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Showing 1001–1020 of 2497 tools from Hacker News
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April 23, 2026 at 04:00 AM
Show HN: LangGraph architecture that scales (hexagonal pattern, 110 tests)
Show HN (score: 12)[Code Quality] Show HN: LangGraph architecture that scales (hexagonal pattern, 110 tests) I kept hitting the same wall with LangGraph: tutorials show you how to build a graph, not how to maintain one when you have 8 nodes, 3 agents, and shared state across subgraphs.<p>So I built a reference architecture with: - Platform layer separation (framework-independent core) - Contract validation on every state mutation - 110 tests including architecture boundary enforcement - Patterns that AI coding agents can't accidentally break<p>Repo: <a href="https://github.com/cleverhoods/sagecompass" rel="nofollow">https://github.com/cleverhoods/sagecompass</a> Wrote about the patterns: <a href="https://dev.to/cleverhoods/from-prompt-to-platform-architecture-rules-i-use-59gp" rel="nofollow">https://dev.to/cleverhoods/from-prompt-to-platform-architect...</a><p>It's MIT licensed. Would love feedback on the approach - especially from anyone who's scaled LangGraph past the tutorial stage.
Linux kernel framework for PCIe device emulation, in userspace
Hacker News (score: 63)[Other] Linux kernel framework for PCIe device emulation, in userspace
KAOS – The Kubernetes Agent Orchestration System
Hacker News (score: 16)[Other] KAOS – The Kubernetes Agent Orchestration System
[Other] Show HN: Txt2plotter – True centerline vectors from Flux.2 for pen plotters I’ve been working on a project to bridge the gap between AI generation and my AxiDraw, and I think I finally have a workflow that avoids the usual headaches.<p>If you’ve tried plotting AI-generated images, you probably know the struggle: generic tracing tools (like Potrace) trace the <i>outline</i> of a line, resulting in double-strokes that ruin the look and take twice as long to plot.<p>What I tried previously:<p>- Potrace / Inkscape Trace: Great for filled shapes, but results in "hollow" lines for line art.<p>- Canny Edge Detection: Often too messy; it picks up noise and creates jittery paths.<p>- Standard SDXL: Struggled with geometric coherence, often breaking lines or hallucinating perspective.<p>- A bunch of projects that claimed to be txt2svg but which produced extremely poor results, at least for pen plotting. (Chat2SVG, StarVector, OmniSVG, DeepSVG, SVG-VAE, VectorFusion, DiffSketcher, SVGDreamer, SVGDreamer++, NeuralSVG, SVGFusion, VectorWeaver, SwiftSketch, CLIPasso, CLIPDraw, InternSVG)<p>My Approach:<p>I ended up writing a Python tool that combines a few specific technologies to get a true "centerline" vector:<p>1. Prompt Engineering: An LLM rewrites the prompt to enforce a "Technical Drawing" style optimized for the generator.<p>2. Generation: I'm using Flux.2-dev (4-bit). It seems significantly better than SDXL at maintaining straight lines and coherent geometry.<p>3. Skeletonization: This is the key part. Instead of tracing contours, I use Lee’s Method (via scikit-image) to erode the image down to a 1-pixel wide skeleton. This recovers the actual stroke path.<p>4. Graph Conversion: The pixel skeleton is converted into a graph to identify nodes and edges, pruning out small artifacts/noise.<p>5. Optimization: Finally, I feed it into vpype to merge segments and sort the paths (TSP) so the plotter isn't jumping around constantly.<p>You can see the results in the examples inside the Github repo.<p>The project is currently quite barebones, but it produces better results than other options I've tested so I'm publishing it. I'm interested in implementing better pre/post processing, API-based generation, and identifying shapes for cross-hatching.
