Tool Use
Tool use is the capability of AI agents to invoke external functions, APIs, databases, and services to retrieve information or take actions in the real world beyond generating text.
理解する Tool Use
Raw language models can only generate text. Tool use transforms them into agents that can act. When an LLM has access to tools, it can decide to call a function to search the web, read a file, query a database, send an email, or interact with any API. The model receives the tool's output and incorporates it into its reasoning, enabling a cycle of thought, action, and observation that allows complex multi-step tasks to be completed. Tool use works through a standardized protocol. The LLM is given a list of available tools with their names, descriptions, and parameter schemas. When the model determines a tool should be called, it generates a structured tool call (typically JSON) with the function name and arguments. The application executes the call, collects the result, and returns it to the model as a new message. The model then continues reasoning with the tool output available. The quality of tool descriptions dramatically affects whether the model calls tools correctly. Well-written descriptions tell the model when to use a tool, what it does, and what parameters are required. Poor descriptions lead to incorrect tool selection or malformed arguments. ReAct (Reasoning and Acting) is a popular pattern for tool use that interleaves reasoning steps with tool calls, letting the model think about what to do, act, observe the result, and then reason about next steps.
GAIAの活用方法 Tool Use
Tool use is central to GAIA's ability to act across your digital tools. GAIA's agents use tool calling to read and send Gmail messages, create and update calendar events, manage tasks in Todoist and Linear, post to Slack, query databases, and interact with all 50+ connected integrations. Each tool is exposed through MCP, providing the agent with structured descriptions of what each tool does and how to call it correctly.
関連概念
Function Calling
Function calling is a feature of AI models that allows them to generate structured, machine-readable invocations of predefined functions, enabling AI systems to reliably call external APIs and tools with the correct arguments.
AIエージェント
AIエージェントとは、環境を認識し、状況に応じた判断を下し、特定の目標を継続的な人間の指示なしに達成するために自律的に行動するソフトウェアシステムです。
モデルコンテキストプロトコル（MCP）
モデルコンテキストプロトコル（MCP）は、AIモデルが外部ツールやデータソース、サービスと安全に接続できる統一インターフェースを提供するオープンな標準規格です。
API統合
API統合とは、アプリケーションプログラミングインターフェースを介してさまざまなソフトウェアアプリケーションを接続し、データと機能をシームレスに共有できるようにするプロセスです。
エージェンティックAI
エージェンティックAIは、自律的に意思決定を行い、複数のステップから成るタスクを最小限の人間の監督で遂行するよう設計された人工知能システムを指します。
