Shrimp Task Manager
目录
MCP Shrimp 任务管理器

🚀 基于模型上下文协议(MCP)的智能任务管理系统,为AI代理提供高效的编程工作流框架。
Shrimp Task Manager 通过结构化的工作流引导 Agent 进行系统化编程,增强任务内存管理机制,有效避免冗余重复的编码工作。
Related MCP server: Vibe Coder MCP
✨ 特点
任务规划与分析:深入理解和分析复杂的任务需求
智能任务分解:自动将大任务分解为可管理的小任务
依赖管理:精确处理任务之间的依赖关系,确保正确的执行顺序
执行状态追踪:实时监控任务执行进度及状态
任务完整性验证:确保任务结果满足预期要求
任务复杂度评估:自动评估任务复杂度并提供最优处理建议
自动任务摘要更新:任务完成后自动生成摘要,优化内存性能
任务记忆功能:自动备份任务历史记录,提供长期记忆和参考能力
研究模式:系统的技术研究能力,具有探索技术、最佳实践和解决方案比较的指导工作流程
项目规则初始化:定义项目标准和规则,以保持大型项目的一致性
Web GUI :提供可选的基于 Web 的图形用户界面,用于任务管理。通过在
.env文件中设置ENABLE_GUI=true来启用。启用后,将在DATA_DIR中创建一个包含访问地址的WebGUI.md文件。
🧭 使用指南
Shrimp Task Manager 通过引导式工作流程和系统化任务管理为 AI 辅助编程提供结构化方法。
什么是虾?
Shrimp 本质上是一个提示模板,用于引导 AI 代理更好地理解和处理您的项目。它使用一系列提示来确保代理与您项目的特定需求和惯例紧密契合。
研究模式实践
在深入任务规划之前,您可以利用研究模式进行技术调查和知识收集。这在以下情况下尤其有用:
你需要探索新技术或框架
您想比较不同的解决方案
您正在调查项目的最佳实践
你需要理解复杂的技术概念
只需告诉代理“研究[你的主题]”或“进入[技术/问题]研究模式”,即可开始系统性调查。研究结果将为你后续的任务规划和开发决策提供参考。
首次设置
在处理新项目时,只需告诉代理“初始化项目规则”。这将引导代理生成一套根据项目特定需求和结构定制的规则。
任务规划流程
要开发或更新功能,请使用命令“plan task [您的描述]”。系统将参考之前制定的规则,尝试了解您的项目,搜索相关的代码段,并根据项目的当前状态提出全面的计划。
反馈机制
在规划过程中,Shrimp 会引导 Agent 完成多个思考步骤。您可以回顾此流程,如果觉得方向不对,可以提出反馈。只需打断并分享您的观点,Agent 就会采纳您的反馈,并继续规划流程。
任务执行
当您对计划满意后,使用“执行任务 [任务名称或 ID]”来执行该计划。如果您未指定任务名称或 ID,系统将自动识别并执行优先级最高的任务。
连续模式
如果您希望按顺序执行所有任务而不手动干预每个任务,请使用“连续模式”自动处理整个任务队列。
代币限制说明
由于 LLM 令牌限制,长时间对话中可能会丢失上下文。如果发生这种情况,只需打开新的聊天会话并请求代理继续执行即可。系统将从中断处继续执行,无需您重复任务详细信息或上下文。
提示语言和定制
您可以通过设置TEMPLATES_USE环境变量来切换系统提示语言。它默认支持en (英语)和zh (繁体中文)。此外,您还可以将现有模板目录(例如src/prompts/templates_en )复制到DATA_DIR指定的位置,进行修改,然后将TEMPLATES_USE指向您的自定义模板目录名称。这允许更深入地自定义提示。有关详细说明,请参阅。
🔬 研究模式
Shrimp Task Manager 包含一个专门的研究模式,旨在进行系统的技术调查和知识收集。
什么是研究模式?
