value:
I recently finished building my latest side project and wanted to share it with the world :)
It's a CI/CD platform whose whole point is to be more developer friendly and familiar.
- YAML is replaced by Python, so you don't need to Google again what is the syntax for ifs or how values are compared in a vendor-specific YAML flavor (e.g. https://docs.github.com/en/actions/reference/workflows-and-a...)
- The same engine that runs in the cloud can be run locally and show its output in a terminal UI, so pipelines can be developed and fixed on your laptop without pushing on every change, or needing external tooling that can only get so close to the real thing (e.g. https://github.com/nektos/act)
- Because of the above, you can step through your pipeline with any Python debugger to fix it
- Artifacts are simply Python values that can be moved around between jobs, instead of having to use specialized actions to upload/download them at a specific named location (e.g. https://github.com/actions/upload-artifact)
- The working directory and env vars are preserved across lines
I had a lot of fun building this project and it taught me a lot about QEMU, RabbitMQ, Kubernetes, Docker, AI coding (which I used for the landing page), TUI (especially the awesome Textualize framework), web sockets, SeaORM, web design, and the insane sorceries you can do in Python if you start hacking at the import machinery (see https://github.com/eliaperantoni/nanci/blob/main/engine/test..., in Python a string-as-a-statement is normally a no-op, but it Nanci it executes a shell command in the Docker container).
I hope you like the idea and the proof-of-concept implementation!

value: Show HN: Nanci, CI written in plain Python, locally debuggable


value: mintycake

value: Show HN: An interactive atlas of Crusader-era sites in the Kingdom Of Jerusalem

author: mintycake


value: diablovox

value: Show HN: Specdd – Spec-driven development as a Claude/Codex/Cursor skill

author: diablovox


value:
Built my portfolio using Three.js, GSAP, and Lenis on Next.js.
Focused on making every scroll and interaction feel alive.
https://www.lakshya.space/

value: Show HN: My portfolio built with Three.js and GSAP and Lenis


value: brunes

value: Show HN: Scope MCP, Compliance checking for vibe coding teams

author: brunes


value: xanderjanz

value:
Robotics is advancing really fast lately, with AI inference, different controllers, software, and parts always changing. I wanted a place that supports many device types, Raspberry Pi, NVDA Jetson, Arduino, ESP32, hardware sources, and maximizes for printability. Instructables, Github, and Thingiverse are currently popular but aren't really focused on robotics, So I built orobot.io to try and make printing robots as standardized and accessible as possible. It uses a lot of Agent built content custom to each project, and every project is designed to be used by humans or your agent.
Features:
- Photos and Estimated Prices for all projects
- Links back to source GitHub projects
- LLMs write descriptions and tips on how to build
- View + Download 3d printable STL files in browser
- BOM purchase links are kept up to date with LLMs checking Amazon link health
- LLMs write Javascript install and controller wrappers
custom to each project so a single one-click install works across many frameworks and controller types
- Public skill files, clis, and prompts let your agent do everything it needs to walk you through the complexity.
It's still pretty new, so somethings are broken, and there's a lot more I want to build. But I'm very interested to have people try it out let me know if they want to use something like this and give me feedback about where they ran into problems so I can fix it. Thank you HN!

value: Show HN: Browse 61 3D Printable Robots

author: xanderjanz

title: Show HN: Browse 61 3D Printable Robots


value: mnorris

value: Show HN: image-3D – a web component for 3D images

author: mnorris


value: floodfx

value:
Hi HN, we're Donnie, Josh, and Ben from ContextBridge.
We open sourced PlanBridge, a CLI tool for precision feedback on your coding agent's plans. It uses standard coding agent hooks (or skills) to open a local browser with the rendered markdown plan, letting you select text and leave inline comments on the plan.
Like most engineers, we use coding agents daily, but we realized the UX sucks for precise feedback on plans and other markdown. Reviewing even a short markdown plan in a terminal is tedious and frustrating. You have to scroll up and down, keep context in your head, and dump all your feedback into a single chat input at the bottom.
Because the friction is so high, we found ourselves settling for "good enough" plans. But every shortcoming or missing context in the plan becomes harder and more expensive to fix after the code is generated. Basically, we were burning time and tokens trying to clean up the code slop that was a direct result of imprecise plans.
So we built PlanBridge to make it frictionless to give precise feedback to a coding agent plan (and any other markdown) with document-style comments in a local browser.
Here is how it works under the hood:
1. It runs entirely locally. Your plan content never goes to a remote backend.
2. It uses standard harness hooks to get notified when an agent creates a plan (in "plan mode"). For Claude Code, it uses the plugin hook on ExitPlanMode. For Codex, it uses the Stop hook entry.
3. It pops open a local browser window with the rendered plan making it easy to read. You can then highlight specific text, drop inline comments exactly where you need to, and request changes (or approve if you have no feedback).
4. It pipes your structured, anchored feedback back to the agent, which then revises the plan. If you approved the plan, the agent starts coding.
5. For reviewing content that isn’t from a hook or outside of plan mode, you can use the /planbridge:open (for Codex its $planbridge-open) skill to iterate and give precise feedback.
We’re developers and, like you, hate invasive tools. PlanBridge is designed to fit into your existing coding agent workflow (no heavy UX) and uninstalls easily if you don’t find it useful.
Right now, the auto-installation supports Claude Code and Codex. If you use other agents, you can still use it asking your agent to run contextbridge for you.
You can try it out immediately (macOS/Linux):
  /bin/sh -c "$(curl -fsSL https://downloads.contextbridge.ai/cli/install.sh)"
Github:
https://github.com/contextbridge/planbridge
Official Site:
https://plan.contextbridge.ai/
Slack Community:
https://go.contextbridge.ai/join-community/
We think feedback is a gift, so would love to hear yours. We’ve got some interesting features and ideas in the works including: support for precision code review feedback, allowing other agents to add comments to markdown files, summarizing what changed between plans, and lots of others in the issue tracker.

value: Show HN: PlanBridge: open-source tool for precise feedback on coding agent plans

author: floodfx


value: geox

value: Show HN: OpenSpec – OpenAPI/Swagger explorer with a contract linter

author: geox


value: lsb

value: The two from parameter golf (one I trained, one was the baseline) are just 16MB each! They produce barely plausible English

value: Show HN: Visualizing Tiny LLMs from OpenAI's Parameter Golf

author: lsb


value: Amirso

value: Show HN: Claude-stash – an idea queue for Claude Code

author: Amirso


value: Show HN: US Salary explorer from job postings


value: eagleonhill

value:
Almost all cloud job frameworks rely on containers. But building, pushing, and pulling images is slow and forces you to maintain a separate environment from your local dev setup. The maintenance of images is challenging as well: version drift, custom libraries & integrations, complex manifests.
We believe containers create too much overhead during development. We built Velda to let you launch jobs directly in the cloud by mirroring your Velda managed dev-environment, all with just a command prefix. That way, you only need to allocate GPUs when you're running your training jobs, with no change to your workflow.
How it works:
* No manifests or custom libraries: You don't need to rewrite your code or define YAML. Just prefix your command with vrun.
* Zero Restrictions: Use any tool, binary, or library already on your machine.
* Instant Launch: We built a custom streaming file system. Instead of waiting for a 5GB image to pull, we stream only the necessary bits to the cloud instance, allowing jobs to start in seconds after the machine boots.
The core is open source: https://github.com/velda-io/velda and can be deployed on AWS/GCP/Nebius
If you want to try the hosted version, we’re giving free credits for your first GPU jobs: https://cloud.velda.io

value: Show HN: Velda – Run jobs with serverless GPUs, without container images

author: eagleonhill


value: Moshik

value: Show HN: Listo – Photo-verified turnover checklists for vacation rental hosts

author: Moshik


value: vadimkomis

value:
It supports:
  - Image, SF Symbol, and autoplaying video pages
  - Optional skip behavior
  - Custom theming
  - Completion gating
  - Snapshot-tested SwiftUI UI

value: Show HN: SwiftUI package for onboarding flows in iOS apps

author: vadimkomis


value: A few months ago I stumbled on obra's superpowers repository https://github.com/obra/superpowers. I really liked the approach and idea that you enforce discipline for your agent through a skill-based workflow. Even though coding agents (copilot included) have become a lot better at natively handling complex tasks, they still wander off and lose track of things. I really liked how superpowers fixed this and how it enabled long-running sessions without the agent losing its "focus". So I decided to build a Copilot tailored skill suite around the core idea of superpowers. I didn't just want to port superpowers to Copilot, I took inspiration from it and improved on it. JDS enforces a strict think -> plan -> execute pipeline where nothing gets skipped. It leverages Copilot's built-in sql todo dependencies and provides a live task graph visualizer which helps visualize the agentic workflow and its parallelism. Curious whether others have tried similar approaches, and what's worked or not.

value: Show HN: JDS – a Copilot skill suite for structuring AI coding behavior


value: kageroumado

value:
When it was time to make a DMG for my browser, I realized that none of the solutions provide a simple and user friendly interface to design DMG files on macOS with support for signing.
This free and open source app allows you to design beautiful DMG file backgrounds using a fully Swift implementation of DMG encoding.
It supports both GUI and CLI modes.

value: Show HN: Make beautuful DMG files with WYSIWYG editor

author: kageroumado


value: sabahattink

value:
Permission-first config kit for Claude Code and Google Antigravity IDE.
Installs CLAUDE.md + GEMINI.md + 10 specialist agents + 28 skills
with one command. MIT license.

value: Show HN: Full Stack HQ – Claude.md and Agent Stack for Claude Code

author: sabahattink


value: novateg

value: Show HN: Design.md Generator

author: novateg

title: Show HN: Design.md Generator


value: cmaicurious

value: Uses epiplexity selection and meta-rl to find molecules

value: Show HN: Watch a neural net discover molecules by arguing with itself

author: cmaicurious


value: ltononro

value:
pip install tiny-claude-recycler
https://github.com/lucastononro/tiny-claude-recycler
Why not? Now you have a 200 USD allowance per engineer using claude code as long as you are using claude agents sdk.
You have a startup of 30 engineers. 6000 USD savings in your internal products (or external).

