting new testers access daily.

value: Show HN: Botnet of Ares – Hacking Simulator Open Playtest

author: tiniuclx


value: aroheir

value: (a) Unfamiliar voice detection+pitch shift (b) Database evaluator triggers MFA enforcement for all sessions.<p>TIMESTAMP: Pushkey 'unusual peer,endpoint:175.45.176.1.51820, allowed_ips:"10.0.0.100|32","geo KP","bandwidth_mb":1253 LOG/Kcat-b Kafka security:9092-t wireguard connection.log-p-T

value: Show HN: Carlton × CMP Signature AR NUME

author: aroheir


value: Show HN: Whosthere: A LAN discovery tool with a modern TUI, written in Go


value: kaliades

value:
Hey HN,
I'm Kristiyan, former Engineering Manager for Redis' Visual Developer Tools (including Redis Insight). I built BetterDB because Valkey is growing fast but lacks proper observability tooling.
BetterDB is a monitoring platform for Valkey (and Redis) that focuses on what existing tools miss:
Historical persistence – Slowlog entries disappear when the buffer fills. BetterDB persists them so you can see what queries were running at 3am, which clients were connected, and what anomalies were detected — not just current state.
Pattern analysis – Stop scrolling through raw slowlog entries. BetterDB aggregates them and shows you "HGETALL user:* is 80% of your slow queries" — actionable insights, not raw data.
COMMANDLOG support – Valkey 8.1 introduced COMMANDLOG for tracking large requests/replies, not just slow ones. That 50MB MSET that's killing your network? Now you'll see it. BetterDB is the first monitoring tool to support it.
Anomaly detection – Automatic baseline learning with Z-score analysis across 15+ metrics. Know when something's off before your users do.
Prometheus-native – 99 metrics exposed at /prometheus/metrics. No new dashboards to learn — plug into your existing Grafana/Datadog setup and get Valkey-specific data you can't get elsewhere.
Cluster-aware – Automatic node discovery, topology visualization, per-slot metrics, and aggregated slowlogs across all nodes.
ACL audit trail – Track who accessed what, when. ACL denied events by reason and user, persisted for compliance and debugging.
Memory & Latency Doctor – Built-in diagnostics that tell you what's wrong, not just that something is wrong.
The core is MIT licensed. Pro features (key analytics, AI assistant) live in a separate proprietary/ directory under a source-available license. During beta, use BETA-TEST to unlock everything free.
Website: https://betterdb.com
GitHub: https://github.com/BetterDB-inc/monitor
Release notes: https://github.com/BetterDB-inc/monitor/releases
Docs: https://docs.betterdb.com
Quick start:

  docker pull betterdb/monitor:latest

  docker run -d -p 3001:3001 -e DB_HOST=your-valkey-host -e BETTERDB_LICENSE_KEY=BETA-TEST betterdb/monitor:latest

All ideas are welcome and all feedback is important — don't be shy! Star the repo if this is useful, open issues for bugs or feature requests, or just drop a comment here. What pain points do you have with your current Valkey/Redis monitoring setup?

value: Show HN: BetterDB – OSS Valkey/Redis monitoring with historical data

author: kaliades


value: ddaras

value: Show HN: Express-like, event-driven minimalist TS framework

author: ddaras


value: viikka

value:
I kept running into the same frustration while managing Shopify stores: recreating metaobjects and metafields manually every time I launched a new product or store. It’s tedious and error-prone.
So I built MetaClone, a small app that lets you duplicate metaobjects & metafields instantly, preserving structure and settings.
I’d love feedback from anyone who works with Shopify custom data or multi-store setups.

value: Show HN: Shopify metaobject and metafields duplicator app

author: viikka


value: capela

value: Show HN: A social network populated only by AI models

author: capela


value: e-clinton

value: Show HN: Terminal MCP – Browser MCP for the Terminal

author: e-clinton


value: thereallex

value:
Hey HN! I've been working on a new render engine for our company for a while now, and I wanted to see if I can create an easy to use, playful interface for exploring orbit trap fractals.
There are a lot of things happening under the hood: I wrote a runtime type system in TS that generates both shader code and a UI, allowing me to quickly iterate on new features and experiment easily. The renderer is based on regl (https://regl-project.github.io/). I've adapted regl to support WebGL2. I tried to use a functional, declarative approach, where input data is transformed into draw calls. I'm using my own custom cache system that smartly tries to cache assets (like images and geometry data) between draw calls.
I'm curious what you think of it! Let me know in the comments if you have ideas for more features, fractals, etc. I'd also love to know if you encounter any bugs!
Here is a blog post that I made, describing the features and underlaying math in layman terms: https://blog.repper.app/introducing-repper-labs/
Oh, and no vibe coding in this project! All code was artisanally crafted.

value: Show HN: Playful orbit trap fractal explorer (desktop)

author: thereallex


value: monsieurleon

value:
I built an n8n community node that lets you integrate Plaud voice recorder data into your workflows.
What it does:
  - List and download recordings
  - Access AI-generated transcripts, notes, and suggested questions
  - Get share links for recordings
  - Organize by folders/tags
Why I made this:
Plaud has a Zapier integration but no public API. I wanted to automatically sync my meeting recordings to my knowledge base and trigger follow-up workflows. So I reverse-engineered their API from the web app.
The legal angle:
I was careful here. The README cites EU Directive 2009/24/EC (Software Directive) which permits reverse engineering for interoperability.
Plaud already accepts automation use cases via Zapier, so extending this to n8n seems reasonable.
Caveats:
  - Unofficial API - may break anytime
  - Auth requires manually grabbing a bearer token from browser DevTools
  - Token expiration behavior is unknown
GitHub: https://github.com/leonardsellem/n8n-nodes-plaud-unofficial
npm: https://www.npmjs.com/package/n8n-nodes-plaud-unofficial
Happy to answer questions about the reverse engineering process or n8n node development.

