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llm-chess-mcp

by prepaser

llm-chess-mcp

一个 MCP 国际象棋运行时,让 LLM 能够对弈、分析并根据自身强度调整水平,而无需将每一步决策都外包给引擎。

它不会返回单一最佳着法,而是暴露客观强度(Stockfish)、人类着法概率(Maia3)和真实对局统计(Lichess),让 LLM 自行决定其希望如何行棋。LLM 负责策略与判断;MCP 服务器负责所有计算。

引擎

引擎

角色

运行时

Stockfish 18(WASM)

客观评估、最佳着法、多变化(multipv)

进程内(npm stockfish)

Maia3 5M(ONNX)

基于 Elo 的人类风格行棋概率

进程内(onnxruntime-node)

Lichess explorer

真实人类对局统计

HTTP(需要令牌)

所有内容都在 Node 进程内运行——部署时无需外部引擎进程或 Python 运行时。发布的包已将 Maia3 5M 模型打包;除非单独提供 ONNX 文件,否则其他导出变体不是运行时选项。

Related MCP server: Chess MCP

安装

需要 Node.js 20 或更高版本。

无需安装——直接用 npx 运行:

npx -y llm-chess-mcp

Maia3 模型已随包提供,因此无需安装 Python、torch 或引擎二进制文件。npx 首次运行时获取包并缓存。

若要永久安装,改为:

npm install -g llm-chess-mcp

从源码构建

pnpm install
pnpm build
pnpm test

pnpm test:unit 运行单元测试套件。pnpm test:e2e 先构建,然后运行 MCP 传输测试。pnpm check 运行完整的本地门禁;发布前请使用 pnpm release:check。

维护者

架构 描述了运行时与服务边界。

本地质量命令:

pnpm typecheck
pnpm test:coverage
pnpm contract:check
pnpm check
pnpm test:package

pnpm test:stress 运行短时真实引擎并发检查。pnpm test:live 仅在设置了 LICHESS_TOKEN 时查询 Lichess;否则跳过,不发起网络请求。

将 Maia3 导出为 ONNX(仅构建时)

此步骤需要一次 Python + PyTorch。它会下载 Maia3 检查点,验证重构实现与原始实现是否一致,并导出 models/maia3-5m.onnx。

uv venv .venv-maia3 --python 3.13
uv pip install --python .venv-maia3/bin/python -r scripts/requirements.txt
uv pip install --python .venv-maia3/bin/python "maia3 @ git+https://github.com/CSSLab/maia3.git@1e13597c42d4858b7cfd7cfdae01e297263364b2"
pnpm export:maia3            # -> models/maia3-5m.onnx

生成的 .onnx 会被提交/打包;最终用户永远不需要 Python 或 torch。

Lichess 令牌(可选)

开局棋谱浏览器现在需要认证。在 https://lichess.org/account/oauth/token/create 生成个人访问令牌,并在 .env 中设置:

cp .env.example .env
# set LICHESS_TOKEN=...

没有令牌时,opening_explorer 返回禁用提示;其他所有工具均正常工作。

棋谱浏览器过滤条件严格。速度选项为 ultraBullet、bullet、blitz、rapid、classical 和 correspondence;评级区间为 0、1000、1200、1400、1600、1800、2000、2200 和 2500。masters 不接受任何过滤条件。无效过滤条件会在本地失败。瞬时故障(网络、超时、429 和 5xx)会在 12 秒总预算内重试一次;无效请求和其他 4xx 响应不重试。

在 MCP 客户端中配置

opencode

添加到 opencode.json(项目)或 ~/.config/opencode/opencode.json(全局):

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "llm-chess-mcp": {
      "type": "local",
      "command": ["npx", "-y", "llm-chess-mcp"],
      "enabled": true,
      "environment": {
        "LICHESS_TOKEN": "your-token"
      }
    }
  }
}

Claude Code

添加到 .mcp.json(项目)或 ~/.claude.json(全局),或运行:

claude mcp add llm-chess-mcp -- npx -y llm-chess-mcp
{
  "mcpServers": {
    "llm-chess-mcp": {
      "command": "npx",
      "args": ["-y", "llm-chess-mcp"],
      "env": {
        "LICHESS_TOKEN": "your-token"
      }
    }
  }
}

