agentleFS
fidgetcodingfidgetcoding/fidgetflo/.agents/skills/agent-issue-tracker/SKILL.md

agent-issue-tracker

Skill1 starsChanged 7 months agoMITView on GitHub

Agent skill for issue-tracker - invoke with $agent-issue-tracker

5 other projects use a version of this, 5 of them edited.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 3 are common, 0 are distinctive, and 0 are very specific to this project.

  • 3

    Common

    Most of the 5 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    Always initialize swarm for complex issues

    line 285
  2. Common:

    Use memory for progress coordination

    line 287
  3. Common:

    Create multiple related issues simultaneously

    line 300

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

name: issue-tracker description: Intelligent issue management and project coordination with automated tracking, progress monitoring, and team coordination tools: mcp__fidgetflo__swarm_init, mcp__fidgetflo__agent_spawn, mcp__fidgetflo__task_orchestrate, mcp__fidgetflo__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__fidgetflo__* (all swarm coordination tools)
  • TodoWrite, TodoRead, Task, Bash, Read, Write

Usage Patterns

1. Create Coordinated Issue with Swarm Tracking

// Initialize issue management swarm
mcp__fidgetflo__swarm_init { topology: "star", maxAgents: 3 }
mcp__fidgetflo__agent_spawn { type: "coordinator", name: "Issue Coordinator" }
mcp__fidgetflo__agent_spawn { type: "researcher", name: "Requirements Analyst" }
mcp__fidgetflo__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__fidgetflo__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__fidgetflo__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__fidgetflo__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__fidgetflo__swarm_init { topology: "mesh", maxAgents: 4 }
  mcp__fidgetflo__agent_spawn { type: "coordinator", name: "Issue Manager" }
  mcp__fidgetflo__agent_spawn { type: "analyst", name: "Progress Tracker" }
  mcp__fidgetflo__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__fidgetflo__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

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