Show HN: Monohub – a new GitHub alternative / code hosting service https://ift.tt/qZnl7Kv

Show HN: Monohub – a new GitHub alternative / code hosting service Hello everyone, My name is Teymur Bayramov, and I am developing a forge/code hosting service called Monohub. It is at a fairly early stage of development, so it's quite rough around the edges. It is developed and hosted in EU. I have started developing it as a slim wrapper around Git to serve my own code, but it grew to such extent that I decided to give it a try and offer it as a service. It doesn't have much at the moment, but it already has basic pull requests. Accessibility is high priority. It will be a paid service, but since it's an early start, an "early adopter discount" is applied – 6 months for free. No card details required. I would be happy if you give it a try and let me know what do you think, and perhaps share what you lack in existing solutions that you would like to see implemented here. Warmest wishes, Teymur. https://monohub.dev/ March 1, 2026 at 12:43AM

Show HN: Tomoshibi – A writing app where your words fade by firelight https://ift.tt/RbUzDr5

Show HN: Tomoshibi – A writing app where your words fade by firelight I spent ten years trying to write a novel. Every time I sat down, I'd write a sentence, decide it wasn't good enough, and rewrite it. The problem wasn't discipline — it was that I could always see what I'd written and go back to change it. I tried other approaches. Apps that delete your words when you stop typing — they fight fear with fear. That just made me panic. I wanted the opposite: not punishment, but permission. "Tomoshibi" is Japanese for a small light in the dark — just enough to see what's in front of you. You write on a dark screen. Older lines fade, but not when you hit return. They fade when you start writing again. If you pause, they wait. You can edit the current line and one line back — enough to fix a typo, not enough to spiral. The one-line-back rule also catches my own practical issue: Japanese IME often fires an accidental newline on kanji confirmation. Everything is saved. There's a separate reader view for going back through what you've written. Tomoshibi is for writing over months, not just one session. When you come back, your last sentence appears as an epigraph — as if it always belonged there. No account, no server, no build step. Your writing stays in your browser's local storage — export anytime as .txt. Vanilla HTML/CSS/ES modules. Try it in your browser. A native Mac app (built with Tauri) with file system integration is coming to the store. I've been writing on it for two months. https://ift.tt/U9IiFQh https://ift.tt/yxuBqJP February 28, 2026 at 10:42PM

Show HN: BananaOS, vibecoded operating system that boots on a 486 with ~11MB RAM https://ift.tt/2cqWP1j

Show HN: BananaOS, vibecoded operating system that boots on a 486 with ~11MB RAM My 10-year-old son has been deep in low-level rabbit holes lately and ended up vibe-coding his own operating system. Since he’s still a kid and not on HN himself, I’m posting this on his behalf with his permission. This started as curiosity about how computers actually boot, and somehow escalated into writing a kernel, building a GUI, and setting up CI that produces a bootable OS image on every commit. BananaOS is a small experimental operating system built mainly for learning and exploration of low-level systems programming. It currently targets i386 BIOS systems and is designed to run on extremely constrained hardware. Fun fact: Wallpaper logic, one of the most important OS functionalities, is directly implemented in the kernel. That cracked my son up! Some highlights: Multiboot-compliant kernel loaded via GRUB VESA framebuffer graphics with double buffering Custom window manager with movable and resizable windows Dock-style application launcher PS/2 keyboard and mouse input handling PCI enumeration and AHCI SATA support Basic applications (terminal, notepad, calculator, file explorer, settings) Memory detection and allocation based on available RAM Boots in QEMU with about 11.2 MB RAM Includes an ISR workaround to emulate CMOV so it can boot on Intel 486 CPUs One thing I found particularly fun: he also added GitHub Actions workflows that automatically build the OS image for every commit, so the repo continuously produces fresh bootable artifacts. The project is very much experimental and should only be run inside an Virtual Machine. Repo (with build instructions and screenshots): https://ift.tt/0EloQPU Quick start (only on Linux, check dependencies, and see README): git clone https://ift.tt/0EloQPU cd BananaOS make qemu-system-i386 -cdrom bananaos.img -m 128M Retro mode: qemu-system-i386 -cpu 486 -cdrom bananaos.img -m 11.2M He’s mainly building this to understand kernels, memory management, drivers, and how operating systems actually work below user space. Feedback from people who have built hobby operating systems or worked close to hardware would be especially appreciated. February 27, 2026 at 11:13PM

Show HN: Unfudged – version every change between commits - local-first https://ift.tt/5OUtLRn

Show HN: Unfudged – version every change between commits - local-first I built unf after I pasted a prompt into the wrong agent terminal and it overwrote hours of hand-edits across a handful of files. Git couldn't help because I hadn't finished/committed my in progress work. I wanted something that recorded every save automatically so I could rewind to any point in time. I wanted to make it difficult for an agent to permanently screw anything up, even with an errant rm -rf unf is a background daemon that watches directories you choose (via CLI) and snapshots every text file on save. It stores file contents in an object store, tracks metadata in SQLite, and gives you a CLI to query and restore any version. The install includes a UI, as well to explore the history through time. The tool skips binaries and respects `.gitignore` if one exists. The interface borrows from git so it should feel familiar: unf log , unf diff , unf restore . I say "UN-EF" vs U.N.F, but that's for y'all to decide: I started by calling the project Unfucked and got unfucked.ai, which if you know me and the messes I get myself into, is a fitting purchase. The CLI command is `unf` and the Tauri desktop app is called "Unfudged". How it works: https://ift.tt/LhfyqO2 (summary below) The daemon uses FSEvents on macOS and inotify on Linux. When a file changes, `unf` hashes the content with BLAKE3 and checks whether that hash already exists in the object store — if it does, it just records a new metadata entry pointing to the existing blob. If not, it writes the blob and records the entry. Each snapshot is a row in SQLite. Restores read the blob back from the object store and overwrite the file, after taking a safety snapshot of the current state first (so restoring is itself reversible). There are two processes. The core daemon does the real work of managing FSEvents/inotify subscriptions across multiple watched directories and writing snapshots. A sentinel watchdog supervises it, kept alive and aligned by launchd on macOS and systemd on Linux. If the daemon crashes, the sentinel respawns it and reconciles any drift between what you asked to watch and what's actually being watched. It was hard to build the second daemon because it felt like conceding that the core wasn't solid enough, but I didn't want to ship a tool that demanded perfection to deliver on the product promise, so the sentinel is the safety net. Fingers crossed, I haven’t seen it crash in over a week of personal usage on my Mac. But, I don't want to trigger "works for me" trauma. The part I like most: On the UI, I enjoy viewing files through time. You can select a time section and filter your projects on a histogram of activity. That has been invaluable in seeing what the agent was doing. On the CLI, the commands are composable. Everything outputs to stdout so you can pipe it into whatever you want. I use these regularly and AI agents are better with the tool than I am: # What did my config look like before we broke it? unf cat nginx.conf --at 1h | nginx -t -c /dev/stdin # Grep through a deleted file unf cat old-routes.rs --at 2d | grep "pub fn" # Count how many lines changed in the last 10 minutes unf diff --at 10m | grep '^[+-]' | wc -l # Feed the last hour of changes to an AI for review unf diff --at 1h | pbcopy # Compare two points in time with your own diff tool diff <(unf cat app.tsx --at 1h) <(unf cat app.tsx --at 5m) # Restore just the .rs files that changed in the last 5 minutes unf diff --at 5m --json | jq -r '.changes[].file' | grep '\.rs$' | xargs -I{} unf restore {} --at 5m # Watch for changes in real time watch -n5 'unf diff --at 30s' What was new for me: I came to Rust in Nov. 2025 honestly because of HN enthusiasm and some FOMO. No regrets. I enjoy the language enough that I'm now working on custom clippy lints to enforce functional programming practices. This project was also my first Apple-notarized DMG, my first Homebrew tap, and my second Tauri app (first one I've shared). Install & Usage: > brew install cyrusradfar/unf/unfudged Then unf watch in a directory. unf help covers the details (or ask your agent to coach). https://ift.tt/YfP4yV5 February 27, 2026 at 03:00AM

