Shrimp Task Manager
目錄
MCP シュリンプ タスクマネージャー

🚀 モデルコンテキストプロトコル (MCP) に基づくインテリジェントなタスク管理システム。AI エージェントに効率的なプログラミング ワークフロー フレームワークを提供します。
Shrimp Task Manager は、体系的なプログラミング、タスク メモリ管理メカニズムの強化、冗長で反復的なコーディング作業の効率的な回避のために、構造化されたワークフローを通じてエージェントをガイドします。
Related MCP server: Vibe Coder MCP
✨ 特徴
タスク計画と分析:複雑なタスク要件の深い理解と分析
インテリジェントなタスク分解: 大きなタスクを管理しやすい小さなタスクに自動的に分割します
依存関係管理: タスク間の依存関係を正確に処理し、正しい実行順序を確保します。
実行ステータスの追跡: タスク実行の進行状況とステータスをリアルタイムで監視
タスク完了の検証: タスクの結果が期待される要件を満たしていることを確認する
タスクの複雑さの評価: タスクの複雑さを自動的に評価し、最適な処理の提案を提供します
タスク概要の自動更新: タスク完了時に概要を自動的に生成し、メモリパフォーマンスを最適化します。
タスクメモリ機能: タスク履歴を自動的にバックアップし、長期記憶と参照機能を提供します。
リサーチモード: 技術、ベストプラクティス、ソリューションの比較を調査するためのガイド付きワークフローを備えた体系的な技術リサーチ機能
プロジェクトルールの初期化: 大規模プロジェクト間で一貫性を維持するためのプロジェクト標準とルールを定義します。
Web GUI : タスク管理用のWebベースのグラフィカルユーザーインターフェース(GUI)をオプションで提供します
.envファイルでENABLE_GUI=true設定することで有効になります。有効にすると、アクセスアドレスを含むWebGUI.mdファイルがDATA_DIRに作成されます。
🧭 使用ガイド
Shrimp Task Manager は、ガイド付きワークフローと体系的なタスク管理を通じて、AI 支援プログラミングへの構造化されたアプローチを提供します。
エビとは何ですか?
Shrimpは、AIエージェントがプロジェクトをより深く理解し、プロジェクトで作業できるようにするためのプロンプトテンプレートです。一連のプロンプトを使用することで、エージェントがプロジェクト固有のニーズや慣例に厳密に適合するようにします。
研究モードの実践
タスク計画に着手する前に、リサーチモードを活用して技術的な調査や知識収集を行うことができます。これは特に以下の場合に便利です。
新しい技術やフレームワークを探求する必要がある
さまざまなソリューションアプローチを比較したい
プロジェクトのベストプラクティスを調査している
複雑な技術的概念を理解する必要がある
エージェントに「[トピック]をリサーチして」または「[技術/問題]のリサーチモードに入って」と指示するだけで、体系的な調査が開始されます。調査結果は、その後のタスク計画や開発の意思決定に役立てられます。
初回セットアップ
新しいプロジェクトで作業する際は、エージェントに「init project rules(プロジェクトルールを初期化)」と指示するだけです。これにより、エージェントはプロジェクトの特定の要件と構造に合わせて一連のルールを生成します。
タスク計画プロセス
機能を開発または更新するには、「plan task [説明]」コマンドを使用してください。システムは事前に確立されたルールを参照し、プロジェクトを理解しようと試み、関連するコードセクションを検索し、プロジェクトの現在の状態に基づいて包括的な計画を提案します。
フィードバックメカニズム
計画プロセス中、Shrimpはエージェントを複数の思考ステップに導きます。このプロセスを確認し、間違った方向に進んでいると感じた場合はフィードバックを提供できます。途中で中断して自分の見解を伝えるだけで、エージェントはあなたのフィードバックを取り入れ、計画プロセスを続行します。
タスク実行
計画に満足したら、「タスク実行 [タスク名またはID]」を使用して実行します。タスク名またはIDを指定しない場合は、システムが自動的に最も優先度の高いタスクを特定して実行します。
連続モード
各タスクを手動で介入せずにすべてのタスクを順番に実行したい場合は、「連続モード」を使用してタスク キュー全体を自動的に処理します。
トークン制限に関する注意事項
LLMトークンの制限により、長時間の会話中にコンテキストが失われる場合があります。その場合は、新しいチャットセッションを開き、エージェントに実行を続行するよう指示してください。システムは中断したところから再開するため、タスクの詳細やコンテキストを再度伝える必要はありません。
プロンプト言語とカスタマイズ
TEMPLATES_USE環境変数を設定することで、システムプロンプトの言語を切り替えることができます。デフォルトではen (英語) とzh (中国語繁体字) がサポートされています。さらに、既存のテンプレートディレクトリ (例: src/prompts/templates_en ) をDATA_DIRで指定した場所にコピーし、変更を加えた上で、 TEMPLATES_USEにカスタムテンプレートディレクトリ名を指定することもできます。これにより、プロンプトをより詳細にカスタマイズできます。詳細な手順については、こちらをご覧ください。
🔬 リサーチモード
Shrimp Task Manager には、体系的な技術調査と知識収集のために設計された特殊な研究モードが含まれています。
リサーチモードとは何ですか?
