Question 1

How do I add custom tools to SwarmSDK agents?

Accepted Answer

Use the plugin system to define tools in Ruby, then register them via SwarmSDK.register_plugin. The documentation provides examples for integrating external APIs or internal logic, making extensions straightforward.

Question 2

SwarmSDK vs LangChain for building AI agents in Ruby?

Accepted Answer

SwarmSDK is Ruby-native with a single-process design and integrated memory, ideal for tight Ruby integration. LangChain supports multiple languages but is less optimized for Ruby; choose SwarmSDK for Ruby-centric projects and LangChain for cross-language needs.

Question 3

Can SwarmSDK handle long-running agent workflows?

Accepted Answer

Yes, through node workflows that define dependencies between agents for multi-stage pipelines. SwarmMemory ensures persistent context across sessions, suitable for continuous tasks like research or monitoring.

Question 4

How to monitor costs when using multiple LLM providers?

Accepted Answer

SwarmSDK includes built-in cost tracking that logs token usage and expenses per agent execution. Configure logging in the Ruby DSL or YAML to output detailed cost data for analysis and optimization.

Question 5

What's the best way to debug agent interactions?

Accepted Answer

Use the interactive REPL mode in SwarmCLI for real-time conversation stepping, or enable structured logging to capture execution flows and hook outputs, as detailed in the production features guide.

Question 6

How to migrate from Claude Swarm v1 to SwarmSDK v2?

Accepted Answer

The documentation highlights key differences: v2 uses single-process RubyLLM instead of multi-process MCP. Convert YAML configurations and leverage the Ruby DSL for more control, following the migration notes in the docs.

Claude Swarm

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