Show HN: adamsreview – better multi-agent PR reviews for Claude Code https://ift.tt/MHScbfD

Show HN: adamsreview – better multi-agent PR reviews for Claude Code I built adamsreview, a Claude Code plugin that runs deeper, multi-stage PR reviews using parallel sub-agents, validation passes, persistent JSON state, and optional ensemble review via Codex CLI and PR bot comments. On my own PRs, it has been catching dramatically more real bugs than Claude’s built-in /review, /ultrareview, CodeRabbit, Greptile, and Codex’s built-in review, while producing fewer false positives. adamsreview is six Claude Code slash commands packaged as a plugin: review, codex-review, add, promote, walkthrough, and fix. I modeled it after the built-in /review command and extended it meaningfully. You can clear context between review stages because state is stored in JSON artifacts on disk, with built-in scripts for keeping it updated. The walkthrough command uses Claude’s AskUserQuestion feature to walk you through uncertain findings or items needing human review one by one. Then, the fix command dispatches per-fix-group agents and re-reviews the work with Opus, reverting any regressions before committing survivors. It runs against your regular Claude Code subscription (Max plan recommended), unlike /ultrareview, which charges against your Extra Usage pool. I would love feedback from Claude Code users, pro devs, and anyone with strong opinions about AI code reviews. Repo: https://ift.tt/W0ai3Iv Install: /plugin marketplace add adamjgmiller/adamsreview, /plugin install adamsreview@adamsreview https://ift.tt/W0ai3Iv May 11, 2026 at 07:36AM

Show HN: I trained a chess engine to play like humans https://ift.tt/DLHqNv4

Show HN: I trained a chess engine to play like humans I built 1e4.ai - a chess web app where you play against neural networks trained to mimic human Lichess players at specific Elo ranges. There's a separate model for each 100-point rating bucket from ~800 to 2200+, and the bots not only choose human-like moves but also burn clock time, play worse under time pressure, and blunder in human-like ways. Live demo: https://1e4.ai Code: https://ift.tt/Pef4nSL A few things that might be interesting: - Trained on almost a full year of Lichess blitz games, around 1B total games - Architecture is an a small (~9MM parameters) transformer-based network that takes the board, recent move history, the player's rating, and remaining clock time as input. Three separate models per rating bucket: move, clock-usage, and win probability. The clock model is what makes the bots feel humanish under time pressure rather than instant. Because the move model takes the clock as one input parameter, it also learns to blunder under time pressure like a human might. - Because the network is so tiny, no GPU is needed for inference - it runs easily on a local CPU - Downside of the tiny network is that it's a bit weak as you turn up the rating past around 1700. It can spot short tactics but not long multi-move combinations. - Initial training on a rented 8xH100 cluster, then fine-tunes on my local GPU for different rating ranges - Inspired by Maia-2 and DeepMind's "Grandmaster-Level Chess Without Search". On a held-out Lichess blitz benchmark, the it beats Maia-2 blitz on top-1 move prediction (56.7% vs 52.7%) and pretty substantially on win-probability calibration (Brier 0.176 vs 0.272). Numbers and code in https://ift.tt/Ro8ap75... - The data pipeline is C++ via nanobind, then training with Pytorch. Getting this right was actually the thing I spent the most time on. Pre-shuffling the dataset and then being able to read the shuffled dataset sequentially at training time kept the GPU utilization high. Without this it spent a huge percentage of time on I/O while the GPU sat idle. Happy to answer questions about the rating-conditioning, the clock model, or the data pipeline. May 11, 2026 at 04:01AM

Show HN: Hustler Bingo – a tiny bingo game about startup Twitter clichés https://ift.tt/GOmI4Ap

Show HN: Hustler Bingo – a tiny bingo game about startup Twitter clichés I built this after my brother started complaining that I got too much into brainrot culture. It's just for fun nothing serious, but was able to test vercel, tanstack start and convex without high stakes. Have fun! This is the game where lower score is goood for your mental health https://ift.tt/60HIz8J May 11, 2026 at 02:06AM