Show HN: Subth.ink – write something and see how many others wrote the same
Hacker News (score: 54)[Other] Show HN: Subth.ink – write something and see how many others wrote the same Hey HN, this is a small Haskell learning project that I wanted to share. It's just a website where you can see how many people write the exact same text as you (thought it was a fun idea).<p>It's built using Scotty, SQLite, Redis and Caddy. Currently it's running in a small DigitalOcean droplet (1 Gb RAM).<p>Using Haskell for web development (specifically with Scotty) was slightly easier than I thought, but still a relatively hard task compared to other languages. One of my main friction points was Haskell's multiple string-like types: String, Text (& lazy), ByteString (& lazy), and each library choosing to consume a different one amongst these. There is also a soft requirement to learn monad transformers (e.g. to understand what liftIO is doing) which made the initial development more difficult.
Show HN: Pipenet – A Modern Alternative to Localtunnel
Hacker News (score: 58)[Other] Show HN: Pipenet – A Modern Alternative to Localtunnel Hey HN!<p>localtunnel's server needs random ports per client. That doesn't work on Fly.io or behind strict firewalls.<p>We rewrote it in TypeScript and added multiplexing over a single port. Open-source and 100% self-hostable.<p>Public instance at *.pipenet.dev if you don't want to self-host.<p>Built at Glama for our MCP Inspector, but it's a generic tunnel with no ties to our infra.<p><a href="https://github.com/punkpeye/pipenet" rel="nofollow">https://github.com/punkpeye/pipenet</a>
Show HN: Visual Database Schema Designer (Angular 21 and .NET 10)
Show HN (score: 6)[Database] Show HN: Visual Database Schema Designer (Angular 21 and .NET 10) Hi HN, OP here.<p>I built this because I was frustrated with the current state of DB design tools. They are usually either heavy enterprise desktop apps (like DataGrip/Workbench) or simple drawing tools that don't export usable code.<p>I wanted a "VS Code-like" experience in the browser: dark mode, strict typing, and instant visual feedback.<p>The tech stack is quite aggressive: - Frontend: Angular 21 (Latest). I'm using Signals exclusively for the graph state management to handle 100+ nodes without layout thrashing. - Backend: .NET 10 for DDL generation and schema validation.<p>Current features: - Visual Table/Column editor. - Drag & drop relationships (1:N handling). - Exports to PostgreSQL DDL and Entity Framework Core.<p>It's an MVP, so I'm looking for feedback on the graph interaction and the UI feel.<p>Does the "IDE-like" layout work for you for this kind of task?
Building Robust Helm Charts
Hacker News (score: 41)[Other] Building Robust Helm Charts
Show HN: AWS-doctor – A terminal-based AWS health check and cost optimizer in Go
Hacker News (score: 15)[CLI Tool] Show HN: AWS-doctor – A terminal-based AWS health check and cost optimizer in Go
[Other] Show HN: HTTP:COLON – A quick HTTP header/directive inspector and reference Hi HN -- I built HTTP:COLON, a small, open-source web tool for quickly checking a site’s HTTP response headers and learning what they mean as you go.<p>Link: <a href="https://httpcolon.dev/" rel="nofollow">https://httpcolon.dev/</a><p>What it does<p>- Enter a URL and fetch its response headers<p>- Groups common headers into handy buckets (cache, content, security)<p>- Includes short docs/tooltips for headers and directives so you can look things up while debugging. I find hovering on highlighted headers quite useful!<p>Supports different HTTP methods (GET/POST/PUT/DELETE)<p>Deep links<p>- You can link directly to a host, e.g. <a href="https://httpcolon.dev/www.google.com" rel="nofollow">https://httpcolon.dev/www.google.com</a><p>(or any domain) to jump straight into inspecting it.<p>Why I made it<p>- I kept bouncing between DevTools, MDN, and random blog posts while debugging caching + security headers. I wanted one place that’s quick for “what am I getting back?” and “what does this header/directive do?”<p>It’s in beta, and I’d love feedback on:<p>- Missing features you’d want for day-to-day debugging (export/share formats, comparisons, presets, etc.)<p>Thanks!
