agent-data

Name: agent-data
Availability: InStock
Author: fabiomilennials1234-a11y

Automate product analytics metrics and dashboards with materialized views and pg_cron refresh.

Updated Jan 29, 2026

Search Tags:#analytics #dashboards #metrics #etl #data-modeling #olap #pg_cron

Ready to run

npx skills add https://github.com/fabiomilennials1234-a11y/v8milennialsb2bv2 --skill agent-data-fabiomilennials1234-a11y

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agent-data
Source: https://github.com/fabiomilennials1234-a11y/v8milennialsb2bv2/tree/main/.claude/skills/agent-data
Command: npx skills add https://github.com/fabiomilennials1234-a11y/v8milennialsb2bv2 --skill agent-data-fabiomilennials1234-a11y

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data / Analytics engineer agent ensures reliable product metrics, dashboards, materialized aggregations, event tracking, and analytic schemas (OLAP) with refresh via pg_cron, enabling external BI ETL workflows and clear data exposure. It distinguishes from a DBA, which optimizes OLTP schemas and runtime queries; the Data role focuses on analytics and decision-support.

Core Features & Use Cases

Defines core product metrics across domains (funnel, time, origin, campaign, copilot, product, revenue) and exposes them via analytics views.
Builds analytic schemas (star schema with dimension and fact tables), uses materialized views with pg_cron refresh, and supports partitioned event tables for performance.
Tracks product events with versioned schemas and supports multi-tenant isolation using row-level security (RLS).
Provides dashboards for admin masters and orgs, with export options and ad-hoc querying capabilities.

Quick Start

Configure the analytics contract, map sources, and establish a materialized-view refresh cadence to begin collecting product metrics for an organization.

Frequently Asked Questions about agent-data

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

FAQPage Schema

How do I automate materialized view refresh for product analytics dashboards?▼

Automate materialized view refresh for product analytics dashboards using pg_cron. This Skill configures scheduled refreshes to ensure metrics and aggregations remain current and available for external BI ETL workflows.

What is the difference between a DBA and a data analytics engineer for metric definition?▼

A DBA focuses on optimizing OLTP schemas and runtime queries, whereas this data analytics role focuses on metric definition, decision-support, and building OLAP analytic schemas like star schemas with dimension and fact tables.

How do I track versioned product events with multi-tenant isolation using RLS?▼

Track versioned product events with multi-tenant isolation using RLS by configuring partitioned event tables. This Skill supports versioned schemas and enforces row-level security to isolate tenant data across organizations.

Can I build a star schema with dimension and fact tables for multi-tenant organizations?▼

Yes, you can build a star schema with dimension and fact tables for multi-tenant organizations. This Skill structures analytic schemas and exposes core product metrics across domains like funnel, revenue, and campaign.

Does pg_cron work with materialized views to schedule ETL workflows?▼

Yes, pg_cron works with materialized views to schedule ETL workflows. This Skill uses pg_cron to establish a refresh cadence, automating the production of materialized aggregations and enabling clear data exposure.

What are the limitations of using materialized views for partitioned event tables?▼

Materialized views require scheduled refreshes via pg_cron to stay current, meaning data is not real-time. This Skill manages partitioned event tables for performance but relies on configured refresh cadences rather than live updates.