/issue-tracker
Intelligent issue management and project coordination with ruv-swarm integration for automated tracking, progress monitoring, and team coordination.
$ npx -y skills add spencermarx/open-code-review --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/issue-tracker
Context preview
What this command does when you run it.
Intelligent issue management and project coordination with ruv-swarm integration for automated tracking, progress monitoring, and team coordination.
Command definition
issue-tracker.mdGitHub 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: `## ๐ 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: `## ๐ Progress Update
### Completed Tasks
- โ
Architecture review completed (agent-1751574161764)
- โ
Dependency analysis finished (agent-1751574162044)
- โ
Integration testing verified (agent-1751574162300)
### Current Status
- ๐ Documentation review in progress
- ๐ Integration score: 89% (Excellent)
### Next Steps
- Final validation and merge preparation
---
๐ค 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:
## ๐ 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*
Read more
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: `## ๐ 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: `## ๐ Progress Update
### Completed Tasks
- โ
Architecture review completed (agent-1751574161764)
- โ
Dependency analysis finished (agent-1751574162044)
- โ
Integration testing verified (agent-1751574162300)
### Current Status
- ๐ Documentation review in progress
- ๐ Integration score: 89% (Excellent)
### Next Steps
- Final validation and merge preparation
---
๐ค 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:
## ๐ 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*
AI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse.
Repo: spencermarx/open-code-review
Other commands on open-code-review.
- /COMMAND_COMPLIANCE_REPORT
Reviewed all command files in `.claude/commands/analysis/` directory to ensure proper usage of: - `mcp__claude-flow__*` tools (preferred) - `npx claude-flow` commands (as fallback) - No direct implementation calls
Open command - /bottleneck-detect
Analyze performance bottlenecks in swarm operations and suggest optimizations.
Open command - /performance-bottlenecks
Identify and resolve performance bottlenecks in your development workflow.
Open command - /performance-report
Generate comprehensive performance reports for swarm operations.
Open command - /token-efficiency
Reduce token consumption while maintaining quality through intelligent coordination.
Open command - /token-usage
Analyze token usage patterns and optimize for efficiency.
Open command