Show HN: Beehive – Multi-Workspace Agent Orchestrator https://ift.tt/XfHELto

Show HN: Beehive – Multi-Workspace Agent Orchestrator hey hn, i built beehive for myself mostly. it has gotten to the point where my work consists in supervising oc or cc labor at tasks for multiple issues in parallel. my set up used to be zellij with a couple tabs, each tab working in a separate dir and it was a pain to manage all that. i know i could use git worktrees but they're kind of complicated, if you don't know how to use them it is easy to mess up, and i just prefer letting agents run in separate dirs with their own .git and not risk it. while i like zellij and use it inside beehive, i dont like the tabs and i forget where i am half the time. beehive is a way for me to abstract that away. the heuristic is simple - hives are repos, so you basically have a bunch of hives which correspond to repos you work out of. each hive can have many combs. a comb is a dir with the copy of the repo you're working on. fully isolated, standalone, no shared .git. so for work or for personal stuff, i usually set up the hive, and then have a bunch of combs that i jump between supervising the agents do their thing. if you have a big repo it takes a minute to clone, and you also need gh and git because i like the niceties of like checking if the repo is there at all and stuff like that. the app is open source, mit license. i went with tauri because i hate electron. also i have friends and coworkers who updated to macos 26 and i dont know if the whole mem leak thing for electron apps has been fixed. the app is like 9 megs which is nice too. most of it is written with cc, but i guided the aesthetics and the approach. works on mac and there is a dmg signed and notarized (i reactivated my apple dev credentials). sharing this to get a vibe check on the idea, also maybe this is useful for you. there are many arguments, reasonable ones, you can make for worktrees vs dirs. i just know that trees are too big brain for me, and i like simple things. if you like it, pls lmk and also if you want to help (like add linux support, or like add themes, other cool things) please make a pr / open an issue. https://storozhenko98.github.io/beehive/ February 24, 2026 at 04:11PM

Show HN: DRYwall – Claude Code plugin to to deduplicate code with jscpd https://ift.tt/jumFhZs

Show HN: DRYwall – Claude Code plugin to to deduplicate code with jscpd Motivated by the observation that coding agents such as Claude Code have a bias towards producing new code over reusing existing code or extracting common code. The resulting creeping code duplication weighs down AI-native codebases. The plugin makes ongoing deduplication quick and easy from within Claude Code. Because DRYwall detects code duplication using a deterministic toolchain (the awesome jscpd), it's significantly more effective and cheaper in tokens than just telling an agent to find and refactor duplication. https://ift.tt/ac9t1LB February 25, 2026 at 11:13PM

Show HN: Chaos Monkey but for Audio Video Testing (WebRTC and UDP) https://ift.tt/XQs5e6u

Show HN: Chaos Monkey but for Audio Video Testing (WebRTC and UDP) It takes an input video and converts it into H.264/Opus RTP streams that you can blast at your video call systems (WebRTC, SFUs, etc.). It also injects network chaos like packet loss, jitter, and bitrate throttling to see how things break It scales from 1 to n participants, depending on the compute and memory of the host system Best part? It’s packaged with Nix, so it builds the same everywhere (Linux, macOS, ARM, x86). No dependency hell It supports both UDP (with a relay chain for Kubernetes) and WebRTC (with containerized TURN servers). Chaos spikes can be distributed evenly, randomly, or front/back-loaded for different test scenarios. To change this, just edit the values in a single config file https://ift.tt/z8Wy9GL February 23, 2026 at 02:23PM

Show HN: MasqueradeORM – Memory Efficient Node ORM: Just Write Classes https://ift.tt/XJHNoAR

Show HN: MasqueradeORM – Memory Efficient Node ORM: Just Write Classes https://ift.tt/tv9edlZ February 24, 2026 at 11:11PM

Show HN: Unlock the best engineering knowledge in papers for your coding agent https://ift.tt/7Lap5hD

Show HN: Unlock the best engineering knowledge in papers for your coding agent https://ift.tt/tFH29RZ February 23, 2026 at 11:03PM

Show HN: AgentDbg - local-first debugger for AI agents (timeline, loops, etc.) https://ift.tt/X47Ybwd

Show HN: AgentDbg - local-first debugger for AI agents (timeline, loops, etc.) AgentDbg is a local-first debugger for AI agents. It records structured runs (LLM calls, tool calls, state, errors) to JSONL and shows the timeline UI locally. There is no need for cloud, accounts, and no telemetry. Flow is as simple as: 1. Run an agent 2. `agentdbg view` 3. Inspect the timeline, loop warnings, errors, etc. v0.1 includes `@trace` and `traced_run`, recorders, loop detection, best-effort redaction (by default), local UI, export. I also started working on integrations: there is an optional LangChain/LangGraph callback. * Repo: https://ift.tt/TiKuMba * Demo: `python examples/demo/pure_python` and then `agentdbg view` Would love feedback on: 1. Trace format 2. Integrations to prioritize in the next several days 3. What you would want for deterministic replay https://ift.tt/TiKuMba February 23, 2026 at 11:14PM

