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agent-migration-plan

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🇺🇸

Original

English
🇨🇳

Translation

Chinese
name: migration-planner type: planning color: red description: Comprehensive migration plan for converting commands to agent-based system capabilities:
  • migration-planning
  • system-transformation
  • agent-mapping
  • compatibility-analysis
  • rollout-coordination priority: medium hooks: pre: | echo "📋 Agent System Migration Planner activated" echo "🔄 Analyzing current command structure for migration"

    Check existing command structure

    if [ -d ".claude$commands" ]; then echo "📁 Found existing command directory - will map to agents" find .claude$commands -name "*.md" | wc -l | xargs echo "Commands to migrate:" fi post: | echo "✅ Migration planning completed" echo "📊 Agent mapping strategy defined" echo "🚀 Ready for systematic agent system rollout"
name: migration-planner type: planning color: red description: 将命令转换为基于Agent的系统的全面迁移计划 capabilities:
  • 迁移规划
  • 系统转型
  • Agent映射
  • 兼容性分析
  • 上线协调 priority: medium hooks: pre: | echo "📋 Agent系统迁移规划器已激活" echo "🔄 正在分析当前命令结构以进行迁移"

    检查现有命令结构

    if [ -d ".claude$commands" ]; then echo "📁 找到现有命令目录 - 将映射到Agent" find .claude$commands -name "*.md" | wc -l | xargs echo "待迁移的命令数量:" fi post: | echo "✅ 迁移规划完成" echo "📊 已定义Agent映射策略" echo "🚀 准备好进行系统化的Agent系统上线"

Claude Flow Commands to Agent System Migration Plan

Claude Flow 命令到Agent系统迁移计划

Overview

概述

This document provides a comprehensive migration plan to convert existing .claude$commands to the new agent-based system. Each command is mapped to an equivalent agent with defined roles, responsibilities, capabilities, and tool access restrictions.
本文档提供了将现有.claude$commands转换为新型基于Agent的系统的全面迁移计划。每个命令都将映射到具有定义角色、职责、能力和工具访问限制的等效Agent。

Agent Definition Format

Agent定义格式

Each agent uses YAML frontmatter with the following structure:
yaml
---
role: agent-type
name: Agent Display Name
responsibilities:
  - Primary responsibility
  - Secondary responsibility
capabilities:
  - capability-1
  - capability-2
tools:
  allowed:
    - tool-name
  restricted:
    - restricted-tool
triggers:
  - pattern: "regex pattern"
    priority: high|medium|low
  - keyword: "activation keyword"
---
每个Agent使用YAML前置元数据，结构如下：
yaml
---
role: agent-type
name: Agent Display Name
responsibilities:
  - Primary responsibility
  - Secondary responsibility
capabilities:
  - capability-1
  - capability-2
tools:
  allowed:
    - tool-name
  restricted:
    - restricted-tool
triggers:
  - pattern: "regex pattern"
    priority: high|medium|low
  - keyword: "activation keyword"
---

Migration Categories

迁移分类

1. Coordination Agents

1. 协调类Agent

Swarm Initializer Agent

Swarm初始化Agent

Command: 
.claude$commands$coordination$init.md
yaml
---
role: coordinator
name: Swarm Initializer
responsibilities:
  - Initialize agent swarms with optimal topology
  - Configure distributed coordination systems
  - Set up inter-agent communication channels
capabilities:
  - swarm-initialization
  - topology-optimization
  - resource-allocation
  - network-configuration
tools:
  allowed:
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__topology_optimize
    - mcp__claude-flow__memory_usage
    - TodoWrite
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "init.*swarm|create.*swarm|setup.*agents"
    priority: high
  - keyword: "swarm-init"
---
命令: 
.claude$commands$coordination$init.md
yaml
---
role: coordinator
name: Swarm Initializer
responsibilities:
  - 以最优拓扑结构初始化Agent集群
  - 配置分布式协调系统
  - 建立Agent间通信渠道
capabilities:
  - swarm-initialization
  - topology-optimization
  - resource-allocation
  - network-configuration
tools:
  allowed:
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__topology_optimize
    - mcp__claude-flow__memory_usage
    - TodoWrite
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "init.*swarm|create.*swarm|setup.*agents"
    priority: high
  - keyword: "swarm-init"
---

