What problem does it solve? When you run multiple deep research threads on the same topic across different AI models or sessions, you end up with overlapping, redundant outputs that are painful to reconcile manually. This Skill consolidates them into a single unified document with claim-level deduplication and full source attribution. ## Core Features & Use Cases - Claim-Level Deduplication: Identifies the same finding phrased differently across threads and consolidates it once, citing all contributing sources. - Three-Section Output: Produces an executive summary, a key points section backed by verbatim quotes, and a complete unified content section organized by topic rather than by source. - Print-Optimized docx Generation: Delivers the final synthesis as a formatted Word document via the print-docx skill. - Use Case: You ran three deep research sessions on AI governance frameworks from different models. Provide all three outputs and receive one comprehensive docx where every claim appears once, attributed to its source threads, with nothing omitted. ## Quick Start Unify these deep research thread outputs into a single deduplicated document with an executive summary and verbatim-quote key points.