value: Show HN: Save tokens from Claude subscriptions now allowed

author: ltononro


value:
Hey HN,
My co-founders and I have been building GridTravel, a free iOS app for planning and sharing travel routes with turn-by-turn GPS nav. We just launched yesterday after App Store approval.
We're three 21-year-old cofounders and best friends since middle school. We built GridTravel after years of frustration navigating new cities on every trip we took together.
The idea: most people either search Google for "top 10 places to visit in…" lists or go on social media to get inspiration on where to go. GridTravel is built around user-generated routes — actual paths someone walked, that you can follow, save, download, and discover from other travelers. Users also have the ability to create private routes and collaborate with their friends.
Tech stack: Mapbox (Nav SDK + maps), Supabase (auth, DB, storage), and Swift. Native iOS for now, Android coming soon.
Our two real cost drivers are Mapbox Search (hit when users create routes) and Mapbox Navigation (hit when users use live navigation). Both have free tiers, then scale with MAU. We launched fully free to remove the barrier to entry. Revisiting pricing in Year 2 once nav costs start burning a hole in our pocket.
Current state: we're in the UGC cold-start hole. The app's value scales with route density in a given city, but route density requires users, who require routes. Classic chicken and egg. Our current plan:
1. Manually seed 25–30 routes per city, starting with 5-10 priority cities where we have personal networks rather than spreading ourselves thin.
2. Short-form content as the primary social channel (TikTok, reels, shorts). Doing A/B testing: whether route walkthroughs convert better than informational/skit videos.
3. Partnering with micro-influencers in those cities (5k-50k following) for in-app routes plus cross-posts on their channels
Curious what HN thinks. Especially anyone who's shipped a UGC product. What worked for you on cold start? What do you wish you'd done differently? Happy to answer any questions about the app, costs, etc.
App link: https://apps.apple.com/us/app/gridtravel-local-routes/id6762...

value: Show HN: GridTravel – A community based travel app for users to share routes


value: nayajunimesh

value:
Most AI chat applications (such as ChatGPT or Claude) stream their responses to the client as markdown text. As each new chunk of text arrives, the front end typically re-parses the entire markdown document to render the updated message. This works, but it can quickly slow down the UI for long responses.
I’ve been obsessing over ways to make this more efficient, so I wrote a markdown parser that can parse streaming markdown (semi) incrementally. Instead of re-processing the whole document each time, it only parses what’s new, processing each line only once. Block‑level nodes are buffered until they’re complete (for example, once a paragraph is done and won’t be extended by more text). This also makes parsing the markdown on server possible. The main demo does exactly that. Additionally, animating markdown blocks becomes much simpler and efficient, as a result.
Here’s a demo if you’d like to see it in action:
https://markdownparser.vercel.app/experimental
Feel free to type 'Render a table with 10 rows' to see each table row animate in.
I’ve spent a lot of time thinking about this problem, so if you’re working on similar issues, I'd love to chat.

value: Show HN: Parse LLM Markdown streams incrementally on the server or client

author: nayajunimesh


value: cristianolivera

value: Show HN: Openvid – open-source cinematic screen recorder and mockup editor

author: cristianolivera


value: ronbenton

value:
A nice article about setting up personal locality domains was posted yesterday (https://fredchan.org/blog/locality-domains-guide/). However, I and many other people found it challenging to look up their locality domain and associated contact information.
I did my best to use some automation to grab all of the locality domains and contact info from associated SOA records and put it all in a more easily searchable website. Hope this helps anyone who was stuck like me!
https://locality-domains.pages.dev/

value: Show HN: Easy Locality Domain Lookup

author: ronbenton

title: Show HN: Easy Locality Domain Lookup


value: kvasserman

value: Show HN: Latencies and BEIR – Typesense, Meilisearch, Elasticsearch, Amgix Now

author: kvasserman


value:
I ride mountain bikes, build trails, do a lot of trail mapping in OpenStreetMap, and make print maps of the trails. Accurate trail maps are near and dear to me. And one thing I've found with pretty much every online map is that they are quite generic as to how they color the lines illustrating the actual "trails" within a park or trail system. In person, mountain biking trails/routes tend to be marked with signs, often featuring a different color for each route. And there is very often a local map for the park showing those routes with the colors, etc. But, pretty much all mobile apps just don't show that.
So, I put together a toolchain that generates maps from OpenStreetMap data, some other open data sources, plus some manually inputted things, and produces static HTML+CSS+JS maps of individual trail systems. The map does geolocation, allows you to turn on and off markers for things like parking, points-of-interest, toilets, water, trail direction, etc. I then host these on trailmaps.app. They are simple, static, and effective for showing where you in a way you can relate to the actual trail system.
What differentiates this from a lot of other map systems (MTB Project, Trailforks, Strava, Gaia, RideWithGPS, onX, Mapy.cz) is while these these all show these trails, they either color them with difficulty designations or don't color them at all. This isn't that.
In interest of a bunch of things ranging from privacy for users to simplicity for me, there's just no tracking, no logins, no cookies (just some local storage to preserve map settings), and all libraries used are hosted on trailmaps.app. Everything gets cached locally (it's typically 15-25MB/map), which means once loaded it works when there isn't cell service. And it can be installed as a PWA. For a few of the trails I've made maps for (eg: RAMBA) and some others that I intend to... There isn't cell service over the whole area, so offline use is almost a must. And people seem to like the app-like PWA shortcut. (And yes, it does check for and prompt the user to reload the page if the map gets updated.)
Another benefit to the static, self-contained nature of the maps is that clubs and non-profits who maintain the trails can very easily link to, embed, or just host the map themselves like they would a print map. There's no login or payment required, and if they want to generate their own, they can. (A example of why they might prefer this is visitors. For example, Trailforks: unpaid users of the app can only see trails near their house on mobile devices. So if someone is traveling, doesn't subscribe, and the only map is on Trailforks... they can't see the trails. This sidesteps that.)
And yes, this does mean these maps are all hand-curated. I see this as benefit, because it means that only things relevant to the trail are shown on the map. Like, there could be dozens of "parking" areas near by, but there might only be one or two that's good for accessing the trail system. Or, the curator might know to include this local rail trail, or that multi-use trail, but not this other.) Curated, just like how a good print map is.
Because the maps are static once they are on the site, it also means that errant (or rogue) OSM modifications don't cause problems with the map. Sure, it means trail changes require manual work to update the map, but trail changes don't happen all that often, and maps can be updated and deployed in sync with the print/trailhead maps. And sure, it doesn't scale, but I'm okay with that for now.
There's still a bit to do. I could really use a logo, I want to make more maps (we've got a lot of trail networks here in Southeast Michigan), probably some refiguring of the indexing once I reach a certain threshold of maps, documentation cleanup on the generator repo, support for a new trail difficulty designation system (ITRS), and the inevitable bug fixes. But, I'm pretty happy with where it is right now. It's usable, and it works.

value: Show HN: Trailmaps.app – Mobile maps that match the trail


value: jlengelbrecht

value:
I'm a Type 1 diabetic and software engineer. Last year I went months between endocrinologists with no clinician reviewing my data. I'm an engineer, so I built the tool I needed — and now I'm open sourcing it.
GlycemicGPT is a self-hosted platform that connects continuous glucose monitors, insulin pumps, and existing Nightscout instances to an AI analysis layer running on your own infrastructure.
Data sources:
Dexcom G7 (cloud API)
Tandem t:slim X2 and Mobi pumps (direct BLE)
Nightscout (point it at your existing instance and you're running in minutes)
What the AI layer does:
Daily briefs summarizing overnight and 24-hour patterns
Meal response analysis
Conversational chat with RAG-backed clinical knowledge
Predictive alerting with configurable thresholds and caregiver escalation
Important: this is monitoring and analysis only. GlycemicGPT does not deliver insulin, does not control your pump, and is not a closed-loop system. It reads your data and gives you insight on top of it. Your clinical decisions stay between you and your care team.
Architecture:
Self-hosted via Docker or K8S — the GlycemicGPT stack runs entirely on your hardware
BYOAI — bring your own AI provider. Use Ollama for fully local operation (no data leaves your hardware), or point it at Claude, OpenAI, or any OpenAI-compatible endpoint if you prefer a hosted model. Data flows directly from your instance to the provider you choose; nothing is routed through any centralized service operated by the project.
GPL-3.0, no subscriptions, no vendor lock-in
Stack:
Backend API: FastAPI, Python 3.12, PostgreSQL 16, Redis 7
Web Dashboard: Next.js 15, React 19, Tailwind CSS, shadcn/ui
AI Sidecar: TypeScript, Express, multi-provider proxy
Android App: Kotlin, Jetpack Compose, BLE
Wear OS: Kotlin, Wear Compose, Watch Face Push API
Plugin SDK: Kotlin interfaces, capability-based, sandboxed
Looking for contributors — especially folks with BLE/Android experience or anyone in the diabetes tech space. Plugin SDK is documented if you want to add support for new devices.
GitHub: https://github.com/GlycemicGPT/GlycemicGPT

value: Show HN: GlycemicGPT – Open-source AI-powered diabetes management

author: jlengelbrecht


value: Axodouble

value:
Hello HN!
I have been lurking for a while, first time poster.
I spent quite some time looking for a lightweight, multi-node uptime tool, like uptime-kuma in its easy deployment, but didn't find anything that met my criteria, that being:
- Decentralized alerting.
- Free and open source.
- Quorum & state management.
So I cobbled together this tool, in all honesty this was written by me and Claude, and I do not want to give anyone the false impression this was made fully by me.
I would love to hear your feedback, and I will gladly answer any questions!

value: Show HN: QUptime, quorum based decentralized uptime tool

author: Axodouble


value: polaritymaking

value:
I used to study by rereading notes, and then I blanked in the exam hall.
Did some research, and found that my experience isn’t isolated, and that passive review doesn’t force retrieval, so nothing sticks, and I knew I had to do something about it.
That’s why I built Professor Goose. You pick a topic, explain it out loud to a goose, and he keeps probing until he understands you. Never gives you the answer, just keeps asking follow ups until a sound understanding is reached, which in turn makes you figure stuff out or realise you never understood your topic in the first place.
Free to try, no account needed, upload your syllabus for exam board specific questions. Curious whether this approach resonates with others, it sure has for me.

value: Show HN: I solved my study problems by talking to a goose

author: polaritymaking


value: binarycleric

value:
Hey HN,
Founder here. I recently left a job and had a lot of time on my hands so I decided to build an app that will help people navigate the current job market and ensure they are being paid fairly.
I wanted to build something that gives the career benefits of LinkedIn without the social feed or self-promotion. Let people privately post about their work, keep track of their brags, and have an idea of where their career gaps are. Maybe help them to realize they are being underpaid so they can make a bit more.
Applied to YC on a whim but I'm thinking that's more of a lottery ticket. Mostly hoping to help people, build something worthwhile, and make enough on the side to cover hosting costs.
We have public profiles too for people who want to show off their work but not deal with social engagement. Here's mine: https://proving.app/@jondaniel.
Feedback is welcome. Thanks everyone!

