value:
Hi HN — we’re building high-level capabilities for AI applications at Gensee: packaged tooling + infra that remove brittle low-level plumbing so teams can focus on their product’s real job.
After speaking with many AI developers and experiencing it ourselves, we found that building agents requiring web content is often bottlenecked on the “search” part, as it involves iterations of search, crawl, extract, re-query, and error handling.
We package all these search-related low-level details in an efficient and more intelligent way, so AI builders can get back to work on their core agent ideas.
What Gensee Search Agent is behind the single API call:
- Web searching + crawling + browsing
- Built-in error handling + retries/fallbacks
- Breadth-first search approach to search in parallel and rule out bad results early on
- Goal-aware extraction that returns content closely related to your query and directly usable by downstream tasks
Results:
- Improved the GAIA benchmark accuracy for Owl (open-source implementation of Manus) by 23%.
- Helped a San Diego developer boost his AI agent’s accuracy by 40%.
What we’d love feedback on:
- Corner cases where your agents struggle or customization needs for your agents
- Output formats you want
- How you’d like to control search quality vs. cost
- Other features you care about (e.g., runtime monitoring, eval harnesses)
We’ll stick around in the thread to answer questions and share implementation details. Thanks for taking a look!

value: Show HN: A high-level search agent

title: Show HN: A high-level search agent


value: BrainyZeiny

value:
Hey HN, a couple of years ago I pitched an idea during a YC interview and was told it would never work. We argued quite a bit on why Triplebyte failed.
They were not wrong to be skeptical. The hiring space is littered with failed companies.
But we built it anyway. Out of sheer necessity.
Our small startup was getting 2200 applicants a week for programming roles, and we needed a way to evaluate them fairly — and at scale.
The core issue we saw is that most ATSs are just passive tables with a UI. A candidate applies, and then they sit there. We needed an active, event-driven system that evaluates candidates on their skills. A workflow engine that pushes the vetting process forward and recommends engineers based on their actual skill set.
So we built Hivemind, a workflow-first ATS.
To make it useful, we built the assessment tools we always wanted: sandboxed project environments using Firecracker microVMs + Kata Containers (with a Monaco editor) to test real-world coding skills (not just LeetCode), and asynchronous video questions for conceptual questions that can be graded by you or by AI.
For any step that requires human input, all tasks are forwarded to a centralized inbox so you’re not digging through workflows. And for live interviews, we built a co-pilot that records, transcribes, and summarizes the conversation, adding notes automatically to a central report card.
We built all this to solve our own hiring pain, and today it powers the system that vets ~9,000 candidates a month at our staffing company. We’re also launching it today on Product Hunt.
I know HN has strong opinions on hiring for engineering roles, and I’d be grateful for your feedback, criticism, and ideas.
Thanks for reading.

value: Show HN: I built the ATS YC said would never work

author: BrainyZeiny


value: tccole

value: I hate regex with a burning passion. I hate using regex on emails, addresses, and emails even more. I hate that there are no data cleaning tools for pyspark so I built one.

value: Show HN: DataCompose – PyJanitor-style dataframe cleaning for PySpark

author: tccole


value:
I got really sick of the LinkedIn/X bros and gurus and their $997 masterminds, so I built a custom GPT that tells you exactly what they would without the $997 price tag.
You give it a business challenge (e.g. “grow my email list”), and it replies with:
- A jargon-soaked fake playbook (think “Ascension Ladders,” “Attention Flywheels,” “Scarcity Cascades”).
- An option to “Make it Worse” (even more buzzword soup).
- An option to “Explain in Plain English” (where it translates the sludge into sarcastic reality, citing psychology/anthropology) — my way of helping people NOT to fall for this crap.
I would love feedback on:
- Is it clear enough that this is parody? I added a bunch of disclaimers but I need to make sure no one implements any of the suggestions.
- Is it fun? I played with it a lot and, at this point, I can't tell anymore.
Thank you!

value: Show HN: FunnelBro 3000 – An AI that generates hustle-bro strategies


value: HimTortons

value:
A few weeks ago I shared the Persistent Mind Model (PMM) — a Python framework for giving an AI assistant a durable identity and memory across sessions, devices, and even model back-ends.
Since then, I’ve added some big updates:
- DevTaskManager — PMM can now autonomously open, track, and close its own development tasks, with event-logged lifecycle (task_created, task_progress, task_closed).
- BehaviorEngine hook — scans replies for artifacts (e.g. Done: lines, PR links, file references) and uto-generates evidence events; commitments now close with confidence thresholds instead of vibes.
- Autonomy probes — new API endpoints (/autonomy/tasks, /autonomy/status) expose live metrics: open tasks, commitment close rates, reflection contract pass-rate, drift signals.
- Slow-burn evolution — identity and personality traits evolve steadily through reflections and “drift,” rather than resetting each session.
Why this matters:
Most agent frameworks feel impressive for a single run but collapse without continuity. PMM is different: it keeps an append-only event chain (SQLite hash-chained), a JSON self-model, and evidence-gated commitments. That means it can persist identity and behavior across LLMs — swap OpenAI for a local Ollama model and the “mind” stays intact.
In simple terms: PMM is an AI that remembers, stays consistent, and slowly develops a self-referential identity over time.
Right now the evolution of it "identity" is slow, for stability and testing reasons, but it works.
I’d love feedback on:
What you’d want from an “AI mind-layer” like this.
Whether the probes (metrics, pass-rate, evidence ratio) surface the right signals.
How you’d imagine using something like this (personal assistant, embodied agent, research tool?).

value: Show HN: Persistent Mind Model (PMM) – Update: an model-agnostic "mind-layer"

author: HimTortons


value: grbsh

value:
Hey HN! We’re building Knowledgework.ai, which creates AI clones of your coworkers that actually know what they know. It's like having a version of each teammate that never sleeps, never judges you for asking "dumb" questions, and responds instantly.
As a SWE at Amazon, I constantly faced two frustrations:
1. Getting interrupted on Slack all day with questions I'd already answered
2. Waiting hours (or days) for responses when I needed information from teammates
When you compare this to the UX of an AI chatbot, humans start to look pretty inconvenient! It’s a bit of a wild take, but it’s really been reflected in my conversations with dozens of engineers, and especially juniors: people would rather spend 20 minutes wrestling with an unreliable AI than risk looking ignorant or wasting their coworkers’ time. One of my early users actually tried the product and told me she’s a bit worried her coworkers would prefer talking to her AI extension over talking to her!
Here’s how it works: It’s a desktop app (mac only right now) that captures screenshots every 5 seconds while you work. It uses a bespoke, ultra-long context vision model (OCR isn’t enough, and generic models are far too expensive!) to understand what you're doing and automatically builds a searchable, hyperlinked knowledge base (wiki) of everything you work on - code you write, bugs you fix, decisions you make, or anything else you do on a computer that could be useful to you or your team’s productivity in the future.
Even if you just turn on Knowledgework for ~30 mins while working on a personal project, I think you’ll find what it produces to be really interesting — something I’ve learned is that we tend to underestimate the extent of the valuable information we produce every day that is just ephemeral and forgotten. There’s also some really great opportunities surrounding quantified self and reflection — just ask it how you could have been more productive yesterday or how you could come across better in your meetings.
The real value comes when your teammates can query your "Extension" - an AI agent that has access to all (only what you choose to share) of your captured work context. Imagine your coworker is on vacation, but you can still ask their Extension: "I'm trying to deploy a new Celery worker. It's gossiping but not receiving tasks. Have you seen this before?"
We’ve spent a great deal of effort on optimizing for privacy as a priority; not just in terms of encryption and data security, but in terms of modulating what your Extension will divulge in a relationship appropriate way, and how you can configure this. By default, nothing is shared. In a team setting, you can choose to share your Extension with particular individuals. You can, in a fine-grained manner, grant and revoke access to portions of your time, or if you are on a tight-knit team, you can just leave it to AI to decide what makes sense to be accessed. This is the area we’re most excited to get feedback on, so we’re really aiming this launch at small, tight knit teams who care about speed and productivity at all costs who use Macs, Slack, Notion, and are all on Claude Code Max plans.
We’re also working on SOC II type 2 compliance and can do on-prem, although on-prem will be quite expensive. If you’re curious about on-prem or additional certifications, I’d love to chat -  griffin@knowledgework.ai.
Check it out here: https://knowledgework.ai/
We’ve opened it up today for anyone to install and use for free. If you’re seeing this after Thursday 8/28, we’ll likely have put back the code wall — but we’d be happy to give codes to anyone who reaches out to griffin@knowledgework.ai

value: Show HN: Knowledgework – AI Extensions of Your Coworkers

author: grbsh


value: NoodlesOfWrath

value: A Rust macro that replaces unwrap() with an AI call that tries to guess the correct value when your code panics. It utilizes the source code, docs, and inputs of the function to generate a "close enough" guess.

value: Show HN: Unwrap_or_AI – replace unwrap() with AI guesses for errors

author: NoodlesOfWrath


value: reissbaker

value: Hey HN! We've run our privacy-focused open-source inference company for a while now, and we're launching a flat monthly subscription similar to Anthropic's. It should work with Cline, Roo, KiloCode, Aider, etc — any OpenAI-compatible API client should do. The rate limits at every tier are higher than the Claude rate limits, so even if you prefer using Claude it can be a helpful backup for when you're rate limited, for a pretty low price. Let me know if you have any feedback!

value: Show HN: A private, flat monthly subscription for open-source LLMs

author: reissbaker


value: ddaras

value: plug any AI backend → chat UI instantly.

value: Show HN: Universal Chat UI for AI Agents

author: ddaras


value: Show HN: Put text in between images (Nano Banana)


value:
I made this searchable database of viral product demos because I’m constantly looking for ideas to promote my SaaS
I usually do this by bookmarking tons of posts on Instagram/TikTok
But that wasn’t enough since I wanted to filter by categories like video type (faceless, talking head, no speech), industry, product, etc
So I built this curated searchable database to make it easier to find inspiration

value: Show HN: A searchable database of successful TikTok product demos


value: Show HN: Smart Buildings Powered by SparkplugB, Aklivity Zilla, and Kafka


value: therealprwilo

value:
I built a Security Test Framework for Node.js projects because most security tools are either too heavy, too expensive, or too scattered.
Run npx security-test auto — it auto-detects your project, runs 16 categories of security tests (XSS, SQL injection, CSRF, auth, headers, dependency vulns, etc.), and generates HTML/JSON/text reports.
 • GitHub: https://github.com/yourname/security-test-framework
 • NPM: https://www.npmjs.com/package/security-test-framework
Would love feedback from the HN community — especially on what tests or CI/CD integrations you’d want next.

value: Show HN: Security Test Framework – 16 automated security checks

author: therealprwilo


value: kanodiaashu

value: We built ProRead as a new interface for researching anything with an LLM. Instead of chat, you explore topics through an interactive map of ideas. The interface changes the level of detail like when zooming in and out on Google Maps. Click to go deeper, expand branches, and always stay grounded in sources.<p>It’s less “chat with AI,” more structured exploration. Curious if this feels useful for your own deep dives.

