quasi:synthesize

To generate a synthesis report, use this Skill to consolidate multiple analysis files into overarching cross-text summaries. It automates insight extraction, producing structured reports that highlight common themes across your research sources.

The best way to aggregate references is using the built-in Python scripts to compile and rank cited works. This creates a unified, comprehensive reading list from your literature review by extracting and consolidating references across multiple files.

Cross-text synthesis works by using sub-agents to process multiple analysis files, extracting key concepts and arguments, and integrating these new findings directly into a persistent knowledge repository for future research workflows.

Yes, you need Python installed because the Skill relies on Python scripts for reference aggregation and sub-agent execution to automate the synthesis and knowledge base update processes.

Yes, you can consolidate findings from various sources into a structured summary. By processing your directory of analysis files, the Skill transforms scattered research into coherent syntheses and comprehensive reading lists.

The main limitation is that automated synthesis requires pre-existing analysis files to process; it cannot generate reports from raw, unanalyzed source text. It depends entirely on the quality of your initial research inputs.