Validates time series forecast quality metrics by comparing current performance against historical benchmarks. Detects degradation in MASE and sMAPE metrics. Activates when user mentions "validate forecast", "check forecast quality", or "assess forecast metrics".
Use when analyzing sales performance, customer metrics, inventory health, or generating forecasts.
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with project-diagrams and generate-image, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.
This skill should be used when creating charts and visualizations from backtest results. It provides patterns for equity curves, drawdown charts, return distributions, rolling metrics, and interactive dashboards using matplotlib, plotly, and seaborn.
Use SAP-RPT-1-OSS open source tabular foundation model for predictive analytics on SAP business data. Handles classification and regression tasks including customer churn prediction, delivery delay forecasting, payment default risk, demand planning, and financial anomaly detection. Use when asked to predict, forecast, classify, or analyze patterns in SAP tabular data exports (CSV/DataFrame). Runs locally via Hugging Face model.
Generic marketing campaign performance analysis patterns. Use when tracking ad spend, calculating ROI, optimizing budgets, or analyzing multi-channel performance. Framework for project-specific implementations.
This skill should be used when creating charts, graphs, dashboards, or data visualizations - covers chart type selection, D3.js patterns, Recharts usage, dashboard design principles, and data storytelling techniques for analytics-reporter and finance-tracker agents.
Develop consistent brand voice and messaging guidelines for companies and personal brands. Creates tone, style, and communication frameworks that align with brand values and target audience preferences.
Analyze Nixtla baseline forecasting results (sMAPE/MASE on M4 or other benchmark datasets). Use when the user asks about baseline performance, model comparisons, or metric interpretation for Nixtla time-series experiments. Trigger with "baseline review", "interpret sMAPE/MASE", or "compare AutoETS vs AutoTheta".
The Pattern Recognizer of the PM Brain. Analyzes company and product strategy, aligns tactical work with strategic objectives, and produces executive-level memos. Use for
Forecasts multiple time series in parallel batches using TimeGPT API. Optimizes throughput with rate limiting and supports portfolio aggregation. Use when processing 10-100+ contracts or needing efficient multi-series forecasting. Trigger with "batch forecast", "portfolio forecast", "parallel forecasting".
Tail risk, EVT, regularization, validation guardrails, and common pitfalls.
End-to-end guide for creating a new X-Fidelity analysis rule. Use when creating rules, adding new checks, or when the user asks about rule development.
Analyze and explain TimeGPT forecast results in plain English. Generates executive summaries with driver analysis. Use when stakeholders need forecast explanations, board presentations, or compliance documentation. Trigger with "explain forecast", "why is the forecast", "forecast narrative".
Comprehensive financial statement analysis including ratio calculation, trend analysis, and peer comparison. Evaluates liquidity, profitability, efficiency, and leverage metrics. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0. Use when analyzing company fundamentals, comparing financial performance, or conducting equity research.
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.
Create structured visualizations of stakeholder perspectives (says, thinks, does, feels) to build deep understanding. Use when conducting user research or validating assumptions.
Analyze Nixtla baseline forecasting results (sMAPE/MASE on M4 or other benchmark datasets). Use when the user asks about baseline performance, model comparisons, or metric interpretation for Nixtla time-series experiments. Trigger with "baseline review", "interpret sMAPE/MASE", or "compare AutoETS vs AutoTheta".
Generate benchmarking pipelines to compare forecasting models and summarize accuracy/speed trade-offs. Use when evaluating TimeGPT vs StatsForecast/MLForecast/NeuralForecast on a dataset. Trigger with "benchmark models", "compare TimeGPT vs StatsForecast", or "model selection".
Use when making structured decisions between multiple options - creates weighted scoring spreadsheet with systematic evaluation across considerations grouped by area
Analyzes content marketing metrics to identify top performers, trends, and optimization opportunities. Use when reviewing blog posts, social media, or campaign performance. Accepts CSV data with engagement metrics and provides actionable insights.
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.
