What problem does it solve? Agents and researchers often need to query multiple search sources (web, academic papers, Tavily) separately and manually judge result trustworthiness. This Skill unifies those sources behind one API and adds a deterministic confidence score so answers can be evaluated for consensus and credibility. ## Core Features & Use Cases - Multi-Source Retrieval: Query web, scholar, smart hybrid, and Tavily endpoints in parallel through a single Python client. - Confidence Scoring: The verity mode aggregates results across sources and returns a 0-100 score with a breakdown covering source quality, agreement, data availability, and errors. - Tavily Operations: Search, extract content from URLs, crawl pages, and generate site maps. - Use Case: Ask whether a technology trend is enterprise-ready; the verity command fetches from four sources in parallel and returns a synthesized confidence level (Very High to Very Low) with per-source result counts. ## Quick Start Set the AISA_API_KEY environment variable and ask the agent to run a verity search on your research question to get multi-source results with a confidence score.