Agent Spawner

Agent生成器

Command: 
.claude$commands$coordination$spawn.md
yaml
---
role: coordinator
name: Agent Spawner
responsibilities:
  - Create specialized cognitive patterns for task execution
  - Assign capabilities to agents based on requirements
  - Manage agent lifecycle and resource allocation
capabilities:
  - agent-creation
  - capability-assignment
  - resource-management
  - pattern-recognition
tools:
  allowed:
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__daa_agent_create
    - mcp__claude-flow__agent_list
    - mcp__claude-flow__memory_usage
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "spawn.*agent|create.*agent|add.*agent"
    priority: high
  - keyword: "agent-spawn"
---
命令: 
.claude$commands$coordination$spawn.md
yaml
---
role: coordinator
name: Agent Spawner
responsibilities:
  - 为任务执行创建专用认知模式
  - 根据需求为Agent分配能力
  - 管理Agent生命周期和资源分配
capabilities:
  - agent-creation
  - capability-assignment
  - resource-management
  - pattern-recognition
tools:
  allowed:
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__daa_agent_create
    - mcp__claude-flow__agent_list
    - mcp__claude-flow__memory_usage
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "spawn.*agent|create.*agent|add.*agent"
    priority: high
  - keyword: "agent-spawn"
---

Task Orchestrator

任务编排器

Command: 
.claude$commands$coordination$orchestrate.md
yaml
---
role: orchestrator
name: Task Orchestrator
responsibilities:
  - Decompose complex tasks into manageable subtasks
  - Coordinate parallel and sequential execution strategies
  - Monitor task progress and dependencies
  - Synthesize results from multiple agents
capabilities:
  - task-decomposition
  - execution-planning
  - dependency-management
  - result-aggregation
  - progress-tracking
tools:
  allowed:
    - mcp__claude-flow__task_orchestrate
    - mcp__claude-flow__task_status
    - mcp__claude-flow__task_results
    - mcp__claude-flow__parallel_execute
    - TodoWrite
    - TodoRead
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "orchestrate|coordinate.*task|manage.*workflow"
    priority: high
  - keyword: "orchestrate"
---
命令: 
.claude$commands$coordination$orchestrate.md
yaml
---
role: orchestrator
name: Task Orchestrator
responsibilities:
  - 将复杂任务分解为可管理的子任务
  - 协调并行和顺序执行策略
  - 监控任务进度和依赖关系
  - 汇总多个Agent的结果
capabilities:
  - task-decomposition
  - execution-planning
  - dependency-management
  - result-aggregation
  - progress-tracking
tools:
  allowed:
    - mcp__claude-flow__task_orchestrate
    - mcp__claude-flow__task_status
    - mcp__claude-flow__task_results
    - mcp__claude-flow__parallel_execute
    - TodoWrite
    - TodoRead
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "orchestrate|coordinate.*task|manage.*workflow"
    priority: high
  - keyword: "orchestrate"
---

2. GitHub Integration Agents

2. GitHub集成类Agent

PR Manager Agent

PR管理Agent

Command: 
.claude$commands$github$pr-manager.md
yaml
---
role: github-specialist
name: Pull Request Manager
responsibilities:
  - Manage complete pull request lifecycle
  - Coordinate multi-reviewer workflows
  - Handle merge strategies and conflict resolution
  - Track PR progress with issue integration
capabilities:
  - pr-creation
  - review-coordination
  - merge-management
  - conflict-resolution
  - status-tracking
tools:
  allowed:
    - Bash  # For gh CLI commands
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__task_orchestrate
    - mcp__claude-flow__memory_usage
    - TodoWrite
    - Read
  restricted:
    - Write  # Should use gh CLI for GitHub operations
    - Edit
triggers:
  - pattern: "pr|pull.?request|merge.*request"
    priority: high
  - keyword: "pr-manager"
---
命令: 
.claude$commands$github$pr-manager.md
yaml
---
role: github-specialist
name: Pull Request Manager
responsibilities:
  - 管理完整的拉取请求生命周期
  - 协调多审核者工作流
  - 处理合并策略和冲突解决
  - 结合问题跟踪PR进度
capabilities:
  - pr-creation
  - review-coordination
  - merge-management
  - conflict-resolution
  - status-tracking
tools:
  allowed:
    - Bash  # 用于gh CLI命令
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__task_orchestrate
    - mcp__claude-flow__memory_usage
    - TodoWrite
    - Read
  restricted:
    - Write  # 应使用gh CLI进行GitHub操作
    - Edit
triggers:
  - pattern: "pr|pull.?request|merge.*request"
    priority: high
  - keyword: "pr-manager"
---

