后端与数据库

langchain4j-tool-function-calling-patterns

giuseppe-trisciuoglio/developer-kit

Provides and generates LangChain4j tool and function calling patterns: annotates methods as tools with @Tool, configures tool executors, registers tools with AiServices, validates tool parameters, and handles tool execution errors. Use when building AI agents that call tools, define function specifications, manage tool responses, or integrate external APIs with LLM-driven applications.

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安装命令

npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill langchain4j-tool-function-calling-patterns

SKILL.md

LangChain4j Tool & Function Calling Patterns

Provides patterns for annotating methods as tools, configuring tool executors, registering tools with AI services, validating parameters, and handling tool execution errors in LangChain4j applications.

Overview

LangChain4j uses the @Tool annotation to expose Java methods as callable functions for AI agents. The AiServices builder registers tools with a chat model, enabling LLMs to perform actions beyond text generation: database queries, API calls, calculations, and business system integrations. Parameters use @P for descriptions that guide the LLM.

When to Use

  • Building AI agents that call external tools (weather, stocks, database queries)
  • Defining function specifications for LLM tool use (@Tool, @P annotations)
  • Registering and managing tool sets with AiServices.builder().tools()
  • Handling tool execution errors, timeouts, and hallucinated tool names
  • Implementing context-aware tools that inject user state via @ToolMemoryId
  • Configuring dynamic tool providers for large or conditional tool sets

Instructions

LangChain4j Tool & Function Calling Patterns

Provides patterns for annotating methods as tools, configuring tool executors, registering tools with AI services, validating parameters, and handling tool execution errors in LangChain4j applications.

Overview

LangChain4j uses the @Tool annotation to expose Java methods as callable functions for AI agents. The AiServices builder registers tools with a chat model, enabling LLMs to perform actions beyond text generation: database queries, API calls, calculations, and business system integrations. Parameters use @P for descriptions that guide the LLM.

When to Use

  • Building AI agents that call external tools (weather, stocks, database queries)
  • Defining function specifications for LLM tool use (@Tool, @P annotations)
  • Registering and managing tool sets with AiServices.builder().tools()
  • Handling tool execution errors, timeouts, and hallucinated tool names
  • Implementing context-aware tools that inject user state via @ToolMemoryId
  • Configuring dynamic tool providers for large or conditional tool sets

Instructions