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home / skills / jeremylongshore / claude-code-plugins-plus-skills / forecast-generator

forecast-generator skill

/skills/12-data-analytics/forecast-generator

This skill guides you through forecast generator workflows, delivering production-ready configurations, validation, and best-practice recommendations for data

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill forecast-generator

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
2.1 KB
---
name: "forecast-generator"
description: |
  Generate forecast generator operations. Auto-activating skill for Data Analytics.
  Triggers on: forecast generator, forecast generator
  Part of the Data Analytics skill category. Use when working with forecast generator functionality. Trigger with phrases like "forecast generator", "forecast generator", "forecast".
allowed-tools: "Read, Write, Edit, Bash(cmd:*), Grep"
version: 1.0.0
license: MIT
author: "Jeremy Longshore <[email protected]>"
---

# Forecast Generator

## Overview

This skill provides automated assistance for forecast generator tasks within the Data Analytics domain.

## When to Use

This skill activates automatically when you:
- Mention "forecast generator" in your request
- Ask about forecast generator patterns or best practices
- Need help with data analytics skills covering sql queries, data visualization, statistical analysis, and business intelligence.

## Instructions

1. Provides step-by-step guidance for forecast generator
2. Follows industry best practices and patterns
3. Generates production-ready code and configurations
4. Validates outputs against common standards

## Examples

**Example: Basic Usage**
Request: "Help me with forecast generator"
Result: Provides step-by-step guidance and generates appropriate configurations


## Prerequisites

- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of data analytics concepts


## Output

- Generated configurations and code
- Best practice recommendations
- Validation results


## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |


## Resources

- Official documentation for related tools
- Best practices guides
- Community examples and tutorials

## Related Skills

Part of the **Data Analytics** skill category.
Tags: sql, analytics, visualization, statistics, bi

Overview

This skill automates forecast generator tasks for data analytics workflows. It guides configuration, generates production-ready code and validation checks, and surfaces best-practice recommendations. Use it to streamline forecasting pipelines, from data prep to model outputs and deployment notes.

How this skill works

The skill inspects your request for forecast-related triggers and responds with step-by-step guidance, SQL snippets, visualization suggestions, and configuration templates. It produces runnable code examples, validation routines, and concise error remediation steps tailored to common data, tooling, and permission issues. Outputs follow standard patterns for reproducibility and deployment.

When to use it

  • You mention "forecast generator" or ask for forecasting guidance
  • Building or validating time-series forecasting pipelines
  • Generating SQL queries or data transforms for forecast inputs
  • Creating visualizations and dashboards for forecast results
  • Preparing production-ready configurations and deployment notes

Best practices

  • Validate and clean time-series data before training (missing values, seasonality, outliers)
  • Split data temporally and use backtesting or rolling-window validation
  • Automate feature engineering for time-based covariates and lag features
  • Version models and configurations; include reproducible seeds and environment specs
  • Include monitoring and alerting for data drift and forecast degradation

Example use cases

  • Generate SQL to aggregate daily sales into weekly series and create lag features
  • Produce a configuration file and Python script to train an ARIMA or Prophet model
  • Create dashboard wireframe and visualization code to display forecast vs. actuals
  • Validate a forecast pipeline with backtest results and automatic metric checks
  • Provide remediation steps when configuration fields are missing or permissions fail

FAQ

What inputs do you need to generate a forecast pipeline?

Provide the time-series column, timestamp format, target column, desired forecast horizon, and details on external covariates or grouping keys.

How do you handle configuration errors?

I identify missing or invalid fields, suggest required parameters, and provide example configurations and commands to fix tool or permission issues.

Can you produce production-ready code?

Yes. I generate code templates, configuration files, and validation routines suited for deployment, including notes on environment dependencies and monitoring.