Codex CLI

添加到 ~/.codex/config.toml:

[mcp_servers.llm-chess-mcp]
command = "npx"
args = ["-y", "llm-chess-mcp"]

[mcp_servers.llm-chess-mcp.env]
LICHESS_TOKEN = "your-token"

或通过 CLI:

codex mcp add llm-chess-mcp --command npx --args -y llm-chess-mcp --env LICHESS_TOKEN=your-token

工具

工具

描述

create_game

创建一局棋(可选从 FEN 开始),返回 game_id

delete_game

删除一局棋并释放其会话

game_state

权威状态:FEN、轮到谁走、修订号、将军/绝杀/和棋标志、历史、最后一步、易位(可选的 ASCII 图)

game_play_move

走一步棋(SAN 或 UCI)——唯一修改性的工具,带过时位置防护

game_legal_moves

所有合法着法及元数据

game_pgn

将棋局导出为 PGN

game_import_pgn

将 PGN 导入为新棋局

position_analyze

Stockfish 多变化行(cp/mate/WDL + PV)、analysis_level 预设

human_move_distribution

Maia3 在目标 Elo 下的人类行棋概率

move_evaluate

评估一个或多个着法 + cpLoss + 分类

move_candidates

主工具:统一候选着法(客观 + 人类 + 开局)

move_candidates_by_intent

便捷层:按战略意图排序的候选着法

opening_explorer

Lichess 人类对局统计

结果格式

structuredContent 是标准的成功结果。处理程序级失败会设置 isError 并提供 structuredContent.error。输入模式失败由 MCP SDK 在处理程序之前生成,并使用其标准的 isError 文本结果,不含 structuredContent。否则,content 只是简短的人类可读摘要,不得解析为数据。

分数约定

  • Stockfish 分数为当前行动方视角:正 cp = 当前行动方更优;mate N = 当前行动方在 N 步内将死。wdl 是当前行动方的胜/和/负千分比 [win, draw, loss]。

  • move_candidates 给出 moverCp(行棋者视角——对选择着法的玩家越高越好)和 whiteCp(固定白方视角),因此符号永远不会翻转。

  • move_evaluate 报告从行棋者视角的分数,加上 cpLoss(相对最佳着法丢失的厘兵)和一个分类: best / excellent / good / inaccuracy / mistake / blunder。

  • maia3Prob 是人类相似度,不是着法质量。高概率的着法在客观上也可能很糟糕。

候选结构

move_candidates 返回每个候选着法的三个独立维度:

{
  "uci": "g1f3",
  "san": "Nf3",
  "objective": { "rank": 1, "moverCp": 55, "whiteCp": 55, "cpLoss": 0, "moverMate": null, "wdl": [153, 844, 3] },
  "human": { "maia3Prob": 0.62, "selfElo": 1500, "opponentElo": 1500 },
  "opening": { "status": "available", "games": 18421, "frequency": 0.31 }
}
  • objective —— Stockfish:引擎强度,绝不与人类相似度混淆。 moverCp 是从行棋者视角(更高 = 对选择者更好)。

  • human —— Maia3 在目标 Elo 下的条件概率。

  • opening —— Lichess 经验频率(与 Maia3 不同的信号)。

opening.status 为 available(可用)、no_data(API 正常但该局面无对局)、unavailable(超时/429/401)或 disabled(无令牌)。Stockfish + Maia3 结果始终返回,不论如何。

move_candidates 还返回 moveSensitivity,描述评估在引擎顶级行之间的变化剧烈程度:

{ "moveSensitivity": { "level": "high", "topMoveSpreadCp": 245 } }

level 为 low(跨度小于 80cp)、medium(80–200cp)或 high(≥200cp)。高灵敏度意味着在合理解法之间做出选择可能显著改变评估——这有助于决定是放松还是精确行棋。

分析级别

Stockfish 工具接受 analysis_level 预设,而非原始 UCI 旋钮:

级别

深度

MultiPV

fast

8

5

normal

15

8

deep

22

10

高级使用仍可通过显式 depth/multipv 覆盖可用。

过时位置防护

每次状态读取都会返回 revision。game_play_move 要求 expected_revision;如果自上次读取后棋局已前进,则移动会被拒绝:

