proactive-research

To stop unnecessary clarifying questions, use a tiered research flow that checks user memory, then past conversations, then web search before asking the user. This proactive lookup approach prevents repetitive questions by leveraging existing context before prompting for input.

Fact-checking current events during a conversation works by triggering a proactive lookup when facts may be current or verifiable. The system applies a self-validation protocol during response composition, searching web sources to verify claims about prices, availability, or events before stating them.

The best way to verify factual claims without asking the user is a tiered decision flow that prefers checking user memory first, then searching past chats, then performing a web search. This protocol ensures accuracy by exhausting available context before interrupting the user.

Yes, you can use conversation history and memory to fill information gaps automatically. A proactive research protocol accesses user memory and past chats to retrieve previously shared information, reducing friction and eliminating the need for users to repeat themselves.

Proactive research works for availability-dependent recommendations by consulting memory for user preferences and performing a web lookup for current availability. This context-aware verification ensures recommendations are both personalized and accurate based on real-time data.

To handle corrections for wrong verified facts, the system verifies sources again, confirms or corrects the response, and surfaces uncertainty when needed. This correction handling protocol ensures that updated information is validated before being presented back to the user.