Tool Use
The ability of LLMs to call external tools and APIs – from calculators to web search to databases and custom functions.
Tool use enables LLMs to call APIs and external services – from web search to database queries. The core of agentic AI.
Explanation
Tool use works through structured outputs: The LLM decides which tool it needs, generates the API call in defined format (JSON), the system executes it, and the result is fed back. Extends LLM capabilities without training.
Marketing Relevance
Core capability for agentic AI: Marketing assistants can retrieve CRM data, launch campaigns, generate reports. GPT-4, Claude, Gemini support native tool use. 2025 standard for productive AI applications.
Example
A marketing agent has tools for: Google Analytics (retrieve data), email system (send newsletter), image generator (create creatives). User says "Analyze last campaign and create report" – agent orchestrates all tools automatically.
Common Pitfalls
Tool selection can be incorrect. Error handling for API failures is important. Security risks with powerful tools. Costs from additional API calls. Latency from tool execution.
Origin & History
Tool use became popular in 2023 with GPT-4 Function Calling and has been standard with all leading LLMs since 2024. Anthropic, Google, and Meta have developed their own implementations.
Comparisons & Differences
Tool Use vs. Function Calling
Function calling is the technical implementation; tool use is the broader concept that also includes planning and orchestration.
Tool Use vs. RAG
RAG only retrieves information; tool use also executes actions (send emails, modify data, call APIs).