{ "error": { "code": "STALE_POSITION", "message": "position changed: expected revision 2, current 3" } }

运行时限制

  • 最多保留 1,000 个对局会话;闲置会话一小时后过期。

  • move_evaluate 每次调用最多接受 10 个着法。

  • 导入的 PGN 限制为 1 MiB 和 4,096 层(ply)。

  • Stockfish 最多接受 32 个活动或排队中的分析。

意图

move_candidates_by_intent 按所选意图对候选着法排序。它是 move_candidates 的便捷层;下面的固定阈值是启发式默认值,并非权威来源:

意图

含义

best

最强引擎着法

strong

引擎强但人类可能下的着法

natural

在目标 Elo 下最具人类典型性的着法

balanced

强度与人类相似度的混合

ease_off

人类可能下的着法,适度减少优势但不改变预期结果

give_chance

人类可能下的不精确着法,显著提升对手的机会

此工具对候选着法排序但不会选择一步棋。请使用返回的信号和对话上下文做出最终决定——不要机械地将用户水平映射到某个意图。

示例流程

正常的对弈循环是三次调用:

  1. create_game → game_id

  2. move_candidates → 选择一步棋

  3. game_play_move(带 expected_revision)→ 提交它

仅在需要时深入:

  • position_analyze —— 客观最佳行棋路线

  • human_move_distribution —— 某个 Elo 的真人会下什么

  • opening_explorer —— 真实对局统计

  • move_evaluate —— 评估某一具体着法(或比较多个)

Maia3 ONNX 验证

导出的 ONNX 模型在固定局面和 Elo 组合上与上游 Maia3 实现进行回归测试:

.venv-maia3/bin/python scripts/verify_maia3.py --model 5m

它检查 top-1/top-k 着法一致性和最大概率误差,以检测导出/运行时回归。随包的 maia3-5m.onnx 通过测试,top-1 和 top-5 一致性为 100%,最大概率误差 < 1e-4。

包验证

包工件在本地验证;本项目有意不设托管 CI 工作流。

运行 pnpm check 进行确定性离线门禁。使用 pnpm test:package 打包项目,在干净的临时目录中安装 tarball,并针对真实的 Stockfish 和 Maia 运行时运行已安装的 llm-chess-mcp 二进制文件。pnpm release:check 同时运行两个检查,并加上生产依赖审计和包清单试运行。

许可证与归属

本项目采用 AGPL-3.0 许可(见 LICENSE)。

它打包并依赖第三方组件:

组件

许可证

来源

Maia3(Chessformer)

AGPL-3.0

UofT CSSLab — Monroe 等人,Chessformer: A Unified Architecture for Chess Modeling(ICLR 2026)

Stockfish(通过 npm stockfish)

GPL-3.0

Stockfish 开发者

onnxruntime-node

MIT

微软

chess.js

BSD-2-Clause

Jeff Hlywa

随附的 Maia3 模型(models/maia3-5m.onnx)衍生自 UofTCSSLab/Maia3-5M at b6559de2398d7140b985f28fd2c19fb5e47ddabe。 ONNX 导出是构建时步骤(scripts/export_maia3.py);运行时 不执行任何 Maia3 Python 代码。

Available Tools

13 tools
create_gameCreate Chess GameA

Create a new chess game and return its game_id. The server is the authoritative source of board state — never track the board yourself. Optionally pass a FEN to start from a custom position.

ParametersJSON Schema
NameRequiredDescriptionDefault
fenNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
game_idYes
revisionYes

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations (readOnlyHint=false) already indicate a write operation, but the description adds the critical behavioral directive to treat the server as the source of truth and avoid local board tracking. It also discloses the return of game_id. This goes beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and front-loaded with the primary action. Each sentence adds value: the core function, the state-tracking warning, and the optional parameter explanation. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple create tool with one optional parameter and an existing output schema, the description covers the essential aspects: what it does, return value, usage caution, and parameter semantics. It does not mention error behavior or prerequisites, but these are not critical for this tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% coverage for the 'fen' parameter, but the description clearly explains that it is optional and used to start from a custom FEN position. This fully compensates for the missing schema description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with a specific verb+resource pair ('Create a new chess game') and explicitly states the return value (game_id), making the tool's purpose unambiguous. It also clearly distinguishes from siblings like delete_game and game_import_pgn.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: the server is authoritative and one should never track the board locally, which implies how to use this with other game-state tools. It also notes the optional FEN for custom positions but does not explicitly exclude alternatives like game_import_pgn.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

delete_gameDelete Chess GameC
DestructiveIdempotent

Delete a game and free its session.

