Skill UI

This comprehensive framework allows users to validate and test both crypto and traditional trading strategies against extensive historical market data. It calculates essential performance metrics (Sharpe Ratio, Sortino Ratio, Max Drawdown), simulates trade execution, generates equity curves, and includes advanced parameter grid search optimization tools for robust strategy validation.

This comprehensive skill simulates an expert business analyst, specializing in transforming complex raw data into actionable, strategic insights. The scope covers modern Business Intelligence (BI) platforms (Tableau, Power BI), AI-powered predictive modeling, designing robust KPI/OKR frameworks, advanced financial modeling, and optimizing business processes. It is designed for users needing to drive data-driven decision-making and create executive-level reports.

This comprehensive guide outlines the process of migrating analytics data from major platforms like Google Analytics, Mixpanel, Amplitude, or Segment to PostHog. It covers implementing a dual-write strategy, mapping historical event names and properties, and performing bulk historical data imports, ensuring a smooth transition and data continuity.

This expert guides users through comprehensive customer research, whether analyzing existing assets (transcripts, surveys, tickets) or gathering new intel from online sources (Reddit, G2, forums). It helps uncover deep customer pains, desired outcomes, and underlying needs (Jobs to Be Done) to ground product strategy, marketing copy, and positioning in real-world evidence.

This expert tool guides users through rigorous statistical analysis, specializing in A/B testing, hypothesis testing, and interpreting experimental results. It helps define sample sizes, executes appropriate tests (Z-test, T-test, Chi-square), and critically distinguishes between 'statistical significance' and 'practical significance' to ensure data-driven decision-making for product and business strategy.

A comprehensive guide to diagnosing and enhancing search relevance within Qdrant. This skill addresses reported issues such as low precision, low recall, or irrelevant matches. It guides users through determining if the problem lies in the embedding model, Qdrant configuration, or the query strategy. Techniques covered include optimizing chunk splitting, tuning HNSW parameters, implementing hybrid search, and utilizing reranking for superior result quality.

This skill simulates a Chief Data Officer's deep interrogation, pressure-testing any plan touching core data strategy. Use it before approving ML model training runs, selecting data infrastructure (warehouse vs. mesh), productizing data assets, or making major team hires. It ensures that all data decisions are grounded in clear business decisions, compliance, and structural necessity.

This skill generates a comprehensive, structured churn analysis, moving far beyond simple headline rates. It meticulously separates avoidable vs. unavoidable customer losses, identifies high-risk segments (by tier, cohort, etc.), calculates critical metrics like Net Revenue Retention (NRR), and pinpoints actionable early warning signals. The output culminates in prioritized, data-driven intervention recommendations to improve customer retention.

A comprehensive tool for analyzing the current market regime (bull, bear, ranging, volatile) using advanced neural models. It detects the prevailing market structure, provides a confidence score, and recommends suitable trading strategies. Ideal for market analysis, backtesting preparation, or general market condition inquiries.

A comprehensive strategic guide for authors targeting the ACM International Conference on Multimedia Retrieval (ICMR). This skill helps authors assess the fit of their multimedia retrieval, cross-modal search, or representation learning work for the venue. It provides specific advice on framing the contribution, defining necessary evidence (e.g., ranking metrics, baselines), and structuring the manuscript to meet ICMR's high standards.

A comprehensive guide for authors submitting papers related to web search, ranking, and data mining to WSDM. It provides critical advice on conference fit assessment, proper manuscript re-framing, required evidence (retrieval/ranking baselines, platform-aware evaluation), and how to position the work against competing top venues like SIGIR and KDD.

A comprehensive guide for authors submitting data mining papers to the ACM SIGKDD Conference. It helps authors assess the manuscript's fit, reframe the contribution (e.g., from journal to conference style), and strengthens the evidence bar by focusing on novelty, scale, reproducibility, and clear real-world impact required by top-tier data science venues.