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

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/ASLN36V Install: /plugin marketplace add adamjgmiller/adamsreview, /plugin install adamsreview@adamsreview https://ift.tt/ASLN36V May 11, 2026 at 09:06AM

Show HN: I trained a chess engine to play like humans https://ift.tt/hnxCAP2

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/OZyWap6 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/5LDTng4... - 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 05:31AM

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

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/adPviwh May 11, 2026 at 03:36AM

Show HN: Mosaic – arrange iOS icons by color using an evolutionary algorithm https://ift.tt/BKShLY6

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/yD1hPWf May 11, 2026 at 01:29AM

Show HN: Create flashcards with Space CLI https://ift.tt/O5D8pY1

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/f38SBoR May 9, 2026 at 09:38PM

Show HN: A search engine for deleted YouTube videos (1.5B+ indexed since 2005) https://ift.tt/eMDGYLy

Show HN: A search engine for deleted YouTube videos (1.5B+ indexed since 2005) https://ift.tt/97yhYsL May 9, 2026 at 10:09PM

Show HN: A lie detector game that reads your pulse through your phone camera https://ift.tt/NkAD6na

Show HN: A lie detector game that reads your pulse through your phone camera https://kouh.me/tells May 9, 2026 at 01:01AM

Show HN: We built a tool that generates 3D objects with editable, separate parts https://ift.tt/dcLFfby

Show HN: We built a tool that generates 3D objects with editable, separate parts https://nova3d.xyz/ May 9, 2026 at 12:11AM

Show HN: UltraCompress – first mathematically lossless 5-bit LLM compression https://ift.tt/0aWUEek

Show HN: UltraCompress – first mathematically lossless 5-bit LLM compression https://ift.tt/EzT5nxD May 8, 2026 at 11:49PM

Show HN: Rejected by YC https://ift.tt/yxc6FEI

Show HN: Rejected by YC https://rejectedbyyc-ten.vercel.app/ May 8, 2026 at 11:31PM

Show HN: Kstack – Skill pack for monitoring/troubleshooting K8s in Claude Code https://ift.tt/jmRno6b

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/1bhQySz 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/1bhQySz May 7, 2026 at 12:24PM

Show HN: Bilig – a headless spreadsheet engine for Node services and agents https://ift.tt/b7srBpO

Show HN: Bilig – a headless spreadsheet engine for Node services and agents https://ift.tt/AzkoTsL May 8, 2026 at 01:16AM

Show HN: Stage CLI – a tool to make reading your AI generated changes easier https://ift.tt/bqIYwi9

Show HN: Stage CLI – a tool to make reading your AI generated changes easier Hey HN! We're Charles and Dean. A few weeks ago we posted about Stage, a code review tool that guides you through reading a PR step by step - https://ift.tt/lABqsyt . We got a lot of great feedback but also heard from many people that they wanted to have the chapters experience even before opening a PR… so we built the Stage CLI as the local, open-source version that anyone can try. Here’s a quick demo video: https://ift.tt/icUMYKh It works with any coding agent of your choice. The skill instructs the agent to read your current branch’s changes, break them down into separate logical chapters, and open them in a local browser. We’ve found that reading changes this way is a lot easier for us than reading them in an IDE or other similar CLI tools, which present diffs to you in repository tree order. You can see a few examples of what it feels like here: https://ift.tt/sLCJH2l . Try it out and let us know what you think! Would love to hear any feedback :) https://ift.tt/GcqIVY0 May 7, 2026 at 10:38PM