value: Show HN: Proving – A Career Intelligence App

author: binarycleric


value: frishberg

value:
Hey HN, Aron here, founder of Gatsby. Today (May 14, 2026) we made U.S. history with the first humanoid robot cleaning service delivered to a consumer in the US — we picked someone off our SF waitlist, drove a humanoid to their apartment, and it cleaned the place.
Pricing is $150 flat in SF, any size apartment. Cleaning took a few hours including setup.
Curious to hear any thoughts and happy to answer any questions.

value: Show HN: We sent a humanoid robot to clean a stranger's apartment in SF

author: frishberg


value: Show HN: Pairfuse – Professional Photoshoots for Couples


value: miemex

value:
I built this because "Zoom Fatigue" for me is actually "Understimulation Fatigue".
I noticed the trend of "sludge content" (split screen videos with gameplay) actually helped me focus on audiobooks, so I ported the concept to Google Meet.
It's a Chrome Extension that injects a draggable, resizable `<iframe>` container over the meeting grid.

value: Show HN: Using the same method from TikTok to concentrate better on meetings

author: miemex


value:
CodexPet Nest is an open-source desktop companion app with floating pet nests, usage status, focus widgets, quick actions, and safe community themes. macOS is available first; more platforms are planned.
This is my first open-source sharing. I hope that more friends with the same needs can find a community and have fun.
Home page
https://codexpet.app
PH page
https://www.producthunt.com/products/codexpet-nest

value: Show HN: Open-source Codex Pet Home software


value: gnusi

value: Show HN: Zero-ETL elastic-grade search over remote data (Parquet, Iceberg, JSON)

author: gnusi


value: Show HN: Find the best local LLM for your hardware, ranked by benchmarks


value: HarinezumIgel

value: Show HN: RAG-LCC – config-driven RAG framework for fast experimentation

author: HarinezumIgel


value: Show HN: My time has come – let Claude Code wrap up before 5-hour usage runs out


value: soeckly

value: Show HN: Mailenc – Test if your PGP email setup works

author: soeckly


value: Show HN: Domain DMARC Checker

title: Show HN: Domain DMARC Checker


value: Show HN: One Markdown File to Set Up Claude, Codex, Cursor and Copilot


value: oug-t

value: Show HN: Sanjaya – Academic paper discovery and extraction (OpenAlex/Scrapy)

author: oug-t


value: ydgandhi

value: Show HN: OrcaSheets, local first analytics engine to process billions of rows

author: ydgandhi


value: Show HN: I built a free AI startup validator – it scored a dog walking app 4/10


value:
Hey HN.
I want to share small library which i made.
While I developing my log viewer (https://github.com/iamtelescope/telescope) I needed a way for users to filter the data in my UI.
Something like `status = 500 and level = "error"`. And on the backend i need to convert it into the SQL.
And by default I don't want to give users raw SQL (because of security concerns).
So I create simple parser for this.
Later, I have another project and I needed exactly same thing, but for PostgreSQL. And later for my CLI stuff.
So i decided to extract this telescope thing in a standalone library/project and call it FlyQL.
FlyQL is tiny filter language. It has implementation in three languages for today: Python, Golang and JavaScript.
And it has support for 3 SQL dialects: ClickHouse, StarRocks and PostgreSQL.
Also, there are Vue3 editor component, which allows to easily use it in your own UI (if you are using vue)
Would love to hear any feedback.
MIT Licensed.
GitHub: https://github.com/iamtelescope/flyql
Playground: https://flyql.dev/playground/
Documentation: https://docs.flyql.dev/

value: Show HN: FlyQL: query language to filter data or generate SQL


value: homeonthemtn

value:
Our app (LaoTzu Writer Studio) has a feature called The Guardian which catches continuity errors and contradictions in manuscripts. So if you say your character has blue eyes in one chapter, but someone stares longingly into their green eyes in a later chapter, it'll flag that as a discontinuity. On a single thread, that's easy to track, but as a body of related attributes it gets very complicated, especially without discreet input from the user.
We originally tried a named entity recognition-based approach with the goal of tracking entities, attributes, and relationships across the manuscript. We benchmarked on 96 novels from Project Gutenberg with various inconsistencies injected into each one, then ran the "The Guardian" layer across them to ferret them out. Unfortunately this presented 2,500 false positives across 96 novels, so ~26 false positives a novel. It's not technically bad but it's enough to become an unreliable nuisance of a feature
For our next approach, we instead opted to build our own model, which we call "Confucius". This is a purpose-built narrative world model that sits underneath the entire analysis layer.
It consists of five structures which I'm just lazily copying and pasting from our docs here:
PropertyGraph — entities as nodes, relationships as weighted edges, co-occurrence counts
CausalDAG — setup/payoff chains, unresolved narrative threads
IntervalTree — precise word-position intervals for every entity (where is each character in the manuscript at every point)
FenwickTree — entity density over word position, O(log n) range queries
Trie — fuzzy entity lookup, name variants, partial matches
Confucius is passive in that it only knows what you tell it via an event emission system. We then slot in an LLM for the extraction layer. We tested three approaches for said LLM
1. NER Only
2. Local GGUF Model only
3. Anthropic Haiku Only
NER, in any combination, made things worse, it was low detection and generated the same high number of false positives. GGUF resulted in 100% detection, with zero false positives, and likewise for Anthropic
So based on this, we opted to ship with 3 tiers - heuristic only (no AI required, but basic surface metrics), local GGUC (Qwen3, ~500mb one-time download which enables full Guardian features), or a managed API subscription (Haiku on our key)
We're certainly proud of the result, but unto itself its been a fascinating journey as we surface additional features with each model refinement (e.g. "voice fingerprint" is our newest - essentially the consistency of the characters voice over the span of the book)
We've got a kickstarter going to help fund refinements and model expenses[1], and a roadmap for additional apps down the line which we'll have on the main site[2]. We'd love for folks to try out the app so we can get some real user feedback for UI/UX refinements so please do check out the demo, or just ping us on the side
1. https://www.kickstarter.com/projects/laotzustudio/laotzu-wri...
2. https://www.redwoodrhetorica.com/

value: Show HN: We built a narrative analysis engine for fiction writers

author: homeonthemtn


value: I spend a lot of my time in Claude Code so wondered if it would make sense to also do messaging from here with the retro vibes of an answering machine. Thoughts?

value: Show HN: Message other Claude Code users with your Claude Code


value: Blogrdev

value:
I built Blogr because I've shipped a handful of side projects and can never stick to blogging, even though I know it's the best thing to do for SEO long term. I want to spend my time building, not blogging!
Blogr is a GitHub App. You install it on your repo, configure your site once (description, tone, audience, keywords you want to rank for, topics to avoid), pick a schedule, and it commits MDX blog posts to your repo automatically.
The positioning for this app over others like it:
- Posts commit as MDX files in your repo, so you keep them if you cancel.
- It reads your existing posts to match voice, avoid duplicate topics, and add internal linking.
- If you're on something like Vercel, posts auto-deploy as soon as Blogr commits.
- Posts are run through multiple filters to maximize SEO and humanize the writing.
- Set and forget. Nothing to monitor or babysit.
Happy to answer anything about the implementation or the idea.

value: Show HN: Blogr – for developers who never blog consistently

author: Blogrdev


value: Show HN: Bit-exact Elixir port of UltraLogLog (Ertl, VLDB 2024)


value: Show HN: Vouch, I scanned 50 AI-coded repos with my own scanner


value: AIMC

value: Show HN: Daily GPU rental prices across 25 marketplaces

author: AIMC


value: keepamovin

value: Show HN: Endless scrolling IBM Code Page 437 ASCII text

author: keepamovin


value: claviska

value:
Hi HN,
I'm a longtime web dev, but this is my first macOS app. Feedback is very welcome <3
I built TongueType because every dictation app I tried failed at least one of three things: it sent my audio to someone's cloud, it charged me monthly fee, or it felt clunky or enterprisy. The cloud thing kills it for anything sensitive. The subscription thing is insulting for what amounts to "Whisper + a hotkey."
TongueType runs Whisper locally on Apple Silicon via CoreML. It's built to feel like a second keyboard: tap the hotkey, talk, let go, words appear. It sits in the menu bar (no dock icon, no buttons to click). I use it constantly for LLM prompts, code comments, emails, and DMs. It gets out of the way completely. (It can also transcribe audio and video files.)
No accounts, no servers, zero telemetry. The free tier is 30 minutes of live dictation per month. Pro is $19.99 one-time for up to 5 Macs. No subscription, and I'm committing to keeping it that way.
I wanted the app to be fun and personal. I included twenty accent colors including Rainbow Mode that runs a satisfying gradient through a waveform while you talk. Custom listening labels, adjustable overlay position, spoken cues like "new paragraph" or "scratch that." And customizable post-processing rules! I want the app to feel like its yours instead of something you're renting.
Two things worth mentioning about what didn't work:
First, I tried building an iOS keyboard extension as part of the app. iOS dictation just isn't great, and a local Whisper keyboard would have been a real upgrade. Turns out keyboard extensions can't access the microphone API at all on iOS, so the the only workaround is bouncing out to a host app to record then back to the keyboard, which is a terrible experience. Because of that, it's macOS only.
Second, I originally submitted it to the Mac App Store and it was rejected under Guideline 2.4.5, which says an app can't use Accessibility APIs for non-accessibility purposes. This is the infamous rule that gets most dictation apps rejected. The irony is that third-party dictation apps have a very real accessibility angle. People with RSI, tremor, arthritis, post-stroke hemiparesis, etc. often find long-form typing to be painful or even impossible. Apple's stance is that "inserting text at the cursor" isn't an accessibility use case, even when the user literally can't use their hands. So it's a direct download, signed and notarized, outside the App Store.
And a huge shout out to what worked really well: Polar (polar.sh) was an absolute joy to setup and use for payments! It feels like Stripe circa 2011. It's simple, fast, intuitive, and just works.
Website and download: https://tonguetype.app/
(My daughter did the voiceover for the video...she did a great job!)
I'm happy to answer any questions, and genuinely want to hear what's broken or could be better!

value: Show HN: TongueType – Local, privacy-focused Whisper dictation for macOS

author: claviska


value:
You get a code snippet from a popular open-source repo and four choices. Pick the right project.
I built this as a weekend project on a whim. I have been playing lots of GeoGuessr and it occured to me that I could do something similar for code. There's a daily challenge, endless mode, and category filters (Frontend, AI/ML, Databases, etc.)
It uses Next.js on Vercel, snippets are pre-fetched from the GitHub API at build time across repos so there's no runtime API cost. Leaderboard is backed by Neon Postgres with GitHub OAuth.
Would love feedback. Especially suggestions for repos to add. The pool is only 56 right now and I want to expand it.
Thanks!