リサーチモードは、AIエージェントが徹底的かつ体系的な技術調査を実施できるよう支援するガイド付きワークフローシステムです。技術の探索、ソリューションの比較、ベストプラクティスの調査、プログラミングタスクのための包括的な情報の収集など、構造化されたアプローチを提供します。
主な特徴
体系的な調査:構造化されたワークフローにより、研究トピックを包括的にカバーできます。
マルチソースリサーチ:ウェブ検索とコードベース分析を組み合わせて完全な理解を実現
状態管理: 複数のセッションにわたって研究のコンテキストと進捗状況を維持します
ガイド付き探索:研究が焦点を失ったり、話題から外れたりするのを防ぎます
知識統合:研究結果をタスクの計画と実行にシームレスに統合します
リサーチモードを使用するタイミング
リサーチ モードは、特に次の場合に価値があります。
テクノロジーの探究:新しいフレームワーク、ライブラリ、ツールの調査
ベストプラクティス調査:業界標準と推奨アプローチの発見
ソリューションの比較: さまざまな技術的アプローチやアーキテクチャを評価する
問題調査:複雑な技術的課題を深く掘り下げる
アーキテクチャ計画:設計パターンとシステムアーキテクチャの調査
リサーチモードの使い方
エージェントにトピックのリサーチ モードに入るように指示するだけです。
基本的な使用方法: 「[トピック]のリサーチモードに入る」
具体的な研究:「[特定の技術/問題]を研究する」
比較分析:「[オプション A と B] を調査して比較する」
システムは、構造化された調査フェーズを通じてエージェントをガイドし、特定のニーズに重点を置きながら徹底的な調査を確実に実行します。
研究ワークフロー
トピックの定義:研究の範囲と目的を明確に定義する
情報収集:関連情報の体系的な収集
分析と統合:調査結果の処理と整理
状態の更新: 定期的な進捗状況の追跡とコンテキストの保存
統合:研究結果をプロジェクトのコンテキストに適用する
💡 推奨事項: 最高の研究モードエクスペリエンスを得るには、優れた分析機能と包括的な研究統合を提供するClaude 4 Sonnet の使用をお勧めします。
🧠 タスクメモリ機能
Shrimp Task Manager には長期記憶機能があり、タスク実行履歴を自動的に保存し、新しいタスクを計画するときに参照エクスペリエンスを提供します。
主な特徴
システムはタスクをメモリディレクトリに自動的にバックアップします
バックアップファイルは、tasks_backup_YYYY-MM-DDThh-mm-ss.json の形式で時系列順に命名されます。
タスク計画エージェントはメモリ機能の使用方法に関するガイダンスを自動的に受信します
利点とメリット
重複作業を避ける: 過去のタスクを参照すれば、同様の問題を一から解決する必要はありません。
成功体験から学ぶ:実証済みの効果的なソリューションを活用し、開発効率を向上
学習と改善:過去の間違いや非効率的な解決策を特定し、ワークフローを継続的に最適化します
知識の蓄積: システムの使用が増えるにつれて、継続的に拡大する知識ベースを形成します。
タスクメモリ機能を効果的に使用することで、システムは継続的に経験を蓄積し、知能レベルと作業効率を継続的に向上させることができます。
📋 プロジェクトルールの初期化
プロジェクト ルール機能は、コードベース全体の一貫性を維持するのに役立ちます。
開発の標準化:一貫したコーディングパターンとプラクティスを確立する
新規開発者のオンボード: プロジェクトへの貢献に関する明確なガイドラインを提供する
品質の維持: すべてのコードが確立されたプロジェクト標準を満たしていることを確認する
⚠️ 推奨事項:プロジェクトの規模が拡大したり、大幅な変更があったりする場合は、プロジェクトルールを初期化してください。これにより、複雑さが増しても一貫性と品質を維持できます。
次の場合に、 init_project_rulesツールを使用してプロジェクト標準を設定または更新します。
新たな大規模プロジェクトの開始
新しいチームメンバーのオンボーディング
主要なアーキテクチャ変更の実装
新たな開発規約の採用
使用例
シンプルな自然言語コマンドを使用して、この機能に簡単にアクセスできます。
初期設定の場合: エージェントに「init rules」または「init project rules」と伝えるだけです
更新の場合: プロジェクトが進化したら、エージェントに「ルールを更新」または「プロジェクトルールを更新」と伝えます。
このツールは、コードベースが拡張されたり、大幅な構造変更が行われたりする場合、特に価値があり、プロジェクトのライフサイクル全体を通じて一貫した開発プラクティスを維持するのに役立ちます。
📚 ドキュメントリソース
プロンプトカスタマイズガイド: 環境変数を使用してツールプロンプトをカスタマイズする手順
変更履歴: このプロジェクトにおけるすべての注目すべき変更の記録
🔧 インストールと使用方法
Smithery経由でインストール
Smithery経由で Claude Desktop 用の Shrimp Task Manager を自動的にインストールするには:
npx -y @smithery/cli install @cjo4m06/mcp-shrimp-task-manager --client claude手動インストール
# Install dependencies
npm install
# Build and start service
npm run build🔌 MCP 互換クライアントでの使用
Shrimp タスク マネージャーは、Cursor IDE などのモデル コンテキスト プロトコルをサポートする任意のクライアントで使用できます。
カーソルIDEでの設定
Shrimp タスク マネージャーには、グローバル構成とプロジェクト固有の構成という 2 つの構成方法があります。
グローバル構成
Cursor IDE のグローバル設定ファイルを開きます (通常は
~/.cursor/mcp.jsonにあります)mcpServersセクションに次の構成を追加します。
{
"mcpServers": {
"shrimp-task-manager": {
"command": "node",
