context-engineering

To optimize agent context, coordinate loading rules files, specs, and source files to prevent overloading or under-informing the agent. This ensures relevant context is available at the right time without context drift, reducing errors and maintaining output quality.

Context engineering organizes context from persistent rules to transient conversation history. It creates and manages rules files for project-wide context persistence, ensuring agents maintain focus and relevance across complex development tasks without overloading.

Loading specifications and source files involves coordinating task-specific context inputs alongside persistent rules. This curates exact information needed for the agent's current development task, preventing context drift and enhancing output quality.

Yes, you can integrate Model Context Protocol servers. MCP integrations provide richer context by connecting external context sources, which helps handle context conflicts and incomplete requirements effectively during development tasks.

The best way to handle context conflicts is through confusion management, which resolves incomplete requirements effectively. This avoids common context engineering anti-patterns, maintaining consistency and preventing agent output degradation.

You should restructure agent context when output degrades or context drift occurs. Avoiding anti-patterns through confusion management and conversation history control maintains consistency and ensures relevant context without overloading the agent.