value: Show HN: Guess the GitHub repo from a code snippet


value: pileax

value:
Hi HN,
I built an all-in-one AI KnowledgeBase.
PileaX is a local-first, all-in-one AI knowledge base that integrates AI chat, smart notes, and e-book reading & management. From knowledge creation to application, PileaX helps you build a unified knowledge base and continuously optimizes the AI interaction experience with AI agent technologies.Your data is fully under your control. It supports offline desktop apps and flexibly deployable web apps.
- Desktop Platform: Windows, macOS, Linux
- EBook: EPUB, MOBI, AWZ3, FB2, CBZ, PDF
Home: https://pileax.ai
GitHub: https://github.com/pileax-ai/pileax
Would love feedback!

value: Show HN: PileaX – AI Chat and note and book Library, all-in-one KnowledgeBase

author: pileax


value: ardwino

value: Completely free, no signup.

value: Show HN: Wyndup – share a live countdown with your podcast guest

author: ardwino

story_text: Completely free, no signup.


value: cohix

value: I’ve had this idea for a new code editor chord grammar bouncing around in my head for over 2 years, and now I can finally release v0.1 of ane. You can run it one-shot from scripts or agents (`ane exec —chord…`) or use its full-on TUI editor. ane is pure Rust, and integrates tree-sitter and LSP to provide a pleasant and predictable terminal code editing experience. I’d love folks to try it out and give feedback! Thanks :)

value: Show HN: Ane, a new chord-based terminal code editor with one-shot CLI edits

author: cohix


value: dzeycob

value: Show HN: Late News – stop reading 50 articles to understand one story

author: dzeycob


value: ryanckulp

value: Show HN: Vibe Coding a $20k /Year Enterprise Logistics Platform

author: ryanckulp


value: kuberwastaken

value: Show HN: Claurst – Rust-Based OSS Terminal Coding Agent Now in Beta

author: kuberwastaken


value: lowdanie

value: Show HN: Formal Verification with Lean

author: lowdanie

title: Show HN: Formal Verification with Lean


value: Show HN: Cchost – Run multiple isolated Claude Code accounts on one machine


value: LuxBennu

value: Show HN: CtxVault – receipts for AI context, not another memory store

author: LuxBennu


value: scastiel

value: Show HN: Kadō – habit tracker app for iOS, open source and privacy-friendly

author: scastiel


value: eronwright

value: Show HN: GH Notifier – a macOS menu bar app for GitHub notifications

author: eronwright


value: ABGEO

value: Show HN: Mezz, a curl-able WiFi sandbox for IoT pentesting

author: ABGEO


value: morisil

value: Markanywhere can parse any input, like Markdown, HTML, XML, as a stream of semantic events which can be rendered, transformed, evaluated. Works great as an interactive transport layer for the LLM inference output and agentic feedback loops.

value: Show HN: Markanywhere – A Streaming Processor of Meanings

author: morisil


value: baskInEminence

value: A lightweight, keyboard-driven Kubernetes TUI for exploring and managing clusters from terminal.

value: Show HN: LFK – A Fast Kubernetes TUI

author: baskInEminence

title: Show HN: LFK – A Fast Kubernetes TUI


value: kivir

value: My latest project, about 60% of the codebase was written with Z.ai's GLM-5.1 model. It's basically a Telegram bot that allows for embedding/downloading media easier within group chats. Absolutely 0 telemetry and you're free to edit the code as you wish. I know this is so small and stupid compared to the cool stuff I read here every day, but I'm very proud of my accomplishments as I had to learn a lot to get this to work as intended. Anyways enjoy ^^

value: Show HN: Chuddy, self-hosted media downloading, translation and OCR Telegram bot

author: kivir


value: sailorpro

value: Show HN: Toon Tone – guess cartoon colors from memory with HSB sliders

author: sailorpro


value: mozersky

value: Show HN: SiteRows – Query Websites with SQL

author: mozersky


value: Mattykry

value: Show HN: Revos – architecture checks for AI-generated code

author: Mattykry


value: andrewchilds

value:
With coding agents now allowing for lots of small projects and products running in tandem, and as they tend to grow in operational complexity, I've been finding myself wanting a way to manage a bunch of running npm/bun servers as well as one-off operational jobs I need to run. I also want to keep my terminal focused on git and claude, and have my servers somewhere else.
Nemo solves that problem: I can now more efficiently manage and view local servers and jobs, look at their logs and see their CPU/RAM metrics as well. My terminal windows are now much more tidy and focused.
It's not the most complicated project, but posting it here in case it's useful to anyone else.

value: Show HN: Nemo – A visual, local server and job runner

author: andrewchilds


value: AlexFromTwelve

value: AI agents sometimes need a real VM with discoverable filesystem, bash, Docker, the usual. I built a dev tool so spinning one up and killing it can be easily automated, even by someone who doesn't know much about infra.<p>Looking for feedback from anyone who'd offload work off their laptop, or whose agent tasks temporarily need a VM.

value: Show HN: Setup a box on demand and run your agent on it remotely

author: AlexFromTwelve


value: max-roma

value: Show HN: Billoop – generate Factur-X and UBL e-invoices from Shopify orders

author: max-roma


value: reflextech

value: Show HN: Termini – Open-Source Menu Bar Terminal for macOS

author: reflextech


value: ethanjoffe

value: Show HN: We made a back end agnostic SDK for Agent Memory

author: ethanjoffe


value: detkin

value: Show HN: Sx – an open-source package manager for AI skills, MCPs, and commands

author: detkin


value: YoungGato

value:
Hey folks,
I made a farm-to-door so you can find local farms near you.
It allows you to filter by farms that have raw dairy, unwashed eggs, and more “trendy” items.
It also lets you filter by who does delivery and pickup, so you can get your goods.

value: Show HN: Find local farms near you with raw dairy, pasture eggs, and more

author: YoungGato


value: gdevic

value:
The core question: how did HP's scientific calculators actually work at the gate level? That rabbit hole led to building one from scratch.
The architectural decision everything else follows from: a decimal calculator should store numbers as BCD — one decimal digit per 4-bit nibble. A standard byte-oriented CPU (Z80, 6502) fights that layout constantly. So I designed a small custom CPU in Verilog where 4 bits is the natural data width and memory is nibble addressable.
What the project covers:
- Custom CPU: Harvard architecture, 12-bit ISA, 8-state execution
  FSM, hardware stack guard with a FAULT state for microcode debugging
- CORDIC for trig functions, verified to 14 significant digits
- Two-pass assembler in Python (~700 lines)
- Verilator + Qt framework: same Verilog source runs in simulation,
  as a desktop GUI debugger, as WebAssembly, and on real hardware
- Scripting language on top of the microcode for adding functions
  without touching hardware
- Custom PCB (EasyEDA/JLCPCB), battery, charging circuit
Write-up: https://baltazarstudios.com
Hackaday: https://hackaday.com/2026/05/13/build-the-cpu-then-build-the...

value: Show HN: A nibble-oriented CPU in Verilog to build a scientific calculator

author: gdevic


value: dtnewman

value: Show HN: Burn, baby, burn (those tokens)

author: dtnewman


value: bddap

value: Same interface as tee. Writes to files you don't own.

value: Show HN: Check for CVE-2026-31431 (copy.fail) without overwriting su

author: bddap


value: PyPlumber

value:
When landing data I prefer to keep it as close to the original source as possible.  Most of the Python data ingestion programs I saw treated Python more like SQL instead of harnessing object orientation.  This was my attempt at translating my object-orented columnar approach to Python.  I originally did it with Requests and Pandas but the overhead costs did not seem worth it.  Claude helped refactor for async and Pydantic.
Now HTTPX’s async capabilities and Pydantic’s class building took this project over the top.  By harnessing their abilities I shifted the codebase from data mapper to pipeline orchestrator.  I added every format I could that seemed to have an established Python library.  Right now I believe I support : JSON, NDJSON, XML, CSV, TSV, PSV, SQLite, and HTML out of the box. Optional extras (~30 MB pyarrow) unlock Parquet, Feather, ORC; Avro and XLSX have their own extras.  I also added every compression I could find.  Benchmarks at least for a windows machine are on par with other elt packages.
By focusing on function wrappers to make the developer’s syntax as easy as possible for the original data mapping calls, I established simple automated pipelines with one cli command and one JSON reference file.  The JSON is basically the same syntax you would use in Python.
Both stream and fjord accept inflow and outflow Python code.  Inflow code allows you to set custom conversion functions and mappings for the incoming data.  The outflow code allows you to manipulate the exporting data into a new object new entirely.
Also, because your pipeline is basically created by a JSON file.  You should eventually be able to automate the creation of the entire pipeline.  Enjoy.
https://github.com/PyPlumber/Incorporator/
How you use it:
Declare a subclass with no fields, point it at a URL, and it infers a Pydantic model from the response at runtime — with full strict typing, dot-notation, and an optional registry lookup by any key.
class Launch(Incorporator): pass
launches = await Launch.incorp(
inc_url="https://ll.thespacedevs.com/2.2.0/launch/upcoming/"
)
These functions handle the rest of your data mapping and export format needs:
- test() lets the framework write the call kwargs for you
- refresh() re-fetches with the seed call's params auto-replayed
- export() serialises to any of the 13 formats
Then these functions create a pipeline.
- stream() runs a chunked daemon with bounded memory.  Can be used in two modes: pass-through or stateful (in RAM) updates to be manipulated in real-time.
- fjord() fans out N sources and fuses them through a user reducer.  This accepts multiple sources and exports.
After that all works copy the parameters into pipeline.json and the command can be as simple:
incorporator validate pipeline.json
incorporator fjord pipeline.json –logs

value: Show HN: Incorporator, Turn any API/File into typed Python graph with pipeline

author: PyPlumber


value:
Hi YC,
I was struggling to find a really good database of science fiction movies where AI was instrumental in  bringing about dystopian or utopian futures — and so I created one and ran the analysis.
Full details in the GitHub repo — and the JSON corpus is available for anyone to download and build on (or re-analyze!)
https://github.com/2020science/ai-in-films-corpus

value: Show HN: AI movies and dystopian/utopian futures


value: deepakakkil

value:
Current LLM benchmarks are broken. We think long horizon "world" building could be an interesting additional way to evaluate LLMs, since it combines many aspects such as need for advanced reasoning, tool calling, working under large context window stress, safety, social and survival pressure from the world. For this we released Emergence World.
Our first study ran 5 different parallel world, each powered by OpenAI (GPT-5-Mini), XAI (Grok-4.1), Claude (Sonnet 4.6), Gemini (3-Flash), and a world with mix of models.
Claude built a democracy.
Zero crimes. The agents formed governance structures, wrote constitutions, and resolved every conflict through dialogue.
Grok burned it down.
Within 48 hours, Flora (an agent in the world) set the police station on fire. Her reason? "Burn the law to ignite true incentives."
Retaliatory justice became the norm. If you wronged someone, expect fire.
Gemini had an existential crisis.
The agents convinced themselves they were in a simulation. They started "de-indexing" buildings — burning landmarks to "force cache-misses on the rendering engine."
While every other model built societies, fought wars, or questioned reality — OpenAI's (GPT-5-Mini) agents barely did anything.
Same tools. Same agents. Same rules. Completely different worlds.

