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VibeCoding System

by Zenobia000
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JavaScript
Hybrid

VibeCoding System 🚀

Build Status npm version License: MIT

Conversation-Driven Development Framework for Rapid MVP/POC Creation

VibeCoding 將傳統軟體開發轉換為 AI 引導的自然對話體驗。透過與專業 MCP 服務的智能對話，快速建構 MVP 和 POC。

📚 完整文檔導航

🎯 設定指南 (按順序閱讀)

  1. IDE 設定完全指南 - 主要設定文檔，支援所有 MCP Host

  2. Cursor MCP 專用說明 - Cursor 用戶必讀

  3. MCP 設定指南 - 深度配置和故障排除

  4. 部署指南 - 生產環境部署

🛠️ 工具與指令參考

🏗️ 架構與進階

Related MCP server: GenZ MCP Server

🚀 完整初始化流程

📦 步驟 1: 系統安裝與設定

# 1. 複製 VibeCoding 模板
git clone https://github.com/Zenobia000/vibeCoding-mcp.git
cd vibeCoding-template

# 2. 安裝依賴並建構系統
npm install && npm run build

# 3. 驗證系統狀態
npm run vibecoding status
# 預期輸出: ✅ All VibeCoding services are enabled

# 4. 測試提示系統
npm run test:prompts
# 預期輸出: 🎉 FULLY OPERATIONAL - All prompts are ready!

🏗️ 步驟 2: 建立你的專案資料夾

🚀 方法一：一鍵增強專案建立 (推薦)

# 建立新專案目錄
mkdir my-awesome-project
cd my-awesome-project

# 🚀 一鍵創建 VibeCoding 增強專案結構 (含專業模板)
# 🌟 推薦使用 v3 版本 (完整整合 v1+v2 所有優勢)
node /path/to/your/vibeCoding-template/scripts/create-enhanced-project-v3.cjs

# 其他版本選擇：
# v2 版本 (架構優化，遵循 .vibecoding/prompts 指導原則)
node /path/to/your/vibeCoding-template/scripts/create-enhanced-project-v2.cjs

# v1 版本 (完整內容)
node /path/to/your/vibeCoding-template/scripts/create-enhanced-project.cjs

# 🎉 完成！自動創建了：
# ✅ 5個開發階段資料夾 + 完整子資料夾結構
# ✅ 基於 design_templates 的專業模板
# ✅ 開發指南、測試策略、部署指南
# ✅ 專案簡報、架構文檔、ADR 模板
# ✅ README.md 和 .gitignore 文件

📝 方法二：手動建立基本結構

# 建立新專案目錄 (在任何位置)
mkdir my-awesome-project
cd my-awesome-project

# 初始化專案結構 (可選，VibeCoding 會自動建立)
mkdir -p {src,tests,docs,config}

# 初始化 git (推薦)
git init
echo "node_modules/" > .gitignore
echo "dist/" >> .gitignore
echo ".env" >> .gitignore

# 建立基本 package.json (可選，VibeCoding 可協助生成)
npm init -y

⚙️ 步驟 3: 配置 IDE 與 MCP 連接

Cursor IDE (推薦 - 無需 API 金鑰)

  1. 開啟 Cursor IDE 設定檔：

    # Windows
code "$env:APPDATA\Cursor\User\settings.json"

# macOS  
code "~/Library/Application Support/Cursor/User/settings.json"

# Linux
code ~/.config/Cursor/User/settings.json

  2. 添加 VibeCoding MCP 設定：

    {
  "mcpServers": {
    "vibecoding-context-manager": {
      "command": "node",
      "args": ["/path/to/your/vibeCoding-template/dist/vibe-services/context-manager/index.js"],
      "description": "VibeCoding 上下文管理服務"
    }
  },
  "vibecoding.enabled": true,
  "vibecoding.defaultProvider": "cursor"
}

  3. 重要: 將 /path/to/your/vibeCoding-template/ 替換為你的實際路徑

Claude Desktop

{
  "mcpServers": {
    "vibecoding-context-manager": {
      "command": "node", 
      "args": ["/path/to/your/vibeCoding-template/dist/vibe-services/context-manager/index.js"],
      "env": {
        "ANTHROPIC_API_KEY": "你的_ANTHROPIC_金鑰"
      }
    }
  }
}

