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swarm-advanced

Orchestrates multi-agent swarms for research, development, testing, and analysis workflows using Claude Flow.

Updated Aug 18, 2026
Search Tags:#workflow automation#parallel execution#multi-agent#agent coordination#swarm orchestration#claude flow#mcp tools
One-click install
npx skills add https://github.com/wandreandrade2018-maker/claude-config --skill swarm-advanced-wandreandrade2018-maker
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: swarm-advanced
Source: https://github.com/wandreandrade2018-maker/claude-config/tree/main/.claude/skills/swarm-advanced
Command: npx skills add https://github.com/wandreandrade2018-maker/claude-config --skill swarm-advanced-wandreandrade2018-maker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires claude-flow.

What problem does it solve? Coordinating multiple AI agents across complex tasks like research, full-stack development, and testing requires manual orchestration, topology selection, and state management. This Skill provides ready-made swarm patterns that handle agent spawning, parallel execution, memory persistence, and error recovery through Claude Flow MCP tools and CLI commands. ## Core Features & Use Cases - Four Swarm Patterns: Pre-built architectures for research (mesh), development (hierarchical), testing (star), and code analysis (mesh) swarms with specialized agent roles. - Topology and Strategy Selection: Guidance on choosing mesh, hierarchical, star, or ring topologies with adaptive, balanced, specialized, or parallel agent strategies. - State and Memory Management: Cross-session persistence, namespaces, snapshots, and backups for long-running swarm workflows. - Fault Tolerance and Monitoring: Auto-recovery strategies, error pattern analysis, real-time swarm monitoring, and performance metrics collection. - Use Case: Spin up a hierarchical development swarm with an architect, backend and frontend developers, testers, and a DevOps engineer to design, implement, test, and deploy a REST API in coordinated phases. ## Quick Start Ask the AI to initialize a Claude Flow swarm with a chosen topology, spawn specialized agents, and orchestrate your research, development, or testing task in parallel.

Frequently Asked Questions about swarm-advanced

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a multi-agent swarm with Claude Flow?▼

Install claude-flow via npm, then initialize a swarm with swarm_init specifying a topology like mesh or hierarchical. Spawn specialized agents with agent_spawn and orchestrate tasks using task_orchestrate or parallel_execute.

Which swarm topology should I use for my task?▼

Use mesh for research and collaborative analysis, hierarchical for structured development workflows, star for centralized testing and validation, and ring for sequential pipeline processing. The choice depends on whether agents need peer communication or central coordination.

Can Claude Flow swarms run tasks in parallel?▼

Yes, parallel_execute runs independent tasks concurrently across spawned agents, and batch_process handles multiple items like test suites. Dependent tasks should use sequential orchestration with defined dependencies.

Does Claude Flow persist state between sessions?▼

Yes, memory tools support cross-session persistence with namespaces, TTL values, state snapshots, and backups. Use memory_persist and state_snapshot to checkpoint progress and context_restore to resume later.

What happens when a swarm agent fails during execution?▼

Fault tolerance strategies like auto-recovery can be configured per agent. On failure, check swarm health with swarm_status, analyze error patterns with error_analysis, and retry with sequential orchestration if the swarm is healthy.

Is there a CLI alternative to Claude Flow MCP tools?▼

Yes, each pattern includes a CLI fallback using npx claude-flow swarm with flags for strategy, mode, agent count, and parallel execution. This works without configuring the MCP server.

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