Data Analysis

Analyze data to produce decision briefs with uncertainty and recommended actions.

Updated Mar 11, 2026

Search Tags:#data #insights #visualization #analyze #cohort #statistical #kpi

Ready to run

npx skills add https://github.com/ISAQQSAI/SkillAttack --skill data-analysis-isaqqsai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Data Analysis
Source: https://github.com/ISAQQSAI/SkillAttack/tree/main/data/hot100skills/023_ivangdavila_data-analysis
Command: npx skills add https://github.com/ISAQQSAI/SkillAttack --skill data-analysis-isaqqsai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data analysis helps turn raw data into meaningful, decision-ready insights through rigorous methodology and clear communication.

Core Features & Use Cases

KPI contracts, chart selection, decision briefs, anomaly detection
Cohort and time series analysis
Time-saving templates for executive reporting

Quick Start

Load your dataset and generate a decision-ready analysis with visuals.

Frequently Asked Questions about Data Analysis

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

FAQPage Schema

How do I turn raw spreadsheet data into actionable insights for executive reporting?▼

To turn raw spreadsheet data into actionable insights, load your dataset to generate structured decision briefs. The analysis applies metric contracts and chart selection guidelines to produce executive reporting templates with recommended actions and visualizations.

What is the best way to perform cohort analysis and anomaly detection on my KPIs?▼

Cohort analysis and anomaly detection are performed by enforcing metric contracts on your dataset. This method isolates time series variations and structural anomalies, producing decision-ready insights that clarify KPI fluctuations and user retention trends.

Can I use this data analysis approach with SQL queries and notebook environments?▼

Yes, this data analysis approach works across SQL, spreadsheets, notebooks, and dashboards. It processes your loaded datasets to output decision briefs complete with uncertainty metrics, caveats, and visualizations regardless of the computing environment.

How do I generate a decision-ready analysis that includes uncertainty and caveats?▼

You generate a decision-ready analysis by loading your dataset into the system, which then evaluates the data and outputs structured briefs. These briefs explicitly state statistical uncertainty, outline limitations, and provide recommended actions.

What chart selection guidelines should I follow for visualizing KPI metrics?▼