其他 IDE

📖 完整設定指南: IDE 設定完全指南 - 支援 VSCode, WebStorm 等

📖 詳細說明: Cursor MCP 專用指南

🎯 步驟 4: 開始你的第一個 VibeCoding 專案

# 在你的專案資料夾中，使用 Cursor 或 Claude Desktop
# 輸入以下指令開始：

# 🆕 簡潔指令 (推薦)
@vibe start "我的專案名稱"

# 📝 完整指令 (向後相容)
@vibecoding-context-manager start-clarification

✅ 步驟 5: 驗證設定成功

在你的 IDE 中測試以下指令：

# 測試基本連接
@vibe start "測試專案"

# 如果看到類似以下回應，表示設定成功：
# 🚀 項目澄清已啟動
# 項目ID: proj_xxxxx
# 問題: 請描述這個專案的主要目標和預期解決的問題？

🌟 核心亮點

⚡ 革命性指令系統

  • 🆕 簡潔指令: @vibe start "專案名" - 平均減少 77% 輸入量

  • 🔄 向後相容: 完整指令仍可使用

  • 🧠 智能對話: 自然語言驅動的開發流程

🤖 6 個專業 MCP 服務

服務

功能

簡潔指令

📋 Context Manager

專案澄清與上下文管理

@vibe start, @vibe prd

⚡ Code Generator

AI 驅動的代碼生成

@vibe code, @vibe api

📦 Dependency Tracker

智能依賴分析

@vibe deps, @vibe scan

🧪 Test Validator

自動化測試生成

@vibe test, @vibe cover

📚 Doc Generator

智能文檔創建

@vibe doc, @vibe readme

🚀 Deployment Manager

CI/CD 與基礎設施自動化

@vibe deploy, @vibe monitor

💡 技術優勢

  • 多 AI 提供者支援: OpenAI, Anthropic, Gemini, 本地模型

  • 階段感知工作流: 動態 AI 指導適應開發階段

  • 模板系統: 豐富模板庫配合 AI 增強

  • 熱配置: 運行時切換提供者無需重啟

🎮 完整開發工作流程

🏗️ 在你的專案資料夾中開始

# 進入你的專案目錄
cd my-awesome-project

# 開啟 Cursor IDE 或其他已配置的 MCP Host
code .  # 或 cursor .

📋 Phase 1: 專案澄清與需求收集

# 🎯 1. 開始新專案澄清
@vibe start "任務管理系統"
# 系統提供 7 個結構化問題收集需求

# 🗨️ 2. 逐一回答澄清問題
@vibe ask "主要解決團隊協作和任務追蹤問題"
# 系統會引導你完成所有 7 個澄清問題

# 📋 3. 生成產品需求文檔 (PRD)
@vibe prd
# 自動創建全面的產品需求文檔並保存到專案中

🏗️ Phase 2: 設計與架構

# 📐 4. 生成實施計劃
@vibe plan
# 基於 PRD 生成詳細的技術實施計劃

# 🏛️ 5. 設計系統架構
@vibe arch "微服務架構，使用 Node.js + Express + MongoDB"
# 生成架構圖和技術選型說明

💻 Phase 3: 開發實作

# 🚀 6. 開始代碼開發
@vibe code "用戶認證系統，包含註冊、登入、JWT 驗證"
@vibe api "任務 CRUD 接口，支援建立、讀取、更新、刪除"

# 🔄 7. 代碼審查與重構
@vibe review "[剛生成的代碼]"
@vibe refactor "提升性能和可讀性"

🧪 Phase 4: 測試與驗證

# 🧪 8. 生成測試代碼
@vibe test
@vibe mock "[API 代碼]"

# 📊 9. 檢查測試覆蓋率
@vibe cover
# 驗證代碼品質和測試覆蓋率

🚀 Phase 5: 部署與監控

# 📚 10. 生成文檔
@vibe doc
@vibe readme

# 🚀 11. 部署應用
@vibe deploy
# 自動設定 CI/CD 流程並部署到雲端平台

🎯 快速原型模式 (30 分鐘 MVP)

# 一鍵式快速開發流程
@vibe start "快速原型"        # 2 分鐘澄清
@vibe prd                     # 1 分鐘生成 PRD  
@vibe code "核心功能"         # 10 分鐘開發
@vibe test                    # 5 分鐘測試
@vibe deploy                  # 12 分鐘部署
# 🎉 30 分鐘完成 MVP！