ParametersJSON Schema
NameRequiredDescriptionDefault
game_idYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
deletedYes
game_idYes

TDQS

C2.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=false, destructiveHint=true, and idempotentHint=true, so the safety profile is covered structurally. The description adds "free its session" as a mild behavioral note but doesn't disclose permanence of deletion, whether related data (moves, analyses) is destroyed, or access requirements. No contradiction with annotations exists; the description adds modest value over what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exactly one sentence (7 words), front-loaded with the action verb. It's efficient but arguably over-terse — the "free its session" concept and the game_id requirement both deserve elaboration. This borders on under-specification rather than genuine conciseness, though it avoids padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 1-parameter destructive tool with good annotations and an output schema, the description is minimally adequate. The main gap is the unexplained "free its session" semantic — whether deletion is permanent, whether sessions are tied to games, and what the caller should expect afterward. Low complexity lowers the bar, but the session concept creates real ambiguity the description should resolve.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description fails to compensate. While game_id is a self-descriptive parameter name, the description doesn't explain how to obtain a valid game_id (e.g., from create_game or game_state), any format expectations, or validation constraints. With zero coverage, the description carries the burden and drops the ball.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Delete a game" clearly identifies the verb and resource, and it implicitly distinguishes from create_game among siblings. However, "free its session" is vague and unexplained — it's unclear what a session is, what freeing it means, or whether it implies releasing resources beyond the game itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, no mention of prerequisites (ownership, active games, permissions), and no reference to sibling tools like create_game as the inverse operation. It neither states exclusions nor implies usage context beyond the literal action.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

game_import_pgnImport Chess PGNA

Import a PGN into a new game. Returns a new game_id with the position after all PGN moves. Rejects malformed or illegal PGN.

ParametersJSON Schema
NameRequiredDescriptionDefault
pgnYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
fenYes
turnYes
isDrawYes
game_idYes
historyYes
isCheckYes
castlingYes
lastMoveYes
revisionYes
isGameOverYes
moveNumberYes
isCheckmateYes
isStalemateYes
isDrawByFiftyMovesYes
isThreefoldRepetitionYes
isInsufficientMaterialYes

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With all annotations false, the description carries the transparency burden. It discloses that a new game is created (side effect), returns a game_id, and rejects invalid PGN. However, it does not mention idempotency, potential side effects on other resources, or permission requirements, but the core side effect is well-stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three concise sentences: action, result, and error handling. No unnecessary details or redundant phrasing. It is well-structured and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, but the description clearly states the output: 'Returns a new game_id.' It also mentions error rejection. It does not describe the error format or potential additional outputs (e.g., full game state), but for a simple import tool, these details are not critical. The description provides sufficient context for a basic understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'pgn' has no description in the schema. The description implies it is a PGN string by the tool name and purpose, and mentions rejection of malformed PGN, but does not elaborate on acceptable format (e.g., whether headers are required) or provide examples. This is minimal but adequate for a standard chess PGN.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Import a PGN into a new game' and its outcome: 'Returns a new game_id with the position after all PGN moves.' This distinguishes it from sibling tools like create_game, game_pgn, and game_play_move by specifying the input format (PGN) and the new game creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions error behavior ('Rejects malformed or illegal PGN') but does not explicitly indicate when to use this tool versus alternatives, such as when a PGN is available versus starting a blank game with create_game. There is no mention of alternatives or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

game_pgnExport Chess PGNB
Read-onlyIdempotent

Export the current game as PGN.

