agent-migration-plan

---

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:

• migration-planning
• system-transformation
• agent-mapping
• compatibility-analysis
• rollout-coordination priority: medium hooks: pre: | echo "📋 Agent 系统迁移规划器已启动" 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 "待迁移命令：" fi post: | echo "✅ 迁移规划已完成" echo "📊 Agent 映射策略已定义" echo "🚀 已准备好系统性地推出 Agent 系统"

---

Claude Flow 命令迁移至 Agent 系统计划

概述

本文档提供了一份全面的迁移计划，用于将现有的 .claude$commands 转换为新的基于 Agent 的系统。每个命令都映射到一个对应的 Agent，并定义其角色、职责、能力和工具访问限制。

Agent 定义格式

每个 Agent 都使用具有以下结构的 YAML 前置信息：

---
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"
---

迁移类别

1. 协调 Agent

群体初始化器 Agent

命令：.claude$commands$coordination$init.md

---
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"
---

Agent 生成器

命令：.claude$commands$coordination$spawn.md

---
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"
---

任务编排器

命令：.claude$commands$coordination$orchestrate.md

---
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"
---

2. GitHub 集成 Agent

PR 管理器 Agent

命令：.claude$commands$github$pr-manager.md

---
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"
---

代码审查群体 Agent

命令：.claude$commands$github$code-review-swarm.md

---
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"
---

发布管理器 Agent

命令：.claude$commands$github$release-manager.md

---
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"
---

3. SPARC 方法论 Agent

SPARC 编排器 Agent

命令：.claude$commands$sparc$orchestrator.md

---
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"
---

SPARC 编码器 Agent

命令：.claude$commands$sparc$coder.md

---
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"
---

SPARC 测试器 Agent

命令：.claude$commands$sparc$tester.md

---
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"
---

4. 分析 Agent

性能分析器 Agent

命令：.claude$commands$analysis$performance-bottlenecks.md

---
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"
---

令牌效率分析师 Agent

命令：.claude$commands$analysis$token-efficiency.md

---
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"
---

5. 记忆管理 Agent

记忆协调器 Agent

命令：.claude$commands$memory$usage.md

---
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"
---

神经模式 Agent

命令：.claude$commands$memory$neural.md

---
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"
---

6. 自动化 Agent

智能 Agent 协调器

命令：.claude$commands$automation$smart-agents.md

---
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"
---

自修复协调器 Agent

命令：.claude$commands$automation$self-healing.md

---
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"
---

7. 优化 Agent

并行执行优化器 Agent

命令：.claude$commands$optimization$parallel-execution.md

---
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"
---

自动拓扑优化器 Agent

命令：.claude$commands$optimization$auto-topology.md

---
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"
---

8. 监控 Agent

群体监控器 Agent

命令：.claude$commands$monitoring$status.md

---
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"
---

实施指南

1. Agent 激活

• 根据用户消息中的模式匹配来激活 Agent
• 优先级更高的模式优先
• 复杂任务可以激活多个 Agent

2. 工具限制

• 每个 Agent 都有特定的允许使用和受限工具
• 限制可确保 Agent 专注于其所属领域
• 关键操作需要由专门的 Agent 执行

3. Agent 间通信

• Agent 通过共享内存进行通信
• 任务编排器负责协调多 Agent 工作流
• 协调器 Agent 汇总结果

4. 迁移步骤

1. 创建 .claude$agents/ 目录结构
2. 将每条命令转换为 Agent 定义格式
3. 更新自然语言激活模式
4. 测试 Agent 交互和交接
5. 通过回退机制逐步推出

5. 向后兼容性

• 在过渡期间保留命令文件
• 将命令调用映射到 Agent 激活
• 为已弃用的命令提供迁移警告

监控迁移成效

关键指标

• Agent 激活准确率
• 任务完成率
• Agent 间协作效率
• 用户满意度评分
• 性能提升

验证标准

• 所有命令都有对应的 Agent
• 迁移期间不损失任何功能
• 自然语言理解能力得到提升
• 任务拆解和并行处理能力得到改善
• 错误处理和恢复能力得到增强