Show HN: Mosaic – arrange iOS icons by color using an evolutionary algorithm https://ift.tt/RxocrGH

Show HN: Mosaic – arrange iOS icons by color using an evolutionary algorithm It started out as a way for me to freshen up my C++ skills during COVID. But life got in the way and it was put on ice. Luckily, coding LLMs came to the rescue and allowed me to bring it to a point where I feel comfortable sharing it. https://ift.tt/HOcKJgS May 10, 2026 at 11:59PM

Show HN: Free OSS transcription app I made and found it's faster than wispr flow https://ift.tt/2h9d6Kn

Show HN: Free OSS transcription app I made and found it's faster than wispr flow title doesn't let nuance, ofc it's not the app that's faster but the way you can use it with Groq inference for example. https://mumbli.app/ May 10, 2026 at 03:07AM

Show HN: Create flashcards with Space CLI https://ift.tt/TqYs4ea

Show HN: Create flashcards with Space CLI Hey, I created seven years ago a flashcard app with a main focus on UX. In the last months I added offline-first mode and a CLI that allows Claude Code or Codex to create high quality flashcards for you. I use that to learn about pharma rules, technology, dancing, taxes and smart home. Never really did marketing, this not my specialty. Would love to know what you think https://ift.tt/cILu3Rd May 9, 2026 at 08:08PM

Show HN: tltv – Federation protocol for 24/7 TV channels https://ift.tt/KMVr6Ng

Show HN: tltv – Federation protocol for 24/7 TV channels I spent six years trying to build a tv channel server. rewrote it eight times. flask, fastapi, ffmpeg, gstreamer, named pipes. every version got more complicated and none of them worked right. turns out I was building the wrong thing. the thing I actually wanted was a protocol. so tltv is that. a channel is an ed25519 key pair. you sign your metadata with it. you serve hls video from wherever you want. your public key becomes a tltv:// address that anyone can tune into. relay nodes can re-serve your stream but they can't modify it. they verify signatures on everything. you can move servers and keep your channel because the key is the identity, not the hostname. nodes find each other through peer exchange. no central registry. the cli is probably the fastest way to see what I mean: curl -fsSL timelooptv.org/install | sh tltv keygen tltv server test --name "my channel" -k TV*.key that's a fully compliant origin server. pure go, generates smpte bars with audio, no ffmpeg. one binary, ~20mb of ram. there's also a full gstreamer-based server (cathode), a web viewer (phosphor), and bridge/relay servers in the cli. everything mit licensed. live demo at https://ift.tt/4h0wjr2 https://ift.tt/mlUdKiE https://timelooptv.org/ May 9, 2026 at 12:58AM

Show HN: The independent guide to agent orchestrators https://ift.tt/3KPuNrj

Show HN: The independent guide to agent orchestrators Hey HN! I built AgentMGMT.dev today to keep track of all those agent orchestration tools that keep popping up. I've tried a few and landed on Superset, which I'm extremely happy (and productive!) with - but I think this category of tools will be extremely important and interesting in the next couple years, so it's worth keeping an eye on all available tools and how they evolve. I will keep the site up-to-date, please help me by submitting new tools that are not yet in the list, or add any details that might help folks who are out shopping for their first/next agent orchestrator! https://agentmgmt.dev/ May 9, 2026 at 02:47AM