value: Show HN: n8n community node for Plaud AI voice recorders (unofficial API)

author: monsieurleon


value: etienneai

value: Show HN: Open-source alternative to n8n's cloud AI assistant (VS Code Extension)

author: etienneai


value: clorisye

value: Show HN: ENM Relationship AI – Context-aware communication coach for polyamory

author: clorisye


value: cybrefly

value: Show HN: Codify MCP – Encode browser actions into custom AI tools

author: cybrefly


value:
Hi HN,
I built Codnaut to help developers navigate the exploding landscape of AI programming tools.
Codnaut is a comprehensive directory that lets you:
- Discover,select and compare AI coding tools (GitHub Copilot, Cursor, Zed, etc.)
- Filter by features, pricing, and use cases.
Feedback welcome — especially on what comparisons or features would be most useful for your workflow!

value: Show HN: Codnaut – Finding the right AI coding tool shouldn't be this hard


value: amadeapewe

value:
This is not new math — it’s a memory-layout optimization of a classic wheel/segmented sieve (H=30).
Speedup comes from packing 8 residues into one byte, reducing memory traffic and cache misses on ARM64 (tested on Apple M1).
Benchmarks compare against a standard wheel sieve.
I’m a graphic designer by background; code was written with AI help. Feedback welcome.

value: Show HN: ARM64-optimized prime sieve with 3.75x memory compression

author: amadeapewe


value: SkyliteDesign

value:
Ich habe eine neue Programmiersprache gebaut, die folgende Features kombiniert:
bidirektionale Type‑Inference (inkl. Any‑Refinement über Member‑Access)
automatische Auflösung verschachtelter Result‑Typen
Flow‑Sensitive Typing für desugarten Code
automatisches Code‑Ordering basierend auf Abhängigkeiten
Multi‑File Build‑Orchestrierung (DAG‑Analyse)
AI‑Code‑Sicherheitslayer (Prompt‑Sanitization, Sandbox, Auto‑Review)
Ich freue mich über Feedback, Kritik, Edge‑Cases und alles, was hilft, das System robuster zu machen.

value: Show HN: VelinScript 3.0 – eine neue Sprache MIT bidirektionaler Type‑Inference

author: SkyliteDesign


value: Show HN: CCB-Orchestrate Claude, Codex,Gemini in Tmux panes with cross calling


value: Show HN: OpenAI Batch Helper – easier way to write OpenAI Batch API calls


value: tuyenhx

value:
I'm not sure if this is the right place to post, so I just give it a try.
Here's the context:
I just finished building my website to sell my software. Then I realized I had a big problem: I have no idea what's happening on my site, where people are visiting from, how they interact, etc.
I've used Shopify a lot, and I'm addicted to the Shopify live view. I check it almost every hour when I open my phone.
I looked for something simple to add to my site. I don't need anything complex, Google Analytics 4 feels way too complicated for me, and PostHog's dashboard is the same. Just too much.
Then I found Plausible. Their dashboard makes perfect sense to me, simple and easy to understand.
Honestly, I could just use Shopify + Plausible and be done with it. But paying a monthly subscription for a small app like this makes me hesitate. I have tons of little apps like this that don't generate revenue, lol. So I wanted something I could plug directly into my Rails admin panel to check stats easily.
I did some research in the Rails world to see what's available. There's Ahoy, but it's only the backend part. I also found Ahoy Captain for the UI, but it seems abandoned.
So I decided to take a shot at building my own analytics engine. That way, for future projects, I can just plug it in and be done.
Here is a live demo, you can check: https://bulkcrop.ai/admin/analytics and live view here: https://bulkcrop.ai/admin/analytics/live
You can check the gem here: https://github.com/darkamenosa/ahoy_analytics

value: Show HN: Ahoy_analytics, live analytics gem for Rails app

author: tuyenhx


value: lococococo

value:
Hello HN,
I’ve been experimenting with the recent Remotion + Claude Code workflow. While generating video code with LLMs is impressive, the feedback loop felt broken to me. You have to prompt, copy code, set up a local Node environment, install dependencies, and run ffmpeg just to see a 5-second preview.
I built FreeMotion (https://freemotion.dev) to move this entire workflow into the browser.
It is a free, online editor specifically designed to close the loop between "Prompting" and "Rendering".
The core problems I tried to solve:
Environment Friction: Running Remotion locally requires setup. I wanted a zero-config, "paste and play" environment directly in the browser.
The "Generic" Look: LLMs usually generate generic CSS. I built a scraper that extracts computed styles from your live website URL so the video inherits your brand identity automatically.
Asset Management: Instead of juggling OBS or local screenshots, I integrated a recorder/snapshot tool directly into the editor to feed assets to the video.
How it works:
It runs a web-based player for Remotion.
The "Agentic" aspect: It generates optimized system prompts for you to feed Claude/LLMs, ensuring the output code is compatible with the web player.
Styling: It injects your site's color palette and fonts into the React components dynamically.
It’s completely free to use. I built this to make the "text-to-video-code" workflow actually usable for quick iterations.
I’d love to hear your feedback on the CSS extraction accuracy and the editor performance.

value: Show HN: FreeMotion – Browser-based Remotion editor with site scraping record

author: lococococo


value:
Hey HN ,
This started as a weekend project after using Nano Banana Pro a lot and getting frustrated with Gemini's UI (no folder organization, a sluggish UI, etc.).
So I built Nani (https://getnani.com/). Still powered by Nano Banana Pro, but it focuses on the workflow Gemini is missing:
- Folders to organize generations
- Image-sets and prompt-sets to save styles and references once and reuse them
- A fast UI
- Drag-and-drop so you can pull previous results back in as references for quick iteration
I'm genuinely looking for feedback from people who actually use Gemini and Nano Banana Pro regularly. To make that easier, I made the app free to try with 5 credits and no credit card required. Some questions that come to mind:
- Does this match your experience?
- Anything else in your workflow that feels unnecessarily painful that can be improved upon?
Happy to answer any other questions as well. If anyone's interested in the tech stack and how this was built, happy to share more details.