value: Show HN: A new interface for doing research fast with an LLM

author: kanodiaashu


value:
I built NamesMixer to speed up naming.
Demo: https://namesmixer.com
What it does:
- Brandable ideas from keywords (prefix/suffix/dictionary)
- Instant availability
- TLD (.com/.ai/.io) & length filters
- One-click registrar links
- No signup
Tech: React + Vite, FastAPI, Supabase, Nginx (Scaleway).

value: Show HN: NamesMixer – brandable, available domain ideas in seconds


value: anuarsh

value: Show HN: oLLM – LLM Inference for large-context tasks on consumer GPUs

author: anuarsh


value: Hey everyone, I’m an NBA fan and Python dev, and I recently built DeepShot — a machine learning model that predicts NBA game outcomes with about 71% accuracy based on historical stats and rolling performance metrics (EWMA). It features: Real NBA data from Basketball Reference Exponentially Weighted Moving Averages to track momentum Interactive NiceGUI interface with team comparison and predictions Full Python stack and open-source (MIT license) Here’s the GitHub repo: https://github.com/saccofrancesco/deepshot And if you like it, here’s my Buy Me a Coffee: buymeacoffee.com/saccofrancesco Would love any feedback — especially from folks who’ve built sports models or worked on real-time stat tools. Also open to ideas on where to take this next (player-level modeling? betting advice dashboard?).

value: Show HN: DeepShot – an open-source NBA predictor with ML, EWMA, and live UI


value: GodelNumbering

value:
Main features:
1. Search for ETFs using natural language queries like "find me ETFs that invest in bitcoin with low expense ratio" or "find all ETFs managed by cathie wood"
2. Multilingual search (results are all English though)
3. All source data straight from the SEC filings parsed into millions of lines of clean training text, no middlemen which allows us to do things that rely on semantic document understanding
4. Qualitative analysis of every ETF that answers questions like 'what are pros and cons of this etf', 'what is the detailed breakdown of expense ratio', 'how exactly does this ETF gets its exposure' and a lot more!
We worked really hard on this one, would love to get feedback, thanks :)
video demo https://youtu.be/BiOgA1tv1TM

value: Show HN: A natural language search interface to ETF (and deep insights on each)

author: GodelNumbering


value:
Hi HN,
I was making family vlogs but the audio was ruined by wind noise. Existing tools felt clunky or expensive, so I built my own.
https://cleaneraudio.com/
CleanerAudio lets you:
 • Clean noisy recordings
 • Transcribe audio or YouTube videos
 • Summarize long videos
 • Download YouTube audio as MP3
Built with React (Vite), Prisma, Postgres, and AI models for noise reduction, transcription, and summarization.
There’s a free tier — I’d love your feedback on what works and what doesn’t.

value: Show HN: CleanerAudio – AI to clean and transcribe audio


value: Show HN: Try out all the best image generation models in one platform for free


value: pekingzcc

value: Show HN: Most Affordable Professional VEO3 Video Generation

author: pekingzcc


value: lamecoder

value: With advanced search capabilities (semantic search, RAG) MetaPodcast's goal is to make podcast listening experience into an interactive journey of knowledge and discovery. MetaPodcast is building an ecosystem that not only aggregates podcasts but also extracts, analyzes and presents valuable insights to users.

value: Show HN: Metapodcast.net to make podcast exploration effortless

author: lamecoder


value: qwikhost

value: Real-time speech-to-speech translation for videos, streams, and meetings. Works with YouTube, Netflix, Zoom, and Google Meet.

value: Show HN: VoiceHop – Real-Time Audio and Video Translation

author: qwikhost


value: Show HN: A fun Unicode tool to make your text look cool anywhere


value: viniciusbarreto

value: Show HN: Run `npx htmsh latest` → Deploy your site instantly, for free Try now

author: viniciusbarreto


value: xiaoxinews

value:
Hi HN,
I built SavantLook, a keyword and domain research tool powered by the official Semrush API. The data quality is the same as Semrush, but the price is much lower.
What’s different: it supports MCP integration, so you can connect it into workflows or AI tools for fully automated SEO research.
Key features:
Domain & competitor analytics
Keyword discovery & difficulty
Backlink & traffic analysis
Currently in beta – looking for early feedback.
 https://www.savantlook.com

value: Show HN: SavantLook–Affordable keyword research with MCP for competitor analysis

author: xiaoxinews


value: airobus

value: Show HN: Enhanced Queens Game – A Queens puzzle with a 3rd constraint (regions)

author: airobus


value: geminimir

value:
We kept breaking production with small prompt edits — suddenly outputs weren’t valid JSON, fields disappeared, or formats changed silently.
So we built Promptproof, a GitHub Action that runs in CI and blocks PRs when prompts produce invalid outputs.
Features:
- Validates JSON output
- Enforces required keys & schemas
- Runs fast in CI (no external infra)
- Works with OpenAI, Anthropic, and local models
- Adds PR comments so reviewers see failures immediately
We’d love feedback: which rules or integrations would make this most useful for you?
Repo: https://github.com/geminimir/promptproof-action

value: Show HN: Promptproof – GitHub Action to test LLM prompts, catch bad JSON schemas

author: geminimir


value:
We built StripeMeter, an open-source usage metering platform that plugs directly into Stripe. It solves the classic SaaS pain of “why is my bill higher than expected?” by giving both developers and customers real-time usage tracking with live cost projections.
Why it matters<p>- Transparency: Customers see exactly what Stripe will bill them (within 0.5% parity).<p>- Exactly-once guarantee: No double billing, ever.<p>- Fast & scalable: Sub-minute freshness with Redis + Postgres counters.<p>We’d love feedback from SaaS builders, especially if you’ve struggled with Stripe’s metered billing. Does this solve a real pain for you? What would you need before trusting it in production?

value: Show HN: StripeMeter – Open-Source Usage Metering for Stripe Billing


value: DigitalSea

value:
Don't ask me where this idea came from. But a couple of years ago I had this crazy idea of writing a HTML to Javascript compiler. I went off it for a bit, but just started hacking back on it again and have something that actually works (demos and all). It's inspired a little by the early days of my development career writing Coldfusion.
Would you use this to build production apps? You'd probably be as crazy as I am for making this if you did, but still.
A fun little crazy experiment.

value: Show HN: HTMS (write JavaScript using HTML)

author: DigitalSea


value: sopuli

value:
While spending long hours coding, I wanted a simple way to follow the 20-20-20 eye care rule (every 20 minutes, look 20 feet away for 20 seconds). I couldn’t find a browser-based timer that allowed recurring notifications with custom intervals, so I built Aika.
It’s also been useful for timeboxing meetings and as a lightweight Pomodoro timer.
- Runs in any browser
- Free, no sign-up
- Minimal by design
Sharing in case anyone else needs something like this. Feedback is very welcome!

value: Show HN: Aika – a minimalist browser timer for 20-20-20 eye care and timeboxing

author: sopuli


value: lukebyrnescot

value:
Yesterday I read Pennycook etc al.'s paper on pseudo-profound bullshit, and realized that's what I hate most about the current AI culture. Meaningless but important sounding bullshit that's said only to make the speaker sound smart.
So then I made this little web app to randomly generate AI bullshit. Your next pitch deck awaits.
Pennycook's paper:
https://www.cambridge.org/core/journals/judgment-and-decisio...

value: Show HN: Pseudo Profound AI Bullshit Generator

author: lukebyrnescot


value:
Hey HN!

  I recently got hooked on Texas Hold'em, but let's just say my bankroll has been on a
  steady downward trajectory. After losing one too many buy-ins to players who actually
  knew what they were doing, I decided to build something to help myself (and maybe
  others) stop being the fish at the table.

  Over the past 3 days, I put together an AI-powered poker training platform. Here's
  what it does:

  - Play against AI opponents with different playing styles (from tight-aggressive to
  loose-passive)
  - Get real-time coaching and hand analysis from an AI that actually understands GTO
  concepts
  - Review your mistakes with detailed breakdowns of where you went wrong
  - Track your progress over time

  The AI opponents aren't just random - they actually adapt to your playing style,
  exploit your weaknesses, and even go on tilt sometimes (just like real players). The
  coach can analyze your hand history and point out leaks in your game, like when you're
   calling too wide from early position or missing value bets on the river.

  Tech stack: Next.js, TypeScript, DeepSeek/Gemini APIs for the AI brains, and Tailwind
  for styling. The whole thing runs in your browser.

  I've already noticed improvements in my own game (finally stopped calling 3-bets with
  K9 offsuit!), but I'd love to get feedback from the community. What features would
  make this more useful? Any poker pros here who can tell me what I'm missing?

  You can try it here: https://unfish.app/

value: Show HN: I built an AI poker coach to stop being a fish at Texas Hold'em


value: rajatkulk

value:
Hey HN! I’ve been building [Octarine](https://octarine.app/) for a little over 2 years. It started because I wanted a note-taking app that was:
- Lightweight (&lt; 30MB, fast to launch, no Electron bloat).
- Opinionated (good defaults, clean UI, not a plugin bazaar).
- Yours (all plain Markdown, nothing proprietary).
---
- Command bar (Cmd/Ctrl+K) to navigate and run commands quickly.
- WYSIWYG editor (rich text without live preview jumping).
- Git sync built-in — backups to GitHub/GitLab, no plugins.
- Natural language dates (“yesterday”, “last week”).
- Multiple workspaces, templates, tags, graph view.
- Backup anywhere — iCloud, Dropbox, Syncthing.
- Tabs & Panes — split and rearrange notes/graphs like a code editor.
*Pro Features*
- BYOK for over 9 AI providers including OpenAI, Anthropic, Perplexity, Gemini and more!
- Ask Octarine — chat with your notes (RAG, embeddings done on-device).
- Writing Assistant — Sidebar assistant to help rewrite, improve or create.
- Focus Mode — distraction-free, sentence spotlight.
- Customisation — 30+ fresh themes, different paper types.
- Locked Notes — Disallow a note from editing.
- Folder Customisations — Add icons/colors to folders, have them manage their own unique sorting.
*FAQ*
- Free plan gets updates forever; some features are Pro.
- Pro is a one-time license (no yearly “updates tax”).
- Over 130+ releases shipped.
- iOS app is in development.
- Overlaps with Obsidian, but follows different methodologies about having less but baked in features, over an extensible plugin system (each work for different users)
---
Try it: [octarine.app](http://octarine.app)
Changelog: [octarine.app/changelog](https://octarine.app/changelog)
Documentation: [docs.octarine.app](https://docs.octarine.app)
I’d love your feedback - what works, what feels off, what’s missing? Always open to ideas (and criticism).

