What problem does it solve? Finding relevant research papers requires manually querying many disconnected sources — arXiv, web search, Zotero, Obsidian, local PDFs, and cloud paper databases — then merging and de-duplicating the results by hand. This Skill runs one query across all of them and returns a single merged, ranked result set with a synthesized landscape report. ## Core Features & Use Cases - Multi-source retrieval: Queries Zotero, Obsidian, local PDF libraries, web search, the arXiv API, and a cloud mechanic-db SEARCH service in one pass, with optional Semantic Scholar, DeepXiv, and Exa extras. - De-duplication and ranking: Merges results across sources by normalized title, arXiv ID, or DOI, and ranks the top papers by relevance to the query. - Structured output: Writes a raw retrieval dump (RESEARCH_LIT.md) and a synthesized landscape report (LANDSCAPE.md) with a paper table, narrative summary, and structural gaps into a per-query folder. - Use Case: Ask "find papers on activation steering across all sources" and receive a deduplicated paper table plus a 3-5 paragraph field narrative saved under msearch/activation_steering/. ## Quick Start Run /msearch followed by your research query, for example: search everything for mechanistic interpretability of attention heads.