recall

Proactive context retrieval uses the memory layer to let agents query past data and rationale directly, filling blind spots left by passive recall. This ensures critical historical information informs current decisions without waiting for triggers.

Active context recall is querying the memory store directly to fetch historical rationale. You need it when writing plans or specs to proactively search for past decisions that inform the current process and avoid overlooking critical information.

Memory layer interaction queries the memory store directly to retrieve historical data and reasoning. It enables cross-module reuse by allowing agents to access consolidated context from past modules during current problem-solving.

Yes, you need the Xihe system to manage and consolidate context effectively. It provides the memory layer required for this Skill to retrieve historical data, review rationale, and learn historical lessons.

The best way to query past decisions is using active context recall to search the memory layer directly. This approach retrieves historical rationale proactively, optimizing methodology queries and historical lesson learning.

Passive memory recall relies on triggered hooks, missing unprompted historical context. Active recall solves this by letting agents query the memory store directly, ensuring no critical information is overlooked during decision-making.