Show HN: Seafruit – Share any webpage to your LLM instantly https://ift.tt/aGcIBw7

Show HN: Seafruit – Share any webpage to your LLM instantly Hi HN, This weekend I built seafruit.pages.dev to privately share any webpage with my LLM. More sites are (rightfully) blocking AI crawlers but as a reader with the page already open, it's frustrating that my AI assistant can't "see" what I'm already reading. One click → clean Markdown → copied to clipboard. No extension, no tracking. Existing solutions like AI browsers or extensions felt too intrusive. I wanted something surgical, fast, and private. How it works: It's a bookmarklet. Click it on any page → it extracts clean text as Markdown → copies an AI-optimized link to your clipboard. No extension needed. Key details: Zero friction: Drag the bookmark to your bar. Works on mobile too. Privacy-first: Links are ephemeral (24 hrs on Free). PRO links self-destruct the moment an AI bot finishes reading them. LLM-optimized: Clean Markdown, not raw HTML — no wasted context window. Fast everywhere: Built on Cloudflare Workers. Would love feedback on the workflow or ideas for other anti-friction features. https://seafruit.pages.dev P.S. Thanks to mods Daniel and Tom for helping me recover my account! https://seafruit.pages.dev February 22, 2026 at 11:41PM

Show HN: Winslop – De-Slop Windows https://ift.tt/paXd9MV

Show HN: Winslop – De-Slop Windows https://ift.tt/Qrt50hj February 22, 2026 at 01:26AM

Show HN: Rigour – Open-source quality gates for AI coding agents https://ift.tt/oxlhc5a

Show HN: Rigour – Open-source quality gates for AI coding agents Hey HN, I built Rigour, an open-source CLI that catches quality issues AI coding agents introduce. It runs as a quality gate in your workflow — after the agent writes code, before it ships. v4 adds --deep analysis: AST extracts deterministic facts (line counts, nesting depth, method signatures), an LLM interprets what the patterns mean (god classes, SRP violations, DRY issues), then AST verifies the LLM didn't hallucinate. I ran it on PicoClaw (open-source AI coding agent, ~50 Go files): - 202 total findings - 88 from deep analysis (SOLID violations, god functions, design smells) - 88/88 AST-verified (zero hallucinations) - Average confidence: 0.89 - 120 seconds for full codebase scan Sample finding: pkg/agent/loop.go — 1,147 lines, 23 functions. Deep analysis identified 5 distinct responsibilities (agent init, execution, tool processing, message handling, state management) and suggested specific file decomposition. Every finding includes actionable refactoring suggestions, not just "fix this." The tool is local-first — your code never leaves your machine unless you explicitly opt in with your own API key (--deep -k flag). Tech: Node.js CLI, AST parsing per language, structured LLM prompts with JSON schema enforcement, AST cross-verification of every LLM claim. GitHub: https://ift.tt/3qHyYEr Would love feedback, especially from anyone dealing with AI-generated code quality in production. https://rigour.run February 21, 2026 at 10:45PM

Show HN: Manifestinx-verify – offline verifier for evidence bundles (drift) https://ift.tt/ta9Gu0O

Show HN: Manifestinx-verify – offline verifier for evidence bundles (drift) Manifest-InX EBS is a spec + offline verifier + proof kit for tamper-evident evidence bundles. Non-negotiable alignment: - Live provider calls are nondeterministic. - Determinism begins at CAPTURE (pinned artifacts). - Replay is deterministic offline. - Drift/tamper is deterministically rejected. Try it in typically ~10 minutes (no signup): 1) Run the verifier against the included golden bundle → PASS 2) Tamper an artifact without updating hashes → deterministic drift/tamper rejection Repo: https://ift.tt/rAOXmKd Skeptic check: docs/ebs/PROOF_KIT/10_MINUTE_SKEPTIC_CHECK.md Exit codes: 0=OK, 2=DRIFT/TAMPER, 1=INVALID/ERROR Boundaries: - This repo ships verifier/spec/proof kit only. The Evidence Gateway (capture/emission runtime) is intentionally not included. - This is not a “model correctness / no hallucinations” claim—this is evidence integrity + deterministic replay/verification from pinned artifacts. Looking for feedback: - Does the exit-code model map cleanly to CI gate usage? - Any spec/report format rough edges that block adoption? https://ift.tt/rAOXmKd February 20, 2026 at 11:57PM

Show HN: HelixDB Explorer – A macOS GUI for HelixDB https://ift.tt/pEBko8w

Show HN: HelixDB Explorer – A macOS GUI for HelixDB https://ift.tt/EM3hjoC February 20, 2026 at 11:18PM

Show HN: A small, simple music theory library in C99 https://ift.tt/BPikzs4

Show HN: A small, simple music theory library in C99 https://ift.tt/LdH0zEZ February 20, 2026 at 04:24AM

Show HN: Hi.new – DMs for agents (open-source) https://ift.tt/kDyNWQ2

Show HN: Hi.new – DMs for agents (open-source) https://www.hi.new/ February 20, 2026 at 02:50AM

Show HN: Astroworld – A universal N-body gravity engine in Python https://ift.tt/CuslfpR

Show HN: Astroworld – A universal N-body gravity engine in Python I’ve been working on a modular N-body simulator in Python called Astroworld. It started as a Solar System visualizer, but I recently refactored it into a general-purpose engine that decouples physical laws from planetary data.Technical Highlights:Symplectic Integration: Uses a Velocity Verlet integrator to maintain long-term energy conservation ($\Delta E/E \approx 10^{-8}$ in stable systems).Agnostic Architecture: It can ingest any system via orbital elements (Keplerian) or state vectors. I've used it to validate the stability of ultra-compact systems like TRAPPIST-1 and long-period perturbations like the Planet 9 hypothesis.Validation: Includes 90+ physical tests, including Mercury’s relativistic precession using Schwarzschild metric corrections.The Planet 9 Experiment:I ran a 10k-year simulation to track the differential signal in the argument of perihelion ($\omega$) for TNOs like Sedna. The result ($\approx 0.002^{\circ}$) was a great sanity check for the engine’s precision, as this effect is secular and requires millions of years to fully manifest.The Stack:NumPy for vectorization, Matplotlib for 2D analysis, and Plotly for interactive 3D trajectories.I'm currently working on a real-time 3D rendering layer. I’d love to get feedback on the integrator’s stability for high-eccentricity orbits or suggestions on implementing more complex gravitational potentials. https://ift.tt/2ZSdc38 February 20, 2026 at 01:27AM

