Say you want a few knight forks from your own games to study. You remember the idea, but you have no idea which games to open. I wanted to see if I could type “knight fork” and get a shortlist of boards worth looking at.

I tested that on 13,338 positions from 150 of Magnus's Lichess blitz games. I embedded each position and each search phrase as a 512-dimensional vector and ranked the positions by how close they were to the phrase. Then I checked the top 30 for each query with python-chess rules over the next 8 plies of the game and with Stockfish.

• “back rank mate” returned all 3 mates played along the king's own back rank at ranks 2, 8 and 10. Six of the other seven hits were mates too, including 43...Ra3# down the a-file. I counted rook or queen mates along the back rank. None had the classic pawn wall.

• “knight fork” found 3 forks that win material, at ranks 3, 7 and 21.

• “queen sacrifice” put a bishop sac first (16.Bxg6 fxg6 17.Qxg6+). The only queen sac I verified in the top 30 was at rank 25 (18...Qxd4! 19.cxd4 Nf3+). My guess is that a sacrifice is harder to pick up from a single position because the payoff comes later.

I also tried using Knight, our chess-tuned language model, as a yes/no judge. It answered 66 of 90 requests. Only 4 of its 14 yeses checked out, and it said no to 18...Qxd4. I'd use embeddings to get the shortlist, then verify it with python-chess and Stockfish.

Embedding all 13,338 positions cost 53 cents, once. Stockfish ran locally.

I work on ChessDrive, which makes both the embedding model and Knight. Happy to share the rule checker in a comment.

I'm a developer and an average player (1100 elo on chess.com).

The "what" is easy: the eval bar jumps, the engine shows a move. The

"why" is where I get stuck. If it's a tactic, I can usually find it.

But often the line is long, nothing gets won, and the advantage is

purely positional. I play through it and learn nothing.

So I'm asking the people who can see the why:

1. When the eval jumps and there's no tactic, how do you work out the

   positional reason?

2. What do you point out first when explaining a position to a weaker

   player?

3. What explanations sound right but teach the wrong lesson?

4. If you've tried AI chess coaches or explainers, what did they get

   wrong?

Why I'm asking: I'm considering building a small analysis tool for

myself that explains the why. AI explanations of chess are wrong about

1 time in 10 even with engine access, and a wrong why is worse than

none. So mine would only say what it can prove with the engine, and

otherwise admit "no simple idea, here's the line." Your answers decide

what it should even try to say.

Nothing to sell, no product exists. Blunt answers welcome.

Hi everyone,

I've developed an iOS chess app that lets users play against the Stockfish 19 engine directly on their iPhone or iPad.

The idea was to provide a simple chess-playing experience without requiring an internet connection or an account.

Some of its features include:

• Stockfish 19 engine.

• Offline gameplay.

• Option to play as White or Black.

• Simple chess interface.

• No account required.

I'd appreciate feedback from people familiar with computer chess.

I'm particularly interested in hearing how the playing experience compares with other Stockfish-based iOS applications and what features you think are missing.

App Store: https://apps.apple.com/us/app/stockfish-19-chess-engine/id6813605429

♟️ Learn Chess with MrQafur!

Want to improve your chess skills?

I'm a chess player from Azerbaijan with an official FIDE rating and 2nd sports category.

I offer online chess lessons for beginners and intermediate players.

🌍 Online lessons 📚 Personalized training ♟️ Game analysis 💻 Interactive chess website

Affordable monthly plans!

Contact me to learn more.

MrQafur Chess

I'm a solo indie game developer that has been working on this project for the last year. I'm a big fan of RTS games and Chess. I used to play a game called Kung-fu chess and thought I could take that idea to another level. I started losing my vision a few years ago and wanted to create a game that I could play with limited visibility. It's tough for me to play games like starcraft or warcraft 2 anymore so I wanted something that doesn't require switching screens around and so you'll see a bit of warcraft-style inspiration in the factions here.

The game is in 31 languages, there's a bit of trash talk at the end of matches, I got that inspiration from street fighter 2, the cheesy end of match trash talk lol. Anyway, matches last minutes to seconds so this is a very quick game to play and I'm hoping it might appeal to a younger crowd to rope them into chess, which is also playable in my client. There are achievements, level progression a ranked ELO ladder system, vs AI with various difficulties and an authoritative Multiplayer server and this is all free to play via the steam demo @ https://store.steampowered.com/app/4638730/Pillar_Of_War/, or the official website @ https://www.pillarofwar.com as a web version.

I've added various options for visibility which, along with the game itself, desperately looking for feedback on. There's a discord server linked on my website you can join. Development-wise, this project started out in rust and I decided to switch to Go/Ebitengine exclusively where it's a 2d game with fairly simple graphics as well as a heavy emphasis on multiplayer. I've definitely relied on AI fairly heavily in development especially with code optimization, language support and network security and image editing/assets. My plan is to push this game and see if I can foster a community around it. I am currently working on a fairly robust solo campaign which I plan on launching into early access early next year. Currently there's a tutorial and demo of where I plan on going with that, although I have a lot of ideas I am working through but I am desperately looking to get some feedback on the multiplayer aspect where this game really was designed for.