Show HN: Lume 0.2 – Build and Run macOS VMs with unattended setup
Hacker News (score: 30)[CLI Tool] Show HN: Lume 0.2 – Build and Run macOS VMs with unattended setup Hey HN, Lume is an open-source CLI for running macOS and Linux VMs on Apple Silicon. Since launch (<a href="https://news.ycombinator.com/item?id=42908061">https://news.ycombinator.com/item?id=42908061</a>), we've been using it to run AI agents in isolated macOS environments. We needed VMs that could set themselves up, so we built that.<p>Here's what's new in 0.2:<p>*Unattended Setup* – Go from IPSW to a fully configured VM without touching the keyboard. We built a VNC + OCR system that clicks through macOS Setup Assistant automatically. No more manual setup before pushing to a registry:<p><pre><code> lume create my-vm --os macos --ipsw latest --unattended tahoe </code></pre> You can write custom YAML configs to set up any macOS version your way.<p>*HTTP API + Daemon* – A REST API on port 7777 that runs as a background service. Your scripts and CI pipelines can manage VMs that persist even if your terminal closes:<p><pre><code> curl -X POST localhost:7777/lume/vms/my-vm/run -d '{"noDisplay": true}' </code></pre> *MCP Server* – Native integration with Claude Desktop and AI coding agents. Claude can create, run, and execute commands in VMs directly:<p><pre><code> # Add to Claude Desktop config "lume": { "command": "lume", "args": ["serve", "--mcp"] } # Then just ask: "Create a sandbox VM and run my tests" </code></pre> *Multi-location Storage* – macOS disk space is always tight, so from user feedback we added support for external drives. Add an SSD, move VMs between locations:<p><pre><code> lume config storage add external-ssd /Volumes/ExternalSSD/lume lume clone my-vm backup --source-storage default --dest-storage external-ssd </code></pre> *Registry Support* – Pull and push VM images from GHCR or GCS. Create a golden image once, share it across your team.<p>We're seeing people use Lume for: - Running Claude Code in an isolated VM (your host stays clean, reset mistakes by cloning) - CI/CD pipelines for Apple platform apps - Automated UI testing across macOS versions - Disposable sandboxes for security research<p>To get started:<p><pre><code> /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh)" lume create sandbox --os macos --ipsw latest --unattended tahoe lume run sandbox --shared-dir ~/my-project </code></pre> Lume is MIT licensed and Apple Silicon only (M1/M2/M3/M4) since it uses Apple's native Virtualization Framework directly—no emulation.<p>Lume runs on EC2 Mac instances and Scaleway if you need cloud infrastructure. We're also working on a managed cloud offering for teams that need macOS compute on demand—if you're interested, reach out.<p>We're actively developing this as part of Cua (<a href="https://github.com/trycua/cua" rel="nofollow">https://github.com/trycua/cua</a>), our Computer Use Agent SDK. We'd love your feedback, bug reports, or feature ideas.<p>GitHub: <a href="https://github.com/trycua/cua" rel="nofollow">https://github.com/trycua/cua</a> Docs: <a href="https://cua.ai/docs/lume">https://cua.ai/docs/lume</a><p>We'll be here to answer questions!
