code-data-analysis-scaffolds

# Code Data Analysis Scaffolds

## Table of Contents
- [Purpose](#purpose)
- [When to Use This Skill](#when-to-use-this-skill)
- [When NOT to Use This Skill](#when-not-to-use-this-skill)
- [What Is It?](#what-is-it)
- [Workflow](#workflow)
- [Scaffold Types](#scaffold-types)
- [Guardrails](#guardrails)
- [Quick Reference](#quick-reference)

## Purpose

This skill provides structured scaffolds (frameworks, checklists, templates) for technical work in software engineering and data science. It helps you approach complex tasks systematically by defining what to do, in what order, and what to validate before proceeding.

## When to Use This Skill

Use this skill when you need to:

- **Write tests systematically** - TDD scaffolding, test suite design, test data generation
- **Explore data rigorously** - EDA plans, data quality checks, feature analysis strategies
- **Design statistical analyses** - A/B tests, causal inference, hypothesis testing frameworks
- **Build predictive models** - Model selection, validation strategy, evaluation metrics
- **Refactor with confidence** - Test coverage strategy, refactoring checklist, regression prevention
- **Validate technical work** - Data validation, model evaluation, code quality checks
- **Clarify technical approach** - Distinguish causal vs predictive goals, choose appropriate methods

**Trigger phrases:**
- "Write tests for [code/feature]"
- "Explore this dataset"
- "Analyze [data/problem]"
- "Build a model to predict..."
- "How should I validate..."
- "Design an A/B test for..."
- "What's the right approach to..."

## When NOT to Use This Skill

Skip this skill when:

- **Just execute, don't plan** - User wants immediate code/analysis without scaffolding
- **Scaffold already exists** - User has clear plan and just needs execution help
- **Non-technical tasks** - Use appropriate skill for writing, planning, decision-making
- **Simple one-liners** - No scaffold needed for trivial tasks
- **Exploratory conversation** - User is br