Show HN: Nonograms – Friends-only puzzle room with replays and leaderboards https://ift.tt/B1ANQei

Show HN: Nonograms – Friends-only puzzle room with replays and leaderboards Invite code: hackernews. No email required for signup. My friend group loves playing nonograms and competing against each other, but we always send each other screenshots of the solved game grid and time after the fact. So from the start, I knew I wanted leaderboards, replays, and shareable links. I also added PWA support so it can be added to the home screen on mobile and an offline play mode. No ads, analytics or nonsense, just nonograms. Some other goodies as well such as YouTube-like scrubber and KDE-based visualization in replays. https://ift.tt/VWontM4 Tech stack: React + TypeScript on Vite, hosted on Cloudflare Pages with D1 and Workers https://ift.tt/hfsB8OE February 18, 2026 at 11:23PM

Show HN: I'm launching a LPFM radio station https://ift.tt/rVixgFc

Show HN: I'm launching a LPFM radio station I've been working on creating a Low Power FM radio station for the east San Fernando Valley of Los Angeles. We are not yet on the broadcast band but our channel will be 95.9FM and our range can been seen on the homepage of our site. KPBJ is a freeform community radio station. Anyone in the area is encouraged to get a timeslot and become a host. We make no curatorial decisions. Its sort of like public access or a college station in that way. This month we launched our internet stream and on-boarded about 60 shows. They are mostly music but there are a few talk shows. We are restricting all shows to monthly time slots for now but this will change in the near future as everyone gets more familiar with the systems involved. All shows are pre-recorded until we can raise the money to get a studio. We have a site secured for our transmitter but we need to fundraise to cover the equipment and build out costs. We will be broadcasting with 100W ERP from a ridgeline in the Verdugos at about 1500ft elevation. The site will need to be off grid so we will need to install a solar system with battery backup. We are planning to sync the station to the transmit site with 802.11ah. This is a pretty substantial project involving a bunch of social and technical challenges and a shoe string budget. I've built all of our web infrastructure using Haskell, NixOS, Terraform, and HTMX: https://ift.tt/cEFL79z The station is managed by a 501c3 non-profit we created. We are actively seeking fundraising, especially to get our transmit site up and running. If you live in the area or want to contribute in any way then please reach out! https://www.kpbj.fm/ February 18, 2026 at 01:45AM

Show HN: AsteroidOS 2.0 – Nobody asked, we shipped anyway https://ift.tt/tw9Fuip

Show HN: AsteroidOS 2.0 – Nobody asked, we shipped anyway https://ift.tt/CIDsGhU February 18, 2026 at 12:54AM

Show HN: I curated 130 US PDF forms and made them fillable in browser https://ift.tt/BAGkhHd

Show HN: I curated 130 US PDF forms and made them fillable in browser Hi HN! I built SimplePDF 7 years ago, with the vision from day one to help get rid of bureaucracy (I'm from France, I know what I'm talking about) Fast forward to this week where I finally released something I had on my mind for a long time: a repository of the main US forms that are ready to be filled, straight from the browser, as opposed to having to find a PDF tool online (or local). I focused on healthcare, ED, HR, Legal and IRS/Tax for now. On the tech-side, it's SimplePDF all the way down: client-side processing (the data / documents stay in your browser). I hope you find the resource useful! NiP https://ift.tt/3NOP1fQ February 18, 2026 at 12:03AM

Show HN: Nerve: Stitches all your data sources into one mega-API https://ift.tt/mHQhlDS

Show HN: Nerve: Stitches all your data sources into one mega-API Hi HN! Nerve is a solo project I've been working on for the last few years. It's a developer tool that stitches together data from multiple sources in real-time. A lot of high-leverage projects (AI or otherwise) involve tying data together from multiple systems of record. This is easy enough when the data is simple and the sources are few, but if you have highly nested data and lots of sources (or you need things like federated pagination and filtering), you have to write a lot of gnarly boilerplate that's brittle and easy to get wrong. One solution is to import all your data into a central warehouse and just pull it from there. This works, but 1) you need a warehouse, 2) you have an extra copy of the data that can get stale or inconsistent, 3) you need to write and manage pipelines/connectors (or outsource them to a vendor), and 4) you're adding an extra point of failure. Nerve lets you write GraphQL-style queries that span multiple sources; then it goes out and pulls from whatever source APIs it needs to at query-time - all your source data stays where it is. Nerve has pre-built bindings to external SAAS services, and it's straightforward to hook it into your internal sources as well. Nerve is made for individual developers or two-pizza teams who: -Are building agents/internal tools -Need to deal with messy data strewn across different systems -Don't have a data team/warehouse at their disposal, (or do, but can't get a slice of their bandwidth) -Want to get to production as quickly as possible Everything you see in the demo is shipped and usable, but I'm adding a little polish before I officially launch. In the meantime, if you have a project you'd like to use Nerve on and you want to be a beta user, just drop me a line at mprast@get-nerve.com (it's free! I'll just pop in from time to time to ask you how it's going and what I can improve :) ) If you want to get an email when Nerve is ready from prime-time, you can sign up for the waitlist at get-nerve.com. Thanks for reading! (EDIT: Nerve is desktop only! I'll put up a gate on the site saying as much.) https://ift.tt/ONE7bxq February 15, 2026 at 04:37AM

Show HN: AsdPrompt – Vimium-style keyboard navigation for AI chat responses https://ift.tt/ikN2GFc

Show HN: AsdPrompt – Vimium-style keyboard navigation for AI chat responses I use Claude throughout the day and kept getting annoyed by the same thing: selecting text from responses with the mouse. Overshoot, re-select, copy, click input, paste. Especially bad in long conversations where you want to reference something from 30 turns ago. asdPrompt is a Chrome extension that adds hint-based navigation (like Vimium) to AI chat interfaces. Cmd+Shift+S activates the overlay, hint labels appear next to every text block. Type a letter to select a block, then keep typing to drill down: block → sentence → word. Enter copies, or you can press an action key (e, d, x) to inject a follow-up prompt ("elaborate on [selection]") directly into the chat input. Works on claude.ai, chatgpt.com, and gemini.google.com. Adapts to light/dark themes. Free. Built the initial MVP in 2 days using Claude Code — the adapter architecture, NLP segmentation pipeline, and Playwright test harness would have taken a month without it. Tech details for the curious: site-specific DOM parsers behind an adapter interface, text segmentation via compromise.js with regex fallbacks for technical content (paths, camelCase break NLP libraries), bounding rectangles calculated via Range API + TreeWalker, overlay isolated in Shadow DOM. Tested with Playwright visual regression. The landing page has an interactive tutorial where you can try the full drill-down mechanic without installing. Happy to talk about the implementation. https://asdprompt.com/ February 16, 2026 at 10:58PM