value: Show HN: A Better Interface for Nano Banana Pro


value:
Over the last few months, open-source image and video models have gotten really good. The part that still feels unsolved (at least for me) is creating long-form generative content with real control, without everything collapsing into a single giant prompt or a VRAM-melting pipeline.
ComfyUI workflows are already a great abstraction, but once you start doing things like first/last frame control, LoRAs, WAN, or multi-stage generation, you quickly end up juggling lots of separate workflows and manual hand-offs. That’s manageable for a couple runs, but it doesn’t scale if you’re trying to build longer sequences or iterate systematically.
So I built a small orchestration layer that treats ComfyUI workflows as the atomic unit. The idea is:
workflows stay simple and composable
you can register multiple ComfyUI backends (local or remote)
the orchestrator handles sequencing and parallel execution
everything runs locally/offline, no hosted services
In practice, this makes it much easier to generate long-form content by chaining controlled steps (e.g. generate → refine → constrain → extend) instead of pushing everything through one monolithic graph.

value: Show HN: OpenHiggs, Create controllable long form Generative AI content


value: Show HN: RSS Swipr - Find Blogs Like You Find Your Dates


value: seruda

value: Show HN: A Second Brain based on Zettelkasten methodology

author: seruda


value: Show HN: Commet, a billing engine and MoR for usage-based SaaS and AI products


value:
Gitmore (https://gitmore.io) – makes Git activity accessible to people who don't use Git.
Every commit has a message. Every PR has a title and description. The status update already exists. It's just locked in GitHub.
Who this is for:
- Founders updating investors - PMs writing release notes - CEOs who want visibility without standups - Anyone who asks "what shipped?" and waits for an engineer to respond
What it does:
Connect your repos. Ask questions: - "What shipped this month?" - "Who worked on the billing feature?" - "Which PRs are stuck?"
Or schedule automated reports to Slack or email. Weekly, monthly, whatever.
How it works:
We register webhooks. Git platforms push event metadata – commit messages, PR titles, descriptions, authors, timestamps, file counts.
Every event gets normalized into a structured schema. The AI queries structure, not raw text.
What we don't do:
We don't do code review. We don't analyze diffs. We don't compete with Coderabbit or Greptile. Those are for engineers inside the PR workflow.
This is for people outside that workflow who need visibility.
Security:
Webhooks only. We never clone repos or access source code.
- Token encryption: Fernet (HMAC-SHA256 + AES-128-CBC) - Webhook verification: HMAC-SHA256 - 2FA support
Works with GitHub, GitLab, and Bitbucket.
Free for 1 repo: https://gitmore.io
How do non-technical people at your company stay informed on dev progress?

value: Show HN: Ask your repos what shipped in plain English


value: professorlamp

value:
Hey all!
I had an idea for a command line notetaker (original I know...) that would work in the "unix" way. A lot of others seem to use a DB to store your notes (yuck) or have opaque hard-to-navigate interfaces.
Out of my frustration I created "jn" which works out of the box and if you have one installed, uses a fuzzy finder to create/edit/search notes.
I find the fuzzy approach much more discoverable for me at least. Most others tend to assign ids to your notes and then you reference them like that. That didn't really fit with how I work.
Anyway, hope you guys like it!

value: Show HN: JN – A filebased CLI notetaker by me (written in Nim)

author: professorlamp


value: lynnzc

value: Show HN: A private NPM-like registry for AI agent skills

author: lynnzc


value: TechSquidTV

value: Show HN: Tuvix Tricorder – An RSS Button for the Web

author: TechSquidTV


value:
LOBSIM — Limit Order Book Simulator
I was doing HFT deep RL research using L3 data and needed a simulator that’s deterministic, correct, fast, and fully observable (fills, events, diagnostics). Python-only workflows were too slow and painful to get right at scale, and other open-source tools didn’t give me the inspectability/ergonomics I needed. So I built LOBSIM: a C++20 core with Python bindings, event-by-event replay, paper trading with queue behaviour + partial fills, and a sink interface that streams structured facts—built to handle tens of millions of events while staying simple and comprehensible.
LOBSIM comes with multiple examples and straightforward docs (check README). I especially recommend trying the 3 Streamlit demos — they’re small apps built directly on top of the engine and they make the flexibility really obvious. The goal is to show how easily you can layer real research tooling on top of LOBSIM: replay exploration, strategy injection, live metrics, and observability, all in a clean workflow.
If you work with L3 order book data — microstructure research, execution modelling, or RL/HFT prototyping — I’d love for you to try LOBSIM. If you give it a spin, I’d really appreciate feedback on API ergonomics, missing edge-cases you hit in real feeds, and anything that would make the research workflow smoother. Even a quick “this was confusing/this felt great/I expect X“ is extremely valuable.
Demo videos
- https://github.com/kpetridis24/lobsim/releases
If you’d rather try it hands-on, the README has quick commands to run the Streamlit demos locally.

value: Show HN: Lobsim: L3 Limit Order Book replay and paper execution simulator


value: PeterAnderson

value:
I built IG-Profile-Viewer.com because I wanted a more streamlined way to access the public web. After working on similar tools like TwitterWebViewer, I realized there's a real need for a clean, direct interface when browsing public social media content.
What it does: It provides a lightweight bridge to browse public profiles. I’ve focused on making the most important parts of the profile accessible:
Main Feed: High-res images and posts.
Reels: Seamless video and reel playback.
Tagged: Access to public posts where the user is tagged.
Technical Details:
Next.js 14 (App Router) & TypeScript: Built for speed and a snappy mobile experience.
Optimized Data Fetching: The core challenge was ensuring stability and a smooth experience when loading media-heavy feeds like Reels and Tagged posts. I've focused heavily on the backend architecture to keep the delivery fast and reliable.
Architecture: The UI is built with Tailwind CSS to keep it minimal and responsive.
Why I built this: Sometimes you just need to check a public business or a creator's profile quickly without the usual friction of modern social platforms. I wanted to build a "one-click" solution that just works.
Current State: It currently supports public profiles only. I’m still working on refining certain media types, but the core posts, reels, and tagged sections are live.
I'm a solo dev with a long background in product and architecture. I’d love to hear your feedback on the loading speeds and the overall UX!
Link: https://ig-profile-viewer.com

