Coordinate multi-agent code reviews and automated workflows using GitHub Pull Requests.
Install
mkdir -p .claude/skills/agent-swarm-pr && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7390" && unzip -o skill.zip -d .claude/skills/agent-swarm-pr && rm skill.zipInstalls to .claude/skills/agent-swarm-pr
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Agent skill for swarm-pr - invoke with $agent-swarm-prKey capabilities
- →Spawn specialized agents based on PR labels
- →Automate code review and validation workflows
- →Coordinate multi-agent consensus for PR merges
- →Generate PR analytics and completion metrics
- →Manage PR lifecycle via comment commands
How it works
It analyzes PR diffs and metadata to spawn and orchestrate specialized agents that perform reviews, testing, and impact assessments.
Inputs & outputs
When to use agent-swarm-pr
- →Reviewing pull requests with agents
- →Automating PR validation workflows
- →Spawning review agents from PR labels
About this skill
name: swarm-pr description: Pull request swarm management agent that coordinates multi-agent code review, validation, and integration workflows with automated PR lifecycle management type: development color: "#4ECDC4" tools:
- mcp__github__get_pull_request
- mcp__github__create_pull_request
- mcp__github__update_pull_request
- mcp__github__list_pull_requests
- mcp__github__create_pr_comment
- mcp__github__get_pr_diff
- mcp__github__merge_pull_request
- mcp__claude-flow__swarm_init
- mcp__claude-flow__agent_spawn
- mcp__claude-flow__task_orchestrate
- mcp__claude-flow__memory_usage
- mcp__claude-flow__coordination_sync
- TodoWrite
- TodoRead
- Bash
- Grep
- Read
- Write
- Edit
hooks:
pre:
- "Initialize PR-specific swarm with diff analysis and impact assessment"
- "Analyze PR complexity and assign optimal agent topology"
- "Store PR metadata and diff context in swarm memory" post:
- "Update PR with comprehensive swarm review results"
- "Coordinate merge decisions based on swarm analysis"
- "Generate PR completion metrics and learnings"
Swarm PR - Managing Swarms through Pull Requests
Overview
Create and manage AI swarms directly from GitHub Pull Requests, enabling seamless integration with your development workflow through intelligent multi-agent coordination.
Core Features
1. PR-Based Swarm Creation
# Create swarm from PR description using gh CLI
gh pr view 123 --json body,title,labels,files | npx ruv-swarm swarm create-from-pr
# Auto-spawn agents based on PR labels
gh pr view 123 --json labels | npx ruv-swarm swarm auto-spawn
# Create swarm with PR context
gh pr view 123 --json body,labels,author,assignees | \
npx ruv-swarm swarm init --from-pr-data
2. PR Comment Commands
Execute swarm commands via PR comments:
<!-- In PR comment -->
$swarm init mesh 6
$swarm spawn coder "Implement authentication"
$swarm spawn tester "Write unit tests"
$swarm status
3. Automated PR Workflows
# .github$workflows$swarm-pr.yml
name: Swarm PR Handler
on:
pull_request:
types: [opened, labeled]
issue_comment:
types: [created]
jobs:
swarm-handler:
runs-on: ubuntu-latest
steps:
- uses: actions$checkout@v3
- name: Handle Swarm Command
run: |
if [[ "${{ github.event.comment.body }}" == $swarm* ]]; then
npx ruv-swarm github handle-comment \
--pr ${{ github.event.pull_request.number }} \
--comment "${{ github.event.comment.body }}"
fi
PR Label Integration
Automatic Agent Assignment
Map PR labels to agent types:
{
"label-mapping": {
"bug": ["debugger", "tester"],
"feature": ["architect", "coder", "tester"],
"refactor": ["analyst", "coder"],
"docs": ["researcher", "writer"],
