nixtla-explain-analyst
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".
When & Why to Use This Skill
The Nixtla Explain Analyst is a specialized Claude skill designed to bridge the gap between complex time-series forecasting and business decision-making. It automatically transforms technical TimeGPT forecast data into clear, plain-English executive summaries, providing deep insights into trends, seasonality, and underlying drivers. By translating data-heavy artifacts into stakeholder-ready narratives, it helps organizations understand the 'why' behind their forecasts and ensures transparency in predictive modeling.
Use Cases
- Board Presentations: Translating quarterly financial or demand forecasts into high-level executive summaries with clear bullet points for leadership review.
- Regulatory Compliance: Generating necessary documentation for SOX or Basel III by explaining model drivers, assumptions, and uncertainty intervals.
- Operational Strategy: Explaining seasonal patterns and trend directions to non-technical department heads to assist in resource allocation and planning.
- Data Science Communication: Creating technical appendices that document model limitations and risks, ensuring data integrity and peer-level transparency.
| name | nixtla-explain-analyst |
|---|---|
| description | 'Analyze and explain TimeGPT forecast results in plain English. Generates |
| allowed-tools | Read,Glob,Grep |
| version | 1.0.0 |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| license | MIT |
Nixtla Explain Analyst
Overview
Generate plain-English explanations of TimeGPT forecasts for non-technical stakeholders, with a short executive narrative plus driver-oriented analysis.
Prerequisites
- A forecast output artifact to explain (CSV/JSON/markdown), or a path under the plugin workspace containing results.
- If using TimeGPT outputs: access to the TimeGPT run metadata used to generate the forecast.
Instructions
- Locate the forecast results file(s) and any run metadata (model, horizon, frequency, training window).
- Summarize forecast context: what is being forecast, horizon, and any known events/holidays/regressors.
- Explain forecast shape using: baseline level, trend direction, seasonal pattern (if present), and uncertainty.
- Provide driver analysis at the level supported by available data (do not fabricate causal drivers).
- Produce a stakeholder-ready narrative plus a short technical appendix (assumptions + limitations).
Output
- Executive: 1-page summary for C-level
- Technical: Detailed analysis for data science
- Compliance: SOX/Basel III documentation
Error Handling
- If only point forecasts are available, state that uncertainty intervals are unavailable and recommend generating prediction intervals.
- If inputs are missing (no horizon/freq), request the minimum details required to interpret results.
- If drivers/regressors are not provided, restrict “drivers” to observable components (trend/seasonality/outliers).
Examples
User: “Explain the Q4 forecast for the board presentation.”
Response structure:
- Executive summary (3–6 bullets)
- What changed vs last quarter (trend/seasonality)
- Key risks and uncertainty
- Assumptions and limitations (what was/wasn’t modeled)
Resources
- Plugin docs and outputs under
005-plugins/nixtla-forecast-explainer/