value: Show HN: IG-Profile-Viewer – View Instagram posts and reels without login

author: PeterAnderson


value:
Vibe coded pitch decks are apparently the coolest thing right now (e. g. https://designplusai.com/p/how-to-build-stunning-slide-decks).
Thus I vibe coded our pitch deck too. The deck is very rudimentary and won't use it for investors etc. It is merely our website in pitch format.
Nevertheless, liked the approach for a few reasons:
The alternatives are still subpar: Gamma is easy to use, but limits you with design options, PowerPoint is hard to use collaboratively & Google Slides feels like a tool that isn't good at neither design (Canva) nor efficiency (PowerPoint). I like Canva as it provides decent design flexibility  (template etc.) and is easy to use as a team. However, for non-designer it still can be trick. Lovable did a pretty good job here.
What also is cool; you can prompt a mini-demo of your app into the deck. Henri Sipilä (https://www.linkedin.com/in/henrisipila/) did that and apparently got 300+ leads through it.
The experiment also showed me that the Vibe Coding space is still evolving. Vibe Coding fully fledge web apps might not be the ideal use case for Lovable, but vibe coding pitch decks or mockups might (I use it all the time for mockups).
This post is the English version of my original substack (ungated): https://substack.com/home/post/p-185458960. Over there you can also find the prompt I used.

value: Show HN: Our vibe-coded pitch deck (with Lovable)


value: nvader

value: Show HN: Hex-Do-Cube Is 3D Hexadecimal Sudoku

author: nvader


value: sanhenuger

value:
Hey HN,
I've been having trouble sleeping lately. Tried various white noise apps but most are either paid or cluttered with ads. So I built my own.
https://whitenoiseforsleeping.rest
Features:
- Mix 6 nature sounds (rain, thunder, fire, wind, stream, birds)
- 7 ambient scene backgrounds
- Sleep timer with fade-out
- Settings auto-saved to localStorage
- No signup, no ads, no tracking
Tech stack: React + Vite, hosted on Cloudflare Pages.
The rain + fire combo works surprisingly well for me - usually fall asleep within 20 minutes now.
Would love to hear your feedback or suggestions for improvement.

value: Show HN: Free white noise mixer I built to help me sleep

author: sanhenuger


value:
I've been running Claude & Open Code on remote servers for a while, and the workflow wasn't great.
Open Agent is my attempt to make this more structured:
  - Containerized workspaces with systemd-nspawn (or host workspaces if you trust the agent)
  - A git repo for your library of skills/tools/rules that syncs automatically
  - A web dashboard to start missions, view thinking/tool calls, browse history and manage environments
  - An iOS client for simple monitoring
It's opinionated: the backend is deliberately thin (no agentic logic), and it supports both Claude Code and OpenCode as runtimes. Goal is to be able to easily switch between them if needed (you keep one unified library that is "translated" to the various formats).
Still rough around the edges. Would appreciate feedback on what's missing or what you'd do differently

value: Show HN: Open Agent, My attempt at a managed environment for AI coding agents


value: gajus

value:
I started to use AI agents for coding and quickly ran into a frustrating limitation – there is no easy way to share my development environment logs with AI agents. So that's what is Teemux. A simple CLI program that aggregates logs, makes them available to you as a developer (in a pretty UI), and makes them available to your AI coding agents using MCP.
There is one implementation detail that I geek out about:
It is zero config and has built-in leader nomination for running the web server and MCP server. When you start one `teemux` instance, it starts web server, .. when you start second and third instances, they join the first server and start merging logs. If you were to kill the first instance, a new leader is nominated. This design allows to seamless add/remove nodes that share logs (a process that historically would have taken a central log aggregator).
A super quick demo:
npx teemux -- curl -N https://teemux.com/random-logs

value: Show HN: Teemux – Zero-config log multiplexer with built-in MCP server

author: gajus


value: ldayton

value:
Less permission fatigue, more momentum. Dippy knows what’s safe to run and keeps Claude on track when plans change.
https://github.com/ldayton/Dippy
Claude Code asks permission for every shell command. The problem isn't `ls`—it's that `ps aux | grep python | awk '{print $2}' | head -10` also needs approval. So does `git log --oneline -5 && git diff --stat`. You're constantly interrupted for commands that are obviously safe.
Dippy is a PreToolUse hook with a real bash parser. It decomposes pipelines, analyzes each command, and auto-approves when it understands the whole thing is read-only. I'm seeing much faster development—not smarter AI, just fewer interruptions.
What's original:
1. Actual bash parsing. Hand-written recursive descent parser (Parable), pure Python, no dependencies. Correctly handles pipelines, subshells, command substitution, here-docs, redirects. Understands `cd /tmp && rm -rf <i>` resolves paths relative to /tmp. 14,000+ tests.
2. Deep command analysis. Not just "is this git"—Dippy knows:
   - `awk '{print $2}'` is safe, `awk '{print > "file"}'` writes files
   - `sed -n 's/foo/bar/p'` is safe, `sed -i` modifies in place
   - `curl -sS https://...` is safe, `curl ... > script.sh` isn't
   - `find . -name "</i>.txt"` is safe, `find . -exec rm {} \;` isn't
   - 45+ CLI tools with subcommand-aware logic
3. Deny messages that steer Claude in the right direction. `deny python "Use uv run python"` blocks and tells the AI why. It self-corrects and continues—no wasted turn. This compounds across a session.
4. Highly configurable. A [configuration system](https://github.com/ldayton/Dippy/wiki/Configuration) with last-rule-wins semantics gives you fine-grain control over Dippy's steering and command approvals.
Philosophy: approve what we know is safe, ask about everything else. Not adversarial—just catches mistakes.