研究模式是一个引导式工作流系统,可帮助 AI 代理进行全面而系统的技术研究。它提供了结构化的方法来探索技术、比较解决方案、研究最佳实践以及收集编程任务所需的全面信息。
主要特点
系统调查:结构化的工作流程确保全面覆盖研究主题
多源研究:结合网络搜索和代码库分析,以获得全面理解
状态管理:维护多个会话中的研究背景和进度
引导式探索:防止研究失去重点或偏离主题
知识整合:将研究成果与任务规划和执行无缝集成
何时使用研究模式
研究模式对于以下方面尤其有价值:
技术探索:研究新的框架、库或工具
最佳实践研究:寻找行业标准和推荐方法
解决方案比较:评估不同的技术方法或架构
问题调查:深入探究复杂的技术挑战
架构规划:研究设计模式和系统架构
如何使用研究模式
只需告诉代理进入您的主题的研究模式:
基本用法:“进入[你的主题]研究模式”
具体研究:“研究[具体技术/问题]”
比较分析:“研究并比较[选项 A 与 B]”
该系统将指导代理完成结构化的研究阶段,确保彻底调查,同时关注您的特定需求。
研究工作流程
主题定义:明确研究范围和目标
信息收集:系统地收集相关信息
分析与综合:处理和组织研究结果
状态更新:定期进度跟踪和上下文保存
整合:将研究成果应用到你的项目环境中
💡 建议:为了获得最佳研究模式体验,我们建议使用Claude 4 Sonnet ,它提供卓越的分析能力和全面的研究综合。
🧠 任务记忆功能
Shrimp Task Manager 具有长期记忆功能,自动保存任务执行历史,为规划新任务时提供参考经验。
主要特点
系统自动备份任务到内存目录
备份文件按时间顺序命名,格式为tasks_backup_YYYY-MM-DDThh-mm-ss.json
任务规划代理自动接收如何使用记忆功能的指导
优势和好处
避免重复工作:参考过去的任务,无需从头开始解决类似的问题
学习成功经验:利用经过验证的有效解决方案,提高开发效率
学习与改进:找出过去的错误或低效的解决方案,不断优化工作流程
知识积累:随着系统使用量的增加,形成不断扩大的知识库
通过有效利用任务记忆功能,系统可以不断积累经验,智能水平和工作效率不断提高。
📋 项目规则初始化
项目规则功能有助于维护整个代码库的一致性:
标准化开发:建立一致的编码模式和实践
加入新开发人员:为项目贡献提供明确的指导
保持质量:确保所有代码符合既定的项目标准
⚠️ 建议:当项目规模扩大或发生重大变更时,初始化项目规则。这有助于在项目复杂性增加的情况下保持一致性和质量。
在以下情况下,使用init_project_rules工具来设置或更新项目标准:
启动一个新的大型项目
招募新团队成员
实施重大架构变革
采用新的开发惯例
使用示例
您可以使用简单的自然语言命令轻松访问此功能:
对于初始设置:只需告诉代理“初始化规则”或“初始化项目规则”
对于更新:当您的项目进展时,告诉代理“更新规则”或“更新项目规则”
当您的代码库扩展或经历重大结构变化时,此工具特别有价值,有助于在整个项目生命周期内保持一致的开发实践。
📚 文档资源
🔧 安装和使用
通过 Smithery 安装
要通过Smithery自动为 Claude Desktop 安装 Shrimp Task Manager:
npx -y @smithery/cli install @cjo4m06/mcp-shrimp-task-manager --client claude手动安装
# Install dependencies
npm install
# Build and start service
npm run build🔌 与 MCP 兼容的客户端一起使用
Shrimp Task Manager 可以与任何支持模型上下文协议的客户端一起使用,例如 Cursor IDE。
Cursor IDE 中的配置
Shrimp Task Manager 提供两种配置方式:全局配置和项目特定配置。
全局配置
打开 Cursor IDE 全局配置文件(通常位于
~/.cursor/mcp.json)在
mcpServers部分添加以下配置:
{
"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"
}
}
}
}⚠️ 请将
/mcp-shrimp-task-manager替换为你的实际路径。
项目特定配置
您还可以为每个项目设置专用配置,以便为不同的项目使用独立的数据目录:
在项目根目录中创建
