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data-manager

Analyze PostgreSQL and MySQL databases with parallelized read-only SQL queries.

Updated Aug 23, 2026
Search Tags:#database#sql#data-analysis#data-quality#kpi#schema-diagnostics
One-click install
npx skills add https://github.com/PedroPaduelo/nommand-toolkit --skill data-manager-pedropaduelo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-manager
Source: https://github.com/PedroPaduelo/nommand-toolkit/tree/main/skills/data-manager
Command: npx skills add https://github.com/PedroPaduelo/nommand-toolkit --skill data-manager-pedropaduelo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides a systematic, senior-level approach to interact with relational databases so users can explore schemas, run safe analytic queries, detect data quality issues, measure KPIs, and get actionable business insights without manually crafting and running dozens of ad-hoc SQL queries.

Core Features & Use Cases

  • Parallelized analysis: Run many independent read-only queries concurrently to speed up EDA, KPI collection, and health checks.
  • Schema discovery & diagnostics: List databases and tables, describe table structures, surface index usage and schema anti-patterns, and suggest indexing or modeling improvements.
  • Data quality & analytics: Produce completeness, uniqueness, validity, and freshness checks, statistical summaries, trend comparisons, cohort and funnel analyses, and executive-ready dashboards.
  • Operational safety: Enforces read-only defaults, query LIMITs, explicit confirmation for destructive actions, and adapts SQL to PostgreSQL/MySQL dialects.
  • Use case: Audit the "sales" schema in production to get table sizes, top data quality issues, monthly revenue trends, key KPIs, and prioritized remediation recommendations.

Quick Start

Ask the skill to explore the "sales" table on the production connection and return an executive summary with KPIs, trends, top data quality issues, and suggested next queries.

Frequently Asked Questions about data-manager

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

FAQPage Schema
How do I run exploratory data analysis on a PostgreSQL database without writing manual SQL?▼

You can run exploratory data analysis by executing parallelized read-only SQL queries to list schemas, describe table structures, and generate statistical summaries. This returns interpreted executive-ready summaries and suggested next queries without manual ad-hoc SQL crafting.

How do I check data quality and freshness in MySQL tables?▼

To check data quality in MySQL, run automated completeness, uniqueness, validity, and freshness checks. This process executes read-only queries concurrently to detect anomalies and returns a prioritized list of top data quality issues with remediation recommendations.

Can I generate KPI dashboards and cohort analyses directly from my relational database?▼

Yes, you can generate KPI dashboards, cohort analyses, and funnel analyses directly from relational databases. The system executes concurrent read-only SQL queries to measure KPIs and returns executive-ready business insights with trend comparisons.

Does this database analysis approach support both PostgreSQL and MySQL environments?▼

Yes, database analysis supports both PostgreSQL and MySQL environments. The system automatically adapts SQL to the specific dialect, enforces query LIMITs, and uses read-only defaults to ensure operational safety across both database platforms.

How do I diagnose schema health and find indexing anti-patterns in my database?▼

You diagnose schema health by listing databases, describing table structures, and surfacing index usage. This analysis detects schema anti-patterns and returns actionable recommendations for indexing and data modeling improvements.

What are the limitations when running cross-database comparisons for analytics?▼

The primary limitation is enforcing read-only defaults and explicit confirmation for destructive actions. While cross-database comparisons are supported, safety limits and query LIMITs are enforced to prevent unintended operational impacts.

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