What problem does it solve? Generic web searches return long lists of links with mixed credibility, making it hard to know which claims to trust. This Skill structures external research into a disciplined workflow of question framing, multi-source discovery, source quality scoring, cross-verification, and synthesis so conclusions are backed by evidence rather than search ranking. ## Core Features & Use Cases - Source triage and quality scoring: Labels sources from A (primary/authoritative) to D (low confidence) and prioritizes official docs, papers, and repos over derivative summaries. - Cross-verification and de-duplication: Clusters repeated claims, traces them to primary origins, and marks findings as confirmed, likely, contested, or unverified. - Structured synthesis outputs: Produces bottom-line summaries, evidence tables, source quality tables, timelines, and open-question lists for briefs, due diligence memos, and landscape scans. - Use Case: When evaluating a fast-moving open-source project, use this Skill to combine official docs, GitHub activity, arXiv papers, and expert blogs into a single evidence-backed brief with confidence levels and remaining uncertainties. ## Quick Start Research the current state of vector database benchmarking and produce an evidence-backed brief with source quality ratings and open questions.