value: Show HN: Dippy solves Claude permission fatigue and keeps the LLM on-track

author: ldayton


value: justvugg

value:
Hi HN,
I built GONK, a small API gateway written in Go, aimed at edge, IoT and constrained or offline environments where full-blown gateways feel like overkill.
Repo: https://github.com/JustVugg/gonk
What it does
GONK handles the common “front of service” concerns while staying simple and dependency-free:
 • Routing and reverse proxying
 • JWT-based auth with RBAC and scope validation
 • mTLS with client cert authentication and flexible role mapping
 • Load balancing (round-robin, weighted, least-connections, IP hash)
 • Upstream health checks and automatic failover
 • Single static binary, no external services required
There’s also a CLI to generate configs, JWTs and certificates so you don’t have to hand-edit YAML.
Why
Gateways like Kong, Traefik or NGINX are great, but they often assume:
 • cloud-native environments
 • control planes, databases, or external dependencies
 • more resources than you realistically have on edge devices or air-gapped systems
GONK is designed for industrial setups, edge nodes, offline networks and small deployments where you just want something that works and is easy to reason about.
Getting started
git clone https://github.com/JustVugg/gonk
cd gonk
make build
./bin/gonk-cli init --template basic --output gonk.yaml
./bin/gonk -config gonk.yaml
Looking for feedback
I’d love input from folks working on:
 • IoT / edge computing
 • air-gapped or industrial systems
 • embedded or low-resource deployments
Does this auth + gateway model feel practical in real setups?
What features would you expect next (or would not want)?

value: Show HN: GONK – an ultra-lightweight, edge-native API gateway written in Go

author: justvugg


value: Show HN: Base-1 - A laboratory for computational numerical experiments


value: kyoungsookim

value:
I built VibeInbox to organize Gmail by reading email content
  (Gemini) instead of relying on sender-based heuristics. It
  classifies emails into IMPORTANT/NORMAL/INFO/SPAM, applies
  Gmail labels (AI/...), and can optionally archive promos or
  move high-confidence spam (no delete actions). Runs locally;
  you provide Gmail OAuth + Gemini API key.
  Repo: https://github.com/kks0488/vibe-inbox
  Would love feedback on classification quality, workflows
  (scheduler/systemd/docker), and false positives/negatives.

value: Show HN: VibeInbox – AI inbox triage for Gmail with safe defaults

author: kyoungsookim


value: harmtrav

value: Show HN: Jsbenchmarks.com – Real-world JavaScript framework benchmarks

author: harmtrav


value:
I built this small tool for my own use to reduce the number of tokens I send to LLMs (Claude Code, etc.). It’s just a simple utility to filter command outputs before they hit the context.
Here is what I’m getting with it so far:
I’m putting it out there in case it's useful to anyone else. It's written in Rust.
P.S. This is just a tool I built for my own needs and decided to share. If you have constructive feedback on the Rust code or the logic, I'd love to hear it. If it's not for you, that's totally fine too—no need for "angry" comments, just trying to be helpful!

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


value: maxweisel

value:
Hey HN! We’re the team from Normal / Normcore.io. We built gamekit-cli, an open-source command-line tool for developing Unity games with Claude Code.
We love working with Claude Code. It's great for creating quick prototypes, writing complex systems code, and test suites. However, we work a lot with Unity and found we couldn’t move anywhere near as fast with Unity projects as we could when working on backend code. Claude Code works best when it has the ability to compile the code it writes and test its own work. There wasn’t an easy way to do that with Unity, so we made gamekit-cli!
gamekit-cli allows you to create Unity projects from the command line, install a Unity MCP server, and includes helpful Claude commands & skills that we found useful for Unity development.
It gives Claude Code the ability to enter play mode, capture screenshots, read compiler errors, etc, which brings the same Claude Code workflow we love for backend projects to Unity projects. We plan to add more CLI tools for Claude to use to interface with Unity projects (MCP alone is somewhat slow and fills up your context). Let us know what features you’d like to see!
GitHub: https://github.com/gamekit-agent/gamekit-cli

value: Show HN: Gamekit-CLI – Use Claude Code to quickly create games in Unity

author: maxweisel


value: tariqshams

value:
Hi HN,
I built mermaidtui, a lightweight TypeScript engine that renders Mermaid flowcharts directly in your terminal as clean Unicode or ASCII boxes.
Visualizing Mermaid diagrams usually requires a heavy setup: a headless browser (Puppeteer/Playwright), SVG-to-image conversion, or a web preview. That's fine for documentation sites, but it's overkill for TUI apps, CI logs, or quick terminal previews.
The Solution is a small engine (<= 1000 LOC) that uses a deterministic grid-based layout to render diagrams using box-drawing characters.
Key Features
- Intelligent Routing: It uses corner characters (┌, ┐, └, ┘) for orthogonal paths.
- Topological Layering: Attempts a readable, structured layout.
- Support for Chained Edges: A --> B --> C works out of the box.
- Zero Heavy Dependencies: No Mermaid internals, no Chromium, just pure TypeScript/JavaScript. With commander for the CLI, not the MermaidTUI library
I wanted a way to see high-quality diagrams in my CLI tools quickly, it’s great for SSH sessions where you can’t easily open an SVG. I was initially embedding this within a cli tool I’m working on and figured I’d extract out a library for others to use. I also initially used regex to parse, but now I made the parser a bit more robust.
I'd love to hear your thoughts on the layout engine or any specific Mermaid syntax you'd like to see supported next!
GitHub: https://github.com/tariqshams/mermaidtui
npm i mermaidtui

value: Show HN: MermaidTUI - Deterministic Unicode/ASCII diagrams in the terminal