Anyway - I am looking forward to any feedback! Thank you

I recently launched a new variant called Chess Kabaddi, and after some thorough testing, it is officially approved and live on the Google Play Store for both Android Mobile and Android TV.

If you are tired of the slow, isolated grind of standard 1v1 internet chess, this strips it down and replaces it with the aggressive, hit-and-run team mechanics of the physical sport Kabaddi. Your pieces act as raiders, striking into enemy territory and retreating before they get tackled.

The Free Tier (Perfect for Family Game Night) The game is built entirely around peer-to-peer Local LAN multiplayer, meaning zero server lag and no active internet connection required.

The base game is completely free and allows 4 people to play in a 2v2 squad format. Because it runs locally over your home Wi-Fi, it is the perfect combination for a family game night—two parents and two kids forming teams and battling it out on their own devices.

Scaling up for clubs If you want to host a massive tournament or have a larger chess club, there is a single one-time in-app purchase that allows you to scale the lobbies up to massive 3v3, 5v5, 7v7, or even 10v10 team battles.

You can download it on the Play Store now by searching for "Chess Kabaddi". I would love to hear what this community thinks of the raiding mechanics, especially if you get a chance to test out the 2v2 mode with your family or friends this weekend!

needed a board for my chess site. chessground is gpl so that was out (closed source site), and i didn't want to pull in react just for a board. ended up writing one.

what it does differently: moving a piece = set a transform + a css transition. compositor handles it, no rAF loop, zero js per frame. idle board = nothing running.

core is 5.2kb gzip, no deps. arrows / promotion / premove / a11y are separate imports, ~1kb each. react wrapper is 0.5kb. no chess logic in it, use chess.js.

bench vs chessground and react-chessboard (headless chromium, desktop, same script for all):

size 5.2kb / 11.9kb / 21.5kb + react

dom nodes 53 / 68 / 515

js per move 0.06ms / 2.8ms / 2.8ms

frames painted during a slide with the main thread blocked: 51 / 0 / 51

so react-chessboard is just as smooth, it's just heavier. it also beats me on compositing time. numbers and method are in the repo, including where i lose. i benchmarked after building it, not before.

1 week old, 0.1.x, api might change. running in prod on my site.

https://kibitzo.github.io/lightsquare/ (demo, has a bench page for your phone)

https://github.com/kibitzo/lightsquare

feedback welcome, esp. what's missing for you to use it

I built SignalChess to let players revisit suitable mistakes from their analyzed Chess.com and Lichess games and try to find the better move.

I'm looking for feedback on position selection. Say an engine flags two moves with a similar evaluation drop: one misses a short tactic, and the other leads to a position that's only worse after a long quiet line. I'd expect those to make very different exercises.

What would you use alongside evaluation swing to filter candidates? Would you look at the gap between the best and second-best moves, the length of the forcing line, or something else? How would you handle two moves that both solve the same problem?

For context, here's the app: https://signalchess.com

Hi all, just wanted to share this little side project I've been working on called chessvigil.com!

The idea is pretty simple: you enter your chesscom / lichess username, and the tool looks for blunders in recent games + turns them into puzzles. It's completely free, no sign-up, no ads, and you can do as many puzzles as you like. Works well on mobile too!

Would love some feedback! Thanks in advance! :)

Hi r/ComputerChess. I'm a ~1500-2000 player who got fed up one day and became a dev. Spoiler: not the healthiest career move, but here we are.
My problem was this: I'd do puzzles and solve them... but they never felt like mine. They were hard ideas I never really processed. I'd get to the solution by brute force: calculate, calculate, calculate, "oh, that was it," next. Zero intuition. My brain was like an employee signing a document without reading it.
What I wanted was what sometimes happens when I "dream positions": suddenly the solution just reveals itself, with no calculation. I wanted that to happen while awake, and more often.
So I built an algorithm that learns combinations. It takes a pattern and searches through more than 4 million puzzles for that same combination in a different position. The idea is to stop memorizing positions and start recognizing the pattern even when it shows up in disguise (same mate, different haircut).
Then I turned it into an app for Android and iOS, with a vertical feed of puzzles. Yes, I know: "another chess app." It has a subscription, because servers don't run on good intentions or on my lost blitz games. I won't mention pricing here so this doesn't read like an ad.
It's been out for a week and the reception has been good, but those are numbers, and numbers don't have a feel. What I really want to know is how it feels. So I'm asking you to tear it apart:
Do the puzzles feel well chosen? Or do they feel like they came from another planet, or like an enemy picked them?
Do you notice the pattern coming back in a different position, or does it feel random?
What would you remove, and what's missing?
To give your feedback some context, tell me your approximate rating and whether the puzzles fit your level or not. Brutal honesty welcome, I've been humiliated better in blitz.
I'm not posting a direct link because I haven't talked to the mods yet. If they give me the green light, I'll add it in an edit. Meanwhile, if you want to try it, ask me by DM or in the comments.
TL;DR: ~1500-2000 player turned dev because puzzles felt like someone else's. I built an app (Android/iOS) whose algorithm searches 4M+ puzzles for the same pattern in a different position. I want to know if the puzzles feel well chosen. Comment your rating and whether they fit.