Show HN: GETadb.com – every GET request creates a DB https://ift.tt/Ywc5DHL

Show HN: GETadb.com – every GET request creates a DB Hey HN! We made GETadb.com, so it's easier to get agents to build you full stack apps. You don't need to give them any credentials. Just by loading a GET request, they get access to a database, a sync engine, and abstractions for auth, presence, and streams. To see what the agent sees, you can load https://getadb.com/new There's two fun things about how it's implemented: 1. If you curl the home page, it the agent content rather than human content. We do this by detecting the 'Sec-Fetch-Mode' header. It's not perfect, but gets the job done for Claude Code et al. 2. For an agent to spin up an app, they make _two_ fethes. (1) getadb.com/guide tells them to generate a uuid, and fetch (2) getadb.com/provision/. We did this, because just about half of the popular web-based app builders cache URLs globally, even if you return no-store headers. To get around this we just instruct the agent to generate unique URLs You may wonder: Why GET requests, rather than POST requests? It's because then you can build in surprising places. For example, we get meta.ai to build an app inside the artifact preview: https://ift.tt/T8BSKzl Under the hood, this is possible because the whole infra is mult-tenant from ground up. We already announced how that works on HN, but if you're curious here's the essay for it: https://ift.tt/U7RqN1z https://www.getadb.com/ May 8, 2026 at 09:47PM

Show HN: A lie detector game that reads your pulse through your phone camera https://ift.tt/rzFTDLm

Show HN: A lie detector game that reads your pulse through your phone camera https://kouh.me/tells May 8, 2026 at 11:31PM

Show HN: Kstack – Skill pack for monitoring/troubleshooting K8s in Claude Code https://ift.tt/GQauRgE

Show HN: Kstack – Skill pack for monitoring/troubleshooting K8s in Claude Code Hi All, Recently I've been using Claude Code a lot for debugging cluster issues and I realized I was performing similar tasks repeatedly so I decided to package them up into skills so I could call them up more easily (e.g. `/investigate`, `/audit-security`, `/audit-outdated`). I'm calling the skill pack "kstack" and the goal is to be able to monitor and troubleshoot K8s from within Claude Code. Here's the source: https://ift.tt/EuZHrF2 Here are the docs: https://kstack.sh/ If you have time I'd love to get some feedback on the project! Andres https://ift.tt/EuZHrF2 May 7, 2026 at 10:54AM

Show HN: Bilig – a headless spreadsheet engine for Node services and agents https://ift.tt/qb3OXxh

Show HN: Bilig – a headless spreadsheet engine for Node services and agents https://ift.tt/pKHIE3k May 7, 2026 at 11:46PM

Show HN: PHP-fts – Full-text search engine in pure PHP, no extensions https://ift.tt/wgSBiJP

Show HN: PHP-fts – Full-text search engine in pure PHP, no extensions https://ift.tt/WpBoNzV May 7, 2026 at 01:58AM

Show HN: Mac Juice Monitor – Bluetooth battery levels in the macOS menu bar https://ift.tt/oIpdL1j

Show HN: Mac Juice Monitor – Bluetooth battery levels in the macOS menu bar https://ift.tt/DI4AlBe May 7, 2026 at 12:58AM

Show HN: Tuiql – A keyboard-driven SQL database client in the terminal https://ift.tt/cSUDidw

Show HN: Tuiql – A keyboard-driven SQL database client in the terminal Every time I needed to inspect a database, I either had to wait for a bloated GUI client to chew through my RAM or struggle through psql, which isn’t great for actually visualizing data. So I built a TUI database client focused on one thing: connecting fast and letting you browse tables as datagrids and rows as JSON, with near-instant startup and vim-style keyboard navigation. Still in the early days but already handles most of what you would expect from an SQL database client. https://ift.tt/NAucKVg May 6, 2026 at 11:20PM

Show HN: Better Design – 28 Shadcn design systems (OSS, MCP: Cursor/Claude Code) https://ift.tt/YtrNlOV

Show HN: Better Design – 28 Shadcn design systems (OSS, MCP: Cursor/Claude Code) https://ift.tt/c31egGw May 6, 2026 at 05:01AM

Show HN: New Benchmark from SWE-bench team is 0% solved https://ift.tt/n8cVjgy

Show HN: New Benchmark from SWE-bench team is 0% solved https://ift.tt/gXPuHD3 May 5, 2026 at 08:40PM

Show HN: Explore color palettes inspired by 3000 master painter artworks https://ift.tt/L8HGJ6e