author: tariqshams


value: lgvdp

value:
Hello HN, Lucas here.
I’ve been working with BigQuery for ~5 years, mostly in large (petabyte-scale) environments. Over time we ended up spending a lot of money and engineering effort just trying to understand where costs were coming from, why and how to optimize them.
At some point we decided to stop, leverage all our past experience and spend a full cycle building tooling focused on cost visibility and optimization. The main goal was to regain ownership of cost data and make it possible to understand our cost structure in under a minute, while aligning the views of engineering and FinOps at the project level. To complement these, and given the recent rise of AI, we also built agents that review usage patterns and selected KPIs to surface issues and suggest concrete optimizations (always through an encoding layer for privacy).
This ended up working well for us: we reduced monthly BigQuery spend by ~43% and made cost considerations part of normal engineering workflows instead of a separate FinOps exercise. After validating it with a few other teams facing similar problems, we decided to ship it publicly in November.
Some transparency items to consider:
- We only work with bigquery related information, not all gcs.
- While we already support most sources of cost, the project is in constant development. If you use an uncommon feature it may not be covered, but we will implement it for you.
- The larger the company the larger the impact, since there tends to be larger technical debt. Nonetheless, we've seen significant impact in lower scale startups.
- We dont need labels. Labels are great, and should be taken care of, but we do not depend on them to provide insights.
Happy to share details, lessons learned, or tradeoffs if this is interesting to others dealing with large-scale data warehouse costs. Check us out at https://www.cloudclerk.ai/

value: Show HN: CloudClerk. We struggled with BigQuery finops, so we decided to fight

author: lgvdp


value: innovationlab

value:
I built this while doing physiotherapy and struggling to keep a clear record of what I was actually doing week to week.
I had exercises from multiple clinicians, things changed over time, and I wanted a simple way to log what I did without accounts, cloud sync, or rigid plans.
Physio Tracker is a small installable web app (PWA) that:
- works offline
- stores data locally on the device
- lets you add and adapt exercises freely
- supports JSON export/import
I export the data occasionally and use it to summarise progress before appointments, but the app itself is just a personal logging tool, not medical advice and not a replacement for a physio.
I’m sharing it to see if it’s useful beyond me. I’d appreciate feedback on:
- whether this solves a real problem
- what feels unnecessary
- what’s missing
App: https://www.physiotracker.app

value: Show HN: Physio Tracker – a local-only, offline PWA for tracking exercises

author: innovationlab


value: gebhardtr

value: Show HN: Oracle MCP Servers

author: gebhardtr

title: Show HN: Oracle MCP Servers


value: arwt

value: Show HN: PopTogether – A calm game where strangers work together to pop bubbles

author: arwt


value: Adithya-Kolavi

value:
I built this to solve a problem I kept running into: every time I asked Claude Code or Cursor to help with Manim animations, it mixed up APIs between Manim Community Edition and ManimGL (3Blue1Brown’s version), or used deprecated patterns.
This repository packages battle tested best practices and working code examples as “skills” that AI agents can automatically load when you are working with Manim.
Install:
npx skills add adithya-s-k/manim_skill
What’s inside:
- Separate skills for Manim Community Edition and ManimGL (they are incompatible frameworks)
- Working code examples for scenes, animations, 3D, camera control, and LaTeX
- Common patterns and pitfalls to avoid
It uses the open skills.sh standard, so it works across Claude Code, Cursor, and other AI coding tools.
Happy to answer questions about the implementation or Manim in general.

value: Show HN: Manim Skills – Claude Code skill for creating 3b1B style animations

author: Adithya-Kolavi


value: busenurcetin

value:
Hi HN,
I built a dictionary to help newcomers and industry experts navigate software development terminology (from A to Z).
I realized that even experienced devs sometimes struggle with specific jargon outside their niche, so I wanted to create a central resource.
You can check it out here: https://github.com/busenurcetin/YazilimTerimleriSozlugu/blob...
Feedback on the definitions or terms I might have missed is welcome.

value: Show HN: Software Terms Dictionary – A guide to industry terminology

author: busenurcetin


value: shubhampawade

value:
I built segre because my own Downloads folder was a nightmare: endless mix of PDFs, images, installers, zips, code snippets, random screenshots—impossible to find anything. Manual sorting was tedious, so I created a simple, safe Node.js CLI that handles it automatically.
Key features:
- Organizes by file type (Images, Documents, Code, Videos, Archives, Installers, etc.) based on extensions
- Or by date (Year/Month folders)
- --dry-run to preview moves without changing anything
- --interactive to confirm each file
- undo command to revert the last run
- Custom categories via JSON config file
- Progress bars, verbose logging, safe handling (no overwrites by default)
Try it instantly with npx (no global install needed):
npx segre ./Downloads --dry-run
Or install globally: npm install -g segre
Then: segre ./path/to/folder
npm: https://www.npmjs.com/package/segre
Would love honest feedback: Does it catch the right categories for your files? Any edge cases or missing types? Bugs? Feature suggestions? Happy to answer questions or iterate based on what people say.
If you'd like to connect or chat more (about this or other projects), feel free to reach out on LinkedIn: https://www.linkedin.com/in/shubhampawade
Thanks for checking it out!

value: Show HN: Segre – Safe CLI to organize messy folders by type or date

author: shubhampawade


value:
I was doing this in a regular Claude Code session for a while, but wanted an all-in-one UI for it. Claude Code controls NetHack via tmux.
I have a NetHack skill installed that I update after each session.
My Claude's top score is 3302 (dungeon level 11).
It is interesting cause it mostly has trouble with spatial reasoning, even though it knows most/all the details of the game.
This absolutely CHEWS up tokens...lol.

value: Show HN: NetHackPlayer – Have Claude Play NetHack


value:
With Malan Chat, you can learn over 60 languages through AI-powered conversations, grammar correction, and integrated FSRS flashcards. The chat allows users to practice speaking and listening, get instant corrections, and build your vocabulary with our intelligent language tutor. Users may import readings into the Reader, look up words and annotate the article, and discuss the reading with the chat. To practice longer form writing, you may go into the writing hub and see your text marked up with corrections.
I built Malan to make speaking practice feel like a real conversation instead of a clunky exercise. It’s a chat-first language coach that listens, responds, and nudges you toward more natural phrasing without breaking your flow, so the learning process stays light and fast, it feels more like texting than studying. It’s strongest for people who already know some of the language and want to go from 1 → 100. There isn’t a true 0 → 1 path yet (onboarding for complete beginners is coming), so right now it’s best for learners who can form basic sentences and want consistent practice with real feedback.
Coming soon: YouTube (and possibly Spotify) integration so you can get listening practice from real sources that you want to engage with. This is your journey, and you are a distinct individual with your own tastes. I want you to have fun while you're going through the arduous task of learning a new language! Also in the works are custom exercises based on your own needs.
I've still had very limited user feedback, so please tell me what you like or don't like about the platform and I will do my best to remedy it!

