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postgresql-bi-agent

Automate PostgreSQL BI analysis from metadata discovery to reporting.

38|12|Updated Feb 4, 2026
Search Tags:#postgresql#reporting#data-analysis#analyze#bi#business-intelligence#sql-generation
One-click install
npx skills add https://github.com/digoal/postgres_skill --skill postgresql-bi-agent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: postgresql-bi-agent
Source: https://github.com/digoal/postgres_skill/tree/main/postgresql-bi-agent
Command: npx skills add https://github.com/digoal/postgres_skill --skill postgresql-bi-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires psycopg2, pandas, numpy, jinja2, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

Automates PostgreSQL BI analysis to reveal metadata, data patterns, and actionable insights.

Core Features & Use Cases

  • Metadata discovery and schema mapping to identify tables, keys, and relationships.
  • Data sampling and pattern analysis to understand value distributions and data quality.
  • SQL generation for business-relevant metrics and automated reporting.
  • End-to-end BI pipeline: discovery, sampling, query execution, analysis, and reporting.
  • Use Case: Connect to a read-only database and generate a comprehensive BI report covering revenue, customers, and product performance.

Quick Start

Run the full BI analysis with: python3 scripts/business_intelligence_agent.py --full-analysis Or run targeted analysis: python3 scripts/business_intelligence_agent.py --skill discover_database_metadata

Frequently Asked Questions about postgresql-bi-agent

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

FAQPage Schema
How do I automate PostgreSQL BI analysis and report generation?▼

Automate PostgreSQL BI analysis by running a Python pipeline that discovers database metadata, samples data patterns, generates SQL, and outputs a comprehensive BI report. Use the --full-analysis command to execute the end-to-end workflow.

What is the best way to discover PostgreSQL schema metadata for business intelligence?▼

Discover PostgreSQL schema metadata by running targeted analysis to identify tables, primary keys, and table relationships. This metadata discovery step maps the database structure to prepare for accurate SQL generation and BI reporting.

Can I use this PostgreSQL BI pipeline against a read-only database instance?▼

Yes, this PostgreSQL BI pipeline is specifically designed for read-only database instances. It safely analyzes data patterns and generates business metrics without requiring write permissions or modifying your database state.

Do I need pandas and psycopg2 to run the PostgreSQL BI reporting pipeline?▼

Yes, you need psycopg2, pandas, numpy, and jinja2 installed. Pandas and numpy handle data sampling and pattern analysis, psycopg2 manages the PostgreSQL connection, and jinja2 renders the final BI report.

How to analyze PostgreSQL data distributions and data quality for BI insights?▼

Analyze PostgreSQL data distributions by running the data sampling and pattern analysis skill. This process examines value distributions and data quality metrics, revealing actionable business insights before generating the final SQL queries.

What are the limitations of automated SQL generation for PostgreSQL business intelligence?▼

Automated SQL generation for PostgreSQL BI is limited to the tables, keys, and relationships discovered during metadata mapping. Complex analytical logic or custom business rules not visible in the schema may require manual SQL adjustments.

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