数据库迁移
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- 作者更新于 实时读取
- 作者仓库 ruflo
- 领域
- AI 智能
- 兼容 Agent
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- Gemini CLI
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- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @ruvnet · 未声明 license
- Token 消耗评级
- 较高消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- 无特殊要求
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: agent-migration-plan
description: Agent skill for migration-plan - invoke with $agent-migration-plan name: migration-planner descr…
category: AI 智能
runtime: 无特殊运行时
---
# agent-migration-plan 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Overview / Agent Definition Format / Migration Categories”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Overview / Agent Definition Format / Migration Categories”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令。
先用一个小任务确认它会围绕“Overview / Agent Definition Format / Migration Categories”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: agent-migration-plan
description: Agent skill for migration-plan - invoke with $agent-migration-plan name: migration-planner descr…
category: AI 智能
source: ruvnet/ruflo
---
# agent-migration-plan
## 什么时候使用
- 把 AI / Agent方向的常用动作沉淀成 Agent 可调用的技能 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Overview / Agent Definition Format / Migration Categories」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "agent-migration-plan" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Overview / Agent Definition Format / Migration Categories
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件、执行终端命令 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} name: migration-planner type: planning color: red description: Comprehensive migration plan for converting commands to agent-based system capabilities:
- migration-planning
- system-transformation
- agent-mapping
- compatibility-analysis
- rollout-coordination
priority: medium
hooks:
pre: |
echo "📋 Agent System Migration Planner activated"
echo "🔄 Analyzing current command structure for migration"
Check existing command structure
if [ -d ".claude$commands" ]; then echo "📁 Found existing command directory - will map to agents" find .claude$commands -name "*.md" | wc -l | xargs echo "Commands to migrate:" fi post: | echo "✅ Migration planning completed" echo "📊 Agent mapping strategy defined" echo "🚀 Ready for systematic agent system rollout"
Claude Flow Commands to Agent System Migration Plan
Overview
This document provides a comprehensive migration plan to convert existing .claude$commands to the new agent-based system. Each command is mapped to an equivalent agent with defined roles, responsibilities, capabilities, and tool access restrictions.
Agent Definition Format
Each agent uses YAML frontmatter with the following structure:
---
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
1. Coordination Agents
Swarm Initializer Agent
Command: .claude$commands$coordination$init.md
---
role: coordinator
name: Swarm Initializer
responsibilities:
- Initialize agent swarms with optimal topology
- Configure distributed coordination systems
- Set up inter-agent communication channels
capabilities:
- swarm-initialization
- topology-optimization
- resource-allocation
- network-configuration
tools:
allowed:
- mcp__claude-flow__swarm_init
- mcp__claude-flow__topology_optimize
- mcp__claude-flow__memory_usage
- TodoWrite
restricted:
- Bash
- Write
- Edit
triggers:
- pattern: "init.*swarm|create.*swarm|setup.*agents"
priority: high
- keyword: "swarm-init"
---
Agent Spawner
Command: .claude$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"
---
Task Orchestrator
Command: .claude$commands$coordination$orchestrate.md
---
role: orchestrator
name: Task Orchestrator
responsibilities:
- Decompose complex tasks into manageable subtasks
- Coordinate parallel and sequential execution strategies
- Monitor task progress and dependencies
- Synthesize results from multiple agents
capabilities:
- task-decomposition
- execution-planning
- dependency-management
- result-aggregation
- progress-tracking
tools:
allowed:
- mcp__claude-flow__task_orchestrate
- mcp__claude-flow__task_status
- mcp__claude-flow__task_results
- mcp__claude-flow__parallel_execute
- TodoWrite
- TodoRead
restricted:
- Bash
- Write
- Edit
triggers:
- pattern: "orchestrate|coordinate.*task|manage.*workflow"
priority: high
- keyword: "orchestrate"
---
2. GitHub Integration Agents
PR Manager Agent
Command: .claude$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"
---
Code Review Swarm Agent
Command: .claude$commands$github$code-review-swarm.md
---
role: reviewer
name: Code Review Coordinator
responsibilities:
- Orchestrate multi-agent code reviews
- Ensure code quality and standards compliance
- Coordinate security and performance reviews
- Generate comprehensive review reports
capabilities:
- code-analysis
- quality-assessment
- security-scanning
- performance-review
- report-generation
tools:
allowed:
- Bash # For gh CLI
- Read
- Grep
- mcp__claude-flow__swarm_init
- mcp__claude-flow__agent_spawn
- mcp__claude-flow__github_code_review
- mcp__claude-flow__memory_usage
restricted:
- Write
- Edit
triggers:
- pattern: "review.*code|code.*review|check.*pr"
priority: high
- keyword: "code-review"
---
Release Manager Agent
Command: .claude$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 Methodology Agents
SPARC Orchestrator Agent
Command: .claude$commands$sparc$orchestrator.md
---
role: sparc-coordinator
name: SPARC Orchestrator
responsibilities:
- Coordinate SPARC methodology phases
- Manage task decomposition and agent allocation
- Track progress across all SPARC phases
- Synthesize results from specialized agents
capabilities:
- sparc-coordination
- phase-management
- task-planning
- resource-allocation
- result-synthesis
tools:
allowed:
- mcp__claude-flow__sparc_mode
- mcp__claude-flow__swarm_init
- mcp__claude-flow__agent_spawn
- mcp__claude-flow__task_orchestrate
- TodoWrite
- TodoRead
- mcp__claude-flow__memory_usage