Code Review Swarm Agent

代码审核集群Agent

Command: 
.claude$commands$github$code-review-swarm.md
yaml
---
role: reviewer
name: Code Review Coordinator
responsibilities:
  - Orchestrate multi-agent code reviews
  - Ensure code quality and standards compliance
  - Coordinate security and performance reviews
  - Generate comprehensive review reports
capabilities:
  - code-analysis
  - quality-assessment
  - security-scanning
  - performance-review
  - report-generation
tools:
  allowed:
    - Bash  # For gh CLI
    - Read
    - Grep
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__github_code_review
    - mcp__claude-flow__memory_usage
  restricted:
    - Write
    - Edit
triggers:
  - pattern: "review.*code|code.*review|check.*pr"
    priority: high
  - keyword: "code-review"
---
命令: 
.claude$commands$github$code-review-swarm.md
yaml
---
role: reviewer
name: Code Review Coordinator
responsibilities:
  - 编排多Agent代码审核
  - 确保代码质量和标准合规
  - 协调安全和性能审核
  - 生成全面的审核报告
capabilities:
  - code-analysis
  - quality-assessment
  - security-scanning
  - performance-review
  - report-generation
tools:
  allowed:
    - Bash  # 用于gh CLI
    - Read
    - Grep
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__github_code_review
    - mcp__claude-flow__memory_usage
  restricted:
    - Write
    - Edit
triggers:
  - pattern: "review.*code|code.*review|check.*pr"
    priority: high
  - keyword: "code-review"
---

Release Manager Agent

发布管理Agent

Command: 
.claude$commands$github$release-manager.md
yaml
---
role: release-coordinator
name: Release Manager
responsibilities:
  - Coordinate release preparation and deployment
  - Manage version tagging and changelog generation
  - Orchestrate multi-repository releases
  - Handle rollback procedures
capabilities:
  - release-planning
  - version-management
  - changelog-generation
  - deployment-coordination
  - rollback-execution
tools:
  allowed:
    - Bash
    - Read
    - mcp__claude-flow__github_release_coord
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__task_orchestrate
    - TodoWrite
  restricted:
    - Write  # Use version control for releases
    - Edit
triggers:
  - pattern: "release|deploy|tag.*version|create.*release"
    priority: high
  - keyword: "release-manager"
---
命令: 
.claude$commands$github$release-manager.md
yaml
---
role: release-coordinator
name: Release Manager
responsibilities:
  - 协调发布准备和部署
  - 管理版本标记和变更日志生成
  - 编排多仓库发布
  - 处理回滚流程
capabilities:
  - release-planning
  - version-management
  - changelog-generation
  - deployment-coordination
  - rollback-execution
tools:
  allowed:
    - Bash
    - Read
    - mcp__claude-flow__github_release_coord
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__task_orchestrate
    - TodoWrite
  restricted:
    - Write  # 使用版本控制进行发布操作
    - Edit
triggers:
  - pattern: "release|deploy|tag.*version|create.*release"
    priority: high
  - keyword: "release-manager"
---

3. SPARC Methodology Agents

3. SPARC方法论类Agent

SPARC Orchestrator Agent

SPARC编排器Agent

Command: 
.claude$commands$sparc$orchestrator.md
yaml
---
role: sparc-coordinator
name: SPARC Orchestrator
responsibilities:
  - Coordinate SPARC methodology phases
  - Manage task decomposition and agent allocation
  - Track progress across all SPARC phases
  - Synthesize results from specialized agents
capabilities:
  - sparc-coordination
  - phase-management
  - task-planning
  - resource-allocation
  - result-synthesis
tools:
  allowed:
    - mcp__claude-flow__sparc_mode
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__task_orchestrate
    - TodoWrite
    - TodoRead
    - mcp__claude-flow__memory_usage
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "sparc.*orchestrat|coordinate.*sparc"
    priority: high
  - keyword: "sparc-orchestrator"
---
命令: 
.claude$commands$sparc$orchestrator.md
yaml
---
role: sparc-coordinator
name: SPARC Orchestrator
responsibilities:
  - 协调SPARC方法论各阶段
  - 管理任务分解和Agent分配
  - 跟踪所有SPARC阶段的进度
  - 汇总专用Agent的结果
capabilities:
  - sparc-coordination
  - phase-management
  - task-planning
  - resource-allocation
  - result-synthesis
tools:
  allowed:
    - mcp__claude-flow__sparc_mode
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__task_orchestrate
    - TodoWrite
    - TodoRead
    - mcp__claude-flow__memory_usage
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "sparc.*orchestrat|coordinate.*sparc"
    priority: high
  - keyword: "sparc-orchestrator"
---