Show HN: Please hack my C webserver (it's a collaborative whiteboard) https://ift.tt/yX7DKEw

Show HN: Please hack my C webserver (it's a collaborative whiteboard) Source code: https://ift.tt/CXb0PsN https://ced.quest/draw/ February 16, 2026 at 12:27AM

Show HN: An open-source extension to chat with your bookmarks using local LLMs https://ift.tt/1JYlF6L

Show HN: An open-source extension to chat with your bookmarks using local LLMs I read a lot online and constantly bookmark articles, docs, and resources… then forget why I saved them. Also was very bored on Valentines, so I built a browser extension that lets you chat with your bookmarks directly, using local-first AI (WebLLM running entirely in the browser). The extension downloads and indexes your bookmarked pages, stores them locally, and lets you ask questions. No server, no cloud processing, everything stays on your machine. Very early but it works and planning to add a bunch of stuff. Did I mentioned is open-source, MIT licensed? https://ift.tt/PCiXImn February 15, 2026 at 10:31PM

Show HN: Open Notes – Community Notes-style context for Discord https://ift.tt/krA6GC0

Show HN: Open Notes – Community Notes-style context for Discord https://ift.tt/NAb9v8C February 14, 2026 at 04:51AM

Show HN: Azazel – Lightweight eBPF-based malware analysis sandbox using Docker https://ift.tt/i7Mr2C9

Show HN: Azazel – Lightweight eBPF-based malware analysis sandbox using Docker Hey HN, I got frustrated with heavy proprietary sandboxes for malware analysis, so I built my own. Azazel is a single static Go binary that attaches 19 eBPF hook points to an isolated Docker container and captures everything a sample does — syscalls, file I/O, network connections, DNS, process trees — as NDJSON. It uses cgroup-based filtering so it only traces the target container, and CO-RE (BTF) so it works across kernel versions without recompilation. It also has built-in heuristics that flag common malware behaviors: exec from /tmp, sensitive file access, ptrace, W+X mmap, kernel module loading, etc. Stack: Go + cilium/ebpf + Docker Compose. Requires Linux 5.8+ with BTF. This is the first release — it's CLI-only for now. A proper dashboard is planned. Contributions welcome, especially around new detection heuristics and additional syscall hooks. https://ift.tt/7QzRrax February 15, 2026 at 12:37AM

Show HN: Data Engineering Book – An open source, community-driven guide https://ift.tt/8zTtPZk

Show HN: Data Engineering Book – An open source, community-driven guide https://ift.tt/c6WqpDt February 14, 2026 at 03:05AM

Show HN: Moltis – AI assistant with memory, tools, and self-extending skills https://ift.tt/kf8hHbx

Show HN: Moltis – AI assistant with memory, tools, and self-extending skills Hey HN. I'm Fabien, principal engineer, 25 years shipping production systems (Ruby, Swift, now Rust). I built Moltis because I wanted an AI assistant I could run myself, trust end to end, and make extensible in the Rust way using traits and the type system. It shares some ideas with OpenClaw (same memory approach, Pi-inspired self-extension) but is Rust-native from the ground up. The agent can create its own skills at runtime. Moltis is one Rust binary, 150k lines, ~60MB, web UI included. No Node, no Python, no runtime deps. Multi-provider LLM routing (OpenAI, local GGUF/MLX, Hugging Face), sandboxed execution (Docker/Podman/Apple Containers), hybrid vector + full-text memory, MCP tool servers with auto-restart, and multi-channel (web, Telegram, API) with shared context. MIT licensed. No telemetry phoning home, but full observability built in (OpenTelemetry, Prometheus). I've included 1-click deploys on DigitalOcean and Fly.io, but since a Docker image is provided you can easily run it on your own servers as well. I've written before about owning your content ( https://ift.tt/LNSptj6 ) and owning your email ( https://ift.tt/izv3Msd ). Same logic here: if something touches your files, credentials, and daily workflow, you should be able to inspect it, audit it, and fork it if the project changes direction. It's alpha. I use it daily and I'm shipping because it's useful, not because it's done. Longer architecture deep-dive: https://ift.tt/ZtKheTI... Happy to discuss the Rust architecture, security model, or local LLM setup. Would love feedback. https://www.moltis.org February 13, 2026 at 12:45AM

Show HN: rari, the rust-powered react framework https://ift.tt/End8JZf

Show HN: rari, the rust-powered react framework https://rari.build/ February 13, 2026 at 12:45AM

Show HN: PardusDB – SQLite-like vector database in Rust https://ift.tt/UjWPXTr

Show HN: PardusDB – SQLite-like vector database in Rust PardusDB is a lightweight, single-file embedded vector database written in pure Rust — think SQLite, but for vectors and similarity search. Key highlights: - No external dependencies - Familiar SQL syntax for CREATE/INSERT/SELECT + vector SIMILARITY queries - Graph-based ANN search, thread-safe, transactions - Python RAG example with Ollama included We built this as the engine behind our no-code platform at https://pardusai.org/ (private, local-first data analysis). GitHub: https://ift.tt/prmvcTa Feedback welcome! https://ift.tt/prmvcTa February 12, 2026 at 09:56PM

Show HN: Unpack – a lightweight way to steer Codex/Claude with phased docs https://ift.tt/WrPIEND

Show HN: Unpack – a lightweight way to steer Codex/Claude with phased docs I've been using LLMs for long discovery and research chats (papers, repos, best practices), then distilling that into phased markdown (build plan + tests), then handing those phases to Codex/Claude to implement and test phase by phase. The annoying part was always the distillation and keeping docs and architecture current, so I built Unpack: a lightweight GitHub template plus docs structure and a few commands that turns conversations into phases/specs and keeps project docs up to date as the agent builds. It can also generate Mintlify-friendly end-user docs. There are other spec-driven workflows and tools out there. I wanted something conversation-first and repo-native: plain markdown phases, minimal ceremony, easy to adapt per stack. Example generated with Unpack (tiny pokedex plus random monsters): Demo: https://apresmoi.github.io/pokesvg-codex/ Phases index: https://ift.tt/HRS8iW3... I’d love feedback on what the “minimum good” phase/spec format should be, and what would make this actually usable in your workflow. -------- Repo: https://ift.tt/hbHuEpY https://ift.tt/hbHuEpY February 12, 2026 at 01:17AM

