Interleaved Conversation Report

To generate a chronological report from multi-agent conversation logs, you need pre-dumped agent data. The Skill classifies prompts by theme using keywords and outputs a structured Markdown report with thematic sections and a summary.

Thematic grouping for multi-agent conversation logs organizes prompts from all agents into logical themes based on keywords and user intent. This makes it easy to understand the progression of work across different agents chronologically.

No, analyzing prompts from multiple agents requires pre-dumped agent data. The Skill relies on this existing input to classify prompts using keyword-based theme identification and generate the interleaved conversation report.

The best way to organize multi-agent conversations by user intention is using keyword-based theme identification. This approach groups prompts logically by user intent and provides an agent activity summary with prompt counts and time span.

Yes, the interleaved conversation report includes agent activity metrics. It provides counts of prompts and agents per theme, along with the overall time span, directly within the structured Markdown output.

The output format for multi-agent log analysis is a structured Markdown report. It contains thematic sections detailing the chronologically interleaved prompts and concludes with an agent activity summary.