docs: add CLI tools collaboration mode to Workflow Decision Guide

Add comprehensive section on multi-model CLI collaboration (Gemini/Qwen/Codex):
- Three execution modes: serial, parallel, and hybrid
- Semantic invocation vs command invocation patterns
- Integration examples with Lite and Full workflows
- Best practices for tool selection and execution strategies

Updates both Chinese and English versions with practical examples showing
how to leverage ultra-long context models (Gemini/Qwen) for analysis and
Codex for precise code implementation.
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Claude
2025-11-20 09:51:50 +00:00
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---
### 7⃣ **CLI 工具协作模式 - 多模型智能协同**
本项目集成了三种 CLI 工具,支持灵活的串联、并行和混合执行方式:
| 工具 | 核心能力 | 上下文长度 | 适用场景 |
|------|---------|-----------|---------|
| **Gemini** | 深度分析、架构设计、规划 | 超长上下文 | 代码理解、执行流追踪、技术方案评估 |
| **Qwen** | 代码审查、模式识别 | 超长上下文 | Gemini 备选、多维度分析 |
| **Codex** | 精确代码撰写、Bug定位 | 标准上下文 | 功能实现、测试生成、代码重构 |
#### 📋 三种执行模式
**1. 串联执行Serial Execution** - 顺序依赖
适用场景:后续任务依赖前一任务的结果
```bash
# 示例:分析后实现
# Step 1: Gemini 分析架构
使用 gemini 分析认证模块的架构设计,识别关键组件和数据流
# Step 2: Codex 基于分析结果实现
让 codex 根据上述架构分析,实现 JWT 认证中间件
```
**执行流程**
```
Gemini 分析 → 输出架构报告 → Codex 读取报告 → 实现代码
```
---
**2. 并行执行Parallel Execution** - 同时进行
适用场景:多个独立任务,无依赖关系
```bash
# 示例:多维度分析
用 gemini 分析认证模块的安全性,关注 JWT、密码存储、会话管理
用 qwen 分析认证模块的性能瓶颈,识别慢查询和优化点
让 codex 为认证模块生成单元测试,覆盖所有核心功能
```
**执行流程**
```
┌─ Gemini: 安全分析 ─┐
并行 ───┼─ Qwen: 性能分析 ──┼─→ 汇总结果
└─ Codex: 测试生成 ─┘
```
---
**3. 混合执行Hybrid Execution** - 串并结合
适用场景:复杂任务,部分并行、部分串联
```bash
# 示例:完整功能开发
# Phase 1: 并行分析(独立任务)
使用 gemini 分析现有认证系统的架构模式
用 qwen 评估 OAuth2 集成的技术方案
# Phase 2: 串联实现(依赖 Phase 1
让 codex 基于上述分析,实现 OAuth2 认证流程
# Phase 3: 并行优化(独立任务)
用 gemini 审查代码质量和安全性
让 codex 生成集成测试
```
**执行流程**
```
Phase 1: Gemini 分析 ──┐
Qwen 评估 ────┼─→ Phase 2: Codex 实现 ──→ Phase 3: Gemini 审查 ──┐
│ Codex 测试 ──┼─→ 完成
└────────────────────────────────────────────────┘
```
---
#### 🎯 语义调用 vs 命令调用
**方式一:自然语言语义调用**(推荐)
```bash
# 用户只需自然描述Claude Code 自动调用工具
"使用 gemini 分析这个模块的依赖关系"
→ Claude Code 自动生成cd src && gemini -p "分析依赖关系"
"让 codex 实现用户注册功能"
→ Claude Code 自动生成codex -C src/auth --full-auto exec "实现注册"
```
**方式二:直接命令调用**
```bash
# 通过 Slash 命令精准调用
/cli:chat --tool gemini "解释这个算法"
/cli:analyze --tool qwen "分析性能瓶颈"
/cli:execute --tool codex "优化查询性能"
```
---
#### 🔄 工作流集成示例
**集成到 Lite 工作流**
```bash
# 1. 规划阶段Gemini 分析
/workflow:lite-plan -e "重构支付模块"
→ 三维确认选择 "CLI 工具执行"
# 2. 执行阶段:选择执行方式
# 选项 A: 串联执行
"使用 gemini 分析支付流程""让 codex 重构代码"
# 选项 B: 并行分析 + 串联实现
"用 gemini 分析架构" + "用 qwen 评估方案"
"让 codex 基于分析结果重构"
```
**集成到 Full 工作流**
```bash
# 1. 规划阶段
/workflow:plan "实现分布式缓存"
/workflow:action-plan-verify
# 2. 分析阶段(并行)
使用 gemini 分析现有缓存架构
用 qwen 评估 Redis 集群方案
# 3. 实现阶段(串联)
/workflow:execute # 或使用 CLI
让 codex 实现 Redis 集群集成
# 4. 测试阶段(并行)
/workflow:test-gen WFS-cache
→ 内部使用 gemini 分析 + codex 生成测试
# 5. 审查阶段(串联)
用 gemini 审查代码质量
/workflow:review --type architecture
```
---
#### 💡 最佳实践
**何时使用串联**
- 实现依赖设计方案
- 测试依赖代码实现
- 优化依赖性能分析
**何时使用并行**
- 多维度分析(安全+性能+架构)
- 多模块独立开发
- 同时生成代码和测试
**何时使用混合**
- 复杂功能开发(分析→设计→实现→测试)
- 大规模重构(评估→规划→执行→验证)
- 技术栈迁移(调研→方案→实施→优化)
**工具选择建议**
1. **需要理解代码** → Gemini首选或 Qwen
2. **需要编写代码** → Codex
3. **复杂分析** → Gemini + Qwen 并行(互补验证)
4. **精确实现** → Codex基于 Gemini 分析)
5. **快速原型** → 直接使用 Codex
---
## 🔄 典型场景完整流程
### 场景A新功能开发知道怎么做

