moai-foundation-context

Manage token budget limits by monitoring token usage against a 200K limit to prevent context overflow. This approach allocates budgets across multiple agents and uses progressive disclosure to load information on-demand, avoiding performance degradation.

Session state persistence saves and restores workflow progress during interruptions. It allows you to resume long-running tasks without losing context, preventing repetitive work and maintaining workflow continuity across session resets.

Handle multi-agent context handoffs by passing only necessary context between agents to minimize overhead. This strategy ensures smooth transitions while preserving critical information across different AI systems without exceeding context limits.

Progressive disclosure optimizes context windows by loading information contextually and on-demand. This mechanism reduces token consumption by ensuring only relevant data is active, effectively preventing context overflow.

Use this for long-running projects involving multiple AI agents to ensure critical information is preserved across session resets and agent handoffs. It prevents repetitive work and maintains workflow continuity throughout complex tasks.