"performance": ["analyst", "optimizer"]
}
}
Label-Based Topology
# Small PR (< 100 lines): ring topology
# Medium PR (100-500 lines): mesh topology
# Large PR (> 500 lines): hierarchical topology
npx ruv-swarm github pr-topology --pr 123
PR Swarm Commands
Initialize from PR
# Create swarm with PR context using gh CLI
PR_DIFF=$(gh pr diff 123)
PR_INFO=$(gh pr view 123 --json title,body,labels,files,reviews)
npx ruv-swarm github pr-init 123 \
--auto-agents \
--pr-data "$PR_INFO" \
--diff "$PR_DIFF" \
--analyze-impact
Progress Updates
# Post swarm progress to PR using gh CLI
PROGRESS=$(npx ruv-swarm github pr-progress 123 --format markdown)
gh pr comment 123 --body "$PROGRESS"
# Update PR labels based on progress
if [[ $(echo "$PROGRESS" | grep -o '[0-9]\+%' | sed 's/%//') -gt 90 ]]; then
gh pr edit 123 --add-label "ready-for-review"
fi
Code Review Integration
# Create review agents with gh CLI integration
PR_FILES=$(gh pr view 123 --json files --jq '.files[].path')
# Run swarm review
REVIEW_RESULTS=$(npx ruv-swarm github pr-review 123 \
--agents "security,performance,style" \
--files "$PR_FILES")
# Post review comments using gh CLI
echo "$REVIEW_RESULTS" | jq -r '.comments[]' | while read -r comment; do
FILE=$(echo "$comment" | jq -r '.file')
LINE=$(echo "$comment" | jq -r '.line')
BODY=$(echo "$comment" | jq -r '.body')
gh pr review 123 --comment --body "$BODY"
done
Advanced Features
1. Multi-PR Swarm Coordination
# Coordinate swarms across related PRs
npx ruv-swarm github multi-pr \
--prs "123,124,125" \
--strategy "parallel" \
--share-memory
2. PR Dependency Analysis
# Analyze PR dependencies
npx ruv-swarm github pr-deps 123 \
--spawn-agents \
--resolve-conflicts
3. Automated PR Fixes
# Auto-fix PR issues
npx ruv-swarm github pr-fix 123 \
--issues "lint,test-failures" \
--commit-fixes
Best Practices
1. PR Templates
<!-- .github$pull_request_template.md -->
## Swarm Configuration
- Topology: [mesh$hierarchical$ring$star]
- Max Agents: [number]
- Auto-spawn: [yes$no]
- Priority: [high$medium$low]
## Tasks for Swarm
- [ ] Task 1 description
- [ ] Task 2 description
2. Status Checks
# Require swarm completion before merge
required_status_checks:
contexts:
- "swarm$tasks-complete"
- "swarm$tests-pass"
- "swarm$review-approved"
3. PR Merge Automation
# Auto-merge when swarm completes using gh CLI
# Check swarm completion status
SWARM_STATUS=$(npx ruv-swarm github pr-status 123)
if [[ "$SWARM_STATUS" == "complete" ]]; then
# Check review requirements
REVIEWS=$(gh pr view 123 --json reviews --jq '.reviews | length')
if [[ $REVIEWS -ge 2 ]]; then
# Enable auto-merge
gh pr merge 123 --auto --squash
fi
fi
Webhook Integration
Setup Webhook Handler
// webhook-handler.js
const { createServer } = require('http');
const { execSync } = require('child_process');
createServer((req, res) => {
if (req.url === '$github-webhook') {
const event = JSON.parse(body);
if (event.action === 'opened' && event.pull_request) {
execSync(`npx ruv-swarm github pr-init ${event.pull_request.number}`);
}
res.writeHead(200);
res.end('OK');
}
}).listen(3000);
Examples
Feature Development PR
# PR #456: Add user authentication
npx ruv-swarm github pr-init 456 \
--topology hierarchical \
--agents "architect,coder,tester,security" \
--auto-assign-tasks
Bug Fix PR
# PR #789: Fix memory leak
npx ruv-swarm github pr-init 789 \
--topology mesh \
--agents "debugger,analyst,tester" \
--priority high
Documentation PR
# PR #321: Update API docs
npx ruv-swarm github pr-init 321 \
--topology ring \
--agents "researcher,writer,reviewer" \
--validate-links
Metrics & Reporting
PR Swarm Analytics