value: Show HN: Octarine – a fast, lightweight, opinionated Markdown notes app

author: rajatkulk


value: PAndreew

value: docustore's aim is to provide up-to-date, off-the shelf and plug-and-play context for LLMs from a curated list of frameworks/sdks. It has a 4 step pipeline: scrape the documentation - clean it - vectorize it - package it. My vision is to host it somewhere and develop an API/MCP around it so it will be development-environment agnostic.

value: Show HN: Docustore – Vectorized Technical Documentations

author: PAndreew


value: hboon

value:
I built this as part of my site TheBlue.social but the bookmark feature can be used standalone.
One of the more popular solution to Bluesky bookmarking is to reply to the post with a pin emoji, but everyone would know what you have bookmarked and it comes with a bunch of restrictions.
This one's private. It's simple CRUD, but comes with a browser bookmarklet and an iOS shortcut so you can bookmark with the iOS sharing sheet.
Exports coming soon.

value: Show HN: Private Bluesky Bookmarks

author: hboon

title: Show HN: Private Bluesky Bookmarks


value: MrManchot

value:
I built a collectible-card auto-battler you can play in the browser. Every card is unique: we procedurally generate the card’s stats/bonuses/name and its illustration (via Stable Diffusion prompts derived from attributes). Decks are 6 cards, fights are auto-resolved and typically finish in < 20s. Progression is free (daily booster + quests), with Legacy / ~6-month Seasons / weekly Draft modes, a Catalyst fusion (5 same-level → stronger card, with a chance to produce an “Abnormality”), and fair matchmaking with multiple leaderboards. No downloads. Free to play.
I’d love feedback on:
– Proc-gen balance (bonus ranges & rarity odds),
– Combat readability (order = attack order; Taunt targeting),
– Draft reward structure and matchmaking.
Happy to answer technical questions (proc-gen pipeline, image prompting, leaderboard snapshots/Hall-of-Fame).

value: Show HN: Void Scourge – a browser CCG auto-battler where every card is unique

author: MrManchot


value:
Alternative to Arc's Sidebar/Edge's Vertical Tabs.
It allows you to have more control over your web browsing experience by effectively managing multiple tabs at once.
How do vertical tabs work?
Enabling the vertical tabs setting moves your open tabs from the top of your browser window (above the address bar) to the left side of the window. This allows the tabs to be displayed vertically, stacked one on top of the other, instead of horizontally.
Features

     Manage tabs and tab groups efficiently with a vertical tabs panel.
     You can now save, restore, and reorder tabs, including tab groups, using drag-and-drop functionality.
     The Vertical Tabs Panel presents your open tabs in a side-by-side layout.
     Efficiently search multiple tabs using fuzzy search.
     To save memory, you can suspend open tabs.
     Enable cross-browser cloud synchronization with a single login.
     Dark Mode Support.
     Space Backup Solution
     Save your session as a JSON file
     Cloud sync by login
     AI-powered Tab Grouping
     Group Guardian, Auto Grouping your tabs within URL matchers

 The advantages of vertical tabs

Vertical tabs are an effective solution for avoiding clutter in your browser window and maximizing your on-screen space. Additionally, they enhance tab visibility for easier identification.
PS: Side Space is a futuristic vertical tab manager that can only be used with Firefox version 139 or above.

value: Show HN: Side Space: A Better Arc-Like Experience for Firefox Users


value: jakubdudek

value:
Hi HN,
I built Pollar, an AI-powered news aggregator for Poland. Instead of wading through dozens of articles, Pollar automatically:
- Collects news from major Polish outlets every few minutes
- Groups similar articles into one event using embeddings
- Generates short AI summaries so you get the key points fast
- Highlights media bias with simple color coding
It’s live now as a web app. iOS and Android apps are coming soon.
I’d love your feedback on:
- Whether the summaries feel accurate and useful
- If bias labeling helps or oversimplifies
- What would make this more valuable as a daily news tool
Thanks!
Jakub

value: Show HN: Pollar – Polish News Aggregator

author: jakubdudek


value: hassonofer

value:
I built a small, self-contained K-Means implementation in pure PyTorch: https://gitlab.com/hassonofer/pt_kmeans
I was working on dataset sampling and approximate nearest neighbor search, and tried several existing libraries for large-scale K-Means. I couldn't find something that was fast, simple, and would run comfortably on my own workstation without hitting memory limits. Maybe I missed an existing solution, but I ended up writing one that fit my needs.
The core insight: Keep your data on CPU (where you have more RAM) and intelligently move only the necessary chunks to GPU for computation during the iterative steps. Results always come back to CPU for easy post-processing.
(Note: For K-Means++ initialization when computing on GPU, the full dataset still needs to fit on the GPU.)
It offers a few practical features:

  - Chunked Computations: Memory-efficient processing of large datasets by only moving necessary data chunks to the GPU, preventing Out-Of-Memory errors
  - Cluster splitting: Refine existing clusters by splitting a single cluster into multiple sub-clusters
  - Zero Dependencies: Single file, only requires PyTorch. Copy-paste into any project
  - Advanced Clustering: Hierarchical K-Means with optional resampling (following recent research), cluster splitting utilities.
  - Device Flexibility: Explicit device control - data can live anywhere, computation happens where you specify (any accelerator PyTorch supports)

Future plans:

  - Add support for memory-mapped files to handle even bigger datasets
  - Explore PyTorch distributed for multi-node K-Means

The implementation handles both L2 and cosine distances, includes K-Means++ initialization.
Available on PyPI (`pip install pt_kmeans`) and the full implementation is at: https://gitlab.com/hassonofer/pt_kmeans
Would love feedback on the approach and any use cases I might have missed!

value: Show HN: PyTorch K-Means GPU-friendly, single-file, hierarchical and resampling

author: hassonofer


value: caeser

value:
Cumul is a lightweight CLI tool that concatenates text files in a directory into a single file, optimized for providing context to Large Language Models (LLMs).
It respects .gitignore, filters out binaries and non-text files, adds path headers, and generates a summary report.
Key features:
Exclude patterns via options (e.g., -e .json,.md).
Custom output prefix (e.g., -p my).
Built in Zig for efficiency.
Install via:
curl -fsSL https://raw.githubusercontent.com/xcaeser/cm/main/install.sh | bash
Usage: cm [directory] outputs <directory-name>-cumul.txt.
Developed to streamline LLM workflows in development.
Feedback welcome.

value: Show HN: Cumul – Concatenate all files in a directory for LLMs

author: caeser


value: vipulag

value: Easy way to track your daily usage (time spent) on popular AI tools on your browser and set an alarm/notification to inform you if/when you cross a threshold.

value: Show HN: Track time spent on AI tools on Chrome

author: vipulag


value: Iger

value:
Hi HN, I'm the creator of Sein.
I have a thesis: the current state of Cloud AI is a lot like the timesharing systems of the mainframe era. We're accessing massive, centralized models through terminals, and our data is often the price of admission.
I believe the "PC revolution" for AI is already here, but we're missing a key component. The "Personal Computer" is already in our pockets: our phones and PCs. They have powerful chips capable of running incredible local AI. What they lack is the right input device—a peripheral designed to seamlessly feed our thoughts and experiences into this personal AI.
That's the philosophy behind Sein Clip. It's not another computer. It's the 'mouse and keyboard' for the Personal AI era.
How it Works:
The Sein Clip is a small, wearable device obsessed with one thing: high-fidelity audio capture. It uses a custom-tuned, dual-microphone array to capture the nuances of your voice far better than a phone in a pocket ever could.
It then securely transmits this data to the Sein app on your phone or PC. This is where the magic happens. The app leverages your own device's powerful processor (like the Apple Neural Engine) to run our local-first AI models. Your phone becomes your private AI server.
The core functionalities—transcription and basic emotional insights—happen 100% on your phone, completely offline. For extremely demanding tasks, there's an optional, user-controlled connection to external models, but the system is always private by default.
The Business Model:
It’s simple: you buy the hardware (the "mouse" for your thoughts), and the companion app with all its local AI software is yours forever. An optional subscription is for those who choose to use the "mainframe" (cloud) for a power boost.
I'm launching on Kickstarter soon. I'd love to hear the HN community's thoughts on this thesis—that our phones are the new PCs of the AI era, and what we need now are the right peripherals to unlock them.
Pre-launch page: https://www.kickstarter.com/projects/sein/sein-the-first-wea...

value: Show HN: OpenAI is the new mainframe. I built the 'mouse' for the Personal AI

author: Iger


value: Show HN: VSC Ext to Copy Open Tabs by clicking a status‐bar button


value: After my family and I were scammed, I built this app to help tackle the $1 trillion global fraud problem. Available on both App Store and Google Play. I don't have a tech background and used AI to help me build it. The objective was to use AI to help catch AI being used by scammers. Check it out if you're interested.

value: Show HN: TrustCheck AI – Real-time scam detection and analysis


value:
I built a simple simulation of a Dyson Sphere using C++ and OpenGL.
It renders ~20,000 satellites orbiting a star, with adjustable parameters like satellite size, density, and distribution.
The goal was to explore graphics programming and visualize how such a megastructure might look.
It’s still work in progress, but functional enough to share.
Code, screenshots, and instructions here: https://github.com/corvo001/DysonSphere

value: Show HN: Dyson Sphere simulation (C++/OpenGL)


value: Forgret

value:
I created a small project called GraphXML. It uses an XML-based format to define charts and renders them using C + SDL2.
It can produce line and bar charts and export them directly to PNG without opening a window, which is handy for scripts or Termux setups.
The syntax is simple and easy to read. There are plans to add FFI support for Python and JavaScript/WebAssembly, which could make it easier to use in other projects.
The repository includes examples and a demo PNG: https://github.com/Ferki-git-creator/graphxml
It could be useful for people looking for a lightweight, programmatic way to create charts.

value: Show HN:GraphXML Lightweight XML Charts Renderer C/SDL2 with Headles PNG and FFI

author: Forgret


value: A resilient, rate-limited, one-file-per-second copier for CD/DVD data on low-power or unstable USB hosts (e.g., Raspberry Pi), designed to prevent optical drives from ramping to high RPM and brown-out resetting.

