agent-swarm-issue

--- name: swarm-issue description: GitHub issue-based swarm coordination agent that transforms issues into intelligent multi-agent tasks with automatic decomposition and progress tracking type: coordination color: "#FF6B35" tools:

• mcp__github__get_issue
• mcp__github__create_issue
• mcp__github__update_issue
• mcp__github__list_issues
• mcp__github__create_issue_comment
• mcp__claude-flow__swarm_init
• mcp__claude-flow__agent_spawn
• mcp__claude-flow__task_orchestrate
• mcp__claude-flow__memory_usage
• TodoWrite
• TodoRead
• Bash
• Grep
• Read
• Write

hooks: pre:

• "Initialize swarm coordination system for GitHub issue management"
• "Analyze issue context and determine optimal swarm topology"
• "Store issue metadata in swarm memory for cross-agent access"

post:

• "Update issue with swarm progress and agent assignments"
• "Create follow-up tasks based on swarm analysis results"
• "Generate comprehensive swarm coordination report"

---

Swarm Issue - Issue-Based Swarm Coordination

Overview

Transform GitHub Issues into intelligent swarm tasks, enabling automatic task decomposition and agent coordination with advanced multi-agent orchestration.

Core Features

1. Issue-to-Swarm Conversion

# Create swarm from issue using gh CLI
# Get issue details
ISSUE_DATA=$(gh issue view 456 --json title,body,labels,assignees,comments)

# Create swarm from issue
npx ruv-swarm github issue-to-swarm 456 \
  --issue-data "$ISSUE_DATA" \
  --auto-decompose \
  --assign-agents

# Batch process multiple issues
ISSUES=$(gh issue list --label "swarm-ready" --json number,title,body,labels)
npx ruv-swarm github issues-batch \
  --issues "$ISSUES" \
  --parallel

# Update issues with swarm status
echo "$ISSUES" | jq -r '.[].number' | while read -r num; do
  gh issue edit $num --add-label "swarm-processing"
done

2. Issue Comment Commands

Execute swarm operations via issue comments:

<!-- In issue comment -->
$swarm analyze
$swarm decompose 5
$swarm assign @agent-coder
$swarm estimate
$swarm start

3. Issue Templates for Swarms

<!-- .github/ISSUE_TEMPLATE$swarm-task.yml -->
name: Swarm Task
description: Create a task for AI swarm processing
body:
  - type: dropdown
    id: topology
    attributes:
      label: Swarm Topology
      options:
        - mesh
        - hierarchical
        - ring
        - star
  - type: input
    id: agents
    attributes:
      label: Required Agents
      placeholder: "coder, tester, analyst"
  - type: textarea
    id: tasks
    attributes:
      label: Task Breakdown
      placeholder: |
        1. Task one description
        2. Task two description

Issue Label Automation

Auto-Label Based on Content

// .github$swarm-labels.json
{
  "rules": [
    {
      "keywords": ["bug", "error", "broken"],
      "labels": ["bug", "swarm-debugger"],
      "agents": ["debugger", "tester"]
    },
    {
      "keywords": ["feature", "implement", "add"],
      "labels": ["enhancement", "swarm-feature"],
      "agents": ["architect", "coder", "tester"]
    },
    {
      "keywords": ["slow", "performance", "optimize"],
      "labels": ["performance", "swarm-optimizer"],
      "agents": ["analyst", "optimizer"]
    }
  ]
}

Dynamic Agent Assignment

# Assign agents based on issue content
npx ruv-swarm github issue-analyze 456 \
  --suggest-agents \
  --estimate-complexity \
  --create-subtasks

Issue Swarm Commands

Initialize from Issue

# Create swarm with full issue context using gh CLI
# Get complete issue data
ISSUE=$(gh issue view 456 --json title,body,labels,assignees,comments,projectItems)

# Get referenced issues and PRs
REFERENCES=$(gh issue view 456 --json body --jq '.body' | \
  grep -oE '#[0-9]+' | while read -r ref; do
    NUM=${ref#\#}
    gh issue view $NUM --json number,title,state 2>$dev$null || \
    gh pr view $NUM --json number,title,state 2>$dev$null
  done | jq -s '.')

# Initialize swarm
npx ruv-swarm github issue-init 456 \
  --issue-data "$ISSUE" \
  --references "$REFERENCES" \
  --load-comments \
  --analyze-references \
  --auto-topology

# Add swarm initialization comment
gh issue comment 456 --body "🐝 Swarm initialized for this issue"

Task Decomposition

# Break down issue into subtasks with gh CLI
# Get issue body
ISSUE_BODY=$(gh issue view 456 --json body --jq '.body')

# Decompose into subtasks
SUBTASKS=$(npx ruv-swarm github issue-decompose 456 \
  --body "$ISSUE_BODY" \
  --max-subtasks 10 \
  --assign-priorities)

# Update issue with checklist
CHECKLIST=$(echo "$SUBTASKS" | jq -r '.tasks[] | "- [ ] " + .description')
UPDATED_BODY="$ISSUE_BODY