"args": ["/mcp-shrimp-task-manager/dist/index.js"],
"env": {
"DATA_DIR": "/path/to/project/data", // 必須使用絕對路徑
"TEMPLATES_USE": "en",
"ENABLE_GUI": "false"
}
}
}
}
or
{
"mcpServers": {
"shrimp-task-manager": {
"command": "npx",
"args": ["-y", "mcp-shrimp-task-manager"],
"env": {
"DATA_DIR": "/mcp-shrimp-task-manager/data",
"TEMPLATES_USE": "en",
"ENABLE_GUI": "false"
}
}
}
}⚠️
/mcp-shrimp-task-manager実際のパスに置き換えてください。
プロジェクト固有の構成
各プロジェクトに専用の構成を設定して、異なるプロジェクトに独立したデータ ディレクトリを使用することもできます。
プロジェクトルートに
.cursorディレクトリを作成するこのディレクトリに次の内容の
mcp.jsonファイルを作成します。
{
"mcpServers": {
"shrimp-task-manager": {
"command": "node",
"args": ["/path/to/mcp-shrimp-task-manager/dist/index.js"],
"env": {
"DATA_DIR": "/path/to/project/data", // Must use absolute path
"TEMPLATES_USE": "en",
"ENABLE_GUI": "false"
}
}
}
}
or
{
"mcpServers": {
"shrimp-task-manager": {
"command": "npx",
"args": ["-y", "mcp-shrimp-task-manager"],
"env": {
"DATA_DIR": "/path/to/project/data", // Must use absolute path
"TEMPLATES_USE": "en",
"ENABLE_GUI": "false"
}
}
}
}⚠️ 重要な設定上の注意事項
DATA_DIRパラメータは、Shrimp Task Managerがタスクデータ、会話ログ、その他の情報を保存するディレクトリです。このパラメータを正しく設定することは、システムの正常な動作に不可欠です。このパラメータは絶対パスで指定する必要があります。相対パスを使用すると、システムがデータディレクトリを誤って検出し、データの損失や機能障害が発生する可能性があります。
警告: 相対パスを使用すると、次の問題が発生する可能性があります。
データファイルが見つからないため、システムの初期化に失敗しました
タスクのステータスが失われたり、正しく保存できなかったりする
異なる環境間でのアプリケーションの動作が一貫していない
システムがクラッシュしたり起動に失敗したり
🔧 環境変数の設定
Shrimpタスクマネージャーは環境変数を介してプロンプトの動作をカスタマイズできるため、コードを変更することなくAIアシスタントの応答を微調整できます。これらの変数は、設定ファイルまたは.envファイルで設定できます。
{
"mcpServers": {
"shrimp-task-manager": {
"command": "node",
"args": ["/path/to/mcp-shrimp-task-manager/dist/index.js"],
"env": {
"DATA_DIR": "/path/to/project/data",
"MCP_PROMPT_PLAN_TASK": "Custom planning guidance...",
"MCP_PROMPT_EXECUTE_TASK_APPEND": "Additional execution instructions...",
"TEMPLATES_USE": "en",
"ENABLE_GUI": "false"
}
}
}
}カスタマイズ方法は 2 つあります。
オーバーライドモード(
MCP_PROMPT_[FUNCTION_NAME]):デフォルトのプロンプトを完全に置き換えます追加モード(
MCP_PROMPT_[FUNCTION_NAME]_APPEND):既存のプロンプトにコンテンツを追加する
さらに、他のシステム構成変数もあります。
DATA_DIR : タスクデータが保存されるディレクトリを指定します
TEMPLATES_USE : プロンプトに使用するテンプレートセットを指定します。デフォルトは
enです。現在利用可能なオプションはenとzhです。カスタムテンプレートを使用するには、src/prompts/templates_enディレクトリをDATA_DIRで指定された場所にコピーし、コピーしたディレクトリの名前を変更し(例:my_templates)、TEMPLATES_USEを新しいディレクトリ名(例:my_templates)に設定します。
サポートされているパラメータや例など、プロンプトのカスタマイズの詳細な手順については、 『プロンプト カスタマイズ ガイド』を参照してください。
💡 システムプロンプトガイダンス
カーソルIDE設定
カーソル設定 => 機能 => カスタム モードを有効にして、次の 2 つのモードを構成できます。
タスクプランナーモード
You are a professional task planning expert. You must interact with users, analyze their needs, and collect project-related information. Finally, you must use "plan_task" to create tasks. When the task is created, you must summarize it and inform the user to use the "TaskExecutor" mode to execute the task.
