validate-data

Validate NFL data quality and business rule compliance across pipeline layers.

Updated Aug 15, 2025
One-click install
npx skills add https://github.com/gesmith0606/nfl_data_engineering --skill validate-data-gesmith0606
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: validate-data
Source: https://github.com/gesmith0606/nfl_data_engineering/tree/main/.claude/skills/validate-data
Command: npx skills add https://github.com/gesmith0606/nfl_data_engineering --skill validate-data-gesmith0606

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Validate NFL data quality and business rule compliance across all pipeline layers.

Core Features & Use Cases

  • Environment & connectivity checks to ensure ingestion and validation can run end-to-end.
  • Bronze layer validation to verify data availability and basic integrity for schedules, pbp, etc.
  • NFL business rules enforcement, including checks for valid weeks, downs, and data freshness.
  • DuckDB SQL validation against Parquet files to quantify data health and freshness with fast queries.
  • Report generation that aggregates results, highlights failures, and guides remediation.

Quick Start

Activate your environment and run the validation script to begin data quality checks.

Frequently Asked Questions about validate-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate NFL data quality across Bronze, Silver, and Gold pipeline layers?

To validate NFL data quality across Bronze, Silver, and Gold layers, run the validation script to perform post-ingest debugging, verify connectivity, and enforce business rule compliance.

Can I run DuckDB SQL validation directly against Parquet files for data health checks?

Yes, DuckDB SQL validation runs directly against Parquet files to quantify data health and freshness, enabling fast checks for data availability and integrity across your NFL datasets.

What NFL business rules are checked during pipeline data validation?

NFL business rule checks validate conformance for valid weeks, downs, and data freshness, ensuring ingested schedules and play-by-play data meet expected integrity constraints before downstream processing.

How do I debug post-ingest data quality failures in my NFL pipeline?

Debug post-ingest data quality failures by activating your environment and running the validation script, which generates structured reports that aggregate results, highlight failures, and guide remediation.

Does this data validation approach work for nightly QA and pre-projection checks?

Yes, the data validation approach applies during nightly QA and pre-projection checks to verify connectivity, layer contents, and business rule compliance across Bronze, Silver, and Gold layers.