What data sources does the reconciliation skill compare?

It compares Profit & Loss (P&L) statement data against operational KPI data sources to ensure that revenue and expense figures align across different systems.

How do I set a specific variance threshold?

You can use the --tolerance-pct argument followed by a number (e.g., --tolerance-pct 1.0) to define the acceptable percentage of variance before an item is flagged.

Can this skill identify missing financial data?

Yes, it performs data completeness checks to identify missing expense categories, expected accounts, or unavailable KPI metrics during the reconciliation process.

What output formats are supported?

The skill generates comprehensive Excel workbooks with multiple sheets (Summary, Validation, Exceptions, etc.) and PowerPoint presentations, both featuring Datarails brand styling.

P&L and KPI Reconciliation

Name: P&L and KPI Reconciliation
Author: Datarails

byDatarails

0•

Analytics & Monitoring

Automates the reconciliation of Profit & Loss statements against KPI data sources to identify financial variances and ensure data integrity.

The P&L and KPI Reconciliation skill provides a robust automated framework for validating financial consistency between general ledger P&L accounts and operational KPI metrics. It streamlines month-end closing processes by performing deep variance analysis, identifying missing expense categories, and validating data completeness within user-defined tolerance thresholds. Designed specifically for finance teams and analysts, it generates professionally styled, Datarails-branded Excel reports and PowerPoint presentations that highlight exceptions and identify root causes, making it an essential tool for audit preparation and internal financial reviews.

Key Features

01Detailed root cause identification for financial variances and timing differences.

02Datarails-branded professional Excel and PowerPoint report generation.

03Comprehensive data quality checks for missing accounts or metrics.

040 GitHub stars

05Automated revenue and expense consistency validation between P&L and KPIs.

06Customizable variance tolerance thresholds for precise discrepancy detection.

Use Cases

01Validating financial performance data before executive presentations and board reviews.

02Preparing for internal or external audits with strict variance tolerance reporting.

03Automating month-end close validation and financial consistency checks.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add datarails/dr-claude-code-plugins-re reconciliation

For use in Claude.ai and ChatGPT

Key Features

01Detailed root cause identification for financial variances and timing differences.

02Datarails-branded professional Excel and PowerPoint report generation.

03Comprehensive data quality checks for missing accounts or metrics.

040 GitHub stars

05Automated revenue and expense consistency validation between P&L and KPIs.

06Customizable variance tolerance thresholds for precise discrepancy detection.

Use Cases

01Validating financial performance data before executive presentations and board reviews.

02Preparing for internal or external audits with strict variance tolerance reporting.

03Automating month-end close validation and financial consistency checks.