Every article tagged Tool Use, in one place.
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"Agent" is used for many things, but the core idea is simple: an AI agent is an LLM that decides which tools to call, sees the results, and keeps going until the task is done . Your code runs the tools; the model chooses what to do next. The loop Send the user...
Tool use (also called function calling) lets a model request that your code run a function. The model never runs code itself; it returns a structured request and waits for your result. 1. Describe the tools tools = [ { "name": "search_products", "description":...
The model chooses tools based only on their names, descriptions and schemas. A vague description is the most common reason an agent picks the wrong tool or invents arguments. Write descriptions like documentation for a new teammate { "name": "create_refund", "...
When a request needs several independent lookups ("compare the weather in Delhi, Mumbai and Bengaluru"), the model can return multiple tool_use blocks in a single response. Running them one after another wastes time. Execute in parallel const toolUses = respon...
Reading data is low-risk. Sending emails, moving money or deleting records is not. A human-in-the-loop step pauses the agent and asks for approval before risky tools run. Classify your tools Read-only (search, get_*): run automatically. Reversible writes (draf...
