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Quality Monitor Skill

Analyze MySQL validation logs and generate timestamped data quality reports.

Updated Aug 27, 2026
Search Tags:#monitoring#database#validation#data integrity#data quality#reporting#MySQL
One-click install
npx skills add https://github.com/fstr21/sportsbot --skill quality-monitor-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Quality Monitor Skill
Source: https://github.com/fstr21/sportsbot/tree/main/.claude/skills/quality-monitor
Command: npx skills add https://github.com/fstr21/sportsbot --skill quality-monitor-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires mysql-connector-python, rich, python-dotenv, and includes scripts (resource) components.

What problem does it solve?

Without active monitoring, data quality issues can go unnoticed, leading to unreliable insights, broken downstream processes, and wasted time. This Skill provides immediate visibility into data validation failures, helping you maintain data integrity.

Core Features & Use Cases

  • Validation Log Analysis: Queries the MySQL data_quality_log table to group errors by data type, severity, and issue type.
  • Pattern Identification: Identifies recurring validation failures and highlights top problematic fields, helping you prioritize fixes.
  • Report Generation: Creates easy-to-read reports in the reports/ directory and displays results in a clear table format.
  • Use Case: After a pipeline run, use this Skill to quickly check for validation issues, generate a daily quality report, or investigate patterns in historical data failures.

Quick Start

Check data quality for the last 24 hours

python .claude/skills/quality-monitor/scripts/check_quality.py

Frequently Asked Questions about Quality Monitor Skill

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

FAQPage Schema
How do I monitor data quality issues in MySQL?▼

Data quality monitoring analyzes validation logs in MySQL to identify errors grouped by data type, severity, and issue type. This Skill queries your data_quality_log table, surfaces top failing fields and recurring patterns, and displays results in ASCII tables so you can spot problems within the last 24 hours.

Can I generate automated data quality reports from validation logs?▼

Yes. This Skill generates timestamped reports exported to a reports/ directory in Eastern Time. After running validation, it creates easy-to-read summaries showing pass rates, error distributions, and problematic fields for daily or weekly review.

What setup do I need to run data quality validation monitoring?▼

You need MySQL database access, Python with mysql-connector-python, rich, and python-dotenv installed, and credentials stored in .env.local. The Skill connects to your MySQL instance and queries the validation log table to generate reports.

How do I identify recurring data validation failures?▼

This Skill groups validation errors by data type, severity, and issue type to expose patterns. It highlights top problematic fields and recurring failures over the last 24 hours, helping you prioritize which data issues to fix first.

Does this work for real-time data quality checks or historical analysis?▼

This Skill analyzes validation logs from the last 24 hours, making it suited for daily or weekly historical reviews rather than real-time streaming. It's designed for post-pipeline quality checks to validate data integrity after batch runs.

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