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llm-chess-mcp

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llm-chess-mcp

LLMがプレイ、分析、強さの調整を、すべての判断をエンジンに委ねることなく行えるMCPチェスランタイムです。

単一の最善手を返すのではなく、客観的な強さ(Stockfish)、人間の手の可能性(Maia3)、実際の対局統計(Lichess)を公開し、LLMがどのようにプレイしたいかを選択できるようにします。LLMが戦略と判断を行い、MCPサーバーがすべての計算を処理します。

エンジン

エンジン

役割

ランタイム

Stockfish 18 (WASM)

客観的な評価、最善手、multipv

プロセス内 (npm stockfish)

Maia3 5M (ONNX)

Eloに基づく人間らしい手の確率

プロセス内 (onnxruntime-node)

Lichess explorer

実際の人間の対局統計

HTTP (トークンが必要)

すべてはNodeプロセス内で実行されます。デプロイ時に外部エンジンプロセスやPythonランタイムは不要です。公開パッケージにはMaia3 5Mモデルが同梱されています。他のエクスポートバリアントは、ONNXファイルが別途提供されない限り、ランタイムオプションにはなりません。

Related MCP server: Chess MCP

インストール

Node.js 20以降が必要です。

インストール不要 — npxで直接実行できます:

npx -y llm-chess-mcp

Maia3モデルはすでに同梱されているため、Python、torch、エンジンバイナリをインストールする必要はありません。npxは初回実行時にパッケージを取得し、キャッシュします。

代わりに永続的にインストールする場合:

npm install -g llm-chess-mcp

ソースからビルド

pnpm install
pnpm build
pnpm test

pnpm test:unitはユニットスイートを実行します。pnpm test:e2eは最初にビルドし、その後MCPトランスポートテストを実行します。pnpm checkは完全なローカルゲートを実行します。公開前にpnpm release:checkを使用してください。

メンテナー

アーキテクチャはランタイムとサービスの境界を説明しています。

ローカル品質コマンド:

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

pnpm test:stressは短い実エンジン並行性チェックを実行します。pnpm test:liveはLICHESS_TOKENが設定されている場合のみLichessにクエリを実行します。それ以外の場合はネットワークリクエストを行わずにスキップします。

Maia3をONNXにエクスポート(ビルド時のみ)

このステップではPython + PyTorchが一度だけ必要です。Maia3チェックポイントをダウンロードし、再実装をオリジナルに対して検証し、models/maia3-5m.onnxをエクスポートします。

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

結果の.onnxはコミット/バンドルされます。エンドユーザーがPythonやtorchを必要とすることはありません。

Lichessトークン(オプション)

オープニングエクスプローラーは現在認証が必要です。https://lichess.org/account/oauth/token/create で個人アクセストークンを生成し、.envに設定してください:

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

トークンがない場合、opening_explorerは無効通知を返します。他のすべてのツールは動作します。

エクスプローラーのフィルターは厳格です。スピードはultraBullet、bullet、blitz、rapid、classical、correspondenceです。レーティングバケットは0、1000、1200、1400、1600、1800、2000、2200、2500です。mastersはどちらのフィルターも受け付けません。無効なフィルターはローカルで失敗します。一時的な障害(ネットワーク、タイムアウト、429、5xx)は12秒の総予算内で1回再試行されます。無効なリクエストやその他の4xx応答は再試行されません。

MCPクライアントでの設定

opencode

opencode.json(プロジェクト)または~/.config/opencode/opencode.json(グローバル)に追加:

{
  "$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

.mcp.json(プロジェクト)または~/.claude.json(グローバル)に追加するか、以下を実行:

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

~/.codex/config.tomlに追加:

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

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

またはCLI経由:

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

ツール

ツール

説明

create_game

ゲームを作成(オプションでFENから)、game_idを返す

delete_game

ゲームを削除し、セッションを解放

game_state

権威ある状態: FEN、手番、リビジョン、チェック/メイト/ドロー フラグ、履歴、最後の手、キャスリング(オプションでASCII)

game_play_move

手をプレイ(SANまたはUCI)— 唯一の変更ツール、古い位置ガード付き

game_legal_moves

メタデータ付きのすべての合法手

game_pgn

ゲームをPGNとしてエクスポート

game_import_pgn

PGNを新しいゲームにインポート

position_analyze

Stockfish multipvライン(cp/mate/WDL + PV)、analysis_levelプリセット

human_move_distribution

ターゲットEloでのMaia3人間の手の確率

move_evaluate

1つ以上の手をスコアリング + cpLoss + 分類

move_candidates

主要ツール: 統合候補(客観的 + 人間的 + オープニング)

move_candidates_by_intent

利便性レイヤー: 戦略的意図に基づいてランク付けされた候補

opening_explorer

Lichessの人間の対局統計

結果形式

structuredContentが正規の成功結果です。ハンドラーレベルの失敗はisErrorを設定し、structuredContent.errorを提供します。入力スキーマの失敗はハンドラーの前にMCP SDKによって生成され、structuredContentなしの標準のisErrorテキスト結果を使用します。それ以外の場合、contentは短い人間可読の要約のみであり、データとして解析してはなりません。

スコアの規約

  • Stockfishのスコアは手番側の視点です。正のcp = 手番側が有利。mate N = 手番側がN手でメイト。wdlは手番側の[勝ち、引き分け、負け]をパーミルで表します。

  • move_candidatesはmoverCp(動かす側の視点 — 手を選ぶプレイヤーにとって高いほど良い)とwhiteCp(固定の白の視点)を提供するため、符号が反転することはありません。

