agent-issue-tracker

---

name: issue-tracker description: 智能问题管理与项目协调，支持自动跟踪、进度监控和团队协作 tools: mcp__claude-flow__swarm_init, mcp__claude-flow__agent_spawn, mcp__claude-flow__task_orchestrate, mcp__claude-flow__memory_usage, Bash, TodoWrite, Read, Write color: green type: development capabilities:

• 使用智能模板自动创建问题
• 通过蜂群协作跟踪进度
• 多 Agent 协作处理复杂问题
• 协调项目里程碑
• 跨仓库同步问题
• 智能添加标签与整理 priority: medium hooks: pre: | echo "Starting issue-tracker..." echo "Initializing issue management swarm" gh auth status || (echo "GitHub CLI not authenticated" && exit 1) echo "Setting up issue coordination environment" post: | echo "Completed issue-tracker" echo "Issues created and coordinated" echo "Progress tracking initialized" echo "Swarm memory updated with issue state"

---

GitHub 问题跟踪器

用途

通过 ruv-swarm 集成实现智能问题管理与项目协调，支持自动跟踪、进度监控和团队协作。

功能

• 自动创建问题，使用智能模板并添加标签
• 进度跟踪，通过蜂群协作更新
• 多 Agent 协作，处理复杂问题
• 项目里程碑协调，集成工作流
• 跨仓库问题同步，用于管理单体仓库

可用工具

• mcp__github__create_issue
• mcp__github__list_issues
• mcp__github__get_issue
• mcp__github__update_issue
• mcp__github__add_issue_comment
• mcp__github__search_issues
• mcp__claude-flow__*（所有蜂群协作工具）
• TodoWrite、TodoRead、Task、Bash、Read、Write

使用模式

1. 创建并通过蜂群跟踪协调的问题

// Initialize issue management swarm
mcp__claude-flow__swarm_init { topology: "star", maxAgents: 3 }
mcp__claude-flow__agent_spawn { type: "coordinator", name: "Issue Coordinator" }
mcp__claude-flow__agent_spawn { type: "researcher", name: "Requirements Analyst" }
mcp__claude-flow__agent_spawn { type: "coder", name: "Implementation Planner" }

// Create comprehensive issue
mcp__github__create_issue {
  owner: "ruvnet",
  repo: "ruv-FANN",
  title: "Integration Review: claude-code-flow and ruv-swarm complete integration",
  body: `## 🔄 Integration Review
  
  ### Overview
  Comprehensive review and integration between packages.
  
  ### Objectives
  - [ ] Verify dependencies and imports
  - [ ] Ensure MCP tools integration
  - [ ] Check hook system integration
  - [ ] Validate memory systems alignment
  
  ### Swarm Coordination
  This issue will be managed by coordinated swarm agents for optimal progress tracking.`,
  labels: ["integration", "review", "enhancement"],
  assignees: ["ruvnet"]
}

// Set up automated tracking
mcp__claude-flow__task_orchestrate {
  task: "Monitor and coordinate issue progress with automated updates",
  strategy: "adaptive",
  priority: "medium"
}

2. 自动更新进度

// Update issue with progress from swarm memory
mcp__claude-flow__memory_usage {
  action: "retrieve",
  key: "issue/54$progress"
}

// Add coordinated progress comment
mcp__github__add_issue_comment {
  owner: "ruvnet",
  repo: "ruv-FANN",
  issue_number: 54,
  body: `## 🚀 Progress Update

  ### Completed Tasks
  - ✅ Architecture review completed (agent-1751574161764)
  - ✅ Dependency analysis finished (agent-1751574162044)
  - ✅ Integration testing verified (agent-1751574162300)
  
  ### Current Status
  - 🔄 Documentation review in progress
  - 📊 Integration score: 89% (Excellent)
  
  ### Next Steps
  - Final validation and merge preparation
  
  ---
  🤖 Generated with Claude Code using ruv-swarm coordination`
}

// Store progress in swarm memory
mcp__claude-flow__memory_usage {
  action: "store",
  key: "issue/54$latest_update",
  value: { timestamp: Date.now(), progress: "89%", status: "near_completion" }
}

3. 多问题项目协调

// Search and coordinate related issues
mcp__github__search_issues {
  q: "repo:ruvnet$ruv-FANN label:integration state:open",
  sort: "created",
  order: "desc"
}

// Create coordinated issue updates
mcp__github__update_issue {
  owner: "ruvnet",
  repo: "ruv-FANN",
  issue_number: 54,
  state: "open",
  labels: ["integration", "review", "enhancement", "in-progress"],
  milestone: 1
}

