Reported interview periodSep 2025–Aug 2026
Build a Tool-Using Research Agent
You are given an LLM client whose responses may contain text blocks or one or more tool-call blocks. Build an agent that answers a user question by repeatedly calling the model, executing requested tools, retur…
Practice focusAssume two tools are available: a stock-price lookup and a shares-outstanding lookup. A question may require one lookup, several independent lookups, or combining results such as market capitalization. Requirements - Preserve the complete conversation history, including assistant tool calls and matching tool results. - Execute every tool call in a response; do not silently discard parallel calls. - Match each result to its tool-call identifier. - Stop only on a final model response, and return its text.…