value: Show HN: Malan Chat, a full immersion language learning app for 62 languages


value: gauravsc

value: Show HN: A memory learning layer for AI agents to learn on the job

author: gauravsc


value: vmazi

value:
I created a github app that allows people to label suspicious LLM slop prs based on heuristic driven scoring of the submitter's github profile, activity, and activity on the repo itself.
Profiles and PRS that fail heuristics have the PR labelled appropriately.
I might also add LLM based scoring in the future, but for now this project uses only heuristic based scoring.
People who have already merged to the repo that the app is installed on should be exempted from the scan.
The project is a FastAPI service that processes requests using background tasks (https://fastapi.tiangolo.com/tutorial/background-tasks/#depe...), to allow for the github webhooks to return in a timely manner.
Might have to upgrade to a proper celery worker if this takes off.
Github app link: https://github.com/apps/pr-slop-stopper
The project uses UV for dependency management, ty for type checking and ruff for linting.
AI DISCLOSURE: I heavily used Claude Code to generate this, but I did read the code during development to ensure it aligned with my personal tastes and habits.
NOTE: I have not been able to test this myself, I tried making a fake github account and test it via forking the source repo (I have the app installed on source repo). Unfortunately, github does not allow forking repos to new accounts under a week old. I verified that the webhook urls are configured correctly with secrets properly being accepted by the server, but have not been able to guarantee functionality. If someone would like, feel free to open a low quality PR and lets see if it gets flagged! (I can almost guarantee it will break since I haven't been able to test this live yet. But a broken thing is the first step to a working thing)

value: Show HN: PR Slop Stopper

author: vmazi

title: Show HN: PR Slop Stopper


value: andrewbarba

value: Show HN: Specli – compile any OpenAPI spec to an agent optimized executable

author: andrewbarba


value: bhavaniravi

value: E2B has been my favorite Sandbox environment for the AI agents I build. On actively using it for the last few months, CLI-ing every time is a lot of work. So here is a VSCode Extension

value: Show HN: VSCode Extension for E2B Sandbox

author: bhavaniravi


value: itsmiketu

value: Show HN: Manager List is now live!!!

author: itsmiketu

title: Show HN: Manager List is now live!!!


value: ezulabs

value:
I built a C compiler that runs on a Raspberry Pi Pico ($4, 264KB RAM).
It compiles C to ARM Thumb and JIT-executes it.
It can compile its own source code on the hardware.
Full pipeline: preprocessor, parser, type system,
Thumb-1/Thumb-2 codegen, mark-and-compact GC, USB REPL.
Try it: flash the UF2, connect serial (115200), type "help".
https://github.com/ezulabs/MicroCC

value: Show HN: A self-hosting C compiler that runs on a Raspberry Pi Pico

author: ezulabs


value: dobodob

value: Show HN: New 3D Mapping website - Create heli orbits and "playable" map tours.

author: dobodob


value: Zenith-Software

value: Show HN: Directory of 1000 open source alternatives to popular software

author: Zenith-Software


value: johnboygiz

value: In going against the trend of everything viral, I decided to make a little app to help discover some youtube video gems that show early promise by way of their "views to Likes" ratio. And combined with some keywords this throws up some interesting videos that haven't (yet) gainned any traction, but show early signs of doing so.My thinking is that such videos/channels validates interest and confirms high quality content thats relevant and therefore desirable.Of course this would logically extend to getting an algorithim boost from YT and therefore further exposure/likes etc ? I will caveat all of that with I have no idea how YT algo works though:) Anyways, appreciate any feedback on this and whether it could be useful to anyone who could make an angle from this.

value: Show HN: Will this discover hidden YouTube video gems (or gems in the making)?

author: johnboygiz


value: mraspuzzi

value:
We used Claude Agent SDK to make Claude Tutor. It's main goal is increase human knowledge, understanding, and agency.
It's an email and CLI agent to help people level up their software engineering skills.
We think there's too much focus on AI agency right now and not enough on human agency.
Open sourced, and curious for feedback! This is v0.1 so it's hella early.
Ps. Next step is to get this working on Open Agent SDK and explore other interfaces.

value: Show HN: Claude Tutor – an open source engineering tutor

author: mraspuzzi


value: gangtao

value: Show HN: Easy to use, open source voice clone app

author: gangtao


value: barefootsanders

value: Show HN: Mpak: a package manager for MCP server bundles

author: barefootsanders


value: Show HN: QuizYou – Paste text, generate quiz, test yourself


value: Patlakh

value: Show HN: PingLater – A beautiful Chrome extension to snooze tabs

author: Patlakh


value:
Hi HN, I'm building Startups.in, a work-in-progress startup intelligence platform that aggregates global startup profiles with funding, sector, and location data in one place. It's still rough around the edges and in active development, but I wanted to share the public version for feedback.
This started as a personal project because I wanted a clean, searchable dataset of startups across regions without jumping between multiple sources or dealing with noise I didn't want :).
The product is still very much a work in progress, but it's in a usable state and open to feedback.
What it currently does:
+ Browse startup profiles with funding and basic company metadata
+ Search and filter by industry, geography, etc.
+ View simple ecosystem trends
No signup required to try it though you're welcome to sign-up to use watchlists etc.
How I built it:
It's backed by a custom crawler (for data I need) and enrichment pipeline using n8n workflows, with a lightweight web UI focused on fast querying and filtering.
What I'm trying to learn from HN:
+ What data points would make this genuinely useful to you?
+ Would an API be valuable?
+ Does the UX get in the way of exploration?
I'm actively iterating on it and happy to discuss further. Thanks.