🏗️ 系統架構

核心服務架構

VibeCoding MCP Server
├── 📋 Context Manager       → 持久化對話與專案狀態
├── ⚡ Code Generator       → AI 驅動的代碼生成  
├── 📦 Dependency Tracker  → 智能依賴管理
├── 🧪 Test Validator      → 自動化測試與品質分析
├── 📚 Doc Generator       → 智能文檔創建
└── 🚀 Deployment Manager → CI/CD 與基礎設施自動化

AI 提示系統

位於 .vibecoding/prompts/，提供智能指導：

  • 核心提示 (3): 系統身份、對話風格、協作規則

  • 服務提示 (6): 每個 MCP 服務的專業提示

  • 工作流提示 (5): 階段特定的開發指導

  • 動態載入: 適應當前專案階段和上下文

開發階段

0_discovery/     → 需求收集和澄清
1_design/        → 架構和 API 設計
2_implementation/→ 源代碼和測試
3_validation/    → 測試報告和品質指標
4_deployment/    → 部署配置
knowledge-base/  → 模式、解決方案和回顧

🔧 API Reference

Context Manager 核心 API

// 開始專案澄清
start-clarification(projectName: string, initialDescription?: string)

// 提供澄清回答
provide-clarification(questionIndex: number, answer: string)

// 生成 PRD
generate-prd()

// 生成實施計劃
generate-impl-plan()

其他服務 API

  • Code Generator: generate-code, code-review, refactor-code

  • Dependency Tracker: analyze-dependencies, security-scan, update-dependencies

  • Test Validator: run-tests, validate-coverage, performance-test

  • Doc Generator: generate-docs, create-api-docs, generate-changelog

  • Deployment Manager: deploy-service, setup-monitoring, rollback-deployment

📖 完整 API 文檔: 工具參考手冊

⚙️ 配置與客製化

系統需求

  • Node.js: >= 18.0.0

  • npm: >= 8.0.0

  • 操作系統: Windows 10/11, macOS, Linux

  • 記憶體: >= 4GB RAM

AI 提供者配置

# 環境變數設定
OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key
GEMINI_API_KEY=your_gemini_key

進階配置

  • 多環境配置: 開發、測試、生產環境分離

  • 團隊協作設定: 共享配置和最佳實踐

  • 企業級部署: 安全性和擴展性考量

📖 完整配置指南: MCP 設定指南

🔍 故障排除

常見問題快速修復

❌ 初始化相關問題

# Q1: VibeCoding 系統初始化失敗
npm cache clean --force && npm install && npm run build

# Q2: npm run vibecoding status 指令無法執行
# 確保在 vibeCoding-template 目錄中執行
cd /path/to/your/vibeCoding-template
npm run vibecoding status

# Q3: MCP 服務無法啟動  
npm run build && npm run test:prompts

# Q4: 找不到 dist/ 目錄
# 重新建構系統
npm run build
ls -la dist/vibe-services/  # 確認服務檔案存在

❌ 專案設定相關問題

# Q5: 在專案資料夾中無法使用 @vibe 指令
# 確保 IDE 已正確配置 MCP 設定，並重啟 IDE

# Q6: 路徑配置問題 - 找不到 VibeCoding 服務
# 使用絕對路徑，確認 dist/ 目錄存在
# Windows 範例: "C:\\Users\\YourName\\vibeCoding-template\\dist\\vibe-services\\context-manager\\index.js"
# macOS/Linux 範例: "/Users/YourName/vibeCoding-template/dist/vibe-services/context-manager/index.js"

# Q7: 專案資料夾結構問題
# VibeCoding 會自動創建需要的資料夾，但你也可以手動建立：
mkdir -p {0_discovery,1_design,2_implementation,3_validation,4_deployment}

❌ IDE 配置相關問題

# Q8: Cursor IDE 無法識別 @vibe 指令
# 1. 檢查 settings.json 格式是否正確 (不能有註解)
# 2. 重啟 Cursor IDE
# 3. 確認 mcpServers 配置正確

# Q9: Claude Desktop 連接失敗
# 1. 檢查 claude_desktop_config.json 格式
# 2. 確認 API 金鑰設定正確
# 3. 重啟 Claude Desktop

# Q10: 權限問題 (Windows)
# 以管理員身分執行 PowerShell，設定執行政策：
Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

獲取幫助

🤝 Contributing

我們歡迎貢獻！請查看 Contributing Guide 了解詳情。

📝 License

本專案採用 MIT License - 詳見 LICENSE 文件。

✅ 設定完成檢查清單

在開始使用 VibeCoding 之前，請確認以下項目：

🔧 系統設定檢查

  • Node.js >= 18.0.0 (node --version)

  • VibeCoding 已下載並建構 (npm run build 成功)

  • 系統狀態正常 (npm run vibecoding status 顯示 ✅)

  • 提示系統運作 (npm run test:prompts 顯示 🎉)

📁 專案設定檢查

  • 專案資料夾已建立 (mkdir my-project && cd my-project)

  • Git 初始化 (git init 和 .gitignore 設定)

  • IDE 已開啟專案 (code . 或 cursor .)