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---
### 7⃣ **CLI Tools Collaboration Mode - Multi-Model Intelligent Coordination**
This project integrates three CLI tools supporting flexible serial, parallel, and hybrid execution:
| Tool | Core Capabilities | Context Length | Use Cases |
|------|------------------|----------------|-----------|
| **Gemini** | Deep analysis, architecture design, planning | Ultra-long context | Code understanding, execution flow tracing, technical solution evaluation |
| **Qwen** | Code review, pattern recognition | Ultra-long context | Gemini alternative, multi-dimensional analysis |
| **Codex** | Precise code writing, bug location | Standard context | Feature implementation, test generation, code refactoring |
#### 📋 Three Execution Modes
**1. Serial Execution** - Sequential dependency
Use case: Subsequent tasks depend on previous results
```bash
# Example: Analyze then implement
# Step 1: Gemini analyzes architecture
Use gemini to analyze the authentication module's architecture design, identify key components and data flow
# Step 2: Codex implements based on analysis
Have codex implement JWT authentication middleware based on the above architecture analysis
```
**Execution flow**:
```
Gemini analysis → Output architecture report → Codex reads report → Implement code
```
---
**2. Parallel Execution** - Concurrent processing
Use case: Multiple independent tasks with no dependencies
```bash
# Example: Multi-dimensional analysis
Use gemini to analyze authentication module security, focus on JWT, password storage, session management
Use qwen to analyze authentication module performance bottlenecks, identify slow queries and optimization points
Have codex generate unit tests for authentication module, covering all core features
```
**Execution flow**:
```
┌─ Gemini: Security analysis ─┐
Parallel ┼─ Qwen: Performance analysis ┼─→ Aggregate results
└─ Codex: Test generation ────┘
```
---
**3. Hybrid Execution** - Combined serial and parallel
Use case: Complex tasks with both parallel and serial phases
```bash
# Example: Complete feature development
# Phase 1: Parallel analysis (independent tasks)
Use gemini to analyze existing authentication system architecture patterns
Use qwen to evaluate OAuth2 integration technical solutions
# Phase 2: Serial implementation (depends on Phase 1)
Have codex implement OAuth2 authentication flow based on above analysis
# Phase 3: Parallel optimization (independent tasks)
Use gemini to review code quality and security
Have codex generate integration tests
```
**Execution flow**:
```
Phase 1: Gemini analysis ──┐
Qwen evaluation ──┼─→ Phase 2: Codex implementation ──→ Phase 3: Gemini review ──┐
│ Codex tests ───┼─→ Complete
└──────────────────────────────────────────────────────────────┘
```
---
#### 🎯 Semantic Invocation vs Command Invocation
**Method 1: Natural Language Semantic Invocation** (Recommended)
```bash
# Users simply describe naturally, Claude Code auto-invokes tools
"Use gemini to analyze this module's dependencies"
→ Claude Code auto-generates: cd src && gemini -p "Analyze dependencies"
"Have codex implement user registration feature"
→ Claude Code auto-generates: codex -C src/auth --full-auto exec "Implement registration"
```
**Method 2: Direct Command Invocation**
```bash
# Precise invocation via Slash commands
/cli:chat --tool gemini "Explain this algorithm"
/cli:analyze --tool qwen "Analyze performance bottlenecks"
/cli:execute --tool codex "Optimize query performance"
```
---
#### 🔄 Workflow Integration Examples
**Integration with Lite Workflow**:
```bash
# 1. Planning phase: Gemini analysis
/workflow:lite-plan -e "Refactor payment module"
→ Three-dimensional confirmation selects "CLI Tools execution"
# 2. Execution phase: Choose execution method
# Option A: Serial execution
"Use gemini to analyze payment flow""Have codex refactor code"
# Option B: Parallel analysis + Serial implementation
"Use gemini to analyze architecture" + "Use qwen to evaluate solution"
"Have codex refactor based on analysis results"
```
**Integration with Full Workflow**:
```bash
# 1. Planning phase
/workflow:plan "Implement distributed cache"
/workflow:action-plan-verify
# 2. Analysis phase (parallel)
Use gemini to analyze existing cache architecture
Use qwen to evaluate Redis cluster solution
# 3. Implementation phase (serial)
/workflow:execute # Or use CLI
Have codex implement Redis cluster integration
# 4. Testing phase (parallel)
/workflow:test-gen WFS-cache
→ Internally uses gemini analysis + codex test generation
# 5. Review phase (serial)
Use gemini to review code quality
/workflow:review --type architecture
```
---
#### 💡 Best Practices
**When to use serial**:
- Implementation depends on design solution
- Testing depends on code implementation
- Optimization depends on performance analysis
**When to use parallel**:
- Multi-dimensional analysis (security + performance + architecture)
- Multi-module independent development
- Simultaneous code and test generation
**When to use hybrid**:
- Complex feature development (analysis → design → implementation → testing)
- Large-scale refactoring (evaluation → planning → execution → verification)
- Tech stack migration (research → solution → implementation → optimization)
**Tool selection guidelines**:
1. **Need to understand code** → Gemini (preferred) or Qwen
2. **Need to write code** → Codex
3. **Complex analysis** → Gemini + Qwen parallel (complementary verification)
4. **Precise implementation** → Codex (based on Gemini analysis)
5. **Quick prototype** → Direct Codex usage
---
## 🔄 Complete Flow for Typical Scenarios
### Scenario A: New Feature Development (Know How to Build)