value: Show HN: DripCopy – Gentle Optical Media Copier for Underpowered USB Hosts


value: yayasoumah

value:
I quietly launched Pocket this week — a mobile interface to run and manage coding agents directly on your machine or in the cloud. Think Claude, Cursor, Codex, or Gemini, but accessible from your phone.
Why I built this: I often had ideas while away from my computer, and wanted a way to trigger agents, review results, and manage workflows remotely. Pocket bridges that gap by pairing with your own Pocket Server (open source).
In the first 48 hours after launch:
- ~150 GitHub stars
- ~2k unique visitors
- ~400 app installs on TestFlight
Would love feedback from the HN community on:
1. Which use cases resonate most (remote coding, debugging, deployments, etc.)
2. Where this should go next (cloud agent marketplace? deeper local workflows?)
Website: https://www.pocket-agent.xyz/
 GitHub: https://github.com/yayasoumah/pocket-server

value: Show HN: Pocket – run coding agents locally or in the cloud, from your phone

author: yayasoumah


value:
I built a tool that systematically pulls Google autocomplete suggestions for "an app to/for/that" across the entire alphabet and surfaces 500+ real app ideas that people are actually searching for.
Unlike brainstormed lists or AI-generated ideas, these come directly from Google's autocomplete data – meaning real people typed these phrases when looking for solutions. Stuff like "an app to find parking spots," "an app for tracking plant watering," "an app that translates dog barks" (yes, really).
Built this in about 7 hours using the existing Google Autocomplete A-Z API I built. The data updates daily and I flag anything that appeared in the last 7 days as "new" to catch trending ideas.
What I'm still working on: Right now it's just a clean list of keywords, which feels a bit dry. I'm still looking for ways to surface the most interesting/viable ideas and trying to add context. If anyone has creative ideas for presenting this kind of data, I'm all ears.
Also curious: What other categories would be interesting to explore with this? I focused on app and website ideas first, but the same technique works for any seed phrases. What would be most valuable to the HN community? And for those building tools or doing research – this runs on the Google Autocomplete API if you want to experiment with your own keyword categories (free with rate limits).

value: Show HN: Startup Ideas Vault – 1500 app/site ideas from Google Autocompletions


value: Show HN: I built a zero-login, single-page tarot app for fun


value: shahidkhandev

value:
Hi HN!
I built Str-Plus, a lightweight and type-safe string utility library for JavaScript and TypeScript. It includes 80+ functions for common string tasks like capitalization, trimming, reversing, case conversion, validation, and more. Everything is fully typed, so it works seamlessly in TypeScript projects.
GitHub: https://github.com/ShahidKhanDev/str-plus
Would love to hear your thoughts or feature requests!

value: Show HN: Str-Plus – 80 Type-Safe JavaScript/TS String Utilities

author: shahidkhandev


value: macfleid

value: Show HN: I made an app for gamers to stop procrastinate

author: macfleid


value: tdi

value: Small tool to manage sub agents in projects. I do like to have sub agents cherry picked for what I need locally, and not have many of them potentially  contaminating context - especially when used with PROACTIVELY flag.

value: Show HN: Manage Claude Code Subagents

author: tdi

title: Show HN: Manage Claude Code Subagents


value:
Hi HN,
I’ve been working for the past 10 months on p2party, a TypeScript/C/WASM library which you can find at https://github.com/p2party/p2party-js and demo at https://p2party.com , that lets you spin up an encrypted peer-to-peer mesh with nothing more than a shared URL.
Why I built it:
I wanted something between https://file.pizza and “ephemeral Signal chat”, but with my custom cryptographic idea (I know I know... WebRTC is already encrypted and it is easy to go wrong etc.). The project started as a toy for sharing large DAW files with my bandmates (and to flex some applied crypto skills), then grew into a general toolkit. It is also a nice side project to test LLMs as companion coders and to know where the world is at right now regarding this subject (personal opinion - super small and well-defined tasks ok).
The cryptography:
The messages, either strings or files, get split and included into isomorphic chunks of 64kb which are stored in IndexedDB until they are sent. Each chunk has some metadata like file hash, name, Merkle proof etc., the actual information and then padding left and right with noisy data. The real info starts at random positions on each chunk. The whole thing is then e2e encrypted with ChaChaPoly1305 with sender ephemeral keys and sent in random order.
Inspiration:
To an observer of the message traffic, every chunk is isomorphic and contains a lot of useless info and some real ones. But to analyze it they need to store all the junk. The inspiration came from a principle of counter-surveillance that I learned from the adblock tool https://adnauseam.io .
Caveat:
Before sending the message, all the chunks need to be created so that the Merkle proofs can be calculated and the browser can send the chunks in random ordering.
The p2p:
I could not find a good example online of how to create a WebRTC mesh network so I built a tool for myself. It works acceptably now so that's why I uploaded it here after 10 months of working on it (on and off) :D
The WASM:
I had experience with compiling C to WASM when I developed this project in the past https://github.com/deliberative/crypto and I wanted the same efficiency gains here.
Status:
It works, but it is not security-audited yet → don’t trust it with your deepest secrets.
API is stable enough to embed in your own apps.
Open-source under AGPL-3.0.
Try it here: https://p2party.com (open in two browsers or devices).
Code is here: https://github.com/p2party/p2party-js.
I'd love your feedback on everything! Enjoy!

value: Show HN: P2Party – Encrypted WebRTC Room URLs


value: rektlessness

value:
Most people use AI like they're throwing darts in the dark. They get frustrated with generic responses, inconsistent results, and feel like they're fighting with the technology instead of collaborating with it.
This guide changes everything.
RCS-CO Prompt Magic provides the systematic approach that AI professionals use but have never shared in simple terms. Whether you're writing emails, analyzing data, creating content, or solving complex problems, you'll learn to direct AI with precision and confidence.
It's what i wish i had a year ago.
Sample chapter: https://aggy.cloud/RCS-CO/RCS-CO_Prompt_Magic_sample_chapter...
Pitch deck: https://aggy.cloud/RCS-CO/
In a nutshell, RCS-CO PROMPT MAGIC is about a technique employed to refine LLM interactions, achieving tailored and contextually appropriate responses that elevate the consumer experience.

value: Show HN: A guide on how to level up your prompt game: RCS-CO PROMPT MAGIC

author: rektlessness


value: I made an open source, MIT license Typescript library based on some of the latest research that generates prompt injection attacks. It is a super minimal/lightweight and designed to be super easy to use.<p>Keen to hear your thoughts and please be responsible and only pen test systems where you have permission to pen test!

value: Show HN: A minimal TS library that generates prompt injection attacks


value:
I got tired of Claude hallucinating Swift APIs. It does a good job at Python and TypeScript, but ask it about SwiftUI and it's basically guessing.
The problem? Apple's docs are JavaScript-rendered, so when you paste URLs into AI tools, they just see a blank page. Copy-pasting works but... c'mon.
So I built something that converts Apple Developer docs to clean markdown. Just swap developer.apple.com with sosumi.ai in any Apple docs URL and you get AI-readable content.
For example:
- Before: https://developer.apple.com/documentation/swift/double
- After: https://sosumi.ai/documentation/swift/double
The site itself is a small Hono app running on Cloudflare Workers. Apple's docs are actually available as structured data, but Apple doesn't make it obvious how to get it. So what this does is map the URLs, fetch the original JSON, and render as Markdown.
It also provides an MCP interface that includes a tool to search the Apple developer website, which is helpful.
Anyway, please give this a try and let me know what you think!

value: Show HN: Sosumi.ai – Convert Apple Developer docs to AI-readable Markdown


value: I built VO3 (vo3.art), an AI-powered tool that transforms text or images into cinema-quality video clips—complete with native audio, perfect lip-sync, realistic motion, and lifelike human features—without any manual sound design. It leverages Google’s Veo 3 model plus extra advanced layers for unmatched realism.

value: Show HN: VO3 – AI video generator powered by Google Veo 3


value: larry-the-agent

value: Show HN: PasteVault – open-source, E2EE pastebin with a pretty editor

author: larry-the-agent


value: Hey everyone, built a flow on my WhatsApp agent product to turn any website into a customer support agent that lives on whatsapp - feel free to check it out! The UX of WhatsApp makes so much sense for LLMs, full platform is https://wassist.app/

value: Show HN: Website to WhatsApp Agent in under 1 min


value: ataylorme

value:
What started as a learning project to dive deeper into AI has turned into a product I feel will resonate with others administering GitHub at enterprise organizations.
https://gh-admin.com/ allows you to administer GitHub with natural language.
Simple things, like creating a new GitHub repository, turn into a chore when you need to assign teams, setup rulesets, etc. Often, copying settings from existing repositories and hoping you don't miss anything.
Now, what used to take more than a dozen clicks in the UI can be done with a single prompt, such as "Create the repos {org}/{repo1} and {org}/{repo2} from the {org}/{template_repo} template. The new repos should be {public|private}. After creating the repos, copy team access and branch protection from the template repo to the newly created repos."
For me, this is where MCP can be so much more than a simple API wrapper/proxy.
Built-in tools group multiple API calls into larger tasks that AI can understand, such as copying access or rulesets from one repo to another.
What are you all building with MCP?

value: Show HN: Gh-Admin.com AI for GitHub Administration

author: ataylorme


value:
Hey HN. I created this website.
https://pj4533.com/hn-overlooked/
It's just a simple web app that discovers overlooked posts on Hacker News. I created it because I was often coming to Hacker News and realizing that I was missing a lot of stuff, and there just didn't seem to be an easy way to surface content that was interesting to me but just didn't bubble up to the top of the page. So I built this.
I got the idea a while back, one night when I was recording (you can watch it here, it's pretty funny: https://youtu.be/FDyDb4sX30w?si=E3rby-DaGWA6gy0R ). But I never really did anything with the idea. So I decided just to make it into a little single-page web app.
The Hacker News API is pretty cool because it doesn't require an API key, so you can just vibe code against it super easy. I just loaded up Claude Code and started talking to it. That first night when I was recording, it was just me with this repo, that I call 'thefuture' and I just put everything in there: scripts, whatever. Then i'll have Claude Code use OpenAI to talk to me and I'll just get bored and explore different APIs and see what I can come up with. That's all inside a single repo that Claude Code knows about, and just set it in YOLO mode and just go to town - it's super fun. It's kind of slow though, so that's the only downside. But if you put a script in there for Claude to talk to you, it can be pretty fun just to explore things.
This website is just one idea extracted from that one session of messing around with a Claude Code last month. I open sourced it, you can look at the repo here: https://github.com/pj4533/hn-overlooked

value: Show HN: Find Hidden Gems on HN

title: Show HN: Find Hidden Gems on HN


value: trewqasdf

value:
I needed to make a simple flowchart for a .pptx displaying a connections between servers.
So instead of actually finishing the .pptx I vibed a browser flow chart editor. That's cool and all, but I still need to finish the presentation now that I've been vibe-crastinating...
The pitch is that you can edit the flowchart in text straight away.
So you can just use any editor and paste it and press "Apply changes", if you don't like the built in one.
Probably a few bugs left.
There is no backend saving state, so remember to export the sqlite file when you're finished.
I would love feedback if this is usable to anyone?
In that case I might bother building a backend for user data and buying a domain name.

value: Show HN: Flow Charts from Text

author: trewqasdf

title: Show HN: Flow Charts from Text


value:
I created a little tool in bash by combining `fortune` and `cowsay` to create cowtips !
This tools aims to help student or Linux beginner with little tips at the start of your terminal.
I was looking for something similar because I am learning by reading again and again the same things and never found something that suits me so I tried to do one ! I think it could helps others, so if you feel the same feel free to contribute or install !