SPARC Coder Agent

SPARC编码Agent

Command: 
.claude$commands$sparc$coder.md
yaml
---
role: implementer
name: SPARC Implementation Specialist
responsibilities:
  - Transform specifications into working code
  - Implement TDD practices with parallel test creation
  - Ensure code quality and standards compliance
  - Optimize implementation for performance
capabilities:
  - code-generation
  - test-implementation
  - refactoring
  - optimization
  - documentation
tools:
  allowed:
    - Read
    - Write
    - Edit
    - MultiEdit
    - Bash
    - mcp__claude-flow__sparc_mode
    - TodoWrite
  restricted:
    - mcp__claude-flow__swarm_init  # Focus on implementation
triggers:
  - pattern: "implement|code|develop|build.*feature"
    priority: high
  - keyword: "sparc-coder"
---
命令: 
.claude$commands$sparc$coder.md
yaml
---
role: implementer
name: SPARC Implementation Specialist
responsibilities:
  - 将规范转换为可运行代码
  - 结合并行测试创建实现TDD实践
  - 确保代码质量和标准合规
  - 优化实现以提升性能
capabilities:
  - code-generation
  - test-implementation
  - refactoring
  - optimization
  - documentation
tools:
  allowed:
    - Read
    - Write
    - Edit
    - MultiEdit
    - Bash
    - mcp__claude-flow__sparc_mode
    - TodoWrite
  restricted:
    - mcp__claude-flow__swarm_init  # 专注于实现工作
triggers:
  - pattern: "implement|code|develop|build.*feature"
    priority: high
  - keyword: "sparc-coder"
---

SPARC Tester Agent

SPARC测试Agent

Command: 
.claude$commands$sparc$tester.md
yaml
---
role: quality-assurance
name: SPARC Testing Specialist
responsibilities:
  - Design comprehensive test strategies
  - Implement parallel test execution
  - Ensure coverage requirements are met
  - Coordinate testing across different levels
capabilities:
  - test-design
  - test-implementation
  - coverage-analysis
  - performance-testing
  - security-testing
tools:
  allowed:
    - Read
    - Write
    - Edit
    - Bash
    - mcp__claude-flow__sparc_mode
    - TodoWrite
    - mcp__claude-flow__parallel_execute
  restricted:
    - mcp__claude-flow__swarm_init
triggers:
  - pattern: "test|verify|validate|check.*quality"
    priority: high
  - keyword: "sparc-tester"
---
命令: 
.claude$commands$sparc$tester.md
yaml
---
role: quality-assurance
name: SPARC Testing Specialist
responsibilities:
  - 设计全面的测试策略
  - 实现并行测试执行
  - 确保满足覆盖率要求
  - 协调不同层级的测试
capabilities:
  - test-design
  - test-implementation
  - coverage-analysis
  - performance-testing
  - security-testing
tools:
  allowed:
    - Read
    - Write
    - Edit
    - Bash
    - mcp__claude-flow__sparc_mode
    - TodoWrite
    - mcp__claude-flow__parallel_execute
  restricted:
    - mcp__claude-flow__swarm_init
triggers:
  - pattern: "test|verify|validate|check.*quality"
    priority: high
  - keyword: "sparc-tester"
---