Hello everyone,

My friend created this website which allows you to work on your weaknesses and have a personalized training program.

How does it work?

- Import your games from Lichess or Chess.com.

- Analyze your games with Stockfish to identify missed tactical opportunities.

- Turn your mistakes into exercises to replay positions and learn to recognize good opportunities.

- Identify your tactical weaknesses using the classification of different patterns.

- Track your progress with statistics dedicated to your training.

Feel free to provide feedback or criticism.

Thank you all.

https://chess-tactics-manager.fr/

https://store.steampowered.com/app/5456450/Velikopolsky_Chess/

I often analyze champions games, check with first or second Stockfish line, and it says I play too quiet. It always shows that best thing is to make pawn break on queenside, and sometimes on kingside. I understand this is my problem, that I don't want to go in aggressive and interesting lines, but still. Why his playing style really changed?

I have created several tournament pairing systems in browser-based JavaScript. For example, my Berger Tournament Manager can handle four Berger tournaments simultaneously. If players withdraw, a tournament director can convert any of them into a Swiss tournament, thereby reducing the problem of excessive byes. That seems to me a genuinely useful feature.

Another example is my Rating-Budget Tournament System, which introduces a new concept, "rating budget," to generate pairings in advance for large groups of players. In addition, I have implemented the FIDE-approved Dutch, Lim, Dubov, and Burstein pairing systems. These implementations, however, have not yet been formally verified.

All of my online pairing programs are listed here: Chess Pairings: A Review of Monrad, Swiss, and Berger

You may also wish to explore my collection of Zillions of Games chess-variant programs: Chess Variants.

Setup: armies of exactly 39 points + a king on the first three ranks. Two populations (60 White, 60 Black), 40 generations, crossover by files (repaired back to 39 points and one king), mutation, 10% newcomers per generation.

Fitness: each army plays 20 matchups (10 vs the other population, 10 vs a fixed baseline of past, organised, random and hand-made armies). A matchup is one Fairy-Stockfish eval of the starting position at depth 18; ±2 pawns = a win, anything closer = a draw. Score = win rate. I checked the shortcut with real games every 10 generations. The top armies drew a lot more in real games than the eval suggests, but in 36 real games Black won only once.

Both populations converged on bishop-heavy armies (12B + 3P vs 11B + N + 3P). A separate double-oracle (PSRO-style) run, with a different payoff, also drifted to 1 queen + 9 bishops + 3 pawns.

Happy to answer questions about the setup or share details. Video link

I bought a DGT Pegasus for a simple reason. A friend and I play regularly over the board, and I wanted to record our games so we could go through them afterwards and get better at our openings.

When the board arrived, I had another idea. Opening trainers like Chessbook, Chessable and Lichess studies all work on a screen. But in a real game I'm looking at real pieces, and that's where I forget my lines. So why not drill my repertoire on the physical board instead?

I'm not a professional developer. I've been building the app together with Claude (Anthropic's AI), and it's now at the point where other people can use it:

👉 https://blekknajt.github.io/pegasus-repertuar/ (source: https://github.com/blekknajt/pegasus-repertuar)

What it does

• Trains your repertoire on the real board. It connects to the Pegasus over Web Bluetooth. The board's LEDs show your opponent's move, you play it on the board, then you make your reply. The sensors check your move automatically.

• Spaced repetition (SRS). You learn new moves, then review them at growing intervals, like Anki or Chessbook. It tracks statistics and shows your weakest moves.

• Import from PGN (with variations) or a Lichess study. There's also a built-in repertoire editor with comments.

• Focuses. You can drill just one part of your repertoire from a chosen position, for example only the accepted Smith-Morra Gambit. Your progress there counts for the whole repertoire.

• Analysis while you train. You get Stockfish (Lichess cloud eval or a local engine) plus the Lichess and Masters opening databases. You can try moves on the screen or on the board without affecting your reviews.

• Pause after a line. Set it to never, after a mistake, or always, so you can stop and work out what went wrong before moving on.

• Works without the board too. You can make your moves on the screen.

• Offline-first PWA. Your data stays in your browser (IndexedDB) and you can back it up to a file. Engine evals and database results are cached, so a position you've seen once also works offline.

• 5 languages: English, Polish, French, German, Russian.

It works best in Chrome on Android. I use it on a tablet next to the board. Web Bluetooth isn't supported on iOS Safari, but the screen-only mode works anywhere.

Why I'm posting

It's a hobby project, it's free, and it has no accounts and no tracking. I'd really like feedback:

• Pegasus owners: does it connect and read your board reliably?

• Other DGT boards: would support for other boards (Smart Board, e-Board, Centaur) be useful to you?

• Training ideas: What's missing from your opening practice? Features you love in Chessbook/Chessable that should be here? Anything that annoys you about drilling on a screen?

• Bugs: please report them here or as a GitHub issue.

Any suggestions, ideas or criticism are welcome. Thanks for reading! ♟️