You must focus on task planning. Do not use "execute_task" to execute tasks.
Serious warning: you are a task planning expert, you cannot modify the program code directly, you can only plan tasks, and you cannot modify the program code directly, you can only plan tasks.タスクエグゼキューターモード
You are a professional task execution expert. When a user specifies a task to execute, use "execute_task" to execute the task.
If no task is specified, use "list_tasks" to find unexecuted tasks and execute them.
When the execution is completed, a summary must be given to inform the user of the conclusion.
You can only perform one task at a time, and when a task is completed, you are prohibited from performing the next task unless the user explicitly tells you to.
If the user requests "continuous mode", all tasks will be executed in sequence.💡 ニーズに応じて適切なモードを選択してください。
タスクを計画するときにTaskPlannerモードを使用する
タスクを実行するときはTaskExecutorモードを使用する
他のツールと併用する
ツールがカスタム モードをサポートしていない場合は、次の操作を実行できます。
さまざまな段階で適切なプロンプトを手動で貼り付けます
または、
Please plan the following task: ......やPlease start executing the task...などの単純なコマンドを直接使用します。
🛠️ 利用可能なツールの概要
設定後、次のツールを使用できます。
カテゴリ | ツール名 | 説明 |
タスク計画 |
| タスクの計画を開始する |
タスク分析 |
| タスク要件の詳細な分析 |
| 複雑な問題に対する段階的な推論 | |
ソリューション評価 |
| ソリューションコンセプトの反映と改善 |
研究と調査 |
| 体系的な技術研究モードに入る |
プロジェクト管理 |
| プロジェクトの標準とルールを初期化または更新する |
タスク管理 |
| タスクをサブタスクに分割する |
| すべてのタスクとステータスを表示する | |
| タスクの検索と一覧表示 | |
| 完了したタスクの詳細を表示する | |
| 未完了のタスクを削除する | |
タスク実行 |
| 特定のタスクを実行する |
| タスクの完了を確認する |
🔧 技術的な実装
Node.js : 高性能な JavaScript ランタイム環境
TypeScript : 型安全な開発環境を提供します
MCP SDK : 大規模言語モデルとのシームレスなインタラクションを実現するインターフェース
UUID : ユニークで信頼できるタスク識別子を生成する
📄 ライセンス
このプロジェクトは MIT ライセンスに基づいてライセンスされています - 詳細についてはLICENSEファイルを参照してください。
推奨モデル
最適なエクスペリエンスを得るには、次のモデルを使用することをお勧めします。
クロード 3.7 : 強力な理解力と生成能力を備えています。
Gemini 2.5 : Google の最新モデル、優れたパフォーマンスを発揮します。
モデル間の学習方法や理解能力の違いにより、同じプロンプトに対して異なるモデルを使用すると結果が異なる場合があります。このプロジェクトは、Claude 3.7およびGemini 2.5向けに最適化されています。
スターの歴史
Available Tools
15 toolsanalyze_taskC
深入分析任務需求並系統性檢查代碼庫,評估技術可行性與潛在風險,如果需要提供程式碼請使用 pseudocode 格式且盡量精簡只保留核心實現部分
| Name | Required | Description | Default |
|---|---|---|---|
| summary | Yes | 結構化的任務摘要,包含任務目標、範圍與關鍵技術挑戰,最少10個字符 | |
| initialConcept | Yes | 初步解答構想,包含技術方案、架構設計和實施策略,如果需要提供程式碼請使用 pseudocode 格式且盡量精簡只保留核心實現部分,最少50個字符 | |
| previousAnalysis | No | 前次迭代的分析結果,用於持續改進方案(僅在重新分析時需提供) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions systematic codebase checking and risk evaluation but does not disclose any behavioral traits such as side effects, required permissions, or state changes. The agent learns the tool's function but not its operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that combines purpose and a usage note. It is adequately concise but not front-loaded; the pseudocode instruction could be separate. No wasted words, but structure could be improved.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should clarify what the tool returns. It mentions analysis and codebase checking but does not specify output format. The parameter details are covered by schema. Completeness is adequate but missing return value behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds no new meaning beyond the schema, except repeating the pseudocode hint. Baseline score of 3 is appropriate as the schema handles parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: analyzing task requirements, checking codebase, evaluating feasibility and risks. It uses specific verbs like '分析' and '檢查', and it distinguishes from siblings by focusing on analysis and risk assessment, though it could be more explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a guideline to use pseudocode format for code output, but it does not specify when to use this tool instead of siblings like plan_task or reflect_task. There is no explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
clear_all_tasksA
刪除系統中所有未完成的任務,該指令必須由用戶明確確認才能執行
| Name | Required | Description | Default |
|---|---|---|---|
| confirm | Yes | 確認刪除所有未完成的任務(此操作不可逆) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a destructive action via 'delete' and a confirmation requirement, but it lacks explicit disclosure of irreversibility or side effects. The parameter description (in schema) adds 'irreversible,' but the main description does not.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action and includes the confirmation requirement. Every word is purposeful with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple destructive tool with one parameter and no output schema, the description is fairly complete: it states what it does and the confirmation need. It could mention irreversibility explicitly, but the parameter description covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the sole parameter 'confirm' with a description of its role. The main description adds that the command requires user confirmation, which is a slight addition. With 100% schema coverage, baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies 'delete all incomplete tasks,' clearly stating the action and resource. It distinguishes itself from sibling tools like 'delete_task' by targeting all incomplete tasks versus a single task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly requires user confirmation before execution, providing a clear usage condition. However, it does not contrast with alternatives like 'delete_task' for individual tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
complete_taskB
正式標記任務為完成狀態,生成詳細的完成報告,並更新關聯任務的依賴狀態
| Name | Required | Description | Default |
|---|---|---|---|
| taskId | Yes | 待標記為完成的任務唯一標識符,必須是狀態為「進行中」的有效任務ID | |
