Langchain4j Tool Function Calling Patterns

This one teaches you how to wire up external function calls in LangChain4j agents using the @Tool annotation system. You annotate methods with @Tool and @P, register them with AiServices.builder().tools(), and the LLM can invoke them during conversations. The skill covers error handlers for when the model hallucinates tool names or passes bad arguments, concurrent execution for independent tools, and timeout configs for external API calls. It's practical if you're building agents that need to query databases, hit APIs, or perform calculations beyond what the LLM can do natively. The examples show calculator tools, email senders with immediate return behavior, and dynamic tool providers that change based on user context.