What problem does it solve? Deciding when a user question needs broad, source-grounded research synthesis versus a single data specialist is error-prone, and routing mistakes produce weak answers or wasted specialist calls. This Skill gives the Hub explicit decision boundaries for invoking research_analysis and combining it with other specialists. ## Core Features & Use Cases - Routing Decision Boundaries: Defines which intents (investment thesis, bull/bear cases, risk analysis, evidence comparison, macro research) belong to research_analysis and which belong to specialists like market_data_analysis, fundamentals_analysis, or options_analysis. - Handoff Preparation Rules: Enforces ticker-to-company-name resolution via screener_lookup before semantic web search, and requires compact context (subject, depth, horizon, constraints) instead of raw transcript. - Call Discipline and Conflict Handling: Limits research_analysis to one call plus at most one follow-up, and specifies how to surface conflicts between research output and specialist data. - Use Case: A user asks for a bull and bear thesis on NVDA with catalyst context. The Hub resolves the ticker, calls research_analysis for qualitative synthesis alongside events_news_analysis for catalysts, then merges the evidence while flagging any contradictions. ## Quick Start Ask the Hub to build a sourced bull and bear investment thesis on a company, and it will route the qualitative synthesis to research_analysis while pulling supporting data from the relevant specialists.
