Agent skill

Agent Swarm Issue

by ruvnet in ruvnet/ruflo

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

MITAuto-check passedAgent Workflows

Install Agent Swarm Issue

skills CLI
$ npx skills add ruvnet/ruflo --skill agent-swarm-issue -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ruvnet/ruflo agent-swarm-issue --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/agent-swarm-issue .claude/skills/agent-swarm-issue && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agent-swarm-issue
GitHub stars
74k
Used in
2 other repos
Token cost
~3.6k tokens
SKILL.md length
327 words
Files
1
Skills in repo
264
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 12 steps: Issue-to-Swarm Conversion → Issue Comment Commands → Issue Templates for Swarms → …
  • Tasks that involve Multi-agent orchestration
  • SKILL.md covers Overview, Core Features, Issue Label Automation and Issue Swarm Commands, plus 5 more sections
  • Calls npx, gh and jq

What it does

Agent Swarm Issue is an agent skill from ruvnet/ruflo. Agent skill for swarm-issue - invoke with $agent-swarm-issue

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Multi-agent orchestration. It works with GitHub and Model Context Protocol. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.

When your agent uses it

  • Tasks that involve Multi-agent orchestration

Example prompts

  • “/agent-swarm-issue”

Requirements

  • Node.js

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Issue-to-Swarm Conversion
  2. Issue Comment Commands
  3. Issue Templates for Swarms
  4. Issue Dependencies
  5. Epic Management
  6. Issue Templates
  7. Issue-PR Linking
  8. Milestone Coordination
  9. Cross-Repo Issues
  10. Issue Templates
  11. Label Strategy
  12. Comment Etiquette

What it can do on your machine

Read from SKILL.md and the folder at commit 58e0ae7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx
    • gh
    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx and gh, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agent Swarm Issue loads about 3.6k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 327 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ruvnet/ruflo at commit 58e0ae7, republished under its MIT licence (© ruvnet). 327 words, ~3,610 tokens.

Download SKILL.mdSave it as .claude/skills/agent-swarm-issue/SKILL.md (or your agent's skills folder).
name
agent-swarm-issue
description
Agent skill for swarm-issue - invoke with $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
bash
# 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:

markdown
<!-- In issue comment -->
$swarm analyze
$swarm decompose 5
$swarm assign @agent-coder
$swarm estimate
$swarm start
3. Issue Templates for Swarms
markdown
<!-- .github/ISSUE_TEMPLATE$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
javascript
// .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
bash
# 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
bash
# 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
bash
# 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
bash
# 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
bash
# Handle issue dependencies
npx ruv-swarm github issue-deps 456 \
  --resolve-order \
  --parallel-safe \
  --update-blocking
2. Epic Management
bash
# Coordinate epic-level swarms
npx ruv-swarm github epic-swarm \
  --epic 123 \
  --child-issues "456,457,458" \
  --orchestrate
3. Issue Templates
bash
# Generate issue from swarm analysis
npx ruv-swarm github create-issues \
  --from-analysis \
  --template "bug-report" \
  --auto-assign

Workflow Integration

GitHub Actions for Issues
yaml
# .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
bash
# 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
bash
# Specialized bug handling
npx ruv-swarm github bug-swarm 456 \
  --reproduce \
  --isolate \
  --fix \
  --test
Feature Requests
bash
# Feature implementation swarm
npx ruv-swarm github feature-swarm 456 \
  --design \
  --implement \
  --document \
  --demo
Technical Debt
bash
# Refactoring swarm
npx ruv-swarm github debt-swarm 456 \
  --analyze-impact \
  --plan-migration \
  --execute \
  --validate

Automation Examples

Auto-Close Stale Issues
bash
# 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
bash
# Automated triage system
npx ruv-swarm github triage \
  --unlabeled \
  --analyze-content \
  --suggest-labels \
  --assign-priority
Duplicate Detection
bash
# Find duplicate issues
npx ruv-swarm github find-duplicates \
  --threshold 0.8 \
  --link-related \
  --close-duplicates

Integration Patterns

1. Issue-PR Linking
bash
# Link issues to PRs automatically
npx ruv-swarm github link-pr \
  --issue 456 \
  --pr 789 \
  --update-both
2. Milestone Coordination
bash
# Coordinate milestone swarms
npx ruv-swarm github milestone-swarm \
  --milestone "v2.0" \
  --parallel-issues \
  --track-progress
3. Cross-Repo Issues
bash
# 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
bash
# Analyze swarm performance
npx ruv-swarm github issue-metrics \
  --issue 456 \
  --metrics "time-to-close,agent-efficiency,subtask-completion"
Swarm Effectiveness
bash
# 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
bash
# 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
bash
# 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
bash
# 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
bash
# 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
javascript
// 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

© ruvnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/agent-swarm-issue of ruvnet/ruflo.

Open the folder on GitHubat commit 58e0ae7

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in ruvnet/ruflo, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Categories

Questions about Agent Swarm Issue

What does Agent Swarm Issue do?

Agent skill for swarm-issue - invoke with $agent-swarm-issue. Agent Swarm Issue is an agent skill from ruvnet/ruflo.

When should I use Agent Swarm Issue?

Agent Swarm Issue fits situations like: tasks that involve Multi-agent orchestration.

How do I install Agent Swarm Issue in Claude Code?

Run `npx skills add ruvnet/ruflo --skill agent-swarm-issue -a claude-code`. Or copy the skill folder (.agents/skills/agent-swarm-issue in ruvnet/ruflo) into .claude/skills/agent-swarm-issue in your project. Claude Code loads it when a task matches its description.

How do I install Agent Swarm Issue in Codex?

Run `npx skills add ruvnet/ruflo --skill agent-swarm-issue -a codex`. Or copy the skill folder (.agents/skills/agent-swarm-issue in ruvnet/ruflo) into .agents/skills/agent-swarm-issue in your project. Codex loads it when a task matches its description.

Can I use Agent Swarm Issue in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/ruflo --skill agent-swarm-issue -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-swarm-issue, .gemini/skills/agent-swarm-issue, .github/skills/agent-swarm-issue and .opencode/skills/agent-swarm-issue in your project.

What does Agent Swarm Issue need to run?

Going by SKILL.md and its folder, Agent Swarm Issue needs the command-line tools its instructions call (npx, gh and jq). Our summary lists: Node.js.

Does Agent Swarm Issue access the network?

SKILL.md contains no URLs. Its commands use npx and gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Agent Swarm Issue safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agent Swarm Issue use?

Agent Swarm Issue is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Swarm Issue use?

About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Agent Swarm Issue?

Skills that share tags, products or a category with Agent Swarm Issue: Skill Seekers Builder (yusufkaraaslan/Skill_Seekers, 15k stars), Codex with ChatGPT Planning Loop (XiaoDuoYa/codex-with-chatgpt, 7.1k stars), MemPalace Task Handoff (MemPalace/mempalace, 59k stars) and Context Mode Ops (mksglu/context-mode, 26k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Swarm Issue?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,159 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 9, 2026.

Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.