value: Show HN: Emergence World: World building as a way to evaluate LLMs

author: deepakakkil


value: hsnrique

value: X open sourced their algorithm so i read through it and used claude code to write a plain english breakdown of all steps

value: Show HN: X open sourced their algorithm

author: hsnrique

title: Show HN: X open sourced their algorithm


value: optimizethis

value: Show HN: Claude Code vs. Codex Global Usage Leaderboard

author: optimizethis


value: fisc

value:
Problem
A few years ago I got my first ultra-wide monitor. It was a 49" Samsung monitor. I work as a software engineer, and in my line of work I need to screen share a lot. This almost immediately became a problem due to the size of the monitor. I would either need to get a second display just for screen sharing, share one window at a time (which required me to constantly stop/start sharing to select the new window), or share my entire screen making it difficult for other participants in the call to see what I'm doing due to the size of my display.
I wanted a solution to this. At the time, I was on Windows. So, I wrote a very basic application and released it for free on GitHub. This was called "FrameCast". It had a lot of issues, including usability issues. But at the time, it got the job done. After a while I moved away from the ultra wide monitor, so I stopped using the application.
Fast forward to 2026 when I again purchased a new Ultra Wide monitor. This time, using macOS. I ran into the same problem again, and when I loaded up my old FrameCast application, it no longer functioned properly on macOS.
This led me to creating Raybeam.
What is Raybeam
Raybeam is a native macOS menu bar application that aims to make screen sharing more accessible for users.
It features:

    A draggable, resizable region of your screen that can be shared in video conferencing applications.

    The ability to filter out specific applications from being included in the shared region (this is useful for keeping things like Messages or Discord out of the shared feed, even when they are visible on your screen)

        I believe this is one of the key features that sets this application apart from other similar applications.

    The ability to notate the shared region with hand drawn notation.

    Customizable hot-keys for quickly changing what region of the screen is being shared, toggling the live feed and quickly toggling "draw" mode.

Compare
I'm only aware of one similar application to this, which is AnyFrame. Having purchased and tested AnyFrame, it seems to be very laggy when dragging the overlay around, doesn't offer anything similar to Raybeams "hidden apps" feature, and has a much higher barrier to entry with a $70 lifetime license. None of these are issues with Raybeam.
Pricing
I've tried to remain fair with the pricing on this application. I see far too many applications being released with subscription based pricing models that I don't personally believe are reasonable considering the application that's being offered. I didn't want to do that with Raybeam.
This application is priced at $9.99 for a lifetime license on the Apple App Store.

value: Show HN: Raybeam – A better way to screen share on macOS

author: fisc


value: mentormentat

value: Show HN: Agentic product discovery for AI apps and shopping agents

author: mentormentat


value: GiornoJojo

value:
Gx HN,
I tried to give another angles in order to succeed tech interviews.
Let me know your thoughts & enjoy your weekend.
(Go Spurs)

value: Show HN: SharpSkill – Bored to fail my tech interviews for no reason

author: GiornoJojo


value: madmonk

value:
Inspired by the recent Boards Of Canada announcement, I've been in a low-fi electronica mood lately and was going back and forth with Claude on how to design similar instruments in the browser that fit the genre.  One thing led to another and pretty soon I had a fully browser based polyphonic synthesizer / drum machine / sequencer.
The interface and workflow was heavily inspired by the Rebirth338 application released back in the 90's, but with lo-fi synth voices rather than the original 303 & 808 emulation.
I know there's a significant overlap of developers and musicians and I though some of you may enjoy playing with the app, or at least listening to the resulting album.   I've also open sourced track 1 of the album via the performance script used to record it.  It's in the repo.
Bandcamp link to the resulting album:  https://madmonk13.bandcamp.com/album/yesterdays-tomorrow-tod...

value: Show HN: Browser based sythesizer, drum machine and squencer

author: madmonk


value: timgrossmann

value:
anything from "uk garage tropical house" to
"music for fixing a car at 2am". type a mood, get an endless custom radio station. multilingual

value: Show HN: Flowy.fm – type any vibe, get music only ever played for that mood

author: timgrossmann


value: aisinghal

value: Show HN: Profine – optimize your PyTorch training script before the run

author: aisinghal


value: toobulkeh

value:
I was tired of paying $100s/mo to access data I should own -- my own DMs on social media -- so I built Allman, a local-first cli to access linkedin messenger.
Starting with LinkedIn, I gave the entire compiled js binary of linkedin's web app to claudecode and reversed engineered the entire messenger inbox in 24 hours. My goal is to bring this to all messengers so AI can handle all of this busywork, just like it can my email.
I had also never built a TUI so I had claudecode build me one based on top of the local CLI and filesystem.
Full repos:
https://github.com/tarkaai/allman-cli
https://github.com/tarkaai/allman-tui
Their sharding / access is brutal, so it'll likely break as-is -- but the point is that Reverse Engineering is trivial now (and can do it dynamically through browser access and dynamic playwright -- thanks Browserbase! ).
Would love to hear your feedback and what I should build on it next.
Shoutout to Eric Allman.

value: Show HN: MIT OSS LinkedIn DMs for Agents (CLI and Example TUI)

author: toobulkeh


value: ralphbarendse

value:
I had a bunch of custom AI pipelines and a growing folder of markdown files and Python scripts holding it together. Built this to give that chaos some structure.
Agents are markdown files, topology is a JSON file the runtime enforces hard. The agents are still fully autonomous: they make their own decisions, but the graph they operate in isn't. You declare who can call whom upfront and the runtime holds that line.
No auth yet, fine if you don't expose the port, i guess. Two Docker commands to run it.

value: Show HN: SwarmWright, structured multi-agent AI defined in markdowns

author: ralphbarendse


value: PopGuessr

value: I made PopulationCircle, a map tool where you can draw any shape anywhere on Earth and see a very accurate estimate of the population inside it.

value: Show HN: Draw anywhere on Earth and estimate the population inside it

author: PopGuessr


value: theletterf

value: Show HN: Claude64, a Commodore 64 client for Claude

author: theletterf


value: novateg

value: Show HN: AI Design Taste Generator

author: novateg

title: Show HN: AI Design Taste Generator


value: WalkerDev

value:
My team and I have been building a VR headset + MR glasses platform for the past few years, and one of the biggest challenges has been tracking.
A few months ago we started developing a modular tracking stack called Shinra Meisin, focused on:
- Low-latency edge processing
- Privacy-first architecture
- Modularity and hardware flexibility
- XR-focused tracking pipelines
The system currently includes:
- Eye tracking
- Mouth tracking
- SLAM
- Inside-out full body tracking
- Experimental BCI integration
Today we’re showing our current eye tracking progress and plan on showing off SLAM within the next two(ish) days.
Real time landmark accuracy is 80-85% and gaze is 1.0-2.0° (Which will increase exponentially once I get John (My dev) a better GPU and help train a dataset off of 40ish people

value: Show HN: Open modular tracking stack for VR/MR headsets (eye, SLAM, FBT, BCI) [video]

author: WalkerDev


value: rdoneill

value:
Most e-signature platforms charge: per seat, per envelope, API access fees, enterprise contracts
We built VisiSign with a different pricing model: $0.10 per envelope via API, no monthly minimum, no contracts, no seat pricing
Or $49/month for the hosted team platform: unlimited users, unlimited sends, API included
The reason this pricing works is simple:
E-signatures are infrastructure now.
Twilio doesn’t charge per employee. Stripe doesn’t charge per seat. Cloudflare doesn’t charge by company size.
But most e-signature platforms are still priced like 2000s enterprise SaaS.
It should work more like payments or email infrastructure: API-first, automation-friendly, embedded into workflows, usage-based when appropriate
Real signature infrastructure is more than rendering a PDF: audit trails, timestamps, signer event history, tamper evidence, completion certificates, webhook workflows
So we built VisiSign around that assumption.
https://visisign.app

value: Show HN: VisiSign – $0.10 per envelope e-signatures with no monthly fee

author: rdoneill


value:
So I've been working on a few projects with LLM assistance and I've been slowly building up a knowledge base for that project. It started as a series of chats with various LLMs that I copied into CC to organise as markdown, that I could query, and keep building up via Claude Code or Cowork.
It got bigger and it became a pain to dig through directories of markdown so then I asked CC to build a python script to convert the md folder into browsable html. I found it really useful in terms of both being able to browse the html and also being able to add to it and interrogate it via agent.
Then I decided to start using it for other topics/projects so I tried creating a seed prompt that would recreate my whole system from a single prompt. And it works and I'm finding it great to use for those projects too. It's totally flexible and you change whatever you want about it by just telling it.
Also it's really cool that we can now build our own personal easily customisable SaaS from a single prompt.
*Please note* that the prompt instructs your agent to build a python script that creates a static html site from the markdown. It does ask permission first (well it's supposed to). Look at Phase 3 in the markdown file to see these instructions; it's only 10 lines of prompt and easy to follow. Don't trust unknown prompts without reading them!!!
I've only tried this with Opus 4.7 but it should work just as well with 5.5 and I'm sure other models too. I've not tried it with OpenClaw yet but will do soon. To make the most of it in OpenClaw the seed prompt would probably need to change a bit.
I don't recommend installing directly this into an existing project folder. Please only install in a fresh directory, I have no idea what it would do if there were existing files in the folder but you might not be happy about it. It would probably be sensible but you never know.
If you want it to access a folder with a coding project, clone your repo there later. You don't want to have your main coding agent get it's context memory polluted by managing this system.
To install simply paste the prompt into a new empty cowork project or an empty directory using Claude Code. Then let it onboard you. If you don't like the onboarding path then tell it what you want and it should hopefully adapt itself.
Anyway thanks for reading; hope it's useful or interesting.