.cursor目录在此目录中创建一个
mcp.json文件,其内容如下:
{
"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"
}
}
}
}⚠️ 重要配置说明
DATA_DIR 参数是 Shrimp Task Manager 存储任务数据、对话日志等信息的目录。正确设置此参数对于系统的正常运行至关重要。此参数必须使用绝对路径;使用相对路径可能会导致系统错误地定位数据目录,从而导致数据丢失或功能失败。
警告:使用相对路径可能会导致以下问题:
找不到数据文件,导致系统初始化失败
任务状态丢失或无法正确保存
不同环境中的应用程序行为不一致
系统崩溃或无法启动
🔧 环境变量配置
Shrimp Task Manager 支持通过环境变量自定义提示行为,让您无需修改代码即可微调 AI 助手的响应。您可以在配置中或通过.env文件设置这些变量:
{
"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"
}
}
}
}定制方法有两种:
覆盖模式(
MCP_PROMPT_[FUNCTION_NAME]):完全替换默认提示附加模式(
MCP_PROMPT_[FUNCTION_NAME]_APPEND):将内容添加到现有提示
此外,还有其他系统配置变量:
DATA_DIR :指定存储任务数据的目录
TEMPLATES_USE :指定提示使用的模板集。默认为
en。当前可用选项为en和zh。要使用自定义模板,请将src/prompts/templates_en目录复制到DATA_DIR指定的位置,重命名复制的目录(例如,重命名为my_templates),并将TEMPLATES_USE设置为新的目录名称(例如,my_templates)。
有关自定义提示的详细说明(包括支持的参数和示例),请参阅提示自定义指南。
💡系统提示引导
游标 IDE 配置
您可以启用“光标设置”=>“功能”=>“自定义模式”,并配置以下两种模式:
TaskPlanner模式
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.TaskExecutor模式
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.💡根据您的需求选择合适的模式:
计划任务时使用TaskPlanner模式
执行任务时使用TaskExecutor模式
与其他工具一起使用
如果您的工具不支持自定义模式,您可以:
在不同阶段手动粘贴适当的提示
或者直接使用简单的命令,如
Please plan the following task: ......或Please start executing the task...
🛠️ 可用工具概览
配置完成后,您可以使用以下工具:
类别 | 工具名称 | 描述 |
任务规划 |
| 开始规划任务 |
任务分析 |
| 深入分析任务需求 |
| 复杂问题的逐步推理 | |
解决方案评估 |
| 反思并改进解决方案概念 |
研究与调查 |
| 进入系统化技术研究模式 |
项目管理 |
| 初始化或更新项目标准和规则 |
任务管理 |
| 将任务分解为子任务 |
| 显示所有任务和状态 | |
| 搜索和列出任务 | |
| 显示完整的任务详细信息 | |
| 删除未完成的任务 | |
任务执行 |
| 执行特定任务 |
| 验证任务完成情况 |
🔧 技术实现
Node.js :高性能 JavaScript 运行时环境
TypeScript :提供类型安全的开发环境
MCP SDK :与大型语言模型无缝交互的接口
UUID :生成唯一且可靠的任务标识符
📄 许可证
该项目根据 MIT 许可证获得许可 - 有关详细信息,请参阅LICENSE文件。
推荐型号
为了获得最佳体验,我们建议使用以下模型:
Claude 3.7 :提供强大的理解和生成能力。
Gemini 2.5 :谷歌最新型号,性能出色。
由于不同模型的训练方法和理解能力存在差异,使用其他模型对相同问题进行处理可能会导致结果不同。本项目已针对 Claude 3.7 和 Gemini 2.5 进行了优化。
星史
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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