Unverified50% confidenceFactExact time
An Agent node can actively call mounted tools and process the returned results before continuing reasoning, which is the key distinction from a regular LLM API call (which only inputs text and returns text).
1
Sources
50%
Confidence
Long-term
Relevance
10/8/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe essence of an Agent is to give an LLM—which can only output text—the ability to access external data and execute operations through a tool-calling mechanism80% similarUnverifiedThe agent flow is: send a message to the model to get a response; if the stop reason is not tool use, return the text; otherwise, iterate through the tool-call blocks, validate parameters, run the function, push the result back as a tool result, and loop.77% similarVerifiedAgents use the Tool Calling mechanism to allow models to output calling intent in a structured JSON format, with external programs executing the actual operations and feeding results back to the model.76% similarVerifiedAn Agent's Action capability relies on standardized interfaces such as Function Calling or Tool Use to convert the model's text output into executable API calls.76% similarUnverifiedTools & Function Calling allows LLMs to invoke external tools and is key to agents breaking through the limitations of pure text generation.74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/987689API
curl https://kongchang.com/api/v1/knowledge/claims/987689MCP
get_claim(id=987689)