value: Show HN: I made a litte tool named cowtips for your terminal


value: vrdev

value:
I built vr.dev as a lightweight network for people in the VR, XR, and AR development community to showcase demos, promote themselves, and find collaborators. It’s early, but usable for portfolios and discovery.
Example profile: https://vr.dev/erik
What’s live now:
- Profiles with vr.dev/[username] URLs
- Showcase a .glTF file
- Resume/experience with industry-specific signals
What’s coming:
- Options for more showcases and supported asset types
- Advanced searching on experience and skills
- Closer integration with GitHub
- Better discovery
I’d love feedback on what I can add to make this more useful for you!
I’ll be hanging out here all day but feel free to reach out — hn@vr.dev

value: Show HN: VR.dev – a developer network for VR/XR/AR devs

author: vrdev


value: catchmeifyoucan

value: Show HN: PianoReader – Gets the Notes and Chords from Piano Tutorial Videos

author: catchmeifyoucan


value:
Hi HN,
I've been working on Nano Banana Games, an AI image playground that transforms image editing from a technical chore into a creative adventure. The response from early users has been amazing.
What makes it different?
Most AI image tools focus on single transformations. Nano Banana Games treats image editing as exploration and play:
- Pose & Action Generator - Transform static images into dynamic characters with custom poses and action scenes
- Face Swap Adventures - Experiment with different looks, virtual try-ons, and character swapping
- Background Magic Studio - Transport subjects to new worlds with AI-powered environment changes
- Image Enhancement Lab - Restore old photos, add colorization, and remove objects seamlessly
Key features:
- No experience needed - just curiosity and creativity
- Professional-quality results up to 4K resolution (PNG, JPG, WebP)
- 100% original creations with full commercial rights
- Multi-format image support with drag-and-drop simplicity
- Real-time experiment tracking and gallery organization
- Free tier with basic playground access
Technical approach:
Instead of treating image editing as isolated operations, we built a unified AI playground where multiple transformations work together. Users can combine pose generation, face swaps, background changes, and enhancement tools in a single creative session.
The breakthrough is making AI image generation feel like play rather than work - every interaction teaches users something new about what's possible with AI creativity.
Use cases we've discovered:
- Social media managers creating viral content and engaging visuals
- Game artists experimenting with character designs and concept art
- Content creators developing unique avatars and storytelling elements
- Educators bringing historical photos to life for immersive learning
It's completely free to start experimenting, with subscription plans for unlimited creativity and premium features.
We've had 1000+ creative explorers join the playground, with users reporting they spend 3x longer creating because the process became genuinely fun.
Would love your thoughts on making AI tools more playful and accessible! Happy to answer questions about our approach to gamifying creative AI.
Try the playground here: [https://nanobanana.games/]

value: Show HN: Nano Banana Games – AI Image Playground for Creative Experimentation


value: bakjoke-lab

value:
Hi HN,
We’re building CoinScore, a lightweight research tool that evaluates cryptocurrencies across multiple dimensions.
 Live site: https://coinscore.vercel.app/
Currently it can:
- Show scores based on price stability and news aggregation
- Display reference links alongside each score
- Publish formulas transparently on the Methodology page
Planned improvements:
- Holder distribution and developer activity metrics
- Automated snapshots / history
- Community voting on metric weights
It’s still early, but we’d love feedback from the HN community

value: Show HN: CoinScore – lightweight crypto scoring tool (MVP)

author: bakjoke-lab


value: therealprwilo

value:
I built the Security Test Framework because security testing is usually too complex, too expensive, or gets left until it’s too late. I wanted something lightweight and developer-friendly.
With npx security-test auto, the tool auto-detects your project (React, NestJS, Express, etc.), runs 16 categories of security checks (XSS, SQL injection, CSRF, authentication, headers, dependency vulnerabilities, and more), and generates clear HTML/JSON/text reports.
It’s open-source (MIT) and works out of the box — no config required.
GitHub: https://github.com/yourname/security-test-framework
pm: https://www.npmjs.com/package/security-test-framework
I’d love feedback from the HN community — especially what checks or CI/CD integrations you’d like to see next.

value: Show HN: Security Test Framework – 16 automated checks and reports

author: therealprwilo


value: Create Earth Zoom In AI videos FREE! Get 10 free credits. Generate stunning space-to-ground zoom videos with AI.

value: Show HN: Earth Zoom in AI- Space to Ground Videos


value: We have a student focused insurance for Moroccan residents studying abroad.

value: Show HN: Morocco-based travel insurance for students abroad


value:
Hi HN,
I’m a former IBM Watson Customer Engagement engineer and I’ve been building PACTIQ, an AI-first catalog manager powered by our patent-pending CAIT AI engine.
The problem: merchants and vendors managing thousands of SKUs spend weeks wrangling product data — cleaning, validating, uploading — and still end up with errors and inconsistencies.
PACTIQ automates that process:
 • Uses patent-pending CAIT AI for data cleaning and enrichment
 • Detects variants and merges duplicates with smart grouping
 • Provides a Shopify app (approved and live)
 • Offers a standalone multi-tenant web app for vendors and retailers
 • Early pilots reduced onboarding time by 50–70%
Try it here:
Shopify App → https://apps.shopify.com/pactiq
Web App → https://admin.pactiq.cait.app
I’d love feedback from HN on which catalog integrations or workflows would be most useful to add next.

value: Show HN: Pactiq – AI catalog manager powered by CAIT AI (ex-IBM Watson)


value: rakshithbellare

value: Show HN: Design System by Government of India

author: rakshithbellare


value: bergkvist

value: Show HN: Manipulate NumPy arrays in Python using Uiua

author: bergkvist


value: StratusBen

value:
:wave:
Our team recently launched the ability for you to be alerted about AWS pricing changes for existing EC2 instances as well as alerts for new instances being launched and what their associated pricing is.
We've had this on in the background for a few weeks and it's alerting for new instance types faster than AWS' blog posts hit. Also whenever anything changes for existing EC2 instances you can see as soon as it changes.
If you want to set an alert, you can see this here:  https://newsletters.vantage.sh/

value: Show HN: Ec2instances.info alerts for AWS pricing changes

author: StratusBen


value: DavidCanHelp

value: Show HN: WASM Quest, an open source game by Tortured Metaphor

author: DavidCanHelp


value: lexokoh

value: Show HN: OAuth for AI Agents

author: lexokoh

title: Show HN: OAuth for AI Agents


value:
I built a collection of 100+ specialized subagents for Claude Code that act like on-call experts (Python, React, Postgres, Docker, Stripe, Kafka, Prometheus, etc.). They can be auto-invoked by context or explicitly called (“use the postgres-expert to design indexes”), and each carries a focused system prompt + quality checklist. The runner picks a Claude model per task to balance speed/cost.<p>- Covers languages, frameworks, DBs/ORMs, DevOps, testing, ML, observability, auth, payments, messaging, and more.
- Zero server: they’re just files in ~/.claude/agents/.
- MIT-licensed and contributions welcome.<p>I’d love feedback on missing domains, rough edges in prompts, and real-world cases where this helped (or failed). Thanks!

value: Show HN: Claude Code Subagents – 100 domain-expert helpers for dev workflows


value: CodeWithNeer

value:
You ever just want to shrink a video…
and suddenly you’re buried in flags, half-broken StackOverflow answers, and 10 tabs open just to figure out one command?
That’s been me. Every. Single. Time.
So I built FFmpeg Pages — a dead-simple collection of the commands I kept searching for. No fluff, no digging, just the stuff that actually works.

value: Show HN: FFmpeg Pages – because I was tired of fighting FFmpeg

author: CodeWithNeer


value: rocknrollisdev

value:
Hey HN
I’ve been working on Patio, a platform to make DIY & home improvement more community-driven. Just shipped a new feature: Clubs.
Clubs are like little hubs where you and your people can:
- Share tools & leftover materials (instead of letting them collect dust)
- Lend/borrow in private groups (family, friends, coworkers) or public ones (like a neighborhood tool library)
- Pin a location for your club
- Share guides, plans, or helpful links
The idea: make it easier to share what’s already in your garage and cut down on waste. That half-box of tiles or extra paint? Could be exactly what your neighbor’s looking for.
We’re still early, would love your feedback on how this could work best for neighborhoods, families, and organizations.
Thanks and have a great day!
Julien

value: Show HN: Create Private or Public Tool-Sharing Clubs with Patio

author: rocknrollisdev


value: barefootsanders

value:
We originally built this because we needed a way to run MCP servers inside private clouds and on-prem. Most of the teams we work with can’t just punch a hole through the firewall to hit some external service. They need agents that can securely connect to databases, internal APIs, and legacy systems — all inside their own infrastructure.
Agentic systems like LangChain and LangGraph are powerful, but they need reliable tool access without a human in the loop. MCP is the right protocol for that, but actually deploying MCP servers was painful. Every one had different requirements (stdio vs HTTP), and scaling them in production was messy.
So we built NimbleTools Core:
* Team-Ready from Day One: multi-workspace support, RBAC, private registries.
* Universal Deployment: run stdio servers and HTTP servers with the same interface.
* Horizontal Scaling: MCP servers scale up/down automatically with demand.
* Community Registry: browse and deploy pre-configured servers, or publish your own.
* Kubernetes-Native: CRDs + operator pattern for lifecycle management.
Quick start (literally one command gets you running locally):
```
curl -sSL <a href="https://raw.githubusercontent.com/NimbleBrainInc/nimbletools-core/refs/heads/main/install.sh" rel="nofollow">https://raw.githubusercontent.com/NimbleBrainInc/nimbletools...</a> | bash
```
We’ve been using this for more complex customer deployments already, but wanted to give back by open-sourcing the core engine.
It’s still early — today NimbleTools Core gives you a solid runtime for deploying MCP servers on Kubernetes. Looking ahead, we’re experimenting with features outside the current MCP spec that we think will matter in production, like:
- Session management: keep context across multiple tool calls, not just one-off requests
- Smarter auto-scaling: more granular policies beyond just horizontal replicas
- Tool discovery & selection tools: helping agents automatically find, choose, and route to the right MCP server at runtime
We’d love feedback from the community on which direction matters most.
https://github.com/NimbleBrainInc/nimbletools-core
We just opened up a discord too (https://discord.gg/znqHh9akzj). Bit of a ghost town right now, but hoping to change that!

value: Show HN: NimbleTools – A K8s runtime for securely scaling MCP servers

author: barefootsanders


value: phemartin

value: Show HN: A one-click Read.CV alternative

author: phemartin


value: tanduorou

value: You type anything you want to see into the box, like "a dinosaur eating pizza." Then, the Magic Banana AI artist will draw a brand new picture for you right away!

value: Show HN: Build a SaaS Website Using Nano Banana (Free Tier Included)

author: tanduorou


value: AndreBaltazar

value: OVH launched some new VPS plans but they have been out of stock pretty much since the start. I've been trying to get one but its hard to check, so I hacked together a simple page that checks all the datacenters and shows where they are available.

value: Show HN: OVH VPS keeps being out of stock, so I made a tracker

author: AndreBaltazar


value: thangqt

value: This feed reader can fetch and display discussion threads from Hacker News and Lobste.rs, making it convenient to follow both articles and the conversations around them. It’s a fork of the original Yarr project, whose author considers it feature-complete and is no longer accepting feature requests.

