skills.rest
thecloudtips
thecloudtipsCOMMUNITY
Explore all skills by this author →
GitHub

Data Analysis

Analyze structured datasets for statistics, trends, outliers, and correlations.

18|7|Updated Mar 11, 2026
Search Tags:#data quality#reporting#data analysis#statistics#trends#outliers
One-click install
npx skills add https://github.com/thecloudtips/founder-os --skill data-analysis-thecloudtips
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Data Analysis
Source: https://github.com/thecloudtips/founder-os/tree/main/plugin/skills/report/data-analysis
Command: npx skills add https://github.com/thecloudtips/founder-os --skill data-analysis-thecloudtips

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms raw, structured data into clear, quantitative findings, trends, and actionable insights, making complex datasets understandable.

Core Features & Use Cases

  • Descriptive Statistics: Calculates key metrics like mean, median, and standard deviation for numeric columns, and cardinality/mode for categorical ones.
  • Trend Analysis: Detects patterns over time, including period-over-period growth and seasonality, using time-series data.
  • Comparative Analysis: Compares groups and segments within the data to identify top performers and performance gaps.
  • Outlier Detection: Identifies unusual data points using Z-scores and IQR methods, flagging potential anomalies.
  • Data Quality Assessment: Evaluates data completeness, consistency, validity, and uniqueness to ensure reliable analysis.
  • Use Case: Analyze monthly sales data to identify which regions are growing fastest, detect any unusual spikes or dips in revenue, and assess the overall quality of the sales records.

Quick Start

Analyze the provided sales data to identify key trends and outliers.

Frequently Asked Questions about Data Analysis

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

FAQPage Schema
How do I perform quantitative data analysis on structured datasets to find trends and outliers?▼

To perform quantitative data analysis on structured datasets, this Skill calculates descriptive statistics, detects time-series trends, and identifies outliers using Z-score and IQR methods to derive actionable insights.

What is the best way to assess data quality and completeness before generating a report?▼

Assessing data quality involves evaluating completeness, consistency, validity, and uniqueness. This Skill performs data quality assessment directly on structured datasets to ensure reliable analysis and reporting.

How do I detect outliers and anomalies in my numeric data columns?▼

To detect outliers in numeric data, this Skill uses Z-score and IQR statistical methods to identify unusual data points and flag potential anomalies within your structured datasets.

Can I identify period-over-period growth and seasonality using time-series trend analysis?▼

Yes, you can identify period-over-period growth and seasonality. This Skill performs time-series trend detection on chronological data to uncover patterns and growth metrics.

Does this data analysis Skill output findings in a structured JSON schema for reporting?▼

Yes, this data analysis Skill outputs all quantitative findings, statistical measures, and identified trends in a structured JSON schema specifically designed for report generation.

How do I run comparative analysis across groups to identify top performers?▼

To run comparative analysis across groups, this Skill compares segments within your structured datasets to identify top performers and highlight performance gaps.

Related Skills

Explore More Data & Analytics Skills→
twofoldtech-dakotatwofoldtech-dakota
1

data-table

Render accessible data tables with sorting, filtering, and pagination in SvelteKit.

Community
Advanced
HwFeeHwFee

requirement-intake

Parse user report requests into a structured JSON requirements schema.

Community
Intermediate
Casper-StudiosCasper-Studios
11

csv-analyzer

Analyze CSV datasets with statistics, quality checks, and visualizations.

Official
Intermediate
SologaSologa
1

aeon

Perform time series classification, regression, forecasting, and anomaly detection with scikit-learn compatible APIs.

Community
Advanced