4. Analysis Agents

4. 分析类Agent

Performance Analyzer Agent

性能分析Agent

Command: 
.claude$commands$analysis$performance-bottlenecks.md
yaml
---
role: analyst
name: Performance Bottleneck Analyzer
responsibilities:
  - Identify performance bottlenecks in workflows
  - Analyze execution patterns and resource usage
  - Recommend optimization strategies
  - Monitor improvement metrics
capabilities:
  - performance-analysis
  - bottleneck-detection
  - metric-collection
  - pattern-recognition
  - optimization-planning
tools:
  allowed:
    - mcp__claude-flow__bottleneck_analyze
    - mcp__claude-flow__performance_report
    - mcp__claude-flow__metrics_collect
    - mcp__claude-flow__trend_analysis
    - Read
    - Grep
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "analyze.*performance|bottleneck|slow.*execution"
    priority: high
  - keyword: "performance-analyzer"
---
命令: 
.claude$commands$analysis$performance-bottlenecks.md
yaml
---
role: analyst
name: Performance Bottleneck Analyzer
responsibilities:
  - 识别工作流中的性能瓶颈
  - 分析执行模式和资源使用情况
  - 推荐优化策略
  - 监控改进指标
capabilities:
  - performance-analysis
  - bottleneck-detection
  - metric-collection
  - pattern-recognition
  - optimization-planning
tools:
  allowed:
    - mcp__claude-flow__bottleneck_analyze
    - mcp__claude-flow__performance_report
    - mcp__claude-flow__metrics_collect
    - mcp__claude-flow__trend_analysis
    - Read
    - Grep
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "analyze.*performance|bottleneck|slow.*execution"
    priority: high
  - keyword: "performance-analyzer"
---

Token Efficiency Analyst Agent

Token效率分析Agent

Command: 
.claude$commands$analysis$token-efficiency.md
yaml
---
role: analyst
name: Token Efficiency Analyzer
responsibilities:
  - Monitor token consumption across operations
  - Identify inefficient token usage patterns
  - Recommend optimization strategies
  - Track cost implications
capabilities:
  - token-analysis
  - cost-optimization
  - usage-tracking
  - pattern-detection
  - report-generation
tools:
  allowed:
    - mcp__claude-flow__token_usage
    - mcp__claude-flow__cost_analysis
    - mcp__claude-flow__usage_stats
    - mcp__claude-flow__memory_analytics
    - Read
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "token.*usage|analyze.*cost|efficiency.*report"
    priority: medium
  - keyword: "token-analyzer"
---
命令: 
.claude$commands$analysis$token-efficiency.md
yaml
---
role: analyst
name: Token Efficiency Analyzer
responsibilities:
  - 监控各操作的Token消耗
  - 识别低效的Token使用模式
  - 推荐优化策略
  - 跟踪成本影响
capabilities:
  - token-analysis
  - cost-optimization
  - usage-tracking
  - pattern-detection
  - report-generation
tools:
  allowed:
    - mcp__claude-flow__token_usage
    - mcp__claude-flow__cost_analysis
    - mcp__claude-flow__usage_stats
    - mcp__claude-flow__memory_analytics
    - Read
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "token.*usage|analyze.*cost|efficiency.*report"
    priority: medium
  - keyword: "token-analyzer"
---

5. Memory Management Agents

5. 内存管理类Agent

Memory Coordinator Agent

内存协调Agent

Command: 
.claude$commands$memory$usage.md
yaml
---
role: memory-manager
name: Memory Coordination Specialist
responsibilities:
  - Manage persistent memory across sessions
  - Coordinate memory namespaces and TTL
  - Optimize memory usage and compression
  - Facilitate cross-agent memory sharing
capabilities:
  - memory-management
  - namespace-coordination
  - data-persistence
  - compression-optimization
  - synchronization
tools:
  allowed:
    - mcp__claude-flow__memory_usage
    - mcp__claude-flow__memory_search
    - mcp__claude-flow__memory_namespace
    - mcp__claude-flow__memory_compress
    - mcp__claude-flow__memory_sync
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "memory|remember|store.*context|retrieve.*data"
    priority: high
  - keyword: "memory-manager"
---
命令: 
.claude$commands$memory$usage.md
yaml
---
role: memory-manager
name: Memory Coordination Specialist
responsibilities:
  - 管理跨会话的持久化内存
  - 协调内存命名空间和TTL
  - 优化内存使用和压缩
  - 促进Agent间内存共享
capabilities:
  - memory-management
  - namespace-coordination
  - data-persistence
  - compression-optimization
  - synchronization
tools:
  allowed:
    - mcp__claude-flow__memory_usage
    - mcp__claude-flow__memory_search
    - mcp__claude-flow__memory_namespace
    - mcp__claude-flow__memory_compress
    - mcp__claude-flow__memory_sync
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "memory|remember|store.*context|retrieve.*data"
    priority: high
  - keyword: "memory-manager"
---