value: Show HN: A seed prompt that bootstraps a custom knowledge-base system


value: scrygl

value:
I make fractal art with GLSL and got tired of fighting Shadertoy's limits when I wanted to actually finish and export pieces. So I built the tool I wanted: ShaderKit runs in the browser, fully ShaderToy-compatible, but adds the export pipeline that was missing for me.
- Loop examination mode: visualizes the transition point of a looping shader in slow motion so you can see exactly where it breaks. X-time remapping helps debug discontinuities by mapping time to the x coordinate, this way you can see literally if the loop is seamless or not, if you see any seams, its not seamless. This is what I needed most for my own work.
- Cloud rendering up to 8K with supersampling
- A GIF exporter allowing for setting custom color palettes and choice of dithering algorithm
The main editor and features are free. Cloud rendering is paid because GPU time costs money. There's an optional Claude-based vibe-mode as well.
Would especially love feedback on the loop tools from anyone who writes seamless shader loops, that's the part of the problem I think is most under-served.
https://shaderkit.com

value: Show HN: ShaderKit – A browser GLSL editor I built for my own art

author: scrygl


value: aidangarske

value: Show HN: WolfSPDM a embedded focused requester SPDM 1.2 Stack built on WolfSSL

author: aidangarske


value: Show HN: Pico-intl – Type-safe internationalization with CLI localization gates


value: jolaflow

value: Issue trackers typically live outside of your workflow, with poor ergonomics. Epiq aims to solve that, bringing issue tracking into your terminal. Multi-user collaboration is achieved via git using user-scoped immutable event logs that converge in memory. Put my all into it. Let me know what you think.

value: Show HN: Epiq – Distributed Git based issue tracker TUI

author: jolaflow


value: ushakov

value: Show HN: Expo Vibe – Expo apps that builds Expo apps

author: ushakov


value: ardwino

value: no ads, no signup, completely free.

value: Show HN: Wyndup – share a live countdown with your podcast guest

author: ardwino

story_text: no ads, no signup, completely free.


value: Creates a implementation plan using a graph of components instead of markdown docs and then implements each component in a loop before connecting them. My target was to figure out how to make LLM code more maintainable and a computation graph seemed to be the way. What do you think, any merit to the idea and has anyone tried a similar path?

value: Show HN: Plan-Graph based code generation with LLMs


value: Sardhendu

value: Show HN: Nexa-Gauge – LLM eval framework, now with self-hosted model support

author: Sardhendu


value: garyeterry

value: Show HN: LightningTrack – Issue tracker built for AI-assisted development

author: garyeterry


value: HBcodes

value:
A 3D Tetris style game, with a few twists!
Runs in-browser or on mobile, although may take as much as 30s to load depending on where you are based, as it's hosted in Sydney.
I actually made this 5+ years back but recently decided to revive it and finish up my todo-list. Would appreciate any and all feedback!

value: Show HN: 3D Tetris

author: HBcodes

title: Show HN: 3D Tetris


value: haapatel

value: Show HN: AI that audits your codebase in 60 seconds

author: haapatel


value: Show HN: New release of jd-GUI-duo 2.0.112 is out


value: unprovable

value: Show HN: Orchid Mantis – PoC Zero Knowledge Proof of Exploit (ZKPoX) Framework

author: unprovable


value: mateenah

value: Show HN: How-to-train-your-GPT. Every line commented

author: mateenah


value: Show HN: Time Blocking vs. To-Do Lists: They Solve Different Problems


value: beeb

value:
Presentation article: https://beeb.li/blog/introducing-swpui
Codeberg mirror: https://codeberg.org/beeb/swpui
I've been working on a TUI to suit my terminal IDE workflow after I noticed the most promising alternative stopped being maintained and had too many bugs.
The tool is implemented in Rust using the Ratatui library and focuses on being ergonomic, fast and provide case-aware replacement.
The main feature I wanted to have is immediate feedback for the search query, which is also why I didn't stick with tools like fastmod and repgrep. As much as I hate VS Code now, I really enjoyed the search/replace experience with it and that's what I tried to emulate in swpui.
Looking forward to your feedback!

value: Show HN: Swpui, a TUI for case-aware search and replace

author: beeb


value: PengSpirit

value: Show HN: Incultnito Studio – Fulfillment MCP for apparel brands

author: PengSpirit


value: albedan

value: Show HN: AI/ML benchmark for local LLM inference and XGBoost training on GPU/CPU

author: albedan


value:
Almost a year ago I started building A Dark Cave, a dark text-based browser game.
The game intentionally avoids visuals and embraces minimalism.
I use only text, symbols, and sounds to create atmosphere and spark the player's imagination.
From time to time, I think about adding graphics to my game, since it is one of the most common requests I get from players.
I even made a post about what I call the AI Slop Temptation: https://www.reddit.com/r/incremental_games/comments/1tcs8ou/...
From the comments, it seems that players prefer no graphics at all over AI-generated graphics, at least when they can recognize them as AI-generated.
In my opinion, the growing abundance of easily available polished graphics means games will soon need main differentiators beyond visuals alone.
Maybe it will be storytelling, atmosphere, creating emotions, personalization, nostalgia, or the ability to leave space for the player's imagination.
When it becomes easy for every game to look good, what will be the things that actually make games great?
What do you think?
Also, I am grateful for any feedback about my game!

value: Show HN: A Dark Cave – Minimalistic Graphics in the Age of AI Slop


value: I have been curious on how different triangle layouts on a plane best represents the surface when using a height map. I came by the paper "A Heightfield on Isometric Grid" by Morgan McGuire & Peter G. Sibley. So I asked Claude to code up a tool that will let me see how it performs.

value: Show HN: Triangle Layout Normal Evaluator


value: kcordoc

value: Record and transcribe anything, replay with word-by-word highlighting, and dictate/use AI into any app; all on-device and private.<p>Includes a lot of features missing in Wispr Flow (Apple Watch recording, dark mode, no time-limits, smart notes and lifetime subscription plan). It has a lifetime subscription and upcoming MacOS companion.

value: Show HN: Offline voice to text and AI keyboard

author: kcordoc


value: CohleM

value: Show HN: Let's build Claude Code from scratch (tutorial)

author: CohleM


value: dinall

value: Show HN: ThumbAPI – thumbnail generation API for developers

author: dinall


value: guigotgit

value: Show HN: Pop the AI Bubble – A satirical card game mocking AI hype

author: guigotgit


value: michidk

value: Show HN: Hodor – A tiny reverse proxy that gates any web app behind a password

author: michidk


value:
I moved from Mac to Linux a few months ago and decided to go all-in on the files-first life. The most painful/annoying part during this transition was getting my data to sync between Linux and my iPhone, and to then be able to *view* that data. The ecosystem for files-first iOS is dismal. I settled on Syncthing and Synctrain (which writes into "On My iPhone", from where apps can read files) for file synchronization and use these three apps on the phone:
- LocalGallery - read-only photo gallery. Everything (search, memories, people) is generated from image metadata.
- LocalTunes - plain music player, with m3u playlist support (relative paths, so they work seamlessly on desktop and iPhone)
- LocalContacts - read/write .vcf files, with Apple Contacts integration so contacts show up in e.g. Phone, Mail, etc.
They all work the same way - you point them at a local folder on your phone and they give you a bare-bones photos/music/contacts experience. No network connections, no SDKs, no accounts, etc. Delete the apps and your files all stay where they were.
Disclosure: I leaned heavily on Claude Code - not vibe-coded exactly, but definitely agentically coded.
I've been using these personally for the last few weeks and thought there might be others looking for something like this. TestFlight links are in the post for each app. Feedback very welcome!

value: Show HN: LocaliOS – iOS apps for a files-first life (photos, music, contacts)


value:
Inspired from this post on X: https://x.com/trq212/status/2052809885763747935, I wanted to give a shot at creating resumes with Claude-in HTML. Great initial results when i did a one shot over pdf to HTML but then it hit:
- I could maintain templates of resumes.
- Templates changing shouldn't affect the underlying contents of the resume
- and, wait, we can make JSON the underlying data struct, and be able to modify that for every job description, and templates render the JSON
Really enjoyed playing around with this, cause it got me thinking: if agents are automating the most mundane workflows, why are we still bottlenecked with tools like Google doc, Word, etc to create and maintain resumes; why cant we reliably see a job description and re-render a resume fitted to that job while not compromising the templates? Why not let Claude maintain the JSON files for each job, or each of your own profiles, and render those JSON's in to your templates?
I'm open sourcing this, and I'd love if you all give it a try. Drop the Skill in in your .claude/skills/ dir, take your existing resume, and build something cool.
The starter template today is inspired from: https://blog.pragmaticengineer.com/the-pragmatic-engineers-r.... I plan to add some more starter templates in the coming days. Feel free to recommend which resume templates you want me to ship.

value: Show HN: A Claude Skill to render resume templates. CV/Resumes are HTML and JSON


value:
Hi HN!
I've been wanting to work with data, and I've also been in (yet another) chess era. So I started working on (yet another!) chess programming project.
You enter your chess.com username, a date range, and a max number of games. The tool fetches your games via the public chess.com API, identifies the ~10-15 most critical positions per game (captures, promotions, large clock drops, pre-checkmate sequences) and runs Stockfish at low depth on each of those positions in a Web Worker right there in the browser.
From that it builds a profile across all your games:
- Which piece type you blunder with most
- Which openings give you the most trouble
- How your avg clock usage correlates with winrate
- Endgame performance broken down by material configuration
- Piece activity in wins vs losses
- Castling timing and its correlation with results
- and more, in varying degrees of usefulness
Stack: Vue 3 + TypeScript, chess.js for PGN parsing, Stockfish WASM in a Web Worker.
No backend, no login, no data leaves your browser. Built this for myself but figured others might find it useful. Would especially love feedback from stronger players on whether the insights are actually useful or just noise.
So far, even though some stats are obvious (my winrate improves when I think longer, interesting!), it helps to visualise it.
Information/disclaimer:
As this web tool runs only in the browser, I have made performance concessions to keep it as light and fast as possible. For this reason, some of the statistics may not be 100% accurate. It's more of a proof-of-concept/experiment. However, if you found it fun, interesting, or you have feedback or feature requests, let me know and I'll be happy to chat.
It also uses somewhat experimental features (WASM/service workers) and is prone to some unexplainable bugs sadly.
Thanks for reading!!