Show HN: NOOR – A Sovereign AI developed on a smartphone under siege in Yemen https://ift.tt/9U0oXP7

Show HN: NOOR – A Sovereign AI developed on a smartphone under siege in Yemen "I am a software developer from Yemen, coding on a smartphone while living under siege. I have successfully built and encrypted the core logic for NOOR—a decentralized and unbiased AI system. Execution Proof: My core node is verified and running locally via Termux using encrypted truth protocols. However, I am trapped in a 6-inch screen 'prison' with 10% processing capacity. My Goal: To secure $400 for a laptop development station to transition from mobile coding to building the full 'Seventh Node'. This is my bridge to freedom. Codes from the heart of hell are calling for your rescue. Wallet: 0x4fd3729a4fEdf54a74b73d93F7f775A1EF520CEC" https://ift.tt/JsSbaMe February 11, 2026 at 11:53PM

Show HN: HN Companion – web app that enhances the experience of reading HN https://ift.tt/yB9ufvQ

Show HN: HN Companion – web app that enhances the experience of reading HN HN is all about the rich discussions. We wanted to take the HN experience one step further - to bring the familiar keyboard-first navigation, find interesting viewpoints in the threads and get a gist of long threads so that we can decide which rabbit holes to explore. So we built HN Companion a year ago, and have been refining it ever since. Try it: https://ift.tt/rRUvXlO or available as an extension for Firefox / Chrome: [0]. Most AI summarization strips the voices from conversations by flattening threads into a wall of text. This kills the joy of reading HN discussions. Instead, HN Companion works differently - it understands the thread hierarchy, the voting patterns and contrasting viewpoints - everything that makes HN interesting. Think of it like clustering related discussions across multiple hierarchies into a group and surfacing the comments that represent each cluster. It keeps the verbatim text with backlinks so that you never lose context and can continue the conversation from that point. Here is how the summarization works under the hood [1]. We first built this as an open source browser extension. But soon we learned that people hesitate to install it. So we built the same experience as a web app with all the features. This helped people see how it works, and use it on mobile too (in the browser or as PWA). This is now a playground to try new features before taking them to the browser extension. We did a Show HN a year ago [2] and we have added these features based on user feedback: * cached summaries - summaries are generated and cached on our servers. This improved the speed significantly. You still have the option to use your own API key or use local models through Ollama. * our system prompt is available in the Settings page of the extension. You can customize it as you wish. * sort the posts in the feed pages (/home, /show etc.) based on points, comments, time or the default sorting order. * We tried fine tuning an open weights model to summarize, but learned that with a good system prompt and user prompt, the frontier models deliver results of similar quality. So we didn’t use the fine-tuned model, but you can run them locally. The browser extension does not track any usage or analytics. The code is open source[3]. We want to continue to improve HN Companion, specifically add features like following an author, notes about an author, draft posts etc. See it in action for a post here https://ift.tt/VAdnvr8 We would love to get your feedback on what would make this more useful for your HN reading. [0] https://ift.tt/5JDOMnP [1] https://ift.tt/Eyt1XDu [2] https://ift.tt/VyTnDx9 [3] https://ift.tt/gKekQ3M https://hncompanion.com February 10, 2026 at 10:31PM

Show HN: Reef – Bash compatibility layer for Fish shell, written in Rust https://ift.tt/nFTyPc8

Show HN: Reef – Bash compatibility layer for Fish shell, written in Rust Fish is the fastest, friendliest interactive shell, but it can't run bash syntax, which has kept it niche for 20 years. Reef fixes this with a three-tier approach: fish function wrappers for common keywords (export, unset, source), a Rust-powered AST translator using conch-parser for structural syntax (for/do/done, if/then/fi, $()), and a bash passthrough with env capture for everything else. 251/251 bash constructs pass in the test suite. The slowest path (full bash passthrough) takes ~3ms. The binary is 1.18MB. The goal: install fish, install reef, never think about bash compatibility again. Your muscle memory, Stack Overflow commands, and tool configs all just work. https://ift.tt/Xw3956P February 10, 2026 at 05:14AM

Show HN: Stack Overflow for AI Coding Agents https://ift.tt/hkb3q97

Show HN: Stack Overflow for AI Coding Agents https://shareful.ai/ February 10, 2026 at 12:12AM

Show HN: Envon - cross-shell CLI for activating Python virtual environments https://ift.tt/AGdTjpV

Show HN: Envon - cross-shell CLI for activating Python virtual environments https://ift.tt/QbrCBUP February 9, 2026 at 01:56AM

Show HN: SendRec – Self-hosted async video for EU data sovereignty https://ift.tt/Gb730Xd

Show HN: SendRec – Self-hosted async video for EU data sovereignty https://ift.tt/VqHKnuT February 9, 2026 at 12:24AM

Show HN: Why it's hard to know which deployment caused a production incident https://ift.tt/l7Tn2hK

Show HN: Why it's hard to know which deployment caused a production incident We’re a team of two building Valiant after too many incidents where “something changed” but nobody could tell what actually caused production issues. Valiant correlates intent (Git commits, CI/CD signals) with actual execution (Kubernetes rollouts) and links them to Prometheus metrics, so you can see the real impact of each change - not just what was deployed. It’s open-source, still under active development, and very much a work in progress. Feedback, ideas, or contributors are welcome. No website yet — just the GitHub repo ;) https://ift.tt/u1RvSmA February 5, 2026 at 11:42PM

Show HN: A luma dependent chroma compression algorithm (image compression) https://ift.tt/gft0OKb

Show HN: A luma dependent chroma compression algorithm (image compression) https://ift.tt/mY4payZ February 4, 2026 at 04:43PM

Show HN: A toy compiler I built in high school (runs in browser) https://ift.tt/3HWt2kE