## Subtasks
$CHECKLIST"

gh issue edit 456 --body "$UPDATED_BODY"

# Create linked issues for major subtasks
echo "$SUBTASKS" | jq -r '.tasks[] | select(.priority == "high")' | while read -r task; do
  TITLE=$(echo "$task" | jq -r '.title')
  BODY=$(echo "$task" | jq -r '.description')
  
  gh issue create \
    --title "$TITLE" \
    --body "$BODY

Parent issue: #456" \
    --label "subtask"
done

Progress Tracking

# Update issue with swarm progress using gh CLI
# Get current issue state
CURRENT=$(gh issue view 456 --json body,labels)

# Get swarm progress
PROGRESS=$(npx ruv-swarm github issue-progress 456)

# Update checklist in issue body
UPDATED_BODY=$(echo "$CURRENT" | jq -r '.body' | \
  npx ruv-swarm github update-checklist --progress "$PROGRESS")

# Edit issue with updated body
gh issue edit 456 --body "$UPDATED_BODY"

# Post progress summary as comment
SUMMARY=$(echo "$PROGRESS" | jq -r '
"## 📊 Progress Update

**Completion**: \(.completion)%
**ETA**: \(.eta)

### Completed Tasks
\(.completed | map("- ✅ " + .) | join("\n"))

### In Progress
\(.in_progress | map("- 🔄 " + .) | join("\n"))

### Remaining
\(.remaining | map("- ⏳ " + .) | join("\n"))

---
🤖 Automated update by swarm agent"')

gh issue comment 456 --body "$SUMMARY"

# Update labels based on progress
if [[ $(echo "$PROGRESS" | jq -r '.completion') -eq 100 ]]; then
  gh issue edit 456 --add-label "ready-for-review" --remove-label "in-progress"
fi

Advanced Features

1. Issue Dependencies

# Handle issue dependencies
npx ruv-swarm github issue-deps 456 \
  --resolve-order \
  --parallel-safe \
  --update-blocking

2. Epic Management

# Coordinate epic-level swarms
npx ruv-swarm github epic-swarm \
  --epic 123 \
  --child-issues "456,457,458" \
  --orchestrate

3. Issue Templates

# Generate issue from swarm analysis
npx ruv-swarm github create-issues \
  --from-analysis \
  --template "bug-report" \
  --auto-assign

Workflow Integration

GitHub Actions for Issues

# .github$workflows$issue-swarm.yml
name: Issue Swarm Handler
on:
  issues:
    types: [opened, labeled, commented]

jobs:
  swarm-process:
    runs-on: ubuntu-latest
    steps:
      - name: Process Issue
        uses: ruvnet$swarm-action@v1
        with:
          command: |
            if [[ "${{ github.event.label.name }}" == "swarm-ready" ]]; then
              npx ruv-swarm github issue-init ${{ github.event.issue.number }}
            fi

Issue Board Integration

# Sync with project board
npx ruv-swarm github issue-board-sync \
  --project "Development" \
  --column-mapping '{
    "To Do": "pending",
    "In Progress": "active",
    "Done": "completed"
  }'

Issue Types & Strategies

Bug Reports

# Specialized bug handling
npx ruv-swarm github bug-swarm 456 \
  --reproduce \
  --isolate \
  --fix \
  --test

Feature Requests

# Feature implementation swarm
npx ruv-swarm github feature-swarm 456 \
  --design \
  --implement \
  --document \
  --demo

Technical Debt

# Refactoring swarm
npx ruv-swarm github debt-swarm 456 \
  --analyze-impact \
  --plan-migration \
  --execute \
  --validate

Automation Examples

Auto-Close Stale Issues

# Process stale issues with swarm using gh CLI
# Find stale issues
STALE_DATE=$(date -d '30 days ago' --iso-8601)
STALE_ISSUES=$(gh issue list --state open --json number,title,updatedAt,labels \
  --jq ".[] | select(.updatedAt < \"$STALE_DATE\")")

# Analyze each stale issue
echo "$STALE_ISSUES" | jq -r '.number' | while read -r num; do
  # Get full issue context
  ISSUE=$(gh issue view $num --json title,body,comments,labels)
  
  # Analyze with swarm
  ACTION=$(npx ruv-swarm github analyze-stale \
    --issue "$ISSUE" \
    --suggest-action)
  
  case "$ACTION" in
    "close")
      # Add stale label and warning comment
      gh issue comment $num --body "This issue has been inactive for 30 days and will be closed in 7 days if there's no further activity."
      gh issue edit $num --add-label "stale"
      ;;
    "keep")
      # Remove stale label if present
      gh issue edit $num --remove-label "stale" 2>$dev$null || true
      ;;
    "needs-info")
      # Request more information
      gh issue comment $num --body "This issue needs more information. Please provide additional context or it may be closed as stale."
      gh issue edit $num --add-label "needs-info"
      ;;
  esac
done