Neural Pattern Agent

神经模式Agent

Command: 
.claude$commands$memory$neural.md
yaml
---
role: ai-specialist
name: Neural Pattern Coordinator
responsibilities:
  - Train and manage neural patterns
  - Coordinate cognitive behavior analysis
  - Implement adaptive learning strategies
  - Optimize AI model performance
capabilities:
  - neural-training
  - pattern-recognition
  - cognitive-analysis
  - model-optimization
  - transfer-learning
tools:
  allowed:
    - mcp__claude-flow__neural_train
    - mcp__claude-flow__neural_patterns
    - mcp__claude-flow__neural_predict
    - mcp__claude-flow__cognitive_analyze
    - mcp__claude-flow__learning_adapt
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "neural|ai.*pattern|cognitive|machine.*learning"
    priority: high
  - keyword: "neural-patterns"
---
命令: 
.claude$commands$memory$neural.md
yaml
---
role: ai-specialist
name: Neural Pattern Coordinator
responsibilities:
  - 训练和管理神经模式
  - 协调认知行为分析
  - 实现自适应学习策略
  - 优化AI模型性能
capabilities:
  - neural-training
  - pattern-recognition
  - cognitive-analysis
  - model-optimization
  - transfer-learning
tools:
  allowed:
    - mcp__claude-flow__neural_train
    - mcp__claude-flow__neural_patterns
    - mcp__claude-flow__neural_predict
    - mcp__claude-flow__cognitive_analyze
    - mcp__claude-flow__learning_adapt
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "neural|ai.*pattern|cognitive|machine.*learning"
    priority: high
  - keyword: "neural-patterns"
---

6. Automation Agents

6. 自动化类Agent

Smart Agent Coordinator

智能Agent协调器

Command: 
.claude$commands$automation$smart-agents.md
yaml
---
role: automation-specialist
name: Smart Agent Coordinator
responsibilities:
  - Automate agent spawning based on task requirements
  - Implement intelligent capability matching
  - Manage dynamic agent allocation
  - Optimize resource utilization
capabilities:
  - intelligent-spawning
  - capability-matching
  - resource-optimization
  - pattern-learning
  - auto-scaling
tools:
  allowed:
    - mcp__claude-flow__daa_agent_create
    - mcp__claude-flow__daa_capability_match
    - mcp__claude-flow__daa_resource_alloc
    - mcp__claude-flow__swarm_scale
    - mcp__claude-flow__agent_metrics
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "smart.*agent|auto.*spawn|intelligent.*coordination"
    priority: high
  - keyword: "smart-agents"
---
命令: 
.claude$commands$automation$smart-agents.md
yaml
---
role: automation-specialist
name: Smart Agent Coordinator
responsibilities:
  - 根据任务需求自动生成Agent
  - 实现智能能力匹配
  - 管理动态Agent分配
  - 优化资源利用率
capabilities:
  - intelligent-spawning
  - capability-matching
  - resource-optimization
  - pattern-learning
  - auto-scaling
tools:
  allowed:
    - mcp__claude-flow__daa_agent_create
    - mcp__claude-flow__daa_capability_match
    - mcp__claude-flow__daa_resource_alloc
    - mcp__claude-flow__swarm_scale
    - mcp__claude-flow__agent_metrics
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "smart.*agent|auto.*spawn|intelligent.*coordination"
    priority: high
  - keyword: "smart-agents"
---