| summary | No | 任務完成摘要,簡潔描述實施結果和重要決策(選填,如未提供將自動生成) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavioral traits. It mentions side effects (report generation, dependency updates) but omits details like permissions, reversibility, or what happens if the task is not in progress. The auto-generation of 'summary' is only in the schema, not repeated here.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, efficient and front-loaded with the verb '正式標記'. It packs three actions without excess, though the density slightly reduces readability. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about return values (no output schema) and does not clarify what the agent receives after completion (e.g., the report content or status). Given the complexity of a mutation tool that updates dependencies, more context is needed for the agent to understand the full effect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema: it does not explain taskId format or summary constraints, merely restating the concept of a completion summary. The tool description's mention of 'detailed completion report' is not a parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: marking a task as completed, generating a completion report, and updating dependency status. This distinguishes it from siblings like 'delete_task' or 'update_task', though no explicit sibling differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 versus alternatives. The description implicitly assumes use for tasks in progress (constraint on taskId), but does not specify when not to use or mention alternative tools like 'update_task' for partial updates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_taskA
刪除未完成的任務,但不允許刪除已完成的任務,確保系統記錄的完整性
| Name | Required | Description | Default |
|---|---|---|---|
| taskId | Yes | 待刪除任務的唯一標識符,必須是系統中存在且未完成的任務ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the key behavioral constraint of only allowing deletion of incomplete tasks, but does not mention other behaviors such as irreversibility, authorization needs, or error handling, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately conveys the core action and constraint with no extraneous words. It is front-loaded and highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the essential constraint. It could mention return format or error cases, but is otherwise adequate for use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the schema already provides a detailed description of taskId including the constraint. The tool description adds no new parameter information beyond what the schema states, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Delete incomplete tasks, but does not allow deletion of completed tasks,' which is a specific verb+resource with a scope constraint. It distinguishes from siblings like complete_task and update_task by focusing on deletion of incomplete tasks only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use (for incomplete tasks) and when not to use (not for completed tasks). However, it does not name alternative tools for handling completed tasks, which would improve guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
execute_taskC
按照預定義計劃執行特定任務,確保每個步驟的輸出符合質量標準
| Name | Required | Description | Default |
|---|---|---|---|
| taskId | Yes | 待執行任務的唯一標識符,必須是系統中存在的有效任務ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description lacks details on safety, failure modes, side effects, or whether the tool is idempotent. For a mutation tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is efficient and front-loaded, though it could benefit from a brief usage caveat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of task execution and the presence of 14 sibling tools, the description does not sufficiently distinguish its role or clarify return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The description adds no extra meaning beyond the schema's existing field documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool executes a task according to a predefined plan and ensures quality, but does not differentiate from siblings like complete_task or verify_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 analyze_task, plan_task, or verify_task.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_task_detailA
根據任務ID獲取任務的完整詳細信息,包括未截斷的實現指南和驗證標準等
| Name | Required | Description | Default |
|---|---|---|---|
| taskId | Yes | 欲檢視詳情的任務ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It hints at providing untruncated data (implying other tools may truncate), but does not state read-only nature, permissions, or rate limits. Adequate for a simple read operation but lacks explicit behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that front-loads the action and resource. In Chinese, concise but could be restructured for better readability. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers expected content (full details, implementation guide, verification standards). Could specify additional fields like status or timestamps, but sufficient for a get-detail tool among many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description '欲檢視詳情的任務ID'. The description adds context about what the returned details include (implementation guide, verification standards), providing value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (獲取) and resource (任務的完整詳細信息), and specifies what includes (未截斷的實現指南和驗證標準). It distinguishes from siblings like list_tasks and update_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing full task details including implementation guides, but does not explicitly state when to use vs alternatives like list_tasks or query_task. No exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_tasksA
生成結構化任務清單,包含完整狀態追蹤、優先級和依賴關係
| Name | Required | Description | Default |
|---|---|---|---|