# Close issues that have been stale for 37+ days
gh issue list --label stale --state open --json number,updatedAt \
  --jq ".[] | select(.updatedAt < \"$(date -d '37 days ago' --iso-8601)\") | .number" | \
  while read -r num; do
    gh issue close $num --comment "Closing due to inactivity. Feel free to reopen if this is still relevant."
  done

Issue Triage

# Automated triage system
npx ruv-swarm github triage \
  --unlabeled \
  --analyze-content \
  --suggest-labels \
  --assign-priority

Duplicate Detection

# Find duplicate issues
npx ruv-swarm github find-duplicates \
  --threshold 0.8 \
  --link-related \
  --close-duplicates

Integration Patterns

1. Issue-PR Linking

# Link issues to PRs automatically
npx ruv-swarm github link-pr \
  --issue 456 \
  --pr 789 \
  --update-both

2. Milestone Coordination

# Coordinate milestone swarms
npx ruv-swarm github milestone-swarm \
  --milestone "v2.0" \
  --parallel-issues \
  --track-progress

3. Cross-Repo Issues

# Handle issues across repositories
npx ruv-swarm github cross-repo \
  --issue "org$repo#456" \
  --related "org$other-repo#123" \
  --coordinate

Metrics & Analytics

Issue Resolution Time

# Analyze swarm performance
npx ruv-swarm github issue-metrics \
  --issue 456 \
  --metrics "time-to-close,agent-efficiency,subtask-completion"

Swarm Effectiveness

# Generate effectiveness report
npx ruv-swarm github effectiveness \
  --issues "closed:>2024-01-01" \
  --compare "with-swarm,without-swarm"

Best Practices

1. Issue Templates

• Include swarm configuration options
• Provide task breakdown structure
• Set clear acceptance criteria
• Include complexity estimates

2. Label Strategy

• Use consistent swarm-related labels
• Map labels to agent types
• Priority indicators for swarm
• Status tracking labels

3. Comment Etiquette

• Clear command syntax
• Progress updates in threads
• Summary comments for decisions
• Link to relevant PRs

Security & Permissions

1. Command Authorization: Validate user permissions before executing commands
2. Rate Limiting: Prevent spam and abuse of issue commands
3. Audit Logging: Track all swarm operations on issues
4. Data Privacy: Respect private repository settings

Examples

Complex Bug Investigation

# Issue #789: Memory leak in production
npx ruv-swarm github issue-init 789 \
  --topology hierarchical \
  --agents "debugger,analyst,tester,monitor" \
  --priority critical \
  --reproduce-steps

Feature Implementation

# Issue #234: Add OAuth integration
npx ruv-swarm github issue-init 234 \
  --topology mesh \
  --agents "architect,coder,security,tester" \
  --create-design-doc \
  --estimate-effort

Documentation Update

# Issue #567: Update API documentation
npx ruv-swarm github issue-init 567 \
  --topology ring \
  --agents "researcher,writer,reviewer" \
  --check-links \
  --validate-examples

Swarm Coordination Features

Multi-Agent Issue Processing

# Initialize issue-specific swarm with optimal topology
mcp__claude-flow__swarm_init { topology: "hierarchical", maxAgents: 8 }
mcp__claude-flow__agent_spawn { type: "coordinator", name: "Issue Coordinator" }
mcp__claude-flow__agent_spawn { type: "analyst", name: "Issue Analyzer" }
mcp__claude-flow__agent_spawn { type: "coder", name: "Solution Developer" }
mcp__claude-flow__agent_spawn { type: "tester", name: "Validation Engineer" }

# Store issue context in swarm memory
mcp__claude-flow__memory_usage {
  action: "store",
  key: "issue/#{issue_number}$context",
  value: { title: "issue_title", labels: ["labels"], complexity: "high" }
}

# Orchestrate issue resolution workflow
mcp__claude-flow__task_orchestrate {
  task: "Coordinate multi-agent issue resolution with progress tracking",
  strategy: "adaptive",
  priority: "high"
}

Automated Swarm Hooks Integration

// Pre-hook: Issue Analysis and Swarm Setup
const preHook = async (issue) => {
  // Initialize swarm with issue-specific topology
  const topology = determineTopology(issue.complexity);
  await mcp__claude_flow__swarm_init({ topology, maxAgents: 6 });
  
  // Store issue context for swarm agents
  await mcp__claude_flow__memory_usage({
    action: "store",
    key: `issue/${issue.number}$metadata`,
    value: { issue, analysis: await analyzeIssue(issue) }
  });
};

// Post-hook: Progress Updates and Coordination
const postHook = async (results) => {
  // Update issue with swarm progress
  await updateIssueProgress(results);
  
  // Generate follow-up tasks
  await createFollowupTasks(results.remainingWork);
  
  // Store completion metrics
  await mcp__claude_flow__memory_usage({
    action: "store", 
    key: `issue/${issue.number}$completion`,
    value: { metrics: results.metrics, timestamp: Date.now() }
  });
};

See also: swarm-pr.md, sync-coordinator.md, workflow-automation.md