signal-detector

Ambient signal capture works by detecting original thinking and entity mentions from inbound messages in real-time, running concurrently without blocking responses to continuously enrich an AI agent brain repository.

You extract entity mentions by running the signal-detector skill, which automatically identifies original thinking and entities from inbound messages to create and update cross-linked brain pages.

Real-time entity detection does not block the main response, as the signal capture mechanism runs concurrently in parallel execution, ensuring continuous learning without adding latency to message processing.

The best way to maintain back-link integrity is using an always-on capture mechanism that automatically cross-links all detected entity mentions when creating and updating brain pages for future reference.

Tools that support continuous learning provide search, query, and page management functionalities to analyze detected original thinking and entity mentions captured from real-time inbound message streams.

Yes, you can query and manage previously captured signals because the system includes search, query, and page management tools designed specifically for analyzing and enriching brain page repositories.