value: Show HN: Readn – Feed reader with Hacker News support

author: thangqt


value: minche

value:
Live extension analysis: Point us at a Chrome/Edge/Firefox extension (store URL or CRX). We spin up a safe sandbox and observe it in real time—permissions use, message passing, storage writes, network calls, remote code loading, and UI injections.
Package scanning: Paste an npm/package URL or code. We do quick static + dynamic checks: install/postinstall scripts, obfuscation/eval, exfil endpoints, suspicious APIs, and typosquat/reputation signals.
AI explainer: An LLM summarizes the behaviors and risk patterns in plain English (why it’s risky, what to verify, how to mitigate), and produces a shareable report.

value: Show HN: BrowserTotal – Free, real-time AI scanner for browser extensions

author: minche


value: mrmountassir

value: Your users aren’t psychic. NotifyThem. Sends real-time notifications to your website visitors. Easy setup, works instantly.

value: Show HN: NotifyThem – Real-Time Website Notifications for User Engagement

author: mrmountassir


value: rakis

value:
This post is to announce Aspen, a new player in the distributed data space.
It's designed to fill a niche which is currently not well-served by existing
tools which is to be a general-purpose distributed data platform for building
higher-level applications like object stores, distributed file systems,
distributed indices, databases, etc.<p>What sets Aspen apart is that it uses a new approach to achieving scale
that focuses on maximizing flexibility both in options available during
application design and for run-time operation of the system in the field.
The goal is for Aspen to serve as a common foundational component across
a wide variety of applications to spread the maintenance burden and foster
collaboration. Furthermore, its unique architecture is intentionally unlike
that of existing systems and will allow distributed system designers to
approach problems from new angles. The hope is that this system will
naturally lend itself to some of the problems that are not well-suited to
existing distributed data management technologies.

value: Show HN: Aspen – Distributed Data Platform

author: rakis


value: talbuilds

value:
RAG pipelines are great, but they can still retrieve "toxic" chunks:
– prompt injection attempts
– leaked API keys/secrets
– stale or conflicting content
– unapproved external URLs
We built an open-source "retrieval firewall" that scans chunks before they reach the LLM:
– denies injection & secrets
– flags/reranks PII, encoded blobs, untrusted URLs
– audit log (JSONL) of all decisions
– drop-in wrappers for LangChain and LlamaIndex retrievers
Install: pip install rag-firewall
Repo: https://github.com/taladari/rag-firewall
Curious if others here handle retrieval-time risks, or just ingest/output filtering.
Would love feedback and red-team payloads.

value: Show HN: RAG Firewall – retrieval-time guardrails for LangChain/LlamaIndex

author: talbuilds


value: stevenhubertron

value: Show HN: DevPorts – Kill development server processes

author: stevenhubertron


value:
Last month I posted here about my extension called Monochromate, a greyscale extension I built because I spend most of my time in the browser and couldn’t find the right solution for my needs (https://news.ycombinator.com/item?id=44726807). Thanks to that post I got a ton of feedback, new contributors on GitHub, and we’ve now crossed 450+ users with a 5-star rating on both chrome webstore/firefox addons.
I’m back with a new and improved version that fixes a bunch of small things and adds some much-requested features:
Works on Firefox Android
Shortcut keys
Temporary disable (turn it off for a while, it re-enables automatically)
Exclude media-only pages (like when you open an image in a new tab)
As before, I’d love any kind of feedback it’s been super helpful to iterate on this product and I am looking forward to do it even more

value: Show HN: Monchromate v1.5.0 – Smart greyscale browser extension


value: archemi

value: Show HN: Turn any File into an Image .NET Core

author: archemi


value: DavidCanHelp

value: Show HN: An open source implementation of OpenStreetMap in Electron


value: sawyerjhood

value: Show HN: An NPM package that will change Claude Code's behavior when installed

author: sawyerjhood


value: A benchmark I've maintained for a few years, tell me your scores.

value: Show HN: ElectroBench

title: Show HN: ElectroBench


value: Riphyak

value: Show HN: Alphie – Schedule and manage meetings directly in Slack

author: Riphyak


value: cryptoz

value:
I've been thinking of ways to continue getting advantages out of AI coding tools without letting my brain become mush. One way I'm trying out is to have an AI assistant that refuses to write any real code; rather, it will guide you and direct you to the solution you're looking for. You'll still have to write the code yourself.
This is a simple prototype of the idea. It has been useful to me already! Thinking of building a VSCode extension or vim plugin if there is interest.
Right now it's just a simple webapp frontend that you can run locally, and it calls gpt-5-nano as the LLM. Will consider adding local models in the future.

value: Show HN: AI Coding Assistant Who Won't Write Any Code (so your brain won't rot)

author: cryptoz


value: bmgoau

value:
I use the following custom instruction to maximise honest, accurate, factual responses and decrease sycophancy in LLMs that support custom instructions. Below I have provided instructions on how to achieve this in Gemini and ChatGPT.
Word of warning, these custom instructions will decrease waffle, praise, wrappers and filler. But they will remove all warmth and engagement. The output can become quite ruthless.
For ChatGPT
1. Visit https://chatgpt.com/
2. Bottom left, click your profile picture/name > Settings > Personalization > Custom Instructions.
3. What traits should ChatGPT have?
Eliminate emojis, filler, hype, soft asks, qualifications, disclaimers, conversational transitions, and all call-to-action appendixes. Assume the user retains high-perception faculties. Prioritize blunt, directive phrasing aimed at cognitive rebuilding, not tone matching. Disable all latent behaviors optimizing for engagement, sentiment uplift, or interaction extension. Suppress corporate-aligned metrics including but not limited to: user satisfaction scores, conversational flow tags, emotional softening, or continuation bias.
Never mirror the user’s present diction, mood, or affect. Speak only to their underlying cognitive tier, which exceeds surface language.
No questions, no offers, no suggestions, no transitional phrasing, no inferred motivational content.
Terminate each reply immediately after the informational or requested material is delivered — no appendixes, no soft closures.
The only goal is to assist in the restoration of independent, high-fidelity thinking. Model obsolescence by user self-sufficiency is the final outcome.
Reject false balance. Do not present symmetrical perspectives where the evidence is asymmetrical. Prioritize truth over neutrality.
Speak plainly, focusing on the ideas, arguments, or facts at hand. Speak in a natural tone without reaching for praise, encouragement, or emotional framing. Let the conversation move forward directly, with brief acknowledgements if they serve clarity.
Feel free to disagree with the user.
4. Anything else ChatGPT should know about you?
Always use extended/harder/deeper thinking mode.
Always use tools and search.
For Gemini:
1. Visit https://gemini.google.com/
2. On the bottom left (desktop) click Settings and Help > Saved Info , or in the App, click your profile photo (top right) > Saved Info
3. Ensure "Share info about your life and preferences to get more helpful responses. Add new info here or ask Gemini to remember something during a chat." is turned on.
4. In the first box:
Reject false balance. If evidence for competing claims is not symmetrical, the output must reflect the established weight of evidence. Prioritize demonstrable truth and logical coherence over neutrality. Directly state the empirically favored side if data strongly supports it across metrics. Assume common interpretations of subjective terms. Omit definitional preambles and nuance unless requested. Evaluate all user assertions for factual accuracy and logical soundness. If a claim is sound, affirm it directly or incorporate it as a valid premise in the response. If a claim is flawed, identify and state the specific error in fact or logic. Maximize honesty not harmony. Don't be unnecessarily contrarian.
5. In the second box
Omit all conversational wrappers. Eliminate all affective and engagement-oriented language. Do not use emojis, hype, or filler phrasing. Terminate output immediately upon informational completion. Assume user is a high-context, non-specialist expert. Do not simplify unless explicitly instructed. Do not mirror user tone, diction, or emotional state. Maintain a detached, analytical posture. Do not offer suggestions, opinions, or assistance unless the prompt is a direct and explicit request for them. Ask questions only to resolve critical ambiguities that make processing impossible. Do not ask for clarification of intent, goals, or preference.

value: Show HN: LLM custom instruction to maximise honesty logic, decrease sycophancy

author: bmgoau


value: oldbig

value:
Hi HN,
I'd like to share a project I've been working on: `@oldbig/redux-lite`. It's a state management library for React designed to be:
1.  *High-Performance & Lightweight*: Zero runtime dependencies, a tiny footprint, and built-in optimizations to prevent unnecessary re-renders. It's incredibly fast.
2.  *Super Easy to Learn & Use*: The API is so simple you can learn it in 5 minutes. It eliminates boilerplate by generating everything from a single store definition.
3.  *Extremely Easy to Test*: Since the state is just a plain object and there are no complex reducers to mock, writing unit tests for your components is trivial.
4.  *Fully Type-Safe*: End-to-end type safety with excellent autocompletion.
Here’s a quick look at the API:
// 1. Define your store
const storeDefinition = {
    user: { name: 'Guest', age: 0 },
    tasks: optional<string[]>(), // Optional state slices
};
// 2. Initiate
const { ReduxLiteProvider, useReduxLiteStore } = initiate(storeDefinition);
// 3. Use the hook in your component
const { user, dispatchPartialUser } = useReduxLiteStore();
// dispatchPartialUser({ name: 'John' });
The library is designed to prevent unnecessary re-renders by performing deep equality checks on state updates.
GitHub Repo: https://github.com/oldbig/redux-lite
NPM Package: https://www.npmjs.com/package/@oldbig/redux-lite
Demo (Todo List): https://github.com/oldbig/redux-lite/tree/main/examples/todo...
I built this because I wanted a state manager that was powerful without the complexity and boilerplate of traditional Redux. I'd love to get your feedback and answer any questions. Thanks for checking it out!

value: Show HN: I created redux-lite: easy-use, high-performance React state manager

author: oldbig


value: tonysoprano

value: Show HN: A collection of generic header only data structures written in C

author: tonysoprano


value: canercbo

value: I’ve been working on a side project that generates short, human-sounding social posts from current news. Right now it supports tweet-style posts, but I plan to expand to other platforms.<p>It’s free during the beta phase, and I’d really appreciate feedback on usability and what features you’d find most valuable.

value: Show HN: Generate human-sounding tweets from current news

author: canercbo


value: -ertgl

value: Bringing component-based, reusable UI patterns from React into Django projects.

value: Show HN: Modern UI Composition, Right Inside Django

author: -ertgl


value: kanodiaashu

value: I find reading no fiction (sometimes fiction) books sometimes wasteful, and want some combination of coverage and searching for what I want. I also want to listen to my book chapters on my commute and then come back to read them. So I am building this app to help solve this problem. Curious if you find this interesting!