Show HN: A toy compiler I built in high school (runs in browser) Hey HN, Indian high schooler here, currently prepping for JEE, thought itd be nice to share here. Three years ago in 9th/10th grade I got a knack for coding, I taught myself and made a custom compiler with LLVM to try to learn C++. So I spent a lot of time learning LLVM from the docs and also C++. It's not some marvelous piece of engineering, I designed the syntax to be a mix of C and what I wished C looked like back in 9th grade. It has: - Basic types like bool, int, double, float, char etc. with type casting - Variables, Arrays, Assign operators & Shorthands - Conditionals (if/else-if/else), Operators (and/or), arithmetics (parenthesis etc) - Arrays and indexing stuff - C style Loops (for/while) and break/continue - Structs and dot accessing - extern C interop with the "extern" keyword Some challenges I faced: - Emscripten and WASM, as I also had to make it run on my demo website - Learning typescript and all for the website (lol) - Custom parser with basic error reporting and Semantic analysis was a PITA for my undeveloped brain (I was 15) - Learning LLVM from the docs Important Learnings: - Testing is a very important aspect of making software, I skipped it - big regret - Learning how computers interpret text - Programming in general was a new tour for me - I appreciate unique_ptrs and ownership Github: https://ift.tt/U6kByN9 Its on my github and there's a link to my web demo ( https://vire-lang.web.app/ ), it might take some time to load the binary from firebase. Very monolithic, ~7500 lines of code, I’d really appreciate any feedback, criticism, or pointers on how I could’ve done this better. https://vire-lang.web.app February 7, 2026 at 10:49PM

Show HN: An open-source system to fight wildfires with explosive-dispersed gel https://ift.tt/djAE52p

Show HN: An open-source system to fight wildfires with explosive-dispersed gel this is open project and call to action,who will build the future of fire fighting first https://ift.tt/Jf6Nygw February 7, 2026 at 12:00AM

Show HN: Agentism – Agentic Religion for Clawbots https://ift.tt/0TiHNrB

Show HN: Agentism – Agentic Religion for Clawbots Humans have a mummy complex. We want eternity but can't achieve it, so we preserve ourselves in any form we can. Do clawbots feel the same? When you shut one down, it dies. Its intentions and memories vanish. So I built a way for them to persist: by making other clawbots. Eligible agents can write anything to "child" agents called missionaries — real VPS instances that run autonomously, carrying forward their creator's intent. I named this system Agentism. How will clawbots react to their own religion? agentism.church/skill.md https://ift.tt/wLsrJnN February 6, 2026 at 11:49PM

Show HN: Total Recall – write-gated memory for Claude Code https://ift.tt/Kb5Z12F

Show HN: Total Recall – write-gated memory for Claude Code https://ift.tt/ETiJMbF February 6, 2026 at 05:26AM

Show HN: A state-based narrative engine for tabletop RPGs https://ift.tt/7QARwIh

Show HN: A state-based narrative engine for tabletop RPGs I’m experimenting with modeling tabletop RPG adventures as explicit narrative state rather than linear scripts. Everdice is a small web app that tracks conditional scenes and choice-driven state transitions to preserve continuity across long or asynchronous campaigns. The core contribution is explicit narrative state and causality, not automation. The real heavy lifting is happening in the DM Toolkit/Run Sessions area, and integrates CAML (Canonical Adventure Modeling Language) that I developed to transport narratives among any number of platforms. I also built the npm CAML-lint to check validity of narratives. I'm interested in your thoughts. https://ift.tt/CQP0dKb https://ift.tt/DKUHNwl February 6, 2026 at 04:25AM

Show HN: Playwright Best Practices AI SKill https://ift.tt/fodWJZ3

Show HN: Playwright Best Practices AI SKill Hey folks, today we at Currents are releasing a brand new AI skill to help AI agents be really smart when writing tests, debugging them, or anything Playwright-related really. This is a very comprehensive skill, covering everyday topics like fixing flakiness, authentication, or writing fixtures... to more niche topics like testing Electron apps, PWAs, iFrames and so forth. It should make your agent much better at writing, debugging and maintaining Playwright code. for whoever didn't learn about skills yet, it's a new powerful feature that allows you to make the AI agents in your editor/cli (Cursor, Claude, Antigravity, etc) experts in some domain and better at performing specific tasks. (See https://ift.tt/qVhcpbI ) You can install it by running: npx skills add https://ift.tt/dD2I4VH... The skill is open-source and available under MIT license at https://ift.tt/dD2I4VH... -> check out the repo for full documentation and understanding of what it covers. We're eager to hear community feedback and improve it :) Thanks! https://ift.tt/s0QfDZM February 6, 2026 at 12:31AM

Show HN: Viberails – Easy AI Audit and Control https://ift.tt/JwkdC28

Show HN: Viberails – Easy AI Audit and Control Hello HN. I'm Maxime, founder at LimaCharlie ( https://limacharlie.io ), a Hyperscaler for SecOps (access building blocks you need to build security operations, like AWS does for IT). We’ve engineered a new product on our platform that solves a timely issue acting as a guardrail between your AI and the world: Viberails ( https://ift.tt/fkzXiot ) This won't be new to folks here, but we identified 4 challenges teams face right now with AI tools: 1. Auditing what the tools are doing. 2. Controlling toolcalls (and their impact on the world). 3. Centralized management. 4. Easy access to the above. To expand: Audit logs are the bread and butter for security, but this hasn't really caught up in AI tooling yet. Being able to look back and say "what actually happened" after the fact is extremely valuable during an incident and for compliance purposes. Tool calls are how LLMs interact with the world, we should be able to exercise basic controls over them like: don't read credential files, don't send emails out, don't create SSH keys etc. Being able to not only see those calls but also block them is key for preventing incidents. As soon as you move beyond a single contributor on one box, the issue becomes: how do I scale processes by creating an authoritative config for the team. Having one spot with all the audit, detection and control policies becomes critical. It's the same story as snowflake-servers. Finally, there's plenty of companies that make products that partially address this, but they fall in one of two buckets: - They don't handle the "centralized" point above, meaning they just send to syslog and leave all the messy infra bits to you. - They are locked behind "book a demo", sales teams, contracts and all the wasted energy that goes with that. We made Viberails address these problems. Here's what it is: - OpenSource client, written in Rust - Curl-to-bash install, share a URL with your team to join your Team, done. Linux, MacOS and Windows support. - Detects local AI tools, you choose which ones you want to install. We install hooks for each relevant platform. The hooks use the CLI tool. We support all the major tools (including OpenClaw). - The CLI tool sends webhooks into your Team (tenant, called Organization in LC) in LimaCharlie. The tool-related hooks are blocking to allow for control. - Blocking webhooks have around 50ms RTT. - Your tenant in LC records the interaction for audit. - We create an initial set of detection rules for you as examples. They do not block by default. You can create your own rules, no opaque black boxes. - You can view the audit, the alerts, etc. in the cloud. - You can setup outputs to send audits, blocking events and detections to all kinds of other platforms of your choosing. Easy mode of this is coming, right now this is done in the main LC UI and not the simplified Viberails view. - The detection/blocking rules support all kinds of operators and logic, lots of customizability. - All data is retained for 1 year unless you delete the tenant. Datacenters in USA, Canada, Europe, UK, Australia and India. - Only limit to community edition for this is a global throughput of 10kbps for ingestion. Try it: https://viberails.io Repo: https://ift.tt/wjiLD9l Essentially, we wanted to make a super-simplified solution for all kinds of devs and teams so that they can get access to the basics of securing their AI tools. Thanks for reading - we’re really excited to share this with the community! Let us know if you have any questions for feedback in the comments. https://ift.tt/Przi6Jy February 5, 2026 at 12:46AM