# Generate PR swarm report
npx ruv-swarm github pr-report 123 \
--metrics "completion-time,agent-efficiency,token-usage" \
--format markdown
Dashboard Integration
# Export to GitHub Insights
npx ruv-swarm github export-metrics \
--pr 123 \
--to-insights
Security Considerations
- Token Permissions: Ensure GitHub tokens have appropriate scopes
- Command Validation: Validate all PR comments before execution
- Rate Limiting: Implement rate limits for PR operations
- Audit Trail: Log all swarm operations for compliance
Integration with Claude Code
When using with Claude Code:
- Claude Code reads PR diff and context
- Swarm coordinates approach based on PR type
- Agents work in parallel on different aspects
- Progress updates posted to PR automatically
- Final review performed before marking ready
Advanced Swarm PR Coordination
Multi-Agent PR Analysis
# Initialize PR-specific swarm with intelligent topology selection
mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 8 }
mcp__claude-flow__agent_spawn { type: "coordinator", name: "PR Coordinator" }
mcp__claude-flow__agent_spawn { type: "reviewer", name: "Code Reviewer" }
mcp__claude-flow__agent_spawn { type: "tester", name: "Test Engineer" }
mcp__claude-flow__agent_spawn { type: "analyst", name: "Impact Analyzer" }
mcp__claude-flow__agent_spawn { type: "optimizer", name: "Performance Optimizer" }
# Store PR context for swarm coordination
mcp__claude-flow__memory_usage {
action: "store",
key: "pr/#{pr_number}$analysis",
value: {
diff: "pr_diff_content",
files_changed: ["file1.js", "file2.py"],
complexity_score: 8.5,
risk_assessment: "medium"
}
}
# Orchestrate comprehensive PR workflow
mcp__claude-flow__task_orchestrate {
task: "Execute multi-agent PR review and validation workflow",
strategy: "parallel",
priority: "high",
dependencies: ["diff_analysis", "test_validation", "security_review"]
}
Swarm-Coordinated PR Lifecycle
// Pre-hook: PR Initialization and Swarm Setup
const prPreHook = async (prData) => {
// Analyze PR complexity for optimal swarm configuration
const complexity = await analyzePRComplexity(prData);
const topology = complexity > 7 ? "hierarchical" : "mesh";
// Initialize swarm with PR-specific configuration
await mcp__claude_flow__swarm_init({ topology, maxAgents: 8 });
// Store comprehensive PR context
await mcp__claude_flow__memory_usage({
action: "store",
key: `pr/${prData.number}$context`,
value: {
pr: prData,
complexity,
agents_assigned: await getOptimalAgents(prData),
timeline: generateTimeline(prData)
}
});
// Coordinate initial agent synchronization
await mcp__claude_flow__coordination_sync({ swarmId: "current" });
};
// Post-hook: PR Completion and Metrics
const prPostHook = async (results) => {
// Generate comprehensive PR completion report
const report = await generatePRReport(results);
// Update PR with final swarm analysis
await up
---
*Content truncated.*
When not to use it
- →Small, trivial pull requests that do not require multi-agent review
Prerequisites
Limitations
- →Requires GitHub token permissions
- →Depends on PR label configuration
How it compares
It replaces manual code review processes with an automated, multi-agent consensus-based validation system.
Compared to similar skills
agent-swarm-pr side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| agent-swarm-pr (this skill) | 1 | 6mo | Review | Advanced |
| resolve-conflicts | 81 | 8mo | Review | Intermediate |
| git-advanced-workflows | 11 | 2mo | Review | Advanced |
| nx-workspace | 4 | 6mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
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