ParametersJSON Schema
NameRequiredDescriptionDefault
game_idYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
pgnYes
game_idYes
revisionYes

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds no new behavioral context. The word 'Export' is consistent with read-only, but there is no elaboration on side effects, permissions, or response details beyond the output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with zero filler. It efficiently states the tool's function without unnecessary detail, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with one parameter and an output schema, so the description covers the core action. However, it lacks any guidance on alternatives or parameter specifics, and the lack of usage context means the description is only minimally adequate for the tool's overall adoption.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must clarify the parameter, but it only refers to 'the current game' without explaining that game_id identifies which game. The lone parameter's meaning is left implicit, forcing the agent to infer from the parameter name alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Export') on a specific resource ('the current game') with a clear output format (PGN). It distinguishes from siblings like game_import_pgn (import) and game_state (state retrieval), making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as game_state or game_import_pgn. The description is a single declarative sentence with no context about scenarios, prerequisites, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

game_play_movePlay Chess MoveA
Destructive

Play a move (SAN like 'e4' or UCI like 'e2e4') and return the resulting state. This is the ONLY tool that mutates the game. expected_revision is required: pass the revision from your most recent game_state/move_candidates read. If the game has advanced since then, the move is rejected with STALE_POSITION.

ParametersJSON Schema
NameRequiredDescriptionDefault
moveYes
game_idYes
expected_revisionYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
fenYes
moveYes
turnYes
isDrawYes
game_idYes
historyYes
isCheckYes
castlingYes
lastMoveYes
revisionYes
isGameOverYes
moveNumberYes
isCheckmateYes
isStalemateYes
isDrawByFiftyMovesYes
isThreefoldRepetitionYes
isInsufficientMaterialYes

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark destructiveHint=true, but the description adds critical concurrency behavior: the STALE_POSITION rejection if the revision is outdated. It also states it returns the resulting state, which is useful even with an output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences deliver the core action, uniqueness, and concurrency requirement with zero fluff. Each sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutating tool with an output schema and annotations, the description covers the essential operational details: mutation, concurrency control, error condition, and move format. It is complete enough for an agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero schema description coverage, the description compensates by explaining the 'move' parameter (SAN vs UCI) and the 'expected_revision' parameter (required, from a recent read, and its role in staleness). The 'game_id' is self-explanatory, so overall it adds substantial meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description explicitly states 'Play a move' and even clarifies SAN/UCI formats. The unique claim 'This is the ONLY tool that mutates the game' clearly differentiates it from all siblings, which are read-only or other operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly states when to use this tool (to make a move) and specifies the required expected_revision from a prior read. It does not explicitly mention alternatives, but by highlighting it's the only mutating tool, it implicitly advises that all other tools are non-mutating.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

game_stateGet Chess Game StateA
Read-onlyIdempotent

Return the authoritative state of a game: FEN, turn, revision, check/mate/draw flags, move history, last move, castling rights. Use this instead of remembering the board. Set include_ascii=true to also get a board diagram.

ParametersJSON Schema
NameRequiredDescriptionDefault
game_idYes
include_asciiNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
fenYes
turnYes
boardNo
isDrawYes
game_idYes
historyYes
isCheckYes
castlingYes
lastMoveYes
revisionYes
isGameOverYes
moveNumberYes
isCheckmateYes
isStalemateYes
isDrawByFiftyMovesYes
isThreefoldRepetitionYes
isInsufficientMaterialYes

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety and repeatability. The description adds value by specifying the content of the response (fields) and the optional include_ascii behavior, but does not disclose additional behavioral nuances like response format or error conditions beyond what annotations already imply. With strong annotations, this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose and fields, followed by an optional usage hint. Every sentence carries value; there is no fluff or redundancy. It is concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (which explains return structure) and the simple parameter set, the description fully covers what the tool does and when to use it. It even lists the key fields for quick understanding and provides a usage example for the optional parameter. It is complete for this tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It explains include_ascii (setting it true provides a board diagram) but leaves game_id implicit, though the name suggests it identifies the game. It adds some meaning for include_ascii, but could have explicitly stated game_id's purpose. Since game_id is evident from context, this partially compensates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the authoritative game state and enumerates specific fields (FEN, turn, revision, flags, move history, etc.). It differentiates itself from siblings like game_pgn (which likely returns a different format) by focusing on the internal state, and explicitly suggests using it instead of remembering the board.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance to use this tool instead of relying on memory, giving a clear when-to-use context. It does not explicitly mention when not to use it or mention alternatives, but the ton of 'authoritative state' and scope differentiate it from related tools. No exclusions are stated, but the implied usage is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

human_move_distributionEstimate Human Chess MovesA
Read-onlyIdempotent

Return the Maia3 human-like move probability distribution for the current position, conditioned on a target Elo. Higher probability = more human-typical at that rating. This is NOT move quality — a high-probability move can still be objectively bad.