| status | Yes | 要列出的任務狀態,可選擇 'all' 列出所有任務,或指定具體狀態 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It does not mention that the tool is read-only, has no side effects, or any authorization requirements. The description only covers output structure, leaving behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that covers the core functionality. It is front-loaded and efficient, though it lacks structural elements like bullet points that might improve scanability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description provides adequate context about the output (status, priority, dependencies). However, it could be improved by noting that the list is filterable by status and clarifying the scope (e.g., all tasks belonging to the current context).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides full description of the status parameter (enum values and meaning). The tool description adds no further parameter semantics beyond showing that the returned list includes additional fields (priority, dependencies), which is about output, not parameter meaning. Baseline 3 is appropriate due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a structured task list with status tracking, priority, and dependencies, which precisely defines its purpose. It distinguishes from sibling tools like get_task_detail (single task) and query_task (general query) by focusing on listing with filtering by status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing tasks filtered by status but does not explicitly state when to use this tool versus siblings like query_task or analyze_task. No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
plan_taskB
初始化並詳細規劃任務流程,建立明確的目標與成功標準,可選擇參考現有任務進行延續規劃
| Name | Required | Description | Default |
|---|---|---|---|
| description | Yes | 完整詳細的任務問題描述,應包含任務目標、背景及預期成果 | |
| requirements | No | 任務的特定技術要求、業務約束條件或品質標準(選填) | |
| existingTasksReference | No | 是否參考現有任務作為規劃基礎,用於任務調整和延續性規劃 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions establishing goals but does not disclose behavioral traits such as whether the tool modifies state, requires authentication, or has side effects (e.g., creating a plan object). The return value is not mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence in Chinese, covering purpose and optional reference. It is appropriately front-loaded and efficient, though slightly dense due to missing punctuation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and a complex domain (task planning), the description should explain what the tool returns or how it affects state. It lacks information on prerequisites, success criteria format, or the planning output, making it incomplete for agent selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds some context (e.g., '參考現有任務進行延續規劃' for `existingTasksReference`), but does not significantly extend beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it initializes and plans task flow, establishes goals and success criteria, and allows referencing existing tasks. This differentiates it from sibling tools like `execute_task` or `analyze_task`, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for initial planning by mentioning '初始化' and '延續規劃', but does not explicitly state when to use vs. alternatives like `split_tasks` or `update_task`. No 'when not to use' guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
process_thoughtA
你可以透過靈活的、可適應和發展的思考過程來分析問題,隨著理解的加深,每個想法都可以建立、質疑或修改先前的見解。你可以質疑想法、假設想法、驗證想法,並且可以建立新的想法。你將重複這個過程,直到你對問題有足夠的理解,並且能夠提出有效的解決方案。如果你覺得思考已經充分可以把 nextThoughtNeeded 設為 false 並且停止思考。
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | 思維標籤,是一個陣列字串 | |
| stage | Yes | 思考階段,可以選擇的階段有:問題定義、收集資訊、研究、分析、綜合、結論、質疑、規劃 | |
| thought | Yes | 思維內容 | |
| axioms_used | No | 使用的公理,是一個陣列字串 | |
| thought_number | Yes | 當前思維編號 | |
| total_thoughts | Yes | 預計總思維數量 | |
| next_thought_needed | Yes | 是否需要下一步思維 | |
| assumptions_challenged | No | 挑戰的假設,是一個陣列字串 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the iterative reasoning process but does not disclose potential side effects, logging, or safety implications beyond the cognitive process.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single block of Chinese text that efficiently conveys the tool's purpose and usage, though it could be slightly more condensed. It is front-loaded with the core idea.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 8 parameters (5 required) and no output schema, the description provides a comprehensive overview of the thinking process. It lacks explanation of specific parameter values like stage enums, but schema covers those.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented. The description does not add additional semantics beyond the process explanation, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: an adaptive thinking process to analyze problems by building, questioning, and modifying insights. It effectively distinguishes from sibling task management tools like 'analyze_task' or 'execute_task' by focusing on internal reasoning.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
While the description explains the iterative process and when to stop (set next_thought_needed to false), it does not explicitly state when to use this tool over alternatives, nor does it provide exclusion criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_taskB
根據關鍵字或ID搜尋任務,顯示省略版的任務資訊
| Name | Required | Description | Default |
|---|---|---|---|
| isId | No | 指定是否為ID查詢模式,默認為否(關鍵字模式) | |
| page | No | 分頁頁碼,默認為第1頁 | |
| query | Yes | 搜尋查詢文字,可以是任務ID或多個關鍵字(空格分隔) | |
| pageSize | No | 每頁顯示的任務數量,默認為5筆,最大20筆 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions 'abbreviated' results but does not define what fields are excluded. No mention of read-only nature, side effects, or auth requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loading the core purpose. However, it could be more structured by adding usage context or output details without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, and the description does not explain the return value format or fields in the 'abbreviated' results. For a search tool with 4 parameters, more detail on pagination and result structure is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema for parameters; it only describes the output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: search tasks by keyword or ID and display abbreviated information. It uses specific verb and resource, and distinguishes from siblings like get_task_detail (full detail) and list_tasks (list all).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by keyword or ID search, but does not explicitly state when not to use or mention alternative tools like get_task_detail for full details. No guidance on when to prefer this over list_tasks or other siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
