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agency-sales-data-extraction-agent

Extract sales metrics from Excel workbooks and insert them into PostgreSQL.

Updated Feb 11, 2026
Search Tags:#postgresql#excel#etl#data-extraction#sales-metrics#file-monitoring
One-click install
npx skills add https://github.com/augustoheiss/LogicDefense --skill agency-sales-data-extraction-agent-augustoheiss
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agency-sales-data-extraction-agent
Source: https://github.com/augustoheiss/LogicDefense/tree/main/.gemini/skills/agency-sales-data-extraction-agent
Command: npx skills add https://github.com/augustoheiss/LogicDefense --skill agency-sales-data-extraction-agent-augustoheiss

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the tedious and error-prone process of monitoring Excel reports and extracting sales metrics (MTD, YTD, Year End), eliminating manual spreadsheet parsing and inconsistent aggregations for live reporting.

Core Features & Use Cases

  • Real-time file monitoring: Watches directories for new or updated .xlsx and .xls files and waits for write completion before processing.
  • Flexible schema mapping: Uses fuzzy column name matching to handle varying formats for revenue, units, deals, and quota, and detects metric type from sheet names.
  • Reliable persistence & auditability: Logs every import (file name, rows processed/failed, timestamps), uses transactional bulk inserts into PostgreSQL, and records source file for audits.
  • Use Case: Sales operations can drop regional Excel exports into a watch folder and have standardized MTD/YTD/Year End metrics automatically normalized and stored for dashboards.

Quick Start

Use the agency-sales-data-extraction-agent to process the 'sales_reports' watch folder and extract MTD, YTD, and Year End metrics into the analytics database.

Frequently Asked Questions about agency-sales-data-extraction-agent

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

FAQPage Schema
How do I automate extracting sales metrics from Excel workbooks into PostgreSQL?▼

Automating Excel sales metrics extraction into PostgreSQL involves watching directories for .xlsx and .xls files, parsing sheets labeled MTD, YTD, or Year End, and bulk inserting normalized revenue, units, deals, and quota data using database transactions.

Can I map sales representative rows by email or full name when importing Excel data?▼

Yes, mapping sales representative rows by email or full name is supported during Excel data import. The pipeline applies fuzzy column matching to identify representative identifiers and normalizes associated sales metrics for accurate database storage.

What is the best way to handle varying column formats in Excel sales reports?▼

Handling varying column formats in Excel sales reports requires fuzzy column name matching. This technique maps inconsistent headers for revenue, units, deals, and quota fields to standardized schema fields before inserting validated metrics into PostgreSQL.

Does this Excel to PostgreSQL ETL process handle temporary lock files?▼

Yes, the Excel to PostgreSQL ETL process handles temporary lock files. It monitors watched directories and waits for file write completion before processing, ensuring that partial or locked Excel workbooks are skipped until fully saved.

How do I consolidate MTD, YTD, and Year End metrics from multiple Excel sheets?▼

Consolidating MTD, YTD, and Year End metrics from multiple Excel sheets involves parsing each workbook, detecting the metric type from sheet names, normalizing financial formatting, and bulk inserting validated rows into PostgreSQL with full import logging.

How to ensure auditability when importing Excel sales data into a database?▼

Ensuring auditability when importing Excel sales data involves logging every import detail, including file name, rows processed, failed rows, and timestamps. The pipeline records the source file for audits and uses transactional bulk inserts for reliable persistence.

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