ParametersJSON Schema
NameRequiredDescriptionDefault
eloNo
top_nNo
game_idYes
oppo_eloNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
eloYes
movesYes
game_idYes
oppo_eloYes
revisionYes

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety and determinism. The description adds crucial behavioral nuances: it clarifies that higher probability means more human-typical, and explicitly notes that this is not move quality, preventing misinterpretation. It does not contradict annotations, and adds context beyond what annotations provide, such as the meaning of the output values.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—two sentences, no fluff. Every word earns its place: the first sentence defines the function and key input (Elo), and the second provides a critical caveat. It is front-loaded with the core purpose and avoids unnecessary details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is relatively simple (read-only, 1 required param) and has an output schema, so the description needn't detail the return structure. It covers the core usage and behavior (human-likeness, Elo conditioning, not-quality warning). The main gap is parameter semantics (covered separately), but overall the description provides sufficient context for an agent to understand what the tool does and when to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must explain parameters. It only mentions 'target Elo' (which maps to elo) but does not clarify top_n (how many moves returned), oppo_elo (opponent rating effect), or game_id (required, identifies position). The word 'distribution' might imply all moves, but top_n suggests a subset, creating ambiguity. This is inadequate for a 4-param tool with no schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the Maia3 human-like move probability distribution for the current position, conditioned on target Elo. It explicitly distinguishes itself from move quality ('This is NOT move quality'), which differentiates it from siblings like move_evaluate or position_analyze. The verb 'Return' and specific resource 'Maia3...distribution' make the purpose precise.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use: when you need human-like probabilities for a given rating, and warns against confusing with move quality. It does not explicitly mention alternatives or when NOT to use it, but the 'NOT move quality' caveat curbs misuse. The 'conditioned on a target Elo' hints at the parameter, but no direct guidance on top_n or oppo_elo is given. So it provides clear context with a partial exclusion but lacks explicit alternative naming.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

move_candidatesGenerate Chess Move CandidatesA
Read-onlyIdempotent

The primary move-selection tool. Combine Stockfish objective evaluation (moverCp, whiteCp, cpLoss, mate, WDL), Maia3 human probability, and Lichess real-game statistics into a unified candidate list. moverCp is from the mover's perspective: higher = better for the player choosing the move. Use this before choosing a move; the final choice is yours.

ParametersJSON Schema
NameRequiredDescriptionDefault
eloNo
game_idYes
sf_depthNo
lichess_dbNolichess
maia_top_nNo
sf_multipvNo
analysis_levelNonormal
lichess_speedsNo
lichess_ratingsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
eloYes
fenYes
turnYes
game_idYes
revisionYes
candidatesYes
analysis_levelYes
moveSensitivityYes

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds valuable behavioral context by explaining that moverCp is from the mover's perspective and that the tool merges three distinct evaluation sources, which goes beyond what annotations or schema convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the tool's primary role, and every sentence adds meaningful context: what the tool does, the moverCp perspective, and when to use it. There is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the presence of an output schema and helpful annotations, the description covers the core selection context well. It could be more complete by explicitly contrasting with sibling tools like move_candidates_by_intent, but the 'primary' framing mitigates this gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain any of the nine input parameters such as elo, sf_depth, lichess_ratings, or analysis_level. It adds meaning to the output metrics but fails to compensate for the lack of parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states this is the primary move-selection tool and that it combines Stockfish evaluation, Maia3 human probability, and Lichess statistics into a unified candidate list. This specific verb+resource combination distinguishes it from sibling tools like move_evaluate or move_candidates_by_intent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly instructs the agent to use this tool before choosing a move, which is strong usage guidance. However, it does not name alternatives or provide when-not-to-use conditions, so it falls short of full differentiation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

move_candidates_by_intentRank Chess Moves by IntentA
Read-onlyIdempotent

Convenience layer over move_candidates: rank candidates for a strategic intent. This tool RANKS candidates but does NOT choose a move — use the returned signals and conversation context to make the final decision. Do not map user skill mechanically to an intent. intents: best (strongest engine move), strong (engine-strong but human-plausible), natural (most human-typical), balanced (blend of strength and human-likeness), ease_off (human-plausible moves that modestly reduce advantage without changing the expected result), give_chance (human-plausible inaccuracies that meaningfully improve the opponent's chances).

