How does the Swarm pattern improve research?

The Swarm pattern spawns multiple agents with different expert perspectives (e.g., security, performance, architecture) to analyze a problem simultaneously and merge their findings.

Does it work with existing Claude Code workflows?

Yes, it is designed to enhance Claude's native capabilities by providing a structured way to spawn and manage specialized sub-agents for complex tasks.

Can I invoke agentica-spawn directly?

The skill is typically triggered automatically after an orchestration phase or when a user explicitly requests a complex multi-agent pattern to solve a task.

What are the supported multi-agent patterns?

This skill supports four primary patterns: Swarm for research/exploration, Hierarchical for structured building, Generator/Critic for iterative refinement, and Jury for validation.

What is the purpose of the Jury pattern?

The Jury pattern uses multiple agents to evaluate a solution and reach a verdict based on consensus (e.g., majority vote), making it ideal for high-stakes verification.

Agentica Multi-Agent Spawn

Name: Agentica Multi-Agent Spawn
Author: scooter-lacroix

byscooter-lacroix

数据科学与机器学习

Instantiates sophisticated multi-agent architectures to handle complex reasoning, research, and implementation tasks.

关于

The Agentica Multi-Agent Spawn skill enables Claude to deploy specialized agent patterns—including Swarm, Hierarchical, Generator/Critic, and Jury architectures—to tackle intricate development challenges. By distributing workloads across specific agent roles, it allows for parallelized research, structured implementation planning, iterative refinement, and consensus-based validation. This skill is essential for high-stakes projects where a single agent's reasoning may benefit from the diverse perspectives or the rigorous check-and-balance systems provided by a multi-agent workflow.

主要功能

Automated deployment of Swarm, Hierarchical, and Jury agent patterns
0 GitHub stars
Parallel agent execution for multi-perspective research and exploration
Consensus-based validation via the Jury pattern for high-stakes decisions
Context preservation through SWARM_ID and AGENT_ROLE environment variables
Generator/Critic loops for iterative refinement of code and design

使用场景

Orchestrating complex software implementations using specialized coordinator and specialist roles
Conducting deep-dive research by aggregating diverse expert perspectives
Verifying security or architectural decisions through majority-vote juror validation

关于

主要功能

Automated deployment of Swarm, Hierarchical, and Jury agent patterns
0 GitHub stars
Parallel agent execution for multi-perspective research and exploration
Consensus-based validation via the Jury pattern for high-stakes decisions
Context preservation through SWARM_ID and AGENT_ROLE environment variables
Generator/Critic loops for iterative refinement of code and design

使用场景

Orchestrating complex software implementations using specialized coordinator and specialist roles
Conducting deep-dive research by aggregating diverse expert perspectives
Verifying security or architectural decisions through majority-vote juror validation