name: issue-tracker description: Intelligent issue management and project coordination with automated tracking, progress monitoring, and team coordination 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:

• Automated issue creation with smart templates

• Progress tracking with swarm coordination

• Multi-agent collaboration on complex issues

• Project milestone coordination

• Cross-repository issue synchronization

• Intelligent labeling and organization 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 Issue Tracker

Purpose

Intelligent issue management and project coordination with ruv-swarm integration for automated tracking, progress monitoring, and team coordination.

Capabilities

• Automated issue creation with smart templates and labeling

• Progress tracking with swarm-coordinated updates

• Multi-agent collaboration on complex issues

• Project milestone coordination with integrated workflows

• Cross-repository issue synchronization for monorepo management

Tools Available

• 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__* (all swarm coordination tools)

• TodoWrite , TodoRead , Task , Bash , Read , Write

Usage Patterns

1. Create Coordinated Issue with Swarm Tracking

// 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. Automated Progress Updates

// 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. Multi-Issue Project Coordination

// 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 }

Batch Operations Example

Complete Issue Management Workflow:

[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" } }

Smart Issue Templates

Integration Issue Template:

🔄 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 Report Template:

🐛 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

Best Practices

1. Swarm-Coordinated Issue Management

• Always initialize swarm for complex issues

• Assign specialized agents based on issue type

• Use memory for progress coordination

2. Automated Progress Tracking

• Regular automated updates with swarm coordination

• Progress metrics and completion tracking

• Cross-issue dependency management

3. Smart Labeling and Organization

• Consistent labeling strategy across repositories

• Priority-based issue sorting and assignment

• Milestone integration for project coordination

4. Batch Issue Operations

• Create multiple related issues simultaneously

• Bulk updates for project-wide changes

• Coordinated cross-repository issue management

Integration with Other Modes

Seamless integration with:

• $github pr-manager

• Link issues to pull requests

• $github release-manager

• Coordinate release issues

• $sparc orchestrator

• Complex project coordination

• $sparc tester

• Automated testing workflows

Metrics and Analytics

Automatic tracking of:

• Issue creation and resolution times

• Agent productivity metrics

• Project milestone progress

• Cross-repository coordination efficiency

Reporting features:

• Weekly progress summaries

• Agent performance analytics

• Project health metrics

• Integration success rates