ParametersJSON Schema
NameRequiredDescriptionDefault
eloNo
intentYes
game_idYes
sf_depthNo
lichess_dbNolichess
maia_top_nNo
sf_multipvNo
analysis_levelNonormal
lichess_speedsNo
lichess_ratingsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
eloYes
fenYes
turnYes
intentYes
game_idYes
revisionYes
candidatesYes
analysis_levelYes
moveSensitivityYes

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds behavioral context by stating it RANKS but does NOT choose a move, and clarifies the meaning of each intent, which is valuable beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph but packs essential information: purpose, relationship to sibling, behavioral caveat, and intent definitions. It is front-loaded with the core purpose and then details intents. Slightly long but each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 10 parameters, 2 required, and an output schema. The description explains the core intent parameter and the tool's role, but does not cover other parameters like elo, sf_depth, or lichess_db. However, the output schema exists, so return values are covered. The description is adequate for a complex tool but could mention how other parameters affect ranking.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the 'intent' parameter in detail with definitions for each enum value, which is critical. However, other parameters like elo, sf_depth, lichess_db, etc., are not explained in the description, relying on the schema's names and defaults. Given the complexity, the description covers the most important parameter but leaves others to inference.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a convenience layer over move_candidates that ranks candidates for a strategic intent. It explicitly distinguishes itself from move_candidates and clarifies it does not choose a move, which differentiates it from siblings like game_play_move.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool: as a ranking layer over move_candidates, and explicitly warns not to map user skill mechanically to an intent. It also lists all intents with definitions, giving clear context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

move_evaluateEvaluate Chess MovesA
Read-onlyIdempotent

Evaluate one or more moves with Stockfish without mutating the game. Pass a single move string or an array of moves to compare. Returns, for each move, the score after the move (from the mover's perspective), cpLoss vs the best move, and a classification (best/excellent/good/inaccuracy/mistake/blunder).

ParametersJSON Schema
NameRequiredDescriptionDefault
moveYes
depthNo
game_idYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
game_idYes
resultsYes
revisionYes

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations include readOnlyHint=true and idempotentHint=true, and the description explicitly states 'without mutating the game,' reinforcing that. It also adds value by describing the output (score, cpLoss, classification) and the engine (Stockfish), which are not required but provide useful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise—three sentences—and front-loaded with the core purpose and non-mutation guarantee. Every sentence adds meaning without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema is present, so detailed return field explanations are unnecessary. The description covers the primary purpose, input flexibility, and key output categories, making it adequate for most usage scenarios. Minor omissions (e.g., depth semantics) are acceptable given the schema's constraints.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description partially compensates by explaining the 'move' parameter format (string or array). However, it does not clarify the 'depth' or 'game_id' parameters beyond what the schema already provides, leaving incomplete semantic coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool evaluates moves using Stockfish, specifying the action (evaluate), resource (moves), and context (without mutating the game). It distinguishes itself from sibling tools like game_play_move (which mutates) and game_legal_moves (which lists legal moves).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies its use for analysis rather than gameplay via 'without mutating the game' and mentions comparing moves, which gives context. However, it does not explicitly name alternative tools or provide exclusion criteria, so it falls short of a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

opening_explorerQuery Lichess Opening ExplorerB
Read-onlyIdempotent

Query the Lichess opening explorer for real human game statistics in the current position (requires LICHESS_TOKEN).