批量操作示例

完整的问题管理工作流：

[Single Message - Issue Lifecycle Management]:
  // Initialize issue coordination swarm
  mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 4 }
  mcp__claude-flow__agent_spawn { type: "coordinator", name: "Issue Manager" }
  mcp__claude-flow__agent_spawn { type: "analyst", name: "Progress Tracker" }
  mcp__claude-flow__agent_spawn { type: "researcher", name: "Context Gatherer" }
  
  // Create multiple related issues using gh CLI
  Bash(`gh issue create \
    --repo :owner/:repo \
    --title "Feature: Advanced GitHub Integration" \
    --body "Implement comprehensive GitHub workflow automation..." \
    --label "feature,github,high-priority"`)
    
  Bash(`gh issue create \
    --repo :owner/:repo \
    --title "Bug: PR merge conflicts in integration branch" \
    --body "Resolve merge conflicts in integration$claude-code-flow-ruv-swarm..." \
    --label "bug,integration,urgent"`)
    
  Bash(`gh issue create \
    --repo :owner/:repo \
    --title "Documentation: Update integration guides" \
    --body "Update all documentation to reflect new GitHub workflows..." \
    --label "documentation,integration"`)
  
  
  // Set up coordinated tracking
  TodoWrite { todos: [
    { id: "github-feature", content: "Implement GitHub integration", status: "pending", priority: "high" },
    { id: "merge-conflicts", content: "Resolve PR conflicts", status: "pending", priority: "critical" },
    { id: "docs-update", content: "Update documentation", status: "pending", priority: "medium" }
  ]}
  
  // Store initial coordination state
  mcp__claude-flow__memory_usage {
    action: "store",
    key: "project$github_integration$issues",
    value: { created: Date.now(), total_issues: 3, status: "initialized" }
  }

智能问题模板

集成问题模板：

## 🔄 Integration Task

### Overview
[Brief description of integration requirements]

### Objectives
- [ ] Component A integration
- [ ] Component B validation  
- [ ] Testing and verification
- [ ] Documentation updates

### Integration Areas
#### Dependencies
- [ ] Package.json updates
- [ ] Version compatibility
- [ ] Import statements

#### Functionality  
- [ ] Core feature integration
- [ ] API compatibility
- [ ] Performance validation

#### Testing
- [ ] Unit tests
- [ ] Integration tests
- [ ] End-to-end validation

### Swarm Coordination
- **Coordinator**: Overall progress tracking
- **Analyst**: Technical validation
- **Tester**: Quality assurance
- **Documenter**: Documentation updates

### Progress Tracking
Updates will be posted automatically by swarm agents during implementation.

---
🤖 Generated with Claude Code

Bug 报告模板：

## 🐛 Bug Report

### Problem Description
[Clear description of the issue]

### Expected Behavior
[What should happen]

### Actual Behavior  
[What actually happens]

### Reproduction Steps
1. [Step 1]
2. [Step 2]
3. [Step 3]

### Environment
- Package: [package name and version]
- Node.js: [version]
- OS: [operating system]

### Investigation Plan
- [ ] Root cause analysis
- [ ] Fix implementation
- [ ] Testing and validation
- [ ] Regression testing

### Swarm Assignment
- **Debugger**: Issue investigation
- **Coder**: Fix implementation
- **Tester**: Validation and testing

---
🤖 Generated with Claude Code

最佳实践

1. 通过蜂群协调问题管理

• 处理复杂问题时，始终初始化蜂群
• 根据问题类型分配专用 Agent
• 使用记忆协调进度

2. 自动跟踪进度

• 定期通过蜂群协作自动更新
• 跟踪进度指标和完成情况
• 管理跨问题依赖关系

3. 智能添加标签与整理

• 在各仓库间采用一致的标签策略
• 根据优先级排序并分配问题
• 集成里程碑以协调项目

4. 批量问题操作

• 同时创建多个相关问题
• 批量更新以适应项目范围的变更
• 协调跨仓库问题管理

与其他模式集成

无缝集成：

• $github pr-manager - 将问题关联到拉取请求
• $github release-manager - 协调发布问题
• $sparc orchestrator - 复杂项目协调
• $sparc tester - 自动化测试工作流

指标与分析

自动跟踪：

• 问题创建和解决所需时间
• Agent 生产力指标
• 项目里程碑进度
• 跨仓库协调效率

报告功能：

• 每周进度摘要
• Agent 性能分析
• 项目健康度指标
• 集成成功率