coworkia-memory

You can preserve context for a multi-agent workflow by using a structured memory store that saves long-term decisions, session histories, and preferences for seamless recall across activations. This ensures the agent operates with full project context.

Long-term memory retrieval automatically fetches relevant history, last-session summaries, and architectural notes at the start of a new session. It uses versioned notes to track project evolution and reduce repetitive explanations during activations.

To load historical context at the start of an agent session, initialize the memory skill during activation. This automatically retrieves pending plans, flight plans, and key decisions to guide the new session without manual input.

Yes, you can track project decisions and knowledge evolution by storing versioned notes and architectural decisions in a centralized memory. This records how the project evolved and why changes were made across multiple activations.

Yes, multi-agent memory retrieval is designed for safe retrieval during execution. It satisfies requirements for a structured memory store, ensuring session histories and pending plans are accessed without disrupting the active workflow.

An agent loses context between sessions because it lacks a centralized long-term memory for preserving decisions and session histories. Implementing contextual retrieval at session start automatically restores full project context and eliminates repetitive explanations.