⚙️ IDE 配置檢查

  • MCP 設定檔已修改 (settings.json 或 claude_desktop_config.json)

  • VibeCoding 路徑正確 (使用絕對路徑)

  • IDE 已重啟 (重啟後配置才生效)

  • 測試指令成功 (@vibe start "測試" 有回應)

🎯 準備開始開發

  • 選擇開發模式:

    • 📋 完整流程: 從需求澄清開始 (@vibe start "專案名")

    • ⚡ 快速原型: 30 分鐘 MVP 模式

    • 💻 直接開發: 跳過澄清，直接生成代碼

🚀 現在開始享受 AI 驅動的對話式開發體驗！

📚 推薦學習路徑

  1. 新手: IDE 設定完全指南 → 完成一個簡單專案

  2. 進階: 完整工具參考手冊 → 探索所有功能

  3. 專家: 架構設計文檔 → 客製化和擴展

💡 提示: 遇到問題？查看上方的 🔍 故障排除 或參考 GitHub Issues

Available Tools

4 tools
generate-impl-planB

Generate a project implementation plan and save it

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates and saves a plan, implying a write operation, but doesn't disclose critical traits: whether it requires user input, how it handles errors, what format the output is in, or if there are rate limits. The description is too vague for a mutation tool with zero annotation coverage.

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

Conciseness5/5

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action ('generate') and includes the secondary action ('save it') concisely. Every word earns its place, making it easy to parse quickly.

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

Completeness2/5

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

Given the tool's complexity (generating and saving a plan, implying mutation) and lack of annotations or output schema, the description is incomplete. It doesn't explain what the plan includes, how it's saved, or what the return value is. For a tool with behavioral implications and no structured support, more detail is needed to guide an agent effectively.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate. Baseline is 4 for zero parameters, as there's nothing to compensate for, and the description doesn't contradict the schema.

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

Purpose4/5

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

The description clearly states the tool's purpose with a specific verb ('generate') and resource ('project implementation plan'), plus an additional action ('save it'). It distinguishes from sibling tools like 'generate-prd' (which creates a different document) and 'provide-clarification'/'start-clarification' (which handle queries rather than planning). However, it doesn't specify what 'save it' entails (e.g., where it's saved), keeping it from a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing project details first), exclusions (e.g., not for small tasks), or comparisons to siblings like 'generate-prd' (for requirements docs) or clarification tools. Usage is implied only by the tool's name and purpose, lacking explicit context.

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

generate-prdB

Generate a project PRD and save it to the project structure

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions generating and saving a PRD, implying a write operation, but doesn't specify permissions needed, whether it overwrites existing files, or the format/location of the saved output. This leaves significant gaps for a tool that modifies project structure.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core action and outcome with zero waste. It uses clear language and avoids unnecessary elaboration, making it easy to parse quickly.

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

Completeness2/5

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

Given the complexity of generating and saving a document (a write operation with potential side effects), no annotations, and no output schema, the description is insufficient. It doesn't explain what a PRD entails, how it's structured, or what 'save it to the project structure' means in practice, leaving the agent with unclear expectations.

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

Parameters4/5

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

There are 0 parameters, and schema description coverage is 100%, so the schema fully documents the lack of inputs. The description doesn't need to add parameter details, and it appropriately focuses on the tool's purpose without redundant information, meeting the baseline for no parameters.

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

Purpose4/5

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

The description clearly states the action ('generate a project PRD') and the outcome ('save it to the project structure'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'generate-impl-plan' or 'provide-clarification', which might involve similar documentation tasks.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'generate-impl-plan' or 'provide-clarification'. It lacks context about prerequisites, such as whether a project must be initialized first, or exclusions for when not to use it.