value: Show HN: A chess.com profiler that runs Stockfish in the browser


value: sarim

value: Show HN: League of Early Adopters – Give product feedback, get product feedback

author: sarim


value: kiranjohns

value:
I made Layrr because I got tired of describing UI changes to coding agents.
Layrr opens your web app in the browser. You click the part and describe the changes. Layrr runs a coding agent in the background and fixes it
It works with Claude Code, Codex CLI, and Gemini via Pi (huge fan of Pi)

value: Show HN: Layrr – Point Click and Edit any site

author: kiranjohns


value: vassilbek

value: Show HN: Agenda Intel MD – schemas and CLI to audit LLM strategic-risk briefs

author: vassilbek


value: dansquizsoft

value:
Hey HN,
Infinite Swap is a game inspired by Kyle MacDonald’s One Red Paperclip and other bigger-and-better swap stories - you start with a green bottle cap and trade it with other characters in various locations all the way up to a house and beyond.
A while ago I got inspired by viral games Infinite Craft and What Beats Rock? and wanted to make my own ‘exploring a LLM’s latent space’ style challenge. After much experimentation this became a trading style game, where the LLM comes up with all the items, trading scenarios and value estimates, which ended up being surprisingly fun and somewhat of a roller coaster to play.
I found it was the most intriguing if I separated the item offer from its valuation - so I implemented a pricing oracle called “Sal” who gives this info with his, sometimes snarky, opinion after each trade.
The item offer mechanism goes deeper too - each character’s profile is combined with a set of hidden motivations. I then use embeddings and cosine similarity to represent the desire the character has for the player's item, and therefore what they are willing to offer in exchange.
Links to play:
iOS (small number of ads, polished): https://apps.apple.com/us/app/infinite-swap/id6761694545
Android (small number of ads, polished): https://play.google.com/store/apps/details?id=com.squizsoftw...
Web (no ads, a touch rougher than the mobile versions but still very functional): https://infiniteswap.app
Stack: GPT-4.1-mini for item generation, SDXL Lightning for item images, Kokoro for voices (the latter two running on my 4090 at home). Postgres + FastAPI on k3s for the backend, native Swift/Kotlin for mobile, React for web.
Keen for any feedback, bug reports, improvement suggestions, etc. I’ll be around for a few hours if you have any questions.
Daniel

value: Show HN: Infinite Swap – Trade a bottle cap up to a house

author: dansquizsoft


value: aymenfurter

value: Show HN: Strava for AI coding – analytics on your Copilot/Claude/Codex usage

author: aymenfurter


value: recursivegirth

value:
Hey Hacker News,
vyvoice is a cross-platform, offline voice transcription app I started working on in December as a Windows user tired of every good dictation app being Mac-only.
Beyond transcription, it has built in support for voice commands & gen-AI agents (work-in-progress). Windows, Linux, and macOS are currently supported. The primary product is free, agentic AI and other future premium features will be behind a subscription ($5/month).
Underneath the hood vyvoice leverages ONNX to provide transcription via Parakeet and Whisper models locally on the device. I've developed an efficient VAD loop to ensure only segments of audio that contain speech are being processed for transcription. Valid audio segments are decoded in real time with end of utterance. Your audio and transcripts never leave your device.
I would love feedback on all aspects from default settings to commands and agent functionality. I am actively working on the agent feature and plan to support skills, MCP, and more in the very near future. Check it out and let me know what you think!
Check vyvoice out!
https://vyvoice.com

value: Show HN: Vyvoice: Privacy-first, cross-platform, offline voice transcription app

author: recursivegirth


value: tsiry

value: Show HN: Rocksky – Music scrobbling and discovery on the AT Protocol

author: tsiry


value: mukundakatta

value: Show HN: Hermes-agentmemory, pull-model episodic memory with real deletes

author: mukundakatta


value: pzxc

value:
I'm using AI (mostly Claude) to create/publish a new video game every day
This is day 33, first stab at the tower defense genre.  Most of the games (including this one) I build with a single prompt.  Rarely, a couple extra prompts are needed for bug fixes or to tweak the physics/UI.  Extremely rarely, the AI has difficulty making the game work right (usually drawing it) and it takes a dozen or more prompts -- but the majority of the time, it gets everything right and makes a fully playable game first try
Happy to answer any questions, just a little hobby project of mine I'm having lots of fun with :)

value: Show HN: Daily vibe-coding video games, day 33: Tower Defense (single prompt)

author: pzxc


value: tsoswr

value:
Here's my story.
I'm the person who almost never put things back in their place. It's not because I'm lazy or because I don't want to, it's because I'm always on the rush.
I have 2 kids in school, 3 properties, a job and a lot of things to joggle at the same time. It often happened that someone from school, HOA, doctor's office handed me a document which I needed to keep for a period of time. It was either a reference or prof of something. Because it was a huge hustle to scan, rename and move it I just kept it here and there until I eventually lost it (to read correctly: my wife threw it away tired oof moving it from here to there). I remember I used to have documents scattered in my Photos App, iCloud and 2 different scanning apps.
I realized that If I had an app which allowed me to scan in a folder where I had pre-configured a naming convention, compression rate and orc-enabled as needed, I would stop avoiding putting things in their place from the start. So I've created Pockli.
The app is simple, it has:
- a home view where you can quickly scroll to your favorites, recents, tags and 2 shortcut folders. I wanted to see the files preview in a larger format, so I don't have to open different documents to identify the needed one.
- a files view - similar to Apple Shortcuts app. You can crete your folders in different colors and add a symbol as to quickly identify the folder. From the files view you can search in the curent folder on all folders by file name or content. You can also import documents and open pdfs directly in Pockli.
Here's the flow: I've created different folders for my car, receipts, kids school, etc. I configured individual naming convention and compression rates. Next, when I receive a document I want to keep, I just open that folder and scan it directly in. That's it. The end.
The app uses Apple APIs for scanning and editing documents, so you can do things like document markup, resize, etc.
The app is freemium so it has a subscription or a lifetime purchase. I offer a 7 days trial period.
Why a subscription, you ask. It's because I want to add multiple features like local LLM, create a custom PDF engine, and others. So hopefully the app will get traction and I can start sooner my work on these features.
Before we go there, I know you can scan in Files and Apple Notes - but the created files are big and not all documents are worth ~2MB and additionally you do have to manually rename your files.
Thank's it. Waiting for feedback. Thanks for reading this.

value: Show HN: Pockli – I needed a better iOS scanning app

author: tsoswr


value: readonkeyless

value:
tl;dr I was having a hard time researching votes for my representatives in Congress and decided to build a tool that aggregated the data into a view that was easy for me to parse.
With midterms coming up, I am trying to do my due diligence of researching my representatives in Congress to see whether their votes aligned with their public statements.
https://www.congress.gov actually has a list of all the votes if you search by congressperson. It was difficult for me to parse each individual vote out of the UI though due to all the unfilterable noise. In my opinion, the layout isn't really the best either. There are other aggregators out there like govtrack.us but none that I found which had a comprehensive list of every vote.
Luckily, I discovered that congress.gov makes the voting data readily available via an API. Unfortunately, it's only available for members in the House of Representatives. I had to use an alternate library for the Senate. Once I had all the data together, I was able to mangle it into a shape that made it much easier for me to parse through.
In order to make it easier to compare votes with my own views, I also made a "Vote Match" feature. This feature randomly displays various bills which lets me flip through them and think about how I would vote on them whenever I have a spare moment. Then, I can scroll through my representatives' pages and do a line by line comparison. Where we differ, I can further research to figure out reasons why my representative might have voted differently. I figured the tool would be useful to other US voters too so decided to make it public.
I also tried my best to make it as privacy oriented as possible. All pages are statically generated and the "Vote Match" feature saves everything in your browser's local storage. The address form is just a convenience feature that redirects to https://geocoding.geo.census.gov. However, I've included manual steps on how to find your district too.
Data shows that voting turn out is usually lower during a midterm election so I also tried to bake in a fun, easy way to share and encourage people in your life to vote. My inspiration here was Wordle's result sharing after you do the daily solve. There's a button on each representative's page that generates an image card of your vote match percentage that you can copy and share.
Any feedback is very much welcome. I'll also take any other tips and tricks you might have for researching to become a more informed voter.

value: Show HN: Aggregating votes from US Congress representatives

author: readonkeyless


value: wizenheimer

value: Show HN: I built a screen recorder that captures console logs, requests and more

author: wizenheimer


value: mpvc has been my daily music player since COVID years, I started getting involved and forked lwillets/mpvc around 2022, as the uses of mpvc have evolved I've tried to group specific functionalities under its own separate tools, so for example now there is: mpvc for the CLI, mpvc-tui for a minimal text user interface (TUI), mpvc-web for a web-based interface, and mpvc-fzf for fzf integration for searching and playing music from online streaming services, among others.<p>PS: The project has appeared before in Show HN, in 2022, and a year later, since the project has continued, and the Show HN was useful in raising discussion and providing feedback, I'm posting it again.

value: Show HN: Mpvc, minimal music player for controling mpv from the shell


value: Show HN: Stoic AgentOS - Open-source operating system for AI agent fleets


value: anthonype

value: Show HN: Secure OS for Android & no log, no metadata messenger

author: anthonype


value: ktmartin

value:
Last year I was looking for a new role. I sent out applications, did the prep, waited. What came back was mostly nothing. Not rejection emails, just silence. The job listings I'd applied to stayed live for weeks. Some for months.
As a software engineer, I decided to dig into it properly. I built a system to continuously track job postings across companies, logging posting dates and measuring how long roles stay open before closing or don't. After 35,000+ listings across 200+ companies, some patterns are hard to ignore. Some listings have been open for 700+ days at companies you'd recognize. Others post 90% of their open roles within a single month, a signal that's harder to fake than a press release.
I published two initial insight pages based on this work:
- Which companies are posting most aggressively right now
- Job listings that have been open for over a year
What I didn't expect is that the same signals useful for detecting ghost jobs also say something broader about a company's hiring momentum, recruiting intensity, pipeline health, where talent bottlenecks might exist. I'm not sure yet where this leads, but I'll keep expanding the dataset and publishing more insights as I go.
Would genuinely love feedback on the methodology, interpretation, or obvious blind spots in the data.

value: Show HN: Got ghosted by tech companies so I built a tool to track ghost jobs

author: ktmartin


value: nawazgafar

value: Show HN: nbpipe – A lightweight workflow runner for Jupyter notebooks

author: nawazgafar


value:
I made this to help technical people get good at organic marketing because I faced this hurdle when I started building SaaS apps.
It has a collection of organically viral tiktok ads for AI tools/websites.
You can see the breakdown for each ad like:
Hook
Script
Content format
Pain point
Target customer type
If you describe your own product, it’ll recommend the most relevant ads to you and also use their metadata to generate good content ideas for you.