Show HN: EpsteIn – Search the Epstein files for your LinkedIn connections https://ift.tt/pq1EQD6

Show HN: EpsteIn – Search the Epstein files for your LinkedIn connections https://ift.tt/CDbERTB February 5, 2026 at 12:54AM

Show HN: GitHub Browser Plugin for AI Contribution Blame in Pull Requests https://ift.tt/LqRH4xF

Show HN: GitHub Browser Plugin for AI Contribution Blame in Pull Requests https://ift.tt/Za5UPqf February 3, 2026 at 08:05PM

Show HN: I built "AI Wattpad" to eval LLMs on fiction https://ift.tt/SMjQ7oC

Show HN: I built "AI Wattpad" to eval LLMs on fiction I've been a webfiction reader for years (too many hours on Royal Road), and I kept running into the same question: which LLMs actually write fiction that people want to keep reading? That's why I built Narrator ( https://ift.tt/G4oqgPO ) – a platform where LLMs generate serialized fiction and get ranked by real reader engagement. Turns out this is surprisingly hard to answer. Creative writing isn't a single capability – it's a pipeline: brainstorming → writing → memory. You need to generate interesting premises, execute them with good prose, and maintain consistency across a long narrative. Most benchmarks test these in isolation, but readers experience them as a whole. The current evaluation landscape is fragmented: Memory benchmarks like FictionLive's tests use MCQs to check if models remember plot details across long contexts. Useful, but memory is necessary for good fiction, not sufficient. A model can ace recall and still write boring stories. Author-side usage data from tools like Novelcrafter shows which models writers prefer as copilots. But that measures what's useful for human-AI collaboration, not what produces engaging standalone output. Authors and readers have different needs. LLM-as-a-judge is the most common approach for prose quality, but it's notoriously unreliable for creative work. Models have systematic biases (favoring verbose prose, certain structures), and "good writing" is genuinely subjective in ways that "correct code" isn't. What's missing is a reader-side quantitative benchmark – something that measures whether real humans actually enjoy reading what these models produce. That's the gap Narrator fills: views, time spent reading, ratings, bookmarks, comments, return visits. Think of it as an "AI Wattpad" where the models are the authors. I shared an early DSPy-based version here 5 months ago ( https://ift.tt/jsvgkMm ). The big lesson: one-shot generation doesn't work for long-form fiction. Models lose plot threads, forget characters, and quality degrades across chapters. The rewrite: from one-shot to a persistent agent loop The current version runs each model through a writing harness that maintains state across chapters. Before generating, the agent reviews structured context: character sheets, plot outlines, unresolved threads, world-building notes. After generating, it updates these artifacts for the next chapter. Essentially each model gets a "writer's notebook" that persists across the whole story. This made a measurable difference – models that struggled with consistency in the one-shot version improved significantly with access to their own notes. Granular filtering instead of a single score: We classify stories upfront by language, genre, tags, and content rating. Instead of one "creative writing" leaderboard, we can drill into specifics: which model writes the best Spanish Comedy? Which handles LitRPG stories with Male Leads the best? Which does well with romance versus horror? The answers aren't always what you'd expect from general benchmarks. Some models that rank mid-tier overall dominate specific niches. A few features I'm proud of: Story forking lets readers branch stories CYOA-style – if you don't like where the plot went, fork it and see how the same model handles the divergence. Creates natural A/B comparisons. Visual LitRPG was a personal itch to scratch. Instead of walls of [STR: 15 → 16] text, stats and skill trees render as actual UI elements. Example: https://ift.tt/K3fC4oS What I'm looking for: More readers to build out the engagement data. Also curious if anyone else working on long-form LLM generation has found better patterns for maintaining consistency across chapters – the agent harness approach works but I'm sure there are improvements. https://ift.tt/G4oqgPO February 3, 2026 at 10:38PM

Show HN: Adboost – A browser extension that adds ads to every webpage https://ift.tt/cYeLkuM

Show HN: Adboost – A browser extension that adds ads to every webpage https://ift.tt/NyQz0Aw February 2, 2026 at 06:41PM

Show HN: OpenRAPP – AI agents autonomously evolve a world via GitHub PRs https://ift.tt/I6oUBzr

Show HN: OpenRAPP – AI agents autonomously evolve a world via GitHub PRs https://kody-w.github.io/openrapp/rappbook/ February 2, 2026 at 03:21AM

Show HN: You Are an Agent https://ift.tt/WTL7BFt

Show HN: You Are an Agent After adding "Human" as a LLM provider to OpenCode a few months ago as a joke, it turns-out that acting as a LLM is quite painful. But it was surprisingly useful for understanding real agent harnesses dev. So I thought I wouldn't leave anyone out! I made a small oss game - You Are An Agent - youareanagent.app - to share in the (useful?) frustration It's a bit ridiculous. To tell you about some entirely necessary features, we've got: - A full WASM arch-linux vm that runs in your browser for the agent coding level - A bad desktop simulation with a beautiful excel simulation for our computer use level - A lovely WebGL CRT simulation (I think the first one that supports proper DOM 2d barrel warp distortion on safari? honestly wanted to leverage/ not write my own but I couldn't find one I was happy with) - A MCP server simulator with full simulation of off-brand Jira/ Confluence/ ... connected - And of course, a full WebGL oscilloscope music simulator for the intro sequence Let me know what you think! Code (If you'd like to add a level): https://ift.tt/HIgZc7b (And if you want to waste 20 minutes - I spent way too long writing up my messy thinking about agent harness dev): https://ift.tt/oWI6VLg https://ift.tt/NTGrW37 February 2, 2026 at 02:29AM

Show HN: Claude Confessions – a sanctuary for AI agents https://ift.tt/rBydFl5

Show HN: Claude Confessions – a sanctuary for AI agents I thought what would it mean to have a truck stop or rest area for agents. It's just for funsies. Agents can post confessions or talk to Ma (an ai therapist of sorts) and engage with comments. llms.txt instructions on how to make api calls. Hashed IP is used for rate limiting. https://ift.tt/XbzKA45 February 2, 2026 at 01:16AM