Skill UI

This rigorous review simulates an interrogation by a Chief AI Officer (CAIO). It pressure-tests any AI plan across six critical dimensions: evaluation metrics, failure mode handling (SLOs), international regulatory compliance (e.g., EU AI Act), technical architecture (API vs. fine-tuning), cost economics, and necessary team roles. Use this when ensuring AI features are robust, safe, and commercially sound before launch or major investment.

This skill provides deep, decision-grade research dossiers on any specific entity (company, person, or organization). Unlike generic profiles, it mandates the user to state a clear hypothesis upfront. The resulting dossier rigorously tests this hypothesis, providing a conclusive verdict, detailed activity timelines, network signals, red flags, and a source-provenance audit log. Ideal for due diligence, investment analysis, or high-stakes meeting preparation.

This skill provides comprehensive intelligence across finance and media. Users can search real-time news, analyze media bias across multiple dimensions, get live stock/crypto data with AI forecasts, price financial options using ML models, and synthesize balanced perspectives on current events. It is ideal for deep research, investment analysis, and media literacy.

Generates a comprehensive and structured financial due diligence framework for any investment, M&A, or major partnership. It produces a detailed document request list, key analytical questions, red flags checklist, and a summarized financial health assessment, tailored to specific transaction types and diligence stages.

This skill generates comprehensive, structured sales or commercial proposals (SOW). It guides the user to structure the proposal around the prospect's core problem rather than just listing product features. It includes mandatory sections for understanding the client's pain points, detailing the proposed solution phases, outlining the investment structure, and defining clear next steps to maximize conversion rates and prevent scope creep.

This skill provides deep, cross-border financial analysis and valuation metrics for stocks across multiple markets (e.g., US, HK). Users can access detailed income statements, balance sheets, cash flow data, analyze business segments, compare valuation multiples (PE, PB), run sophisticated DCF models, and perform value screening. It is an essential tool for fundamental research, investment modeling, and corporate analysis.

A read-only tool designed to compare prediction-market baskets or themes against the user's existing knowledge base, portfolio notes, research memos, or financial context. It performs gap analysis, flagging potential conflicts, stale assumptions, and areas of missing research. This skill provides structured insights into fit and exposure without offering any investment or trading advice.

This skill provides comprehensive, read-only market intelligence for prediction markets. It helps users research market events, compare different venues (like Polymarket, Kalshi), analyze liquidity, and understand underlying assets. It generates source-grounded briefings, emphasizing context and data quality, and strictly avoids providing investment or trading advice.

This skill assists in researching prediction markets, treating them as potential data sources or oracle signals for corporate decision intelligence, product development, and agent inputs. It provides source-grounded analysis of implied probabilities, signal quality, and integration patterns, while strictly avoiding investment advice.

This tool automates the entire process of optimizing investment portfolio allocations using a sophisticated mean-variance engine. Users can set specific risk targets, assess detailed risk metrics (variance, correlation), predict expected returns using neural networks, and generate actionable, step-by-step rebalancing plans. It is designed for quantitative traders managing complex asset baskets and historical pattern analysis.

This skill solves the mean-variance portfolio optimization problem (Σ · x = μ) using the highly efficient Conjugate Gradient (CG) method. It significantly outperforms legacy Neumann series methods, providing state-of-the-art speedup (40-60x) and accuracy for calculating optimal investment weights. It is designed for quantitative finance and risk management applications where computational performance is critical.