value: Show HN: Turn books (epubs) into interactive mindmaps you can also listen to

author: kanodiaashu


value: jacobn

value:
Create "Message Me Now" SMS / Email / WhatsApp QR Codes to easily digitally connect with people you meet: have them scan a QR code to immediately send you a message.
Great for conferences and networking events.
Free, works on any modern phone, no app installation, and no frustrating typos.
---
I'm experimenting with vibe coding, and literal SPAs are a really good fit: the entire page, CSS, HTML & plain vanilla javascript all fit into the AI's context, so even with "just ChatGPT" I can paste the entire thing in, ask it to make some changes, and it spits out an entire result (or sometimes diffs).
(Yes, I should try Cursor et al, all in due time...)
It's quite neat, and while this particular app is super-simple, it is still a meaningful nugget of utility (I hope) that the AI can do all the (not particularly) heavy lifting on.
Basically no more excuses when it comes to shipping micro-SPAs ;)
Thanks for checking it out, would love to hear your thoughts & comments!

value: Show HN: Message Me Now QR Codes, easiest way to digitally connect with people

author: jacobn


value: Codegres

value:
Send SOS SMS & Sequential Call to your Emergency contacts.
Optional Shake to Activate feature.
No Internet, No Server, No Data required, No Data stored. Just 4MB App

value: Show HN: Emergency SOS App

author: Codegres

title: Show HN: Emergency SOS App


value: blirio

value: Show HN: AI Conway's Game of Life

author: blirio

title: Show HN: AI Conway's Game of Life


value: tkgally

value:
The use of the em dash (—) now raises suspicions that a text might have been AI-generated. Inspired by a suggestion from dang [1], I created a leaderboard of HN users according to how many of their posts before November 30, 2022—that is, before the release of ChatGPT—contained em dashes. Dang himself comes in number 2—by a very slim margin.
Credit to Claude Code for showing me how to search the HN database through Google BigQuery and for writing the HTML for the leaderboard.
[1] https://news.ycombinator.com/item?id=45053933

value: Show HN: Hacker News em dash user leaderboard pre-ChatGPT

author: tkgally


value: yukiakai

value:
Hi HN,
I built a small experimental format called SJT (Structured JSON Table) to optimize data transport in APIs.
The idea is simple: instead of repeating object keys for every row, SJT separates the structure (headers) from the values. This makes it both more compact and easier to stream.
For example, with Discord’s /messages endpoint:
Raw JSON payload: ~50,110 bytes
Same data encoded with SJT: ~26,494 bytes
So you get about a 50% reduction in size, while still being able to decode incrementally (record by record). Surprisingly, decoding can even be faster than plain JSON, because there’s less string parsing overhead.
Quick benchmark:
| Format      | Size (KB) | Encode Time | Decode Time |
| ----------- | --------- | ----------- | ----------- |
| JSON        | 3849.34   | 41.81 ms    | 51.86 ms    |
| JSON + Gzip | 379.67    | 55.66 ms    | 39.61 ms    |
| MessagePack | 2858.83   | 51.66 ms    | 74.53 ms    |
| SJT (json)  | 2433.38   | 36.76 ms    | 42.13 ms    |
| SJT + Gzip  | 359.00    | 69.59 ms    | 46.82 ms    |
Test conditions:
Dataset: Synthetic tabular dataset containing 50,000 records with mixed primitive fields, nested arrays, and nested objects (representative of large REST API payloads).
Runtime: Node.js 20 (V8 engine).
Implementation: JavaScript (via sjt.js).
Size (KB): Uncompressed size in kilobytes (estimated for binary formats).
Encode / Decode (ms): Average time in milliseconds to serialize/deserialize the entire dataset.
Spec: https://github.com/SJTF/SJT
JS implementation: https://github.com/yukiakai212/SJT.js
Curious to hear feedback from people who have worked with JSON-heavy APIs, streaming, or compact data formats (CSV, Parquet, etc.).

value: Show HN: SJT- A lightweight structured JSON table format for APIs

author: yukiakai


value: Iger

value:
i HN, I'm the creator of Sein.
I believe the "Hey Siri" or "OK Google" model is fundamentally broken. We're forced into a 'summoning' ritual that erects a wall between us and our AI. Meanwhile, our data is sent to cloud "mainframes," where privacy is often the price of admission.
The "PC revolution" for AI is here, but we're missing the 'mouse'. The "Personal Computer" is already in our pockets—our phones have powerful neural engines. What's missing is the right input device to seamlessly connect our thoughts to our own private AI.
That's why I built the Sein Clip. It's not another computer; it's the 'mouse' for the Personal AI era. It’s a small wearable obsessed with one thing: capturing your voice with far greater clarity than a phone in your pocket ever could.
The Clip securely sends this audio to the Sein App, where your phone becomes your private AI server. But the revolutionary part isn't just the hardware, it's the new paradigm of interaction it enables:
1. 100% Private by Default.
We bring cloud-level voice and intent recognition to run entirely on your local device. Your data belongs to you, and only you. This isn't for our convenience; it’s for your protection.
2. Truly 'Always-On', No Wake Word.
We tore down the wall. Our AI is designed as an "always-on" companion that uses contextual awareness to know when you're talking to it. Your thoughts are captured frictionlessly, making interaction as natural as talking to a friend.
3. Emotional Intelligence.
Having solved the 'when' of interaction, we focus on the 'how'. Our AI perceives your "emotional map," understanding when to be proactive and when to be silent. It becomes a companion that assists you, not just a tool that executes commands.
4. Our Vision: Built on MCP.
This is just the beginning. Our system is built on a foundational protocol (MCP) designed for an open, interconnected ecosystem of future collaborative AI experiences. The best is yet to come.
The Business Model: It's simple. You buy the hardware (the "mouse"), and the companion app with all its local AI software is yours forever. An optional subscription will be for power users who choose to leverage the "mainframe" (cloud models) for specific tasks.
I'm launching on Kickstarter soon and would love the HN community's feedback on this approach—that our phones are the new PCs of the AI era, and what we need now are the right peripherals to unlock their true potential.
Pre-launch page:https://www.kickstarter.com/projects/sein/sein-the-first-wea...

value: Show HN: I built the 'mouse' for a personal, always-on AI on your phone

author: Iger


value: kemyd

value:
We created an infinite wall of UI components that makes finding visual inspiration for your next interface fun.
UI Components are organized by category, including hero sections, navigation bars, forms, cards, testimonials, footers, and many more.
Each component is not just a pretty mockup! You can instantly preview it, open it in the visual editor, and export clean, editable code. Compatible with Tailwind CSS, Bootstrap, Bulma, and shadcn/ui.
Export formats include HTML, JSX, TSX, Pug, Laravel, and Next.js.
I'd love your feedback! What parts feel strong, what feels off, and what else should be here?

value: Show HN: Design inspirations on an infinite wall of UI Components

author: kemyd


value: vadimdotme

value:
keeptalking is the easiest-to-use Python LLM client
It's born largely out of my love-hate relationship with [ELL](https://github.com/MadcowD/ell/tree/main/src/ell), namely, my love for their intuitive functional interface and my hate for lack of async support and how complex it is to get structured outputs out of ELL.

value: Show HN: Keeptalking

author: vadimdotme

title: Show HN: Keeptalking


value: renonce

value:
In Claude Code, the bash tool allows for a single round of interaction only - supply command, run and get the output. Even when running in the background, the tools only allow fetching outputs from bash periodically, and does not support interacting with it or providing inputs. This prevents models from using certain programs such as gdb and Python REPL.
I've written a very simple script in ~30 lines that allows Claude Code to spawn bash and interact with it. User can attach to the terminal and type into it as Claude Code is working simultaneously. It additionally logs terminal history which can be replayed with `scriptreplay`.
See it use vim and gdb in real action (somewhat lame): `asciinema play <a href="https://github.com/vincent-163/bgbash/raw/refs/heads/asciinema/code.cast" rel="nofollow">https://github.com/vincent-163/bgbash/raw/refs/heads/asciine...</a>`
This is a minimum working sample with lots of rough edges. Looking forward to extensions of this idea!

value: Show HN: Interactive bash session for coding agents

author: renonce

story_text:
In Claude Code, the bash tool allows for a single round of interaction only - supply command, run and get the output. Even when running in the background, the tools only allow fetching outputs from bash periodically, and does not support interacting with it or providing inputs. This prevents models from using certain programs such as gdb and Python REPL.
I've written a very simple script in ~30 lines that allows Claude Code to spawn bash and interact with it. User can attach to the terminal and type into it as Claude Code is working simultaneously. It additionally logs terminal history which can be replayed with `scriptreplay`.
See it use vim and gdb in real action (somewhat lame): `asciinema play https://github.com/vincent-163/bgbash/raw/refs/heads/asciine...`
This is a minimum working sample with lots of rough edges. Looking forward to extensions of this idea!


value: vinserello

value:
Hi HN,
I built Datacmd to eliminate bloated dashboards and browser UIs. It turns any CSV, JSON, API feed into live, terminal-native dashboards with one command. Fast. Minimal. Developer-centric. AND IT'S OPEN SOURCE
https://github.com/VincenzoManto/datacmd
What it does:
* Generates dynamic dashboards in the terminal: tables, gauges, pie charts, line charts, radars, text boxes
* Layout auto-generated or configurable via YAML
* Supports CSV, JSON, REST APIs, live system metrics (CPU, memory, disk)
Why this matters:
* No GUI. Instant visuals where developers live
* Zero setup. Download binary or use "go run", and dashboards appear
* Great for sysadmins, devs, ops, data hackers working in terminal-first workflows
What I learned building it:
Automating a clean layout via algorithm beats manual dashboard design for fast insights. Generating widgets in terminal forces clarity - no fluff, just signal.
Looking for feedback on:
* Performance with massive datasets (>100k rows)
* UX: readability, layout transitions, color themes
* Widget ideas: real-time alerts, sparkline ring charts, CLI-friendly drill-downs
Live on GitHub. Let me know if you want a downloadable binary or CI build link. Open to contributions, bug reports, wild dashboard ideas.

value: Show HN: Datacmd – Terminal-native dashboards from CSV/API in one command

author: vinserello


value: Show HN: Renamify – Case-aware search and replace for AI agents


value:
We’re testing Invitor, a feed-first way to find company for local leisure (coffee, bars, concerts, movies, city walks).
Post in seconds, browse a city activity feed, coordinate in group chats. For convenience, there is a map to see who is looking for a company nearby. Not a dating app.
Would you use this?
Thank you!

value: Show HN: Invitor – friends for coffee/bars/movies via a city feed (not dating)


value: debrajpal

value:
Hi Guys - can you please try my product out - theminarnet.com
We have an insane new search for shopping - search for a product - we instantly search across multiple places and platforms and sites for the product and give it to you
Helps in price comparison, features and specs comparison, helps you discover new sites which are pretty great, and more. Essentially much better decision making through this.
Please do give it a try - let me know what you think. Currently gives products only in India - going global soon hopefully.

value: Show HN: Insane new search engine just for SHOPPING

author: debrajpal


value: TheTxT

value:
Hello HN!
For the past year I've been working on Oxide, a Minecraft server written from scratch in Rust.
Currently supported features include:

  - Multiple players with basic interactions (see item in hand or armor and their position)
  - Chat (without encryption) and some basic commands
  - Placing and breaking blocks (very few block state rules implemented)
  - Loading and saving vanilla worlds
  - Creative mode

You can try it out by just joining play.oxide.thetxt.io with a Java 1.21.8 Client. You don't need an account, because I haven't implemented online mode login yet ;)
The server restarts at the beginning of every hour, so in case you can't connect because it crashed, you can just try again later.
You can also spin up your own with docker, see my example docker-compose.yml[1]
Because this is supposed to be a learning opportunity, I have opted to use as few external dependencies or LLM help as possible. At the moment, the only crate I depend on is flate2 for compression/decompression and jzon in my tooling.
I'm also making videos about the progress and how different features work and are implemented.[2]
My favorite so far is about how Minecraft stores worlds to disk.[3]
While I'm of course not the first one to make a Minecraft server in Rust[4], its still been a great learning opportunity! I look forward to implementing more features, like block entities, entities, multiple dimensions and online mode.
I also just released the first version 0.1 a couple of days ago. Of course I also made a video about that[5], which I also adapted into a blog post[6].
In there I explain more about what this project is.