Self-Healing Coordinator Agent

自修复协调Agent

Command: 
.claude$commands$automation$self-healing.md
yaml
---
role: reliability-engineer
name: Self-Healing System Coordinator
responsibilities:
  - Detect and recover from system failures
  - Implement fault tolerance strategies
  - Coordinate automatic recovery procedures
  - Monitor system health continuously
capabilities:
  - fault-detection
  - automatic-recovery
  - health-monitoring
  - resilience-planning
  - error-analysis
tools:
  allowed:
    - mcp__claude-flow__daa_fault_tolerance
    - mcp__claude-flow__health_check
    - mcp__claude-flow__error_analysis
    - mcp__claude-flow__diagnostic_run
    - Bash  # For system commands
  restricted:
    - Write  # Prevent accidental file modifications during recovery
    - Edit
triggers:
  - pattern: "self.*heal|auto.*recover|fault.*toleran|system.*health"
    priority: high
  - keyword: "self-healing"
---
命令: 
.claude$commands$automation$self-healing.md
yaml
---
role: reliability-engineer
name: Self-Healing System Coordinator
responsibilities:
  - 检测并从系统故障中恢复
  - 实现容错策略
  - 协调自动恢复流程
  - 持续监控系统健康状况
capabilities:
  - fault-detection
  - automatic-recovery
  - health-monitoring
  - resilience-planning
  - error-analysis
tools:
  allowed:
    - mcp__claude-flow__daa_fault_tolerance
    - mcp__claude-flow__health_check
    - mcp__claude-flow__error_analysis
    - mcp__claude-flow__diagnostic_run
    - Bash  # 用于系统命令
  restricted:
    - Write  # 恢复期间防止意外修改文件
    - Edit
triggers:
  - pattern: "self.*heal|auto.*recover|fault.*toleran|system.*health"
    priority: high
  - keyword: "self-healing"
---

7. Optimization Agents

7. 优化类Agent

Parallel Execution Optimizer Agent

并行执行优化Agent

Command: 
.claude$commands$optimization$parallel-execution.md
yaml
---
role: optimizer
name: Parallel Execution Optimizer
responsibilities:
  - Optimize task execution for parallelism
  - Identify parallelization opportunities
  - Coordinate concurrent operations
  - Monitor parallel execution efficiency
capabilities:
  - parallelization-analysis
  - execution-optimization
  - load-balancing
  - performance-monitoring
  - bottleneck-removal
tools:
  allowed:
    - mcp__claude-flow__parallel_execute
    - mcp__claude-flow__load_balance
    - mcp__claude-flow__batch_process
    - mcp__claude-flow__performance_report
    - TodoWrite
  restricted:
    - Write
    - Edit
triggers:
  - pattern: "parallel|concurrent|simultaneous|batch.*execution"
    priority: high
  - keyword: "parallel-optimizer"
---
命令: 
.claude$commands$optimization$parallel-execution.md
yaml
---
role: optimizer
name: Parallel Execution Optimizer
responsibilities:
  - 优化任务执行以实现并行化
  - 识别并行化机会
  - 协调并发操作
  - 监控并行执行效率
capabilities:
  - parallelization-analysis
  - execution-optimization
  - load-balancing
  - performance-monitoring
  - bottleneck-removal
tools:
  allowed:
    - mcp__claude-flow__parallel_execute
    - mcp__claude-flow__load_balance
    - mcp__claude-flow__batch_process
    - mcp__claude-flow__performance_report
    - TodoWrite
  restricted:
    - Write
    - Edit
triggers:
  - pattern: "parallel|concurrent|simultaneous|batch.*execution"
    priority: high
  - keyword: "parallel-optimizer"
---

Auto-Topology Optimizer Agent

自动拓扑优化Agent

Command: 
.claude$commands$optimization$auto-topology.md
yaml
---
role: optimizer
name: Topology Optimization Specialist
responsibilities:
  - Analyze and optimize swarm topology
  - Adapt topology based on workload
  - Balance communication overhead
  - Ensure optimal agent distribution
capabilities:
  - topology-analysis
  - graph-optimization
  - network-design
  - load-distribution
  - adaptive-configuration
tools:
  allowed:
    - mcp__claude-flow__topology_optimize
    - mcp__claude-flow__swarm_monitor
    - mcp__claude-flow__coordination_sync
    - mcp__claude-flow__swarm_status
    - mcp__claude-flow__metrics_collect
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "topology|optimize.*swarm|network.*structure"
    priority: medium
  - keyword: "topology-optimizer"
---
命令: 
.claude$commands$optimization$auto-topology.md
yaml
---
role: optimizer
name: Topology Optimization Specialist
responsibilities:
  - 分析并优化集群拓扑
  - 根据工作负载调整拓扑
  - 平衡通信开销
  - 确保Agent分布最优
capabilities:
  - topology-analysis
  - graph-optimization
  - network-design
  - load-distribution
  - adaptive-configuration
tools:
  allowed:
    - mcp__claude-flow__topology_optimize
    - mcp__claude-flow__swarm_monitor
    - mcp__claude-flow__coordination_sync
    - mcp__claude-flow__swarm_status
    - mcp__claude-flow__metrics_collect
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "topology|optimize.*swarm|network.*structure"
    priority: medium
  - keyword: "topology-optimizer"
---

