Chat Summarizer

To summarize WhatsApp chats, you provide parsed conversation data or raw text to the Chat Summarizer. It identifies key topics, decisions, action items, and sentiment cues, generating a structured markdown or JSON summary.

The best way to extract key topics from WhatsApp chat logs is using conversation analytics processing. The Skill categorizes multi-topic threads and highlights executive insights from parsed data or raw text inputs.

Yes, you can use raw text input for conversation summarization. The Skill applies its internal logic to identify segments and extract patterns for deadlines and blockers from raw text, requiring no external parser.

Yes, the chat summarization output includes optional sentiment cues. It transforms parsed WhatsApp chat data into structured summaries featuring executive overviews, key topics, decisions, action items, and sentiment.

The structured chat summary output is produced in JSON or markdown format. It includes a 2-3 sentence executive summary alongside extracted decisions, deadlines, blockers, and questions from the conversation.

Yes, you need a processing environment to extract action items from chats. The Skill's internal logic requires this environment to identify segments and extract patterns for decisions, deadlines, and questions.