Does this skill require pre-configured table IDs?

No, the skill features an adaptive discovery mode that automatically identifies available Finance OS tables and schemas if no specific ID is provided via arguments.

How is the Data Quality Score calculated?

The score is a metric from 0-100, starting at 100 and deducting points based on the count and severity of detected anomalies (e.g., -10 for critical, -5 for high).

Does it apply specific corporate branding to reports?

Yes, the skill automatically applies Datarails brand styling, including Poppins fonts, specific color palettes for favorable/unfavorable variances, and professional header banners.

What kind of output does the anomaly report provide?

It generates a multi-sheet Excel workbook featuring a summary dashboard with quality scores, detailed findings categorized by severity, and deep statistical analysis of the data.

Can I customize the report output location?

Yes, you can use the --output argument to specify a custom filename and path for the generated Excel deliverable.

Datarails Anomaly Detection Report

Name: Datarails Anomaly Detection Report
Author: Datarails

byDatarails

0•

Data Science & ML

Generates comprehensive data quality assessment reports with automated anomaly detection for Datarails Finance OS tables.

The Anomaly Detection Report skill is a specialized diagnostic tool designed for financial data professionals to identify data quality issues without manual configuration. It automatically discovers table structures, profiles numeric and categorical fields, and calculates a comprehensive Data Quality Score (0-100) based on finding severity. By generating professionally formatted Excel reports with Datarails-branded styling—including summary dashboards, critical findings, and statistical analysis—this skill streamlines the audit process, ensures data reliability for month-end closes, and provides actionable insights into potential financial discrepancies directly within your Claude Code environment.

Key Features

01Automated data structure discovery and schema identification

020 GitHub stars

03Detailed statistical profiling of numeric and categorical data fields

04Professional Excel report generation with Datarails brand styling and variance coloring

05Multi-severity anomaly detection for critical, high, medium, and low issues

06Automated Data Quality Score (0-100) calculation for health tracking

Use Cases

01Performing exploratory data audits on unfamiliar or newly imported Finance OS tables

02Conducting automated monthly data quality checks to ensure financial reporting accuracy

03Validating ledger data for critical anomalies before executing a month-end close

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add datarails/dr-claude-code-plugins-re anomalies-report

For use in Claude.ai and ChatGPT

Key Features

01Automated data structure discovery and schema identification

020 GitHub stars

03Detailed statistical profiling of numeric and categorical data fields

04Professional Excel report generation with Datarails brand styling and variance coloring

05Multi-severity anomaly detection for critical, high, medium, and low issues

06Automated Data Quality Score (0-100) calculation for health tracking

Use Cases

01Performing exploratory data audits on unfamiliar or newly imported Finance OS tables

02Conducting automated monthly data quality checks to ensure financial reporting accuracy

03Validating ledger data for critical anomalies before executing a month-end close