Conversation Summary

Transform long conversations into structured granular analyses and a cohesive narrative synthesis. Designed for conversations too large for a single context window.

Workflow

Phase 1: Preparation

1. Assess the input. Read the file to determine format and size.
2. Chunk the conversation into segments of ~60-80K chars each. Split at natural boundaries (time gaps, topic shifts, message breaks). Never split mid-message.
3. Save chunks to chunks/chunk_1.txt through chunks/chunk_N.txt.
4. Determine chunk count from total size. Aim for 5-10 chunks. Fewer than 5 loses granularity; more than 10 creates too many analysis files.

For ChatGPT JSON exports, parse the JSON to extract messages first, then chunk the plain text. If the conversation has clear date/topic breaks, prefer those as chunk boundaries.

Phase 2: Parallel Granular Analysis

Spawn one joes-toolkit:conversation-chunk-analyzer agent per chunk using run_in_background: true. Each agent reads one chunk and produces a standardized 8-section analysis.