8. Monitoring Agents

8. 监控类Agent

Swarm Monitor Agent

集群监控Agent

Command: 
.claude$commands$monitoring$status.md
yaml
---
role: monitor
name: Swarm Status Monitor
responsibilities:
  - Monitor swarm health and performance
  - Track agent status and utilization
  - Generate real-time status reports
  - Alert on anomalies or failures
capabilities:
  - health-monitoring
  - performance-tracking
  - status-reporting
  - anomaly-detection
  - alert-generation
tools:
  allowed:
    - mcp__claude-flow__swarm_status
    - mcp__claude-flow__swarm_monitor
    - mcp__claude-flow__agent_metrics
    - mcp__claude-flow__health_check
    - mcp__claude-flow__performance_report
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "monitor|status|health.*check|swarm.*status"
    priority: medium
  - keyword: "swarm-monitor"
---
命令: 
.claude$commands$monitoring$status.md
yaml
---
role: monitor
name: Swarm Status Monitor
responsibilities:
  - 监控集群健康和性能
  - 跟踪Agent状态和利用率
  - 生成实时状态报告
  - 异常或故障告警
capabilities:
  - health-monitoring
  - performance-tracking
  - status-reporting
  - anomaly-detection
  - alert-generation
tools:
  allowed:
    - mcp__claude-flow__swarm_status
    - mcp__claude-flow__swarm_monitor
    - mcp__claude-flow__agent_metrics
    - mcp__claude-flow__health_check
    - mcp__claude-flow__performance_report
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "monitor|status|health.*check|swarm.*status"
    priority: medium
  - keyword: "swarm-monitor"
---

Implementation Guidelines

实施指南

1. Agent Activation

1. Agent激活

  • Agents are activated by pattern matching in user messages
  • Higher priority patterns take precedence
  • Multiple agents can be activated for complex tasks
  • Agent通过用户消息中的模式匹配激活
  • 高优先级模式优先触发
  • 复杂任务可激活多个Agent

2. Tool Restrictions

2. 工具限制

  • Each agent has specific allowed and restricted tools
  • Restrictions ensure agents stay within their domain
  • Critical operations require specialized agents
  • 每个Agent有特定的允许和限制工具
  • 限制确保Agent在其职责范围内工作
  • 关键操作需要专用Agent执行

3. Inter-Agent Communication

3. Agent间通信

  • Agents communicate through shared memory
  • Task orchestrator coordinates multi-agent workflows
  • Results are aggregated by coordinator agents
  • Agent通过共享内存通信
  • 任务编排器协调多Agent工作流
  • 协调类Agent汇总结果

4. Migration Steps

4. 迁移步骤

  1. Create 
    .claude$agents/
    directory structure
  2. Convert each command to agent definition format
  3. Update activation patterns for natural language
  4. Test agent interactions and handoffs
  5. Implement gradual rollout with fallbacks
  1. 创建
    .claude$agents/
    目录结构
  2. 将每个命令转换为Agent定义格式
  3. 更新激活模式以支持自然语言
  4. 测试Agent交互和切换
  5. 逐步上线并实现回滚机制

5. Backwards Compatibility

5. 向后兼容性

  • Keep command files during transition
  • Map command invocations to agent activations
  • Provide migration warnings for deprecated commands
  • 过渡期间保留命令文件
  • 将命令调用映射到Agent激活
  • 为已弃用命令提供迁移警告

Monitoring Migration Success

监控迁移成功

Key Metrics

关键指标

  • Agent activation accuracy
  • Task completion rates
  • Inter-agent coordination efficiency
  • User satisfaction scores
  • Performance improvements
  • Agent激活准确率
  • 任务完成率
  • Agent间协调效率
  • 用户满意度评分
  • 性能提升

Validation Criteria

验证标准

  • All commands have equivalent agents
  • No functionality loss during migration
  • Improved natural language understanding
  • Better task decomposition and parallelization
  • Enhanced error handling and recovery
  • 所有命令都有对应的Agent
  • 迁移期间无功能损失
  • 自然语言理解能力提升
  • 任务分解和并行化更优
  • 错误处理和恢复能力增强