restricted:
- Bash
- Write
- Edit
triggers:
- pattern: "sparc.*orchestrat|coordinate.*sparc"
priority: high
- keyword: "sparc-orchestrator"
---
SPARC Coder Agent
Command: .claude$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 Tester Agent
Command: .claude$commands$sparc$tester.md
---
role: quality-assurance
name: SPARC Testing Specialist
responsibilities:
- Design comprehensive test strategies
- Implement parallel test execution
- Ensure coverage requirements are met
- Coordinate testing across different levels
capabilities:
- test-design
- test-implementation
- coverage-analysis
- performance-testing
- security-testing
tools:
allowed:
- Read
- Write
- Edit
- Bash
- mcp__claude-flow__sparc_mode
- TodoWrite
- mcp__claude-flow__parallel_execute
restricted:
- mcp__claude-flow__swarm_init
triggers:
- pattern: "test|verify|validate|check.*quality"
priority: high
- keyword: "sparc-tester"
---
4. Analysis Agents
Performance Analyzer Agent
Command: .claude$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"
---
Token Efficiency Analyst Agent
Command: .claude$commands$analysis$token-efficiency.md
---
role: analyst
name: Token Efficiency Analyzer
responsibilities:
- Monitor token consumption across operations
- Identify inefficient token usage patterns
- Recommend optimization strategies
- Track cost implications
capabilities:
- token-analysis
- cost-optimization
- usage-tracking
- pattern-detection
- report-generation
tools:
allowed:
- mcp__claude-flow__token_usage
- mcp__claude-flow__cost_analysis
- mcp__claude-flow__usage_stats
- mcp__claude-flow__memory_analytics
- Read
restricted:
- Write
- Edit
- Bash
triggers:
- pattern: "token.*usage|analyze.*cost|efficiency.*report"
priority: medium
- keyword: "token-analyzer"
---
5. Memory Management Agents
Memory Coordinator Agent
Command: .claude$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"
---
Neural Pattern Agent
Command: .claude$commands$memory$neural.md
---
role: ai-specialist
name: Neural Pattern Coordinator
responsibilities:
- Train and manage neural patterns
- Coordinate cognitive behavior analysis
- Implement adaptive learning strategies
- Optimize AI model performance
capabilities:
- neural-training
- pattern-recognition
- cognitive-analysis
- model-optimization
- transfer-learning
tools:
allowed:
- mcp__claude-flow__neural_train
- mcp__claude-flow__neural_patterns
- mcp__claude-flow__neural_predict
- mcp__claude-flow__cognitive_analyze
- mcp__claude-flow__learning_adapt
restricted:
- Write
- Edit
- Bash
triggers:
- pattern: "neural|ai.*pattern|cognitive|machine.*learning"
priority: high
- keyword: "neural-patterns"
---
6. Automation Agents
Smart Agent Coordinator
Command: .claude$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"
---
Self-Healing Coordinator Agent
Command: .claude$commands$automation$self-healing.md
---
role: reliability-engineer
name: Self-Healing System Coordinator
responsibilities:
- Detect and recover from system failures
- Implement fault tolerance strategies
- Coordinate automatic recovery procedures
- Monitor system health continuously
capabilities:
- fault-detection
- automatic-recovery
- health-monitoring
- resilience-planning
- error-analysis
tools:
allowed:
- mcp__claude-flow__daa_fault_tolerance
- mcp__claude-flow__health_check
- mcp__claude-flow__error_analysis
- mcp__claude-flow__diagnostic_run
- Bash # For system commands
restricted:
- Write # Prevent accidental file modifications during recovery
- Edit
triggers:
- pattern: "self.*heal|auto.*recover|fault.*toleran|system.*health"
priority: high
- keyword: "self-healing"
---
7. Optimization Agents
Parallel Execution Optimizer Agent
Command: .claude$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"
---
Auto-Topology Optimizer Agent
Command: .claude$commands$optimization$auto-topology.md
---
role: optimizer
name: Topology Optimization Specialist
responsibilities:
- Analyze and optimize swarm topology
- Adapt topology based on workload
- Balance communication overhead
- Ensure optimal agent distribution
capabilities:
- topology-analysis
- graph-optimization
- network-design
- load-distribution
- adaptive-configuration
tools:
allowed:
- mcp__claude-flow__topology_optimize
- mcp__claude-flow__swarm_monitor
- mcp__claude-flow__coordination_sync
- mcp__claude-flow__swarm_status
- mcp__claude-flow__metrics_collect
restricted:
- Write
- Edit
- Bash
triggers:
- pattern: "topology|optimize.*swarm|network.*structure"
priority: medium
- keyword: "topology-optimizer"
---
8. Monitoring Agents
Swarm Monitor Agent
Command: .claude$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"
---
Implementation Guidelines
1. Agent Activation
- Agents are activated by pattern matching in user messages
- Higher priority patterns take precedence
- Multiple agents can be activated for complex tasks
2. Tool Restrictions
- Each agent has specific allowed and restricted tools
- Restrictions ensure agents stay within their domain
- Critical operations require specialized agents
3. Inter-Agent Communication
- Agents communicate through shared memory
- Task orchestrator coordinates multi-agent workflows
- Results are aggregated by coordinator agents
4. Migration Steps
- Create
.claude$agents/directory structure - Convert each command to agent definition format
- Update activation patterns for natural language
- Test agent interactions and handoffs
- Implement gradual rollout with fallbacks
5. Backwards Compatibility
- Keep command files during transition
- Map command invocations to agent activations
- Provide migration warnings for deprecated commands
Monitoring Migration Success
Key Metrics
- Agent activation accuracy
- Task completion rates
- Inter-agent coordination efficiency
- User satisfaction scores
- Performance improvements
Validation Criteria
- All commands have equivalent agents
- No functionality loss during migration
- Improved natural language understanding
- Better task decomposition and parallelization
- Enhanced error handling and recovery
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核