FireChess – Find the chess mistakes you keep repeating

Name: FireChess – Find the chess mistakes you keep repeating
Availability: InStock
Author: leonfresh

by leonfresh·Feb 25, 2026·1 point·5 comments

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AI Analysis

●●●BangerSolve My ProblemSlick

Pattern-matches your actual blunders across 300+ games, not just one-game analysis.

Strengths

•Solves a genuine pain point that Lichess/Chess.com don't: cross-game pattern detection at scale.
•Browser-based Stockfish (WASM) means zero server dependency and instant offline analysis.
•Drill mode reinforces the fix by forcing repetition of YOUR mistakes, not generic puzzles.

Weaknesses

•Freemium paywall ($5/mo for depth 12→24 and 300→5k games) might frustrate casual users.
•Chess improvement tools are competitive space; market fit depends on network effects and word-of-mouth.

Post Description

Hey HN, I'm a solo dev and I built FireChess because I kept losing to the same openings without realizing it.

Lichess and Chess.com both have great post-game analysis, but they review one game at a time. I wanted something that looks across hundreds of games at once and says: "You've played this position 14 times and lose 70% of the time — here's what to play instead."

What it does:

- Scans your Lichess or Chess.com games (up to 5,000)

- Finds repeating opening leaks — positions where you consistently pick the wrong move

- Cross-references the Lichess opening explorer to tell you how popular/sound each line is

- Detects missed tactics and endgame mistakes across all your games

- Runs Stockfish 18 (WASM) entirely in your browser — no server-side engine needed

- Includes a drill mode so you can practice the correct moves until they stick

- The free tier gives you 300 games at depth 12. Pro ($5/mo) unlocks 5,000 games, higher depth, and full tactics/endgame scanning.

Tech stack: Next.js, Stockfish 18 WASM, Lichess Explorer API, Stripe. All engine analysis runs client-side in your browser — game data is only stored server-side if you save a report.

I have a short trailer here: https://www.youtube.com/watch?v=m7oUz7t8uZA

Would love feedback on the analysis quality or anything else. Happy to answer questions about the Stockfish WASM integration or the pattern-detection approach.