friction

Detect workflow friction by scanning chat history and session evidence for repeated commands and manual steps. The analysis surfaces categorized friction findings with frequency, automation potential, and effort to highlight hook or skill automation opportunities.

Interaction friction signals are corrections, errors, and pattern markers indicating context loss or miscommunication. They are identified by searching chat history for these markers to surface interaction issues across sessions.

Yes, friction detection can be embedded inside a retrospective recap to surface friction themes across sessions. It also supports standalone usage to analyze interaction and workflow friction from the current chat session context.

Chat session friction analysis requires access to chat history or session context. Providing this session evidence allows the detection process to identify repeated manual steps, corrections, and workflow automation opportunities.

Yes, friction analysis outputs categorized findings that include automation potential and effort metrics. It evaluates session evidence to classify interaction and workflow friction signals by frequency and the effort required to resolve them.