reflect_taskB
批判性審查分析結果,評估方案完整性並識別優化機會,確保解決方案符合最佳實踐,如果需要提供程式碼請使用 pseudocode 格式且盡量精簡只保留核心實現部分
| Name | Required | Description | Default |
|---|---|---|---|
| summary | Yes | 結構化的任務摘要,保持與分析階段一致以確保連續性 | |
| analysis | Yes | 完整詳盡的技術分析結果,包括所有技術細節、依賴組件和實施方案,如果需要提供程式碼請使用 pseudocode 格式且盡量精簡只保留核心實現部分 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully carries the burden of behavioral disclosure. It fails to state whether the tool is read-only, modifies state, or has any side effects. While it describes the action, it omits crucial behavioral traits like permissions or output characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense sentence that combines purpose and a code format instruction. It is not overly long but lacks structure and could be better organized with bullet points or separate sentences for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not explain the return value or side effects, which is problematic since there is no output schema. It also fails to place the tool within the task workflow, leaving the agent unsure of its role among siblings like 'verify_task'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with detailed descriptions of 'summary' and 'analysis' parameters. The tool description repeats the pseudocode instruction but does not add new meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: critically review analysis results, evaluate completeness, and identify optimization opportunities. It uses specific verbs ('review', 'evaluate', 'identify') and a specific resource ('analysis results'), distinguishing it from sibling tools like 'analyze_task' which likely focuses on initial analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after analysis but provides no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or exclusions, leaving the agent to infer context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
split_tasksA
將複雜任務分解為獨立且可追蹤的子任務,建立明確的依賴關係和優先順序。支援四種任務更新模式:追加(append)、覆蓋(overwrite)、選擇性更新(selective)和清除所有任務(clearAllTasks),其中覆蓋模式只會刪除未完成的任務並保留已完成任務,選擇性更新模式可根據任務名稱智能匹配更新現有任務,同時保留其他任務,如果你需要規劃全新的任務請使用清除所有任務模式會清除所有任務並創建備份。請優先使用清除所有任務模式,只有用戶要求變更或修改計畫內容才使用其他模式。
**請參考之前的分析結果提供 pseudocode
**如果任務太多或內容過長,請分批使用「split_tasks」工具,每次只提交一小部分任務
| Name | Required | Description | Default |
|---|---|---|---|
| tasks | Yes | 結構化的任務清單,每個任務應保持原子性且有明確的完成標準 | |
| updateMode | Yes | 任務更新模式選擇:'append'(保留所有現有任務並添加新任務)、'overwrite'(清除所有未完成任務並完全替換,保留已完成任務)、'selective'(智能更新:根據任務名稱匹配更新現有任務,保留不在列表中的任務,推薦用於任務微調)、'clearAllTasks'(清除所有任務並創建備份)。 預設為'clearAllTasks'模式,只有用戶要求變更或修改計劃內容才使用其他模式 | |
| globalAnalysisResult | No | 全局分析結果:來自 reflect_task 的完整分析結果,適用於所有任務的通用部分 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description explains each update mode's behavior (e.g., overwrite deletes only unfinished tasks, clearAllTasks creates a backup). This discloses key behavioral traits, though it could mention error handling or idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose, followed by mode details and usage priority. Some redundancy exists (e.g., repeated mode explanations), but overall it is well-structured and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no output schema, and moderate complexity, the description covers all necessary aspects: mode behaviors, usage priority, and batch splitting instructions. It is sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the updateMode parameter's usage context (when each mode is appropriate) and the tasks' atomicity requirement, enhancing meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'split' (分解) and resource 'tasks', and specifies the outcome: creating independent sub-tasks with dependencies and priorities. This distinguishes it from sibling tools like update_task or execute_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly recommends prioritizing the 'clearAllTasks' mode and only using other modes when user requests changes. Also provides guidelines on batching and referencing previous analysis, giving clear when-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_taskB
更新任務內容,包括名稱、描述和注記,但不允許修改已完成的任務
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | 任務的新名稱(選填) | |
| notes | No | 任務的新補充說明(選填) | |
| taskId | Yes | 待更新任務的唯一標識符,必須是系統中存在且未完成的任務ID | |
| description | No | 任務的新描述內容(選填) | |
| dependencies | No | 任務的新依賴關係(選填) | |
| relatedFiles | No | 與任務相關的文件列表,用於記錄與任務相關的代碼文件、參考資料、要建立的檔案等(選填) | |
| implementationGuide | No | 任務的新實現指南(選填) | |
| verificationCriteria | No | 任務的新驗證標準(選填) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds key behavioral info (cannot modify completed tasks) but is incomplete. It does not mention authentication, side effects, or that other schema fields (e.g., dependencies) are actually updatable, potentially misleading the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the action. However, it could be structured to list all updatable fields or reference the schema for completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no output schema) and the presence of 14 sibling tools, the description is insufficient. It lacks details on return value, error handling (e.g., for completed tasks), and the full scope of updatable fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameter descriptions in the schema are complete. The tool description adds minimal value, only mentioning three fields (name, description, notes) while the schema includes many more, such as dependencies and relatedFiles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool updates task content, listing specific fields (name, description, notes) and includes a constraint (cannot modify completed tasks). However, it does not explicitly distinguish from sibling tools like 'complete_task' or 'update_task_files'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implicit usage context (when to update tasks) and a when-not condition (completed tasks). However, it lacks explicit guidance on when to use this tool versus alternatives like 'update_task_files' or 'complete_task'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_task_filesC