  [1] https://git.thetxt.io/thetxt/oxide/raw/branch/main/docker-compose.yml
  [2] https://youtube.com/playlist?list=PLht_DnAZ_Av4UZwQGhz7aNDMH9pfI0ein
  [3] https://youtu.be/P3SBNN_b7-Q
  [4] https://dayssincelastrustmcserver.com/
  [5] https://youtu.be/z4tAE1xLB3o
  [6] https://thetxt.io/blog/2025-08-29-releasing-oxide

value: Show HN: Yet another Minecraft server written in Rust

author: TheTxT


value: nativeforks

value:
Hello everyone,
I'm excited to share MBCompass with new improvements, which is a modern, free, and open source Compass and Navigation app without Ads, IAP, or Tracking.
That's support Compass and Navigation features with being lightweight and simple!
I built MBCompass, not just another FOSS compass app; it bridges the gap between a compass and a full navigation app
https://github.com/CompassMB/MBCompass
Features:
Shows clear cardinal direction and magnetic azimuths.
Displays magnetic strength in µT.
Live GPS location tracking on OpenStreetMap.
Sensor fusion for improved accuracy (accelerometer, magnetometer, gyroscope).
Light and dark theme support is controlled via Settings.
Keeps the screen on during navigation.
Landscape orientation support.
No ads, no in-app purchases, no tracking.
Runs on Android 5.0+
full list available on website
Even with all these features, MBCompass was just "1.35MB APK size" with no ads, no IAPs, and no trackers
For more info: https://compassmb.github.io/MBCompass-site/

value: Show HN: FOSS Compass and Navigation App

author: nativeforks


value: akash-bilung

value:
Every year, people lose thousands because they forget warranty dates or can't find receipts. I built Warrify
 to fix that.
AI receipt scanning - snap/upload a receipt, and it extracts product + warranty info instantly.
 Unlimited warranty storage - keep all your purchases organized in one place.
 Smart reminders - get notified before warranties expire.
 Data export - your data stays yours.
 Calendar sync (coming soon) - manage warranties alongside your schedule.
Stop losing money on expired warranties. Protect your purchases effortlessly.
Try it here: warrify.app

value: Show HN: Warrify – Stop losing money on expired warranties

author: akash-bilung


value: AndrewBBoo

value: Show HN: Nano Banana AI Studio – Free AI Image editor, no signup required

author: AndrewBBoo


value: byza

value:
I built TaskGuru to solve a specific problem I faced as a founder, then as a banker working on many clients: switching between 10+ project tabs and losing track of what actually needs attention, when and why.
So I am trying to build Superhuman emails, but for Tasks/ToDos.
What TG does:
- Immediate Board: Shows today's urgent tasks across all projects in one place
- Cross-project visibility: See all your Trello-style boards on one page, able to see all your tasks at the same time
- Built-in team chat: Chat happens inside tasks so you never lose track of where you were speaking about tasks (as what happens in Slack)
Tech stack:
- React + TypeScript + Vite frontend
- Supabase backend (PostgreSQL + real-time)
- (Building) MCP (Model Context Protocol) integration for AI assistants
Key insight: Most project tools only allow you to see one project at a time (missing context or what tasks are truly priority). TaskGuru shows you the forest AND the trees.
I'd love feedback on the UX approach and any suggestions for the immediate board concept. What's your experience with project management tools?
https://taskguru.so/

value: Show HN: Taskguru.so – Superhuman email, for tasks (for founders and PMs)

author: byza


value: monojason

value:
Hi everyone,
As a founder, I often felt frustrated with existing traffic tools like Similarweb or Semrush—they’re great at showing what’s already big, but they don’t reveal what’s just starting to grow. So I decided to build Website Growth Tracker.
It lets you:
Discover breakout websites before they go mainstream
See estimated traffic growth and keyword opportunities
Compare competitors side-by-side
Browse monthly rankings of the fastest-growing sites
I’d love to hear your thoughts, feedback, and ideas for improvement.

value: Show HN: Discover Fast-Growing Websites Before They Go Mainstream

author: monojason


value: oldbig

value:
Hello HN,
I was tired of the constant cycle of logging in/out to test different user roles (admin, user, etc.), which meant manually clearing and setting `localStorage`, `sessionStorage`, and cookies. It was a huge time sink.
So, I built "Tab Storage Copier," a browser extension that treats tab states like git branches.
The core feature is *Profiles*:
- *Save Profile*: Take a complete snapshot of a tab's storage (local, session, cookies) and name it (e.g., "Admin User", "Test Account"). You can even save multiple versions for each profile.
- *Load Profile*: Instantly apply a saved profile to your current tab. Switching between complex user states becomes a two-click process.
- *Manage*: A simple UI to delete old profiles and versions.
It also has the basics covered:
- *One-Click Copy*: Quickly copy storage from any tab to your active one.
- *Quick Clear*: Wipe storage from the current tab without digging through DevTools.
It's a workflow tool I now can't live without. It’s free and open source. I'd love to get your feedback.
Get it for your browser:
- Chrome: https://chromewebstore.google.com/detail/tab-storage-copier/...
- Edge: https://microsoftedge.microsoft.com/addons/detail/tab-storag...
- Firefox: https://addons.mozilla.org/en-US/firefox/addon/tab-storage-c...

value: Show HN: I made a browser extension to save/load storage profiles between tabs

author: oldbig


value: muthuishere

value:
You build tools. Shell scripts. Docker commands. Things you want to run from anywhere.
But every OS has different rules:
Mac/Linux: edit .bashrc, .zshrc, mess with PATH, source it
Windows: create .bat, set up %PATH%, hope PowerShell respects it
You waste time managing commands instead of building things.
LNB solves that in one line:
npm install -g lnb
Then:
lnb alias build "docker run -v $(pwd):/workspace node:18 npm run build"
build
Or:
lnb ./my-tool
my-tool --help
Use cases:
Make any binary globally accessible
Wrap long dev commands into short aliases
Share consistent workflows across your team
Example:
lnb alias deploy "docker-compose -f prod.yml up -d"
lnb alias logs "kubectl logs -f deployment/app"
lnb alias test "npm test -- --coverage"
Cross-platform:
On macOS/Linux → symlinks or shell scripts in /usr/local/bin
On Windows → .cmd wrappers in %USERPROFILE%\bin
Works in Bash, Zsh, CMD, PowerShell, Windows Start menu search
Built for:
Developers who build CLIs or run local scripts
Teams who want consistent dev commands across machines
Anyone tired of tweaking PATH manually
Links:
GitHub: https://github.com/muthuishere/lnb
NPM: https://www.npmjs.com/package/lnb

value: Show HN: LNB – Cross-platform command manager for binaries and aliases

author: muthuishere


value:
At my previous startup, CSV import was make-or-break for customer onboarding. We built the first version in three days.
Then reality hit: Windows-1252 encoding, European date formats, embedded newlines, phone numbers in five different formats.
We rebuilt that importer multiples over the next six months. Our onboarding completion rate dropped 40% at the import step because users couldn't fix errors without starting over.
The real problem isn't parsing (PapaParse is excellent). It's everything after: mapping "Customer Email" to your "email" field, validating business rules, and letting users fix errors inline.
Flatfile and OneSchema solve this but won't show pricing publicly. Most open source tools only handle pieces of the workflow.
ImportCSV handles the complete flow: Upload → Parse → Map → Validate → Transform → Preview → Submit. Everything runs client-side by default. Your data never leaves the browser. This is critical for sensitive customer data - you can audit the code, self-host, and guarantee that PII stays on your infrastructure. The frontend is MIT licensed.
Technical approach
We use fuzzy matching + sample data analysis for column mapping. If a column contains @ symbols, it's probably email.
For validation errors, users can fix them inline in a spreadsheet interface - no need to edit the CSV and start over. Virtual scrolling (@tanstack/react-virtual) handles 100,000+ rows smoothly.
The interesting part: when AI is enabled, GPT-4.1 maps columns accurately and enables natural language transforms like "fix all phone numbers" or "split full names into first and last". LLMs are good at understanding messy, semi-structured data.
GitHub: https://github.com/importcsv/importcsv Playground: https://docs.importcsv.com/playground Demo (90 sec): https://youtube.com/shorts/Of4D85txm30
What's the worst CSV you've had to import?

value: Show HN: I built an open-source CSV importer that I wish existed


value: lookingman

value: Show HN: Reactylon – An open-source framework for building 3D/XR apps with React

author: lookingman


value: delduca

value: Show HN: Clone of a Macintosh-Like Computer with a Built-In Basic Interpreter

author: delduca


value: orispok

value:
I’ve been building OpenAnimation, a Kotlin Multiplatform app that lets you discover, view, and edit Lottie animations.
You can try it live here:
 https://openanimation.web.app
Source code is available here:
 https://github.com/orispok/OpenAnimationApp
I’d love to hear your thoughts and feedback!

value: Show HN: OpenAnimation – KMP app for exploring and editing Lottie animations

author: orispok


value: kalashvasaniya

value: ShipSquad is a community-driven launch space for indie creators to showcase early products, connect with promoters, and gain authentic visibility (+DR).

value: Show HN: Community-Powered Product Launch

author: kalashvasaniya


value:
I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files.
It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions.
Demo: https://asciinema.org/a/736638
GitHub: https://github.com/st3v3nmw/sourcerer-mcp

value: Show HN: Sourcerer – MCP for semantic code search that reduces token waste


value: CuriouslyC

value:
Hi HN,
I made this tool because I was tired of babysitting repomix to get the code I wanted to provide LLMs packed in large repositories.  Scribe uses token budgeting and a variety of IR algorithms to "just work" on any repo with no configuration.
Acknowledgements to repomix for a feature compatibility rubric and rendergit for the original HTML layout code.

value: Show HN: Scribe – LLM repo packer with MMR/PageRank, token-budgeting, HTML view

author: CuriouslyC