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Found 1,909 Skills
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
Discover profitable Amazon niches with low competition and high demand. Evaluates niche viability using demand indicators, competition metrics, profit margins, and growth potential.
Use when asked to "thinking in bets", "make decisions under uncertainty", "think probabilistically", "avoid resulting", "separate decision quality from outcomes", or "reduce bias in decisions". Helps make explicit bets and evaluate decisions on process, not results. The Thinking in Bets framework (from Annie Duke) applies poker strategy to business and life decisions.
Assess whether a project is ready for cloud-native deployment. Evaluates statelessness, config, scalability, and produces a readiness score (0-12). Use when user asks about containerization readiness, Docker/Kubernetes compatibility, deployment feasibility, whether their app can run in containers or the cloud, or wants a pre-deployment assessment. Also triggers on "/cloud-native-readiness".
International market expansion strategy. Market selection, entry modes, localization, regulatory compliance, and go-to-market by region. Use when expanding to new countries, evaluating international markets, planning localization, or building regional teams.
Apply Institutional Theory (DiMaggio and Powell, 1983) to analyze how coercive, mimetic, and normative isomorphic pressures shape organizational structures and practices. Use this skill when the user needs to explain why organizations in the same field look alike, evaluate whether a practice was adopted for legitimacy vs efficiency, analyze regulatory or social pressures on strategy, or when they ask 'why do all firms in this industry do the same thing', 'is this best practice or just conformity', or 'how do regulations shape our structure'.
Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis, hedging strategies, load profiling, and sustainability reporting frameworks. Use when procuring energy, optimizing tariffs, managing demand charges, evaluating PPAs, or developing energy strategies.
Use this skill when working with CodeRabbit, such as running CodeRabbit reviews, generating and processing automated CodeRabbit comments, or evaluating CodeRabbit suggestions.
Analyze Taiwan's manufacturing industry structure including semiconductor, electronics, machinery, and petrochemical sectors. Use this skill when the user needs to understand Taiwan's industrial landscape, evaluate manufacturing sector opportunities, assess supply chain positioning, or contextualize Taiwan in global manufacturing — even if they say 'Taiwan manufacturing overview', 'semiconductor supply chain', 'what does Taiwan make', or 'industrial analysis of Taiwan'.
Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".
Evaluate FX carry trade opportunities by combining spot rates, forward points, interest rate differentials, volatility surface analysis, and historical price trends. Use when analyzing carry trades, comparing FX forward curves, assessing carry-to-vol ratios, or evaluating currency pair opportunities.
Buffett-style stock screener — "What would Buffett buy now?" Generates 3–5 candidate stocks from a market / sector / preference query via a two-layer model: hard quant filter (ROE 5y ≥15%, debt/asset ≤50%, FCF positive 3y, listed ≥5y, gross margin ≥30%) → qualitative moat scoring (moat 35% / capital allocation 20% / earnings predictability 20% / valuation 15% / runway 10%). Longbridge CLI first, MCP fallback, WebSearch for gaps only. Output: candidate cards with moat-type tag, quantitative highlights, verdict (🟢 likely buy / 🟡 wait for price / 🔴 not at this price), deep-dive CTA to `longbridge-buffett-moat-analyzer`. Mandatory holding-period education + data-source appendix. Disqualifies airlines, pre-revenue biotech, ST, listing<5y. Triggers: "巴菲特会买什么", "巴菲特选股", "巴菲特风格的股票", "护城河选股", "宽护城河股票", "价值投资选股", "10年不动的股票", "定价权强的公司", "巴菲特會買什麼", "巴菲特選股", "護城河選股", "寬護城河股票", "Buffett screener", "what would Buffett buy", "wide-moat screener", "quality compounder screen", "Berkshire-style screen", "pricing-power screen".