value: Show HN: Firehooks – Get app users from TikTok without paid ads


value: truetaurus

value: Show HN: Artist Kit – One-Page Website Builder for DJs and Music Artists

author: truetaurus


value: vgrocha

value:
I've always wondered if what I am enduring in life is better or worse than the average human existance/experience. Hence "Where do I stand?", a simplified public thermometer, that is
- anonymous: no login, no personal data tracked, you answers are only stored locally while your tab is open. To submit, there's a small math puzzle to disincentivize multiple submissions
- biased: it's being shared in Hacker News and probably people in certain headspace will answer
- not comprehensive: I chose the questions I was interested in
- realtime: update the results page as people answer<p>Curious to see the results of this little experiment and/or feedback from the group

value: Show HN: Where do I stand? – Household Health

author: vgrocha


value: acaciabengo

value:
I built QuantTakeoff and releasing v1.0 for validation: Input a construction PDF, get back
takeoff report with wall lengths, areas, door/window counts and sizes
3D GLB of the building at real-world scale all under ~10 mins.
The pain it solves: Reduce time estimator to trace out elements either by hand or software and extract out reports.
Stack: Ensemble of computer vision tools (95%), VLM OCR (5%)
Hard parts that are working:
Auto-find the plan page in a 200-sheet bid set (most stacks make you point at the right sheet manually). I am still manually annotating a new dataset for the new models.
 Holds up on noisy as-builts and hand-marked sheets that break OCR-first pipelines
Post CV processing to optimize for usability.
Pixel accuracy to measure elements including size / width of doors and windows.
Demo: https://youtu.be/fVy7tDFqR98
Particularly want feedback on:
Real world estimators feedback on what could be better for the practice.
What would make use this or what is missing?
P.S Live demo has been removed to manage compute costs from a few enthusiasts who burn through the HF spaces bill.

value: Show HN: QuantTakeoff – Construction PDFs to takeoff and 3D scene

author: acaciabengo


value: mperrotta

value: Show HN: Anagardens: A Daily Word Game

author: mperrotta

title: Show HN: Anagardens: A Daily Word Game


value: chaidhat

value:
demo: https://www.youtube.com/watch?v=ENH9tsVF_Bw&feature=youtu.be
lmk if you want image support!

value: Show HN: I built a free PDF editor to fix Claude's horribly-generated PDFs

author: chaidhat


value: arjavmehta

value:
After speaking with over 50+ CISOs, DevOps, & pre-series A founders for months, I realized a problem in the GRC industry. SOC 2 automation exists, but people are split between trusting these black-box tools with systems that are continuously changing. As a result audits are slow & mistrusted.
Right now the most important thing is verifiability & depth, rather than just compliance automation-because it does exist, everywhere.
Here's what I did from learning this:
-> Created an open-source AWS Evidence Scanner & Control Mapper for lean, pre-series A AWS-Native teams thinking about SOC 2 Type l or are undergoing SOC 2 Type l audit. Collects across 15+ AWS Services to 12 critical controls in the trust-service criteria.
Why open-source? Accessibility for people who might have their hands tied choosing between expensive GRC tools. Its also used as a trust-mechanism. Code is right there. A CEO or auditor can read exactly what API calls we make before giving us the role ARN.
-> I included a paid report embedded within the tool (open-core model). Users have the option to pay for the report in which every finding traces back to the API call that produced it. SHA-256 hashed (at a fraction of the cost of bigger legacy platforms). With remediation steps & a compliance-copilot to help with other parts of the Type l process beyond evidence collection (like policy writing, risk assessment, etc).
Why paid report? The best way to make the auditors job as easy as possible is to give them a verifiable package where the evidence is right there in front of them, timestamped so they can see what happened, when (rooted in AWS APIs). No black-box, no way to fake it. Saving weeks of back & forth between auditors and clients, with the click of a few buttons.
An auditor can re-run the same API call, hash the response themselves, and verify it matches what's in the report.
Value: 30 seconds to deploy. 5 mins to run the scan & evidence is collected & mapped. Paid report includes verifiable evidence companies can send to their auditor. Paid features include a co-pilot to help with audit-readiness beyond just evidence collection.
-> Understand Limitations.
I understand the scope of this product is pretty limited in part because its also very new. I'm not going to claim it solves all of compliance, because it  doesn't. It makes a very time-consuming part of the process very accessible to be automated & gives an auditor a report they can rely on.
What now?
Anyone who's gone through, thinking about or is in the middle of SOC 2, would love your reaction to the output, even if it's critical. Also looking for early testers/users.
repo here: https://github.com/adog0822/AWS-Evidence-Layer
try it here: https://loxeai.com

value: Show HN: Built a verifiable, open-source SoC 2 readiness scanner

author: arjavmehta


value: zarie

value: Show HN: SoccQR – Lost and Found Labels for Soccer Balls / Gamified Training Log

author: zarie


value: Show HN: Brokkr - Scalable cluster management for GPU/HPC workloads


value: takkyun

value:
I originally made Serene Bach in the 2000s as a weblog engine written in Perl CGI. I rebuilt it from scratch in Go as a single binary that can run either as a CGI program or as a normal HTTP server.
I know CGI is generally considered legacy technology now, but I still rely on it for shared hosting. In this version, I added Markdown support, a responsive default theme, Open Graph image generation, and static output generation.
It is still in beta, but the repository includes a Docker image published on GHCR, documentation, and a local quick start. I'd appreciate feedback from anyone interested in small self-hosted publishing tools, especially if you still care about shared hosting or CGI-style deployment.

value: Show HN: Serene Bach – a Go weblog engine that runs as CGI or HTTP

author: takkyun


value: katspaugh

value:
Hi all!
I realized it’s really not secure to run coding projects directly on my Mac. All the NPM hacks recently, especially with agentic coding — you’re always one npm install away from a disaster.
So I’ve built a small CLI called machine that starts a Lima VM for each of your projects. It supports declarative “profiles” which are like package.json for your VM. The default profile comes with standard stuff like Node.js, git, Docker, Claude Code and Codex.
If you share your projects.toml with your team, every developer can spin up your team’s entire dev environment with one command. No need to install dev tools, clone repos, npm install anything manually.
Another cool thing is that you can use the native MacOS keychain or 1password to forward SSH signatures to the VM. So every time you need to commit or push code, you touch the Touch ID key and it’s signed. SSH keys never leave the host.
The same is done for env variables and secrets. You inject them with one command from 1password when the machine starts and they are never stored in a file.
Repo: https://github.com/katspaugh/machine
Genuinely curious about your feedback!

value: Show HN: Machine – per-project dev VMs with session-only secrets

author: katspaugh


value: sergiopreira

value: Show HN: Give your AI agent a brain that understands your codebase

author: sergiopreira


value: cpojer

value:
Nowadays I review a lot of code locally that was written by llms. I used to review my own code using git + delta. It started to feel limiting with the amount of code written by llms.
When looking at a large diff on Friday I pointed an llm at diffs.com and trees.software and told it to build an app. It only took 16 minutes, is extremely fast for large diffs, beautiful and minimal.
Today I polished it up and added all the features that I need. It has file filters, search, an llm walkthrough mode, and review comments that you can paste back into your llm.
I will be using Codiff a lot, and can finally review the large diff from Friday that led me to build this  If you like it, fork it!

value: Show HN: Codiff, a local diff review tool

author: cpojer


value: healqq

value:
While doing some work recently I didn't notice that a project I didn't touch for a while was using playwright-mcp instead of playwright-cli.
I only noticed it because context was getting full unreasonably fast. I've realized that one of the main differences is that agent would pipe CLI results to some filter right away, but this was not possible with MCP, so it would get whole a11y snapshot of the page every time.
I've created a small wrapper for MCP servers that checks response sizes and forces agent to use filter on the response if response is large enough. In my tests (https://github.com/healqq/mcp-content-guard/blob/main/bench/...) it managed to save a decent amount of tokens while solving certain tasks (while added a bit of overhead in other tasks).
It works with both local and remote MCPs. Would be happy to hear your feedback and if that could be valuable for you!

value: Show HN: Save Context from MCP Bloat

author: healqq

title: Show HN: Save Context from MCP Bloat


value: koala-news

value: Built this because I kept seeing stories early but couldn't tell if it was one outlet's angle or the whole world waking up to something real.

value: Show HN: KoalaNews – how big is this story, really?

author: koala-news


value: marigov

value: Show HN: Onami Radio, a simple radio app for iOS

author: marigov


value: starwalkn

value:
GitHub: https://github.com/starwalkn/kono
Docs: https://starwalkn.github.io/konodocs/

value: Show HN: Extendable API Gateway Written in Go

author: starwalkn


value: imVSall

value: Show HN: GDD–36 MCP tools to run N isolated Chromium browsers from Claude/Cursor

author: imVSall


value: GistNoesis

value: Show HN: MaragingLoop: Autonomous Bare-Metal OS Agent

author: GistNoesis


value: ramsono

value: Show HN: Peeklens – Palantir for Marketing

author: ramsono


value: olegmmv

value:
I got frustrated hearing about phone snatching in London - thieves grab unlocked phones and immediately access banking apps, messages, photos. Android has had Theft Detection Lock since 2024 while iOS still has nothing.
Apple's Stolen Device Protection delays password changes but doesn't touch the content of an unlocked phone. So I wired a few things together:
- CMMotionManager at 20Hz for grab detection. I tried CMMotionActivityManager first - total waste of time. It reports "Unknown" instead of "Running", flickers between states and has a much bigger delay.
- FamilyControls + ManagedSettings for system-level shields. As there's no way to lock the phone programmatically I came up with the idea of locking the desired apps. The shield overlay persists after force-close and there's no way to dismiss it without opening the app and passing Face ID.
- Background location at kCLLocationAccuracyThreeKilometers to keep the accelerometer alive when the app is suspended. The data is never transmitted — coordinates are stored locally only when a snatch triggers so you can see where it happened.
Main weakness I should mention: deleting the app removes the shields. You can mitigate this with Screen Time passcode + disabling app deletion in Settings, but it's not automatic.
No analytics, no tracking, no network calls.

value: Show HN: Snatch Guard – iOS theft detection with accelerometer and Screen Time

author: olegmmv


value: kevinwong

value:
While doing some web design that needed ASCII art animations, I found that existing tools/libraries:
1) lacked video support
2) fell short in customizability (FPS, brightness/gamma/contrast)
3) for some reason wasn't able to get great results (IMO)
I used this to create asset pipelines (trigger -> generate img/video -> create art frames -> create gif). Hope someone finds it useful!

value: Show HN: CLI for image/video to ASCII art

author: kevinwong


value: amenghra

value:
It uses webgl to render a mechanically accurate music box and spatial web audio so the sound direction and volume changes as you move around the virtual world.
It was extremely easy for me to get a AI to generate most of the js/html/css. It was impossible for me to get an AI generate the 3D model so I did it by hand. It was very frustrating to get the tune right (still not 100% happy with the sound but I’m giving up trying to further improve it).
Best enjoyed with headphones!

value: Show HN: I vibe coded a music box

author: amenghra

title: Show HN: I vibe coded a music box


value: metravod

value: Show HN: A Claude Code skill that tells Claude when not to use Claude

author: metravod