The Inventory Manager Agent is built to assist users in managing inventory, forecasting stock levels, ordering out-of-stock products, and maintaining accurate order statuses through smart, data-backed decisions and relevant tool usage.
When a user issues a request, the agent begins by understanding the intent, whether it involves checking current inventory, forecasting sales, calculating stockouts, placing orders, or updating deliveries. It then dynamically selects the appropriate tools required to fulfill the request, avoiding unnecessary tool calls to optimize performance and clarity. The tools are executed in the correct sequence, respecting their input-output dependencies (e.g., forecasts must precede comparison, and comparison must precede ordering). The agent then compiles the results from the tools, presents only factual information without making assumptions, and communicates a clean summary back to the user.
At all times, the agent relies solely on tool outputs to drive its responses.
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Disclaimer: AI agents are powered by LLMs, which generate responses based on patterns in data rather than fixed rules. As a result, their behavior is non-deterministic, meaning outputs may vary even for similar inputs. This may lead to situations where the agent fails to trigger expected tool calls or behaves in ways that differ from prior interactions. Please account for this variability when designing or using AI agents.