The paper describes the /insights command, a new feature in "Claude Code" that generates a detailed report on a user's Claude usage. This command functions as an AI-powered user analytics and feedback system.

The core methodology involves the deep analysis of a user's interaction history with the Claude AI. Specifically, /insights performs the following:

1. Usage Pattern Recognition: It identifies recurring user behaviors and task domains by analyzing the content and sequence of interactions. For instance, it categorized the author as a "browser automation specialist" based on scripting user flows and executing them in Chrome, which leads to characteristically long-running and resource-intensive sessions.
2. Performance Metrics Evaluation: The system assesses efficiency and outcomes of user sessions. It quantifies aspects like conversation abandonment rates, identifying instances where users conclude interactions without achieving discernible "concrete results."
3. Contextual Feedback Generation: Based on the identified patterns and performance metrics, the system formulates personalized feedback. This feedback is designed to mimic a "well-informed, highly trained human manager," offering gentle critiques and actionable recommendations.
4. Prescriptive Solution Provision: The system provides concrete, actionable suggestions for improving user interaction and leveraging Claude more effectively. These suggestions include creating reusable "skills, agents, and hooks," often accompanied by "copy-and-pastable" examples, implying an underlying mechanism that recognizes opportunities for encapsulation and reusability of successful interaction patterns.
5. Adaptive Reporting: The system appears to weight recent user activity heavily in its analysis, leading to reports that can shift emphasis based on differential sessions while maintaining broad consistency.

The system's output prompts user engagement, encouraging users to learn how to interpret AI feedback and justify their work styles to an AI, positioning this interaction as an essential future skill. The author describes the experience as a "striking," "feels like the future" interaction, highlighting its immediate utility despite the current lack of official documentation.