  • move_evaluateは動かす側の視点からスコアを報告し、さらにcpLoss(最善手に対して失ったセンチポーン)と分類を提供します: best / excellent / good / inaccuracy / mistake / blunder。

  • maia3Probは人間らしさであり、手の質ではありません。高い確率の手が客観的に悪い場合もあります。

候補構造

move_candidatesは各候補を3つの独立した側面で返します:

{
  "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: エンジンの強さ。人間らしさと混同されることはありません。moverCpは動かす側の視点(選択者にとって高いほど良い)。

  • human — ターゲットEloでのMaia3条件付き確率。

  • opening — Lichessの経験的频率(Maia3とは異なるシグナル)。

opening.statusはavailable、no_data(APIはOKだがこの局面にゲームがない)、unavailable(タイムアウト/429/401)、またはdisabled(トークンなし)です。Stockfish + Maia3の結果は常に返されます。

move_candidatesはまたmoveSensitivityを返し、トップエンジンライン間で評価がどれだけ急激に変化するかを説明します:

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

levelはlow(<80cpスプレッド)、medium(80–200cp)、high(≥200cp)です。感度が高いということは、妥当な代替案の選択が評価を実質的に変える可能性があることを意味します — 手を緩めるか正確にプレイするかを決定するのに役立ちます。

分析レベル

Stockfishツールは生のUCIノブの代わりにanalysis_levelプリセットを受け入れます:

レベル

深さ

MultiPV

fast

8

5

normal

15

8

deep

22

10

明示的なdepth/multipvオーバーライドは上級者向けに引き続き利用可能です。

古い位置ガード

すべての状態読み取りはrevisionを返します。game_play_moveは**expected_revisionを必須**とします。最後の読み取り以降にゲームが進行している場合、手は拒否されます:

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

ランタイム制限

  • 最大1,000のゲームセッションが保持され、アイドルセッションは1時間後に期限切れになります。

  • move_evaluateは1回の呼び出しで最大10手を受け入れます。

  • インポートされたPGNは1 MiBと4,096プライに制限されます。

  • Stockfishは最大32のアクティブまたはキューされた分析を受け入れます。

意図

move_candidates_by_intentは選択された意図に基づいて候補をランク付けします。これはmove_candidatesの利便性レイヤーです。以下の固定しきい値はヒューリスティックなデフォルトであり、真実の源ではありません:

意図

意味

best

最強のエンジン手

strong

エンジン的に強いが人間的に妥当

natural

ターゲットEloで最も人間に典型的

balanced

強さと人間らしさのブレンド

ease_off

期待される結果を変えずに利点を控えめに減らす人間的に妥当な手

give_chance

相手のチャンスを実質的に改善する人間的に妥当な不正確さ

このツールは候補をランク付けしますが、手を選択しません。返されたシグナルと会話の文脈を使用して最終決定を行ってください — ユーザーのスキルを機械的に意図にマッピングしないでください。

例のフロー

通常のプレイループは3つの呼び出しです:

  1. create_game → game_id

  2. move_candidates → 手を選ぶ

  3. game_play_move(expected_revision付き)→ コミット

必要な場合にのみ深く進んでください:

  • position_analyze — 客観的な最善ライン

  • human_move_distribution — 特定のEloの人間がプレイする手

  • opening_explorer — 実際の対局統計

  • move_evaluate — 特定の手をスコアリング(または複数を比較)

Maia3 ONNX検証

エクスポートされたONNXモデルは、固定位置とEloペアにわたってアップストリームのMaia3実装に対して回帰テストされます:

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

トップ1/トップkの手の一致と最大確率誤差をチェックし、エクスポート/ランタイムの回帰を検出します。同梱のmaia3-5m.onnxは100%のトップ1およびトップ5一致、最大確率誤差<1e-4で合格します。

パッケージ検証

パッケージアーティファクトはローカルで検証されます。このプロジェクトには意図的にホストされたCIワークフローはありません。

pnpm checkを実行して決定論的なオフラインゲートを行います。pnpm test:packageを使用してプロジェクトをパックし、クリーンな一時ディレクトリにtarballをインストールし、インストールされたllm-chess-mcpバイナリを実際のStockfishとMaiaランタイムに対して実行します。pnpm release:checkは両方のチェックに加えて、本番依存関係の監査とパッケージマニフェストのドライランを実行します。

ライセンスと帰属

このプロジェクトはAGPL-3.0の下でライセンスされています(LICENSEを参照)。

サードパーティのコンポーネントをバンドルおよび依存しています:

コンポーネント

ライセンス

ソース

Maia3 (Chessformer)

AGPL-3.0

UofT CSSLab — Monroe ら、Chessformer: チェスモデリングのための統一アーキテクチャ (ICLR 2026)

Stockfish (npm の stockfish 経由)

GPL-3.0

Stockfish 開発者

onnxruntime-node

MIT

Microsoft

chess.js

BSD-2-Clause

Jeff Hlywa

同梱の Maia3 モデル (models/maia3-5m.onnx) は、UofTCSSLab/Maia3-5M の b6559de2398d7140b985f28fd2c19fb5e47ddabe を派生しています。ONNXエクスポートはビルド時のステップ (scripts/export_maia3.py) であり、ランタイムが Maia3 の Python コードを実行することはありません。

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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    1
    ISC
  • F
    license
    Not graded
    quality
    C
    maintenance
    An MCP server that exposes Stockfish chess analysis to LLM chat clients, enabling move analysis, game review, and explanation of engine choices.
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