What problem does it solve? Finding the right research papers for a question is hard: a single keyword search misses sibling methods, citing work, and papers whose abstracts don't state the property you care about. This Skill turns a research query into a complete, verified set of relevant papers instead of one lucky hit. ## Core Features & Use Cases - Semantic paper search: HyDE-based search over paper abstracts via Firecrawl Research, with guidance on reframing queries when results are thin. - Structural and semantic expansion: Grow one good hit into a full set using similar-paper, citers, and references modes ranked to your intent. - In-body verification: Read specific passages inside a paper to confirm a method was actually used, a score was actually reported, or an affiliation matches. - Use Case: Ask "what are alternatives to Adam for optimizer design" and get an expanded family of relevant papers, each checked for relevance, rather than a single top match. ## Quick Start Use the firecrawl-research-index skill to find all papers that propose training-free methods for detecting AI-generated text, including closely related follow-up work.