The `query_memory` tool autonomously searches the vector database and injects relevant data into the prompt.
Core Architecture
How It Works Under The Hood
The Dynamic Contextual Retrieval module is built on a highly optimized C++ and Python bridge. By bypassing standard Windows UI restrictions, Coral AI directly interfaces with system memory, native Win32 APIs, and DOM structures to achieve near-zero latency execution.
Implicit Search
You don't need to say 'search memory'. The AI queries it automatically if it senses missing context.
Semantic Matching
Finds the 'server IP' even if you ask for 'the remote network address'.
Millisecond Injection
Retrieves the fact and executes the task almost instantly.
Cross-Session Continuity
Start a conversation on Monday, and resume the exact context on Friday.
This module does not operate in isolation. It is dynamically invoked by the Coral PlannerAgent via JSON-RPC, allowing it to be chained endlessly with vision and memory modules.