[IDE/Editor] Show HN: Opal Editor, free Obsidian alternative for markdown and site publishing A fully featured markdown editor and publisher. Free, open-source and browser-first (no backend required). Built with modern technologies like React, TypeScript, Shadcn/UI, and Vite. (thoughtfully crafted, not vibe coded)
Show HN: Mist – a lightweight, self-hosted PaaS
Show HN (score: 7)[DevOps] Show HN: Mist – a lightweight, self-hosted PaaS Hi HN,<p>We’re building Mist, a lightweight, self-hosted PaaS for running and managing applications on your own servers.<p>We started Mist because we wanted a middle ground between raw VPS management and heavy, all-in-one platforms. Existing PaaS solutions often felt too complex or resource-intensive for small servers, homelabs, and side projects. We wanted something that keeps the PaaS experience but stays simple and predictable.<p>Our goals with Mist are: - A simple PaaS to deploy and manage apps on your own infrastructure - HTTPS, routing, and app access handled automatically - Low resource usage so it runs well on small VPSes - Self-hosted and transparent, with minimal magic<p>Mist focuses on being an opinionated but lightweight layer on top of your server. It doesn’t try to hide everything behind abstractions, but it does aim to remove the repetitive operational work that comes with managing apps by hand.<p>Mist is still early, and this is where we really need help. We’re actively looking for:<p>- Users who want a simple self-hosted PaaS and can share real-world feedback<p>- Contributors who want to help shape the core features, architecture, and UX<p>Website: <a href="https://trymist.cloud" rel="nofollow">https://trymist.cloud</a><p>Repo: <a href="https://github.com/corecollectives/mist" rel="nofollow">https://github.com/corecollectives/mist</a>
Show HN: KeyEnv – CLI-first secrets manager for dev teams (Rust)
Show HN (score: 5)[CLI Tool] Show HN: KeyEnv – CLI-first secrets manager for dev teams (Rust) Hi HN,<p>I built KeyEnv because I was tired of the "can you Slack me the Stripe key?" workflow.<p><pre><code> The problem: My team's secrets lived in a mix of Slack DMs, shared Google Docs, and .env files that definitely weren't in .gitignore at some point. Enterprise tools like Vault required more DevOps time than we had. Doppler was close but felt heavier than we needed. What KeyEnv does: keyenv init # link project keyenv pull # sync secrets to local .env keyenv run -- npm start # inject secrets, run command That's basically it. Secrets are encrypted client-side (AES-256-GCM) before leaving your machine. Zero-knowledge architecture—we can't read your secrets even if we wanted to. Technical details: - Single Rust binary, no runtime dependencies - Works offline (cached secrets) - RBAC for teams (owner/admin/member/viewer) - Service tokens for CI/CD - Full audit trail Honest tradeoffs: - SaaS only, no self-hosted option - Fewer integrations than Doppler - If you need dynamic secrets or PKI, use Vault Pricing: Free tier (3 projects, 100 secrets), $12/user/month for teams. Would love feedback on the CLI UX and any rough edges. Happy to answer questions about the architecture. </code></pre> <a href="https://www.keyenv.dev" rel="nofollow">https://www.keyenv.dev</a>
Show HN: WebTerm – Browser-based terminal emulator
Show HN (score: 5)[Other] Show HN: WebTerm – Browser-based terminal emulator
Show HN: GibRAM an in-memory ephemeral GraphRAG runtime for retrieval
Hacker News (score: 25)[Other] Show HN: GibRAM an in-memory ephemeral GraphRAG runtime for retrieval Hi HN,<p>I have been working with regulation-heavy documents lately, and one thing kept bothering me. Flat RAG pipelines often fail to retrieve related articles together, even when they are clearly connected through references, definitions, or clauses.<p>After trying several RAG setups, I subjectively felt that GraphRAG was a better mental model for this kind of data. The Microsoft GraphRAG paper and reference implementation were helpful starting points. However, in practice, I found one recurring friction point: graph storage and vector indexing are usually handled by separate systems, which felt unnecessarily heavy for short-lived analysis tasks.<p>To explore this tradeoff, I built GibRAM (Graph in-buffer Retrieval and Associative Memory). It is an experimental, in-memory GraphRAG runtime where entities, relationships, text units, and embeddings live side by side in a single process.<p>GibRAM is intentionally ephemeral. It is designed for exploratory tasks like summarization or conversational querying over a bounded document set. Data lives in memory, scoped by session, and is automatically cleaned up via TTL. There are no durability guarantees, and recomputation is considered cheaper than persistence for the intended use cases.<p>This is not a database and not a production-ready system. It is a casual project, largely vibe-coded, meant to explore what GraphRAG looks like when memory is the primary constraint instead of storage. Technical debt exists, and many tradeoffs are explicit.<p>The project is open source, and I would really appreciate feedback, especially from people working on RAG, search infrastructure, or graph-based retrieval.<p>GitHub: <a href="https://github.com/gibram-io/gibram" rel="nofollow">https://github.com/gibram-io/gibram</a><p>Happy to answer questions or hear why this approach might be flawed.