ParametersJSON Schema
NameRequiredDescriptionDefault
dbNolichess
speedsNo
game_idYes
ratingsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
dbYes
blackYes
drawsYes
movesYes
whiteYes
game_idYes
openingYes
revisionYes

TDQS

B3.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations (readOnlyHint, openWorldHint, idempotentHint) already indicate a safe read-only operation. Description adds environment requirement: the question requires a token. Does not mention permissions, read-only side effects, or returns.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Short description of one sentence with no unnecessary details. However, the output or result not mentioned.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite output schema(true), annotations (readOnly/openWorld/idempotent), the description doesn't mention what the tool returns (opening list/names/counts), so the agent may not know if it can fulfill the request. the description is too sparse for interactive decision-making.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description gives no parameter semantics. The input schema covers params and types but does not explain the source or valid values. There are 4 parameters and he documentation does not cover the specific role of `db`, `speeds`, `ratings`, or `game_id`. Coverage is 0% and the description doesn't compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses a specific verb ('Query') with the Lichess opening explorer and the current position context. However, it doesn't distinguish itself from sibling tools other than by name and implicit use case.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs alternatives like position_move or game_analysis. The only guidance meaning implied: 'current position' and 'requires a token'. Not enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

position_analyzeAnalyze Chess PositionA
Read-onlyIdempotent

Run Stockfish on the current position and return the top engine lines (multipv). Scores are from the side-to-move perspective: positive cp = side to move is better; mate N = side to move mates in N. wdl is [win, draw, loss] in permille for the side to move. Use analysis_level (fast/normal/deep) or explicit depth/multipv. Does NOT mutate the game.

ParametersJSON Schema
NameRequiredDescriptionDefault
depthNo
game_idYes
multipvNo
analysis_levelNonormal

Output Schema

ParametersJSON Schema
NameRequiredDescription
fenYes
turnYes
linesYes
game_idYes
revisionYes
analysis_levelYes

TDQS

A4.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint, so the description's statement 'Does NOT mutate the game' adds no new information, but it does clarify the evaluation perspective and wdl format, and explains analysis levels without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

All sentences are purposeful and detailed without redundancy, front-loading the core action and then explaining parameters and output semantics efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter tool with output schema and strong annotations, the description covers the tool's functionality, parameter choices, and output interpretation (cp, mate, wdl) completely, making it highly usable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description explains the meaning and effect of analysis_level, depth, and multipv, and clarifies that game_id is required to identify the position. This compensates fully for the lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs Stockfish on the current position and returns top engine lines, distinguishing it from sibling tools like move_evaluate and move_candidates.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains how to specify analysis level or depth/multipv, and mentions it does not mutate the game, but lacks explicit when-not-to-use or alternative tool comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 13 tool updatesv0.3.1
    • First observedcreate_game
    • First observeddelete_game
    • First observedgame_import_pgn
    • First observedgame_legal_moves
    • First observedgame_pgn
    • First observedgame_play_move
    • First observedgame_state
    • First observedhuman_move_distribution
    • First observedmove_candidates
    • First observedmove_candidates_by_intent
    • First observedmove_evaluate
    • First observedopening_explorer
    • First observedposition_analyze

TDQS

A3.7/5.0

Scored across 13 tools

Disambiguation4/5

Game lifecycle tools are clearly distinct: create, delete, state, move, legal moves, PGN export/import. The move-analysis tools overlap somewhat—position_analyze, move_evaluate, move_candidates, and move_candidates_by_intent all return evaluation-like signals—but their descriptions clarify different purposes: raw engine lines, per-move comparison, unified candidate selection, and intent-based ranking. An agent could hesitate between these, but they are not truly interchangeable.

Naming Consistency3/5

Some names follow verb_noun (create_game, delete_game), while others are noun phrases or prefixed differently (game_state, game_pgn, game_import_pgn, position_analyze, opening_explorer). The move_* group is predictable, but the overall naming is a mix of conventions. Names are still readable and snake_case consistent, so the inconsistency is moderate rather than chaotic.

Tool Count5/5

Thirteen tools is well within the ideal range and appropriate for a chess server that handles game lifecycle, PGN import/export, legal move queries, engine analysis, human-move modeling, and opening statistics. Each tool has a defined role, and the count does not feel bloated or thin.

Completeness5/5

The surface covers the full lifecycle: create, read state, mutate via play move, legal moves, delete, and PGN import/export. Analysis coverage is also strong: Stockfish lines, move evaluation, human move distributions, unified candidates, intent-based ranking, and opening explorer. There are no obvious dead ends for playing or analyzing a chess game.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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