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

provide-clarificationD

Provide a clarification answer

ParametersJSON Schema
NameRequiredDescriptionDefault
answerYes
questionIndexYes

TDQS

D1.7/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails completely. It doesn't indicate whether this is a read or write operation, what permissions might be required, whether it has side effects, what format the clarification takes, or how it interacts with the system. The single phrase offers no behavioral insight beyond the basic action implied by the name.

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

Conciseness5/5

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

The description is maximally concise - a single three-word phrase with no wasted words. While this conciseness comes at the expense of completeness, the description is perfectly structured as a minimal statement of function without unnecessary elaboration or redundancy.

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

Completeness1/5

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

Given the complexity implied by having two required parameters, no annotations, no output schema, and sibling tools that suggest this is part of a larger workflow, the description is completely inadequate. It doesn't explain what a 'clarification answer' is, how it relates to the parameters, what the tool actually does with the input, or what the expected outcome is. This leaves the agent with insufficient information to use the tool effectively.

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

Parameters1/5

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

With 0% schema description coverage and two required parameters ('answer' and 'questionIndex'), the description provides zero information about what these parameters mean or how they should be used. The description doesn't mention parameters at all, leaving the agent with no semantic understanding of what 'answer' should contain or what 'questionIndex' refers to in the context of providing clarification.

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

Purpose2/5

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

The description 'Provide a clarification answer' is a tautology that essentially restates the tool name 'provide-clarification' with minimal additional meaning. It doesn't specify what kind of clarification, for what purpose, or what resource/context it operates on. While it includes the verb 'provide' and object 'clarification answer', this is too vague to understand the tool's specific function.

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

Usage Guidelines1/5

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

The description provides absolutely no guidance about when to use this tool versus alternatives. With sibling tools like 'generate-impl-plan', 'generate-prd', and 'start-clarification' available, there's no indication of how this tool fits into a workflow or when it should be selected over those other options. The description is completely silent on usage context.

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

start-clarificationC

Start a project clarification process

ParametersJSON Schema
NameRequiredDescriptionDefault
initialDescriptionNoInitial description of the project
projectNameYesThe name of the project

TDQS

C2.9/5.0
Behavior2/5

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 states 'start a process' but doesn't disclose behavioral traits like whether this initiates a long-running task, requires user authentication, has side effects, or what the expected outcome is. This leaves significant gaps for an agent to understand the tool's behavior.

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

Conciseness5/5

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

The description is a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for the tool's purpose, making it easy to parse quickly.

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

Completeness2/5

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

Given the complexity of starting a process with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, how the clarification process works, or any behavioral context, leaving the agent with insufficient information for effective use.

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

Parameters3/5

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

The input schema has 100% description coverage, with clear documentation for both parameters. The description adds no additional meaning beyond the schema, such as explaining how 'initialDescription' and 'projectName' relate to the clarification process. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the action ('start') and the resource ('project clarification process'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'provide-clarification' or 'generate-prd', which might involve similar clarification activities, so it's not fully specific.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'provide-clarification' or 'generate-prd'. It lacks context about prerequisites, such as whether this is an initial step in a workflow or when it's appropriate to invoke.

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.

  1. 4 tool updatesv1.0.0
    • First observedgenerate-impl-plan
    • First observedgenerate-prd
    • First observedprovide-clarification
    • First observedstart-clarification
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TDQS

C2.9/5.0
Disambiguation4/5

The tools have mostly distinct purposes: generate-impl-plan and generate-prd both generate documents but target different outputs (implementation plan vs PRD), while start-clarification and provide-clarification form a clear two-step clarification workflow. There is minor potential confusion between the two generation tools, but their descriptions clarify the different document types.

Naming Consistency4/5

All tools use kebab-case consistently. Three tools follow a verb-noun pattern (generate-impl-plan, generate-prd, provide-clarification), while start-clarification uses a verb-noun pattern but with a slightly different verb style. The naming is mostly consistent with one minor deviation.

Tool Count5/5

With 4 tools, this is a well-scoped set for a project planning/development assistance system. Each tool serves a clear purpose in the workflow: generating documents (PRD and implementation plan) and handling clarification processes. The count is appropriate and manageable for the domain.

Completeness4/5

The toolset covers key project initiation activities: generating both PRD and implementation plans, plus a clarification workflow. A minor gap exists in document management (e.g., no tools to list, update, or delete generated documents), but the core workflow is complete and agents can work around this limitation.

Maintenance

ActivityInactive
ResponsivenessSyncing

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