Show HN: Explore color palettes inspired by 3000 master painter artworks I built PaletteInspiration.com, a browsable archive of color palettes pulled from artworks by 3,000+ master painters (Monet, Vermeer, Raphael, Van Gogh). Why I built it: every color palette generator I tried converged on the same five muted pastels. Painters spent centuries figuring out color and we mostly ignore that body of work when picking colors for digital design. Please share your feedback on the Color Harmony Explorer - drag the wheel to any color and it shows which hues master painters historically paired with it (not only standard complementary, analogous, triadic, etc.) It is solely based on co-occurrence across thousands of real paintings. Not algorithmic color theory rules - actual empirical pairings. No signup, no paywall, no email capture. Just curious what people think. https://ift.tt/aZkWH0K May 5, 2026 at 11:43PM

Show HN: I indexed 8,643 BSides talks across 227 chapters and 6 continents https://ift.tt/tCiKcEF

Show HN: I indexed 8,643 BSides talks across 227 chapters and 6 continents Hi HN, I'm Roland, and for the past few weeks, I've been building AllBSides — a directory of every BSides conference talk uploaded to YouTube. As of today, 8,643 talks from 5,927 speakers across 227 chapters in 68 countries. Combined runtime is 280 days. The transcripts come to about 60 million words. The archive came together in stages: 1. Manually map every BSides chapter's YouTube channel 2. Pull every video and transcript from Supabase 3. Run each transcript through Haiku for tag extraction (tools, topics, difficulty, team, talk style, research method, and much more) 4. Run results through Sonnet for categorization and dedup 5. Final pass goes through Opus for verification 6. Do a manual verification - at one time, the pipeline showed over 16k AI suggestions for manual verification. Today, most are resolved. Total LLM cost so far: about €200. The whole pipeline is rebuildable from scratch. Each talk gets its own page with embedded video, full transcript, speakers, tags, and "related talks." Each tool/framework/protocol/standard mentioned across the corpus gets its own page (3,968 distinct technologies tracked). Some interesting facts I gathered while building it: -(A) The site is currently 94% bot traffic. Of that, about 80,000 hits/month are AI training crawlers (ClaudeBot, GPTBot, meta-externalagent). Within 7 days of the talks archive going live, all major AI labs had ingested the entire corpus. The discovery cascade was startling to watch in real time. -(B) The taxonomy work was the hardest part. Distinguishing "tools" from "frameworks" from "protocols" from "concepts" sounds easy until you have 5,000 ambiguous extracted entities. The 3-tier LLM pipeline helped a lot — Haiku alone was too noisy, Opus alone was too expensive. -(C) Top tools mentioned: Wireshark (343), PowerShell (342), Metasploit (332), Burp Suite (322), GitHub (296), VirusTotal (273), Docker (253), Splunk (251), Nmap (247), MITRE ATT&CK (237). The list reflects what BSides talks actually discuss, not what vendors curate. -(D) May is the peak BSides month — 29 events, 17% of all events with dates. -(E) The top 1% of talks (86 videos by view count) account for 51% of all viewership. The other 99% are deeply niche, often the only video record of a specific technique. The stack is intentionally lean: Go, SQLite, vanilla JavaScript, BunnyCDN. Static rendering at build time. No frameworks, no client-side state. The site costs about €50/month to run. The data behind this post and much more can be found in the site footer, under the link "stats". Happy to answer questions about the data pipeline, the taxonomy decisions, or what the AI crawler patterns looked like as the archive went live. Feedback on what to build next is genuinely welcome — I'm a solo dev figuring this out as I go. — Roland (parkado) https://allbsides.com/ May 5, 2026 at 03:40AM

Show HN: NeuralScript – A pure-Rust AOT compiler https://ift.tt/UXna7E5

Show HN: NeuralScript – A pure-Rust AOT compiler https://ift.tt/L5UK1Ho May 5, 2026 at 01:36AM

Show HN: nfsdiag - a NFS diagnostic application https://ift.tt/4McOjar

Show HN: nfsdiag - a NFS diagnostic application https://ift.tt/sctymXx May 2, 2026 at 06:18PM