Show HN: Figma-use – CLI to control Figma for AI agents
Hacker News (score: 30)[CLI Tool] Show HN: Figma-use – CLI to control Figma for AI agents I'm Dan, and I built a CLI that lets AI agents design in Figma.<p>What it does: 100 commands to create shapes, text, frames, components, modify styles, export assets. JSX importing that's ~100x faster than any plugin API import. Works with any LLM coding assistant.<p>Why I built it: The official Figma MCP server can only read files. I wanted AI to actually design — create buttons, build layouts, generate entire component systems. Existing solutions were either read-only or required verbose JSON schemas that burn through tokens.<p>Demo (45 sec): <a href="https://youtu.be/9eSYVZRle7o" rel="nofollow">https://youtu.be/9eSYVZRle7o</a><p>Tech stack: Bun + Citty for CLI, Elysia WebSocket proxy, Figma plugin. The render command connects to Figma's internal multiplayer protocol via Chrome DevTools for extra performance when dealing with large groups of objects.<p>Try it: bun install -g @dannote/figma-use<p>Looking for feedback on CLI ergonomics, missing commands, and whether the JSX syntax feels natural.
Show HN: E80: an 8-bit CPU in structural VHDL
Hacker News (score: 17)[Other] Show HN: E80: an 8-bit CPU in structural VHDL I built a new 8-bit CPU in VHDL from scratch (starting from the ISA). I felt that most educational soft-cores hide too much behind abstraction, eg. if I can do a+b with a single assignment that calls an optimized arithmetic library, then why did I learn the ripple carry adder in the first place ? And why did I learn flip flops if I can do all my control logic with a simple PROCESS statement like I would with a programming language ? Of course abstraction is the main selling point of HDLs, but would it work if I tried to keep strictly structural and rely on ieee.std_logic_1164 only ?<p>Well, it did and it works nicely. No arithmetic libraries, no PROCESS except for the DFF component (obviously). Of course it's a bit of a "resource hog" compared to optimized cores, (eg. the RAM is build out of flip flops instead of a block ram that takes advantage of FPGA intermal memory) but you can actually trace every signal through the datapath as it happens.<p>I also build an assembler in C99 without external libraries (please be forgiving, my code is very primitive I think). I bundled Sci1 (Scintilla), GHDL and GTKWave into a single installer so you can write assembly and see the waveforms immediately without having to spend hours configuring simulators. Currently Windows only, but at some point I'll have to do it on Linux too. I tested it on the Tang Primer 25K and Cyclone IV, and I included my Gowin, Quartus and Vivado projects files. That should make easy to run on your FPGA.<p>Everything is under the GPL3.<p>(Edit: I did not use AI. Not was it a waste of time for the VHDL because my design is too novel -- but even for beta testing it would waste my time because those LLMs are too well trained for x86/ARM and my flag logic draws from 6502/6800 and even my ripple carry adder doesn't flip the carry bit in subtraction. Point is -- AI couldn't help. It only kept complaining that my assembler's C code wasn't up to 2026 standards)
Show HN: WebGPU React Renderer Using Vello
Show HN (score: 5)[Other] Show HN: WebGPU React Renderer Using Vello I've built a package to use Raph Levien's Vello as a blazing fast 2D renderer for React on WebGPU. It uses WASM to hook into the Rust code
Show HN: ChunkHound, a local-first tool for understanding large codebases
Hacker News (score: 28)[Other] Show HN: ChunkHound, a local-first tool for understanding large codebases ChunkHound’s goal is simple: local-first codebase intelligence that helps you pull deep, core-dev-level insights on demand, generate always-up-to-date docs, and scale from small repos to enterprise monorepos — while staying free + open source and provider-agnostic (VoyageAI / OpenAI / Qwen3, Anthropic / OpenAI / Gemini / Grok, and more).<p>I’d love your feedback — and if you have, thank you for being part of the journey!