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swarm-advanced

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

Updated May 8, 2026
Search Tags:#parallel execution#multi-agent#agent coordination#distributed workflows#testing automation#swarm orchestration#mcp tools
One-click install
npx skills add https://github.com/FrekiManagarm/d-chambaud --skill swarm-advanced-frekimanagarm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: swarm-advanced
Source: https://github.com/FrekiManagarm/d-chambaud/tree/main/.agents/skills/swarm-advanced
Command: npx skills add https://github.com/FrekiManagarm/d-chambaud --skill swarm-advanced-frekimanagarm

SYSTEM DOCUMENTATION & REQUIREMENTS

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 error handling that is difficult to manage ad hoc. ## Core Features & Use Cases - Swarm Topologies: Configure mesh, hierarchical, star, or ring topologies matched to research, development, testing, or pipeline workflows. - Parallel Orchestration: Spawn specialized agents (researchers, coders, testers, analysts) and execute tasks in parallel with memory-based state sharing. - Fault Tolerance & Monitoring: Auto-recovery strategies, state snapshots, health checks, and performance metrics for long-running swarms. - 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. ## Quick Start Initialize a mesh swarm with six agents and orchestrate a parallel research task on a topic of your choice.

Frequently Asked Questions about swarm-advanced

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

FAQPage Schema
How do I orchestrate multiple AI agents for a research task?▼

Initialize a mesh topology swarm, spawn researcher and analyst agents with specific capabilities, then use parallel task execution for information gathering followed by analysis and report generation phases.

Which swarm topology should I use for software development?▼

Hierarchical topology works best for development because it provides a clear command structure with a coordinator and supports sequential workflows. Mesh suits research, star suits testing, and ring suits pipeline processing.

Can I run swarm orchestration from the command line without MCP tools?▼

Yes, the skill provides CLI fallbacks using npx Codex-flow swarm commands with flags for strategy, mode, max agents, and parallel execution, covering research, development, and testing patterns.

How do I handle agent failures during parallel execution?▼

Enable fault tolerance with auto-recovery strategies, monitor swarm health status, analyze error patterns from logs, and retry failed tasks with sequential orchestration as a fallback.

Does swarm state persist across sessions?▼

Yes, memory can be persisted across sessions using namespaces, TTL settings, state snapshots, and backups, allowing agents to restore context and share findings between runs.

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