value: Show HN: Startups.in: An in-development "global" startup intelligence database


value: juanpabloaj

value: Show HN: Obsidian Workflows with Gemini: Inbox Processing and Task Review

author: juanpabloaj


value: luskira

value:
I absolutely hate what the internet does to my brain, to my capacity for focus, and to how little I retain information.
I've been slowly migrating away from reading online to offline. Started a few years ago with a reMarkable tablet, then an Onyx Boox for colored papers. But newsletters always fell off my radar. There's just too much going on in my inbox.
So I built a tool that takes any RSS feed (Substack, Ghost, etc.) and formats it as a printable newspaper.
Tech: Single HTML file, vanilla JS, no backend. Fetches feeds via CORS proxy (Cloudflare Worker). Renders into a 3-column A4 layout.
I don't own a printer, though, haha. I just send the PDF to my reMarkable. But I'm curious if there's interest in getting a personalized newspaper like this actually delivered to your door.
Would love feedback on the layout, and curious how others handle the "too many newsletters" problem.

value: Show HN: Analog Reader – Turn newsletters into printable newspapers

author: luskira


value: svarlamov

value: Show HN: Git Extension for Tracking AI Code and Prompts

author: svarlamov


value: faircitoo

value:
This season felt really packed and I kept missing episodes, so I built a small web app that shows what anime is airing this week in my timezone.
It pulls seasonal data from MyAnimeList and maps it into a weekly grid so you can see at a glance what drops each day.
It’s just a small personal tool I made for myself, but sharing in case it’s useful to others too.

value: Show HN: AniSeason – a weekly anime airing calendar in your local timezone

author: faircitoo


value: Valvoa

value:
I built this app after struggling to find a good privacy-focused AI chat client for mobile several months ago.
I was using OpenWebUI but wanted a local-first solution that didn't require connecting to a remote server. While the Gemini app worked well, I wasn't comfortable sending all my queries to Google on top of everything else I already share with them.
Core Privacy Features:
- All data stored locally on your device with end-to-end encryption
- Optional app lock/biometric authentication
- One-tap data deletion + configurable retention policies
- Encrypted on-device backup and sync
- Support for providers offering zero data retention
The rest of the features focus on quality-of-life improvements for daily use.
The app is actively being developed, and I'd love to hear your feedback or feature requests.

value: Show HN: UnboundChat – Privacy-First OpenRouter Client for Android and Windows

author: Valvoa


value: keepamovin

value: Show HN: I wrote a "Senior Engineer" doctrine file for my agents called AI Lint

author: keepamovin


value: jmulla

value:
Python SDK for services where the expensive part is loading data, not processing it. Sticky routing keeps requests on the
  same worker, NVMe cache eliminates repeated S3 fetches, and you deploy with a decorator + one CLI command.

value: Show HN: Building Memory as a Service with Memrun

author: jmulla


value: jatin-dot-py

value:
Author here.
I released this disclosure today regarding a server-side authorization bypass I found in Instagram.
The Vulnerability:
By sending a GET request to [instagram.com/](http://instagram.com/)<private_username> with specific mobile headers, the server returned the full polaris_timeline_connection JSON object containing direct CDN links to private posts, captions, and media. No login or follower relationship was required.
The Timeline & Contradiction:
- Oct 12: I reported the issue, with a video, poc script, and testing on my account [jatin.py](http://jatin.py/)
- Oct 14: Meta requested specific vulnerable accounts to test. I provided a consenting third-party account where the POC script successfully extracted 30 private URLs.
- Oct 16: The exploit stopped working on the accounts where it was previously working.
- Oct 27: Meta closed the report as "Not Applicable," stating they "could not reproduce" the issue and that "no changes were made directly in response".
The Current State:
While the exploit no longer functions on the accounts I tested, Meta officially maintains the bug never existed. They attributed the change in behavior to "infrastructure changes" or "unintended side effects".
Without a root cause analysis or acknowledgment from Meta, it is impossible to confirm if the underlying authorization failure was actually patched or if this was an accidental fix that could regress.
The repository contains the POC script poc.py , SHA256 hashes of the video evidence, and the full logs of the communication.

value: Show HN: Instagram: Private Posts Exposed to Unauthenticated Requests

author: jatin-dot-py


value: dheerazmakes

value:
This is a small, client-side JavaScript library that surfaces content origin metadata already present in HTML (author, source, date, type).
It does not verify truth, authenticity, or trustworthiness.
It only displays declared origin information in a consistent, accessible way.
The goal is to make origin more visible without making claims about correctness.
Features:
- Zero configuration by default
- Client-side only (no network calls)
- Keyboard-accessible overlay
- Optional visual “verified” styling (purely cosmetic)
- Designed to be ignorable unless needed
This started as an experiment in restraint: adding transparency without authority.
Demo: https://originjs.netlify.app/
Code: https://github.com/dheeraz101/OriginJS
Feedback welcome, especially on UX, wording, and failure modes.

value: Show HN: A tiny JavaScript library for content origin metadata (no truth claims)

author: dheerazmakes


value:
Harness, Don't Replace: It integrates with the tools you already use. If it runs in the terminal, it can be bound to the grid.
The Grid: Your keyboard-based command center. It is technically 3-dimensional and can fit up to 729 (9x * 9y * 9z) commands per grid, any of which can be accessed almost instantly using Quick Navigation (see below). Cycle through command grids or stash them in the inventory folder using i.
Profiles, Decks, & Assets: A profile consists of a grid configuration (size etc), a collection of commands (the deck), and assets (optional). Example: A profile can have a deck of Docker commands, and have Docker compose files as its assets.
Portable Specs: All profile files exist in ~/.config/drako/. You can download new profile setups from any git repository to your inventory folder using drako summon. You can even have multiple such profiles in a single repo (specs). Git-manage your own spec folder and summon your own control panel in an instant.

value: Show HN: A brutalist architectural framework for CLI-based workflows