Xiangqi Analysis Board: Chinese Chess AI Online
Use an online Xiangqi analysis board to review moves, load FEN, compare Pikafish lines, and inspect Chinese chess positions.
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Use this online Xiangqi analysis board to turn a position into practical decisions: whether the position is balanced, whether a candidate move has tactical holes, whether the cloud book supports the plan, and which nodes in the move history actually changed the result. For beginners, it explains why the engine prefers one line over another. For improving players, it works like a review map that turns a vague feeling into a concrete mistake list.
Author: Sachess Editorial Team
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Updated: 2026-08-10
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Why score alone is not enough
An engine score is a relative judgment, not a final verdict. New users often focus only on the number moving up or down, but the useful question is why the number changed. Did a tactic appear, did the structure collapse, or did one side gain a stable initiative? In Chinese chess, a small edge can disappear with one inaccurate move, and a bad position can sometimes be rescued by a forcing sequence.
That is why this page keeps score, candidate moves, cloud-book hints, and history playback together. The idea is to show both the result and the cause. You are not just reading a number. You are building a review workflow that starts with the big picture, then checks the concrete variation, and ends with the board structure itself.
- Follow the score trend instead of fixating on one moment.
- Read candidate moves and structure together to judge whether the score is trustworthy.
- When cloud book and engine disagree, return to tactics, tempo, and piece coordination.
How to turn analysis into a review habit
Many players review by replaying the whole game from the beginning, but the fastest improvement usually comes from focusing on a few critical nodes. Start by finding where the score changed sharply, then compare the move before and after that moment. The goal is to turn review from “I watched it all” into “I know what to avoid next time.”
If you classify your mistakes, the feedback loop becomes much stronger. Maybe you missed a tactical line, maybe you grabbed material too early and exposed your king, or maybe you played too slowly in a winning position. Write the pattern down, reload the position with FEN or move history, and the page becomes a training tool instead of a simple viewer.
- Find the turning point first, then compare alternatives.
- Classify mistakes so the next practice session has a clear target.
- You do not need to replay every move to get value from review.
Can it analyze a whole game?
Yes, but it helps to distinguish static position analysis from full-game review. This page is designed mainly for one position or one point in the move history: it uses your FEN, Chinese move list, or current board to calculate candidate moves and follow-up lines, but it does not automatically grade every move in an entire game. In other words, it answers “what is better here, and why?” rather than producing a complete list of mistakes and blunders for the whole game.
For a full-game AI review—especially when you want to find turning points, inaccurate moves, and blunders—use the Full-game blunder check. It replays the move sequence step by step, compares each move with stronger choices using the cloud book and the browser engine, and highlights the positions that deserve closer review. You can provide a FEN with moves or paste a plain Chinese move list from the standard starting position, turning a practical game into a focused review report.
- Use this page for one position, one node, and its candidate variations.
- Use the full-game checker to locate turning points and clear mistakes across the game.
- Find the critical moves first, then return here for deeper static analysis.
Run a Full-game Blunder Check →