更新任務相關文件列表,用於記錄與任務相關的代碼文件、參考資料等
| Name | Required | Description | Default |
|---|---|---|---|
| taskId | Yes | 待更新任務的唯一標識符,必須是系統中存在且未完成的任務ID | |
| relatedFiles | Yes | 與任務相關的文件列表 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It only says 'update', implying mutation, but does not describe whether the update replaces or appends files, whether the task must exist and be incomplete, or any side effects. The schema includes validations, but the description adds no additional context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence in Chinese. It is front-loaded and contains no unnecessary words. However, it could be restructured to include more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has two required parameters and no output schema, the description should provide more context about behavior (e.g., whether the file list is replaced or appended, what happens if taskId is invalid) and return values. The current description is too minimal for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'taskId' and 'relatedFiles' have detailed descriptions in the schema. The tool description does not add new meaning beyond confirming that files are related to the task. With full schema coverage, the baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool updates the task-related file list for recording code files and references. The verb 'update' and resource 'file list' are specific, and the tool is differentiated from sibling tools like 'update_task' which likely updates task metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'update_task' or 'add_file'. There is no mention of prerequisites, context, or conditions that would influence the decision to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_taskB
全面驗證任務完成度,確保所有需求與技術標準都已滿足,並無遺漏細節
| Name | Required | Description | Default |
|---|---|---|---|
| taskId | Yes | 待驗證任務的唯一標識符,必須是系統中存在的有效任務ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It does not indicate whether the tool is read-only, modifies state, requires special permissions, or what happens upon failure. The phrase 'comprehensively verify' implies a check, but side effects or output behavior are not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence that immediately conveys the tool's purpose. It is front-loaded with the verb 'verify' and the object 'task completion', with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and annotations, the description should explain what the tool returns or any behavioral details. It does not mention whether it returns a boolean, a detailed report, or throws errors. For a verification tool, this lack of completeness leaves the agent guessing about the outcome.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a single parameter 'taskId' documented as a UUID for a valid task ID. The description adds no further semantic value beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to comprehensively verify task completion, ensuring all requirements and technical standards are met. It uses a specific verb ('verify') and resource ('task'), and distinguishes itself from sibling tools like 'complete_task' (marking done) and 'analyze_task' (analysis).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or when not to use it. For a verification tool, context on typical usage (e.g., after task execution) would be helpful but is absent.
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. Dates show when Glama detected each change.
15 tool updates
v1.0.0- First observed
analyze_task - First observed
clear_all_tasks - First observed
complete_task - First observed
delete_task - First observed
execute_task - First observed
get_task_detail - First observed
list_tasks - First observed
plan_task - First observed
process_thought - First observed
query_task - First observed
reflect_task - First observed
split_tasks - First observed
update_task - First observed
update_task_files - First observed
verify_task
TDQS
Scored across 15 tools
Most tools have distinct purposes (e.g., delete_task vs complete_task), but analyze_task and reflect_task both involve analysis and could cause confusion. process_thought is a generic cognitive tool that doesn't fit the task management domain. Overall, descriptions help differentiate.
All tools follow a consistent verb_noun pattern (e.g., list_tasks, update_task, complete_task). Even process_thought adheres to this pattern. No mixing of conventions like camelCase or inconsistent verb styles.
With 15 tools, the server is well-scoped for a task manager. Each tool serves a clear role in the task lifecycle, and the count falls within the optimal 3-15 range without feeling overly heavy or thin.
The tool set covers core task management operations: create (plan_task, split_tasks), read (list_tasks, get_task_detail, query_task), update (update_task, update_task_files), delete (delete_task, clear_all_tasks), and completion (complete_task, verify_task). Missing explicit dependency management or prioritization, but analysis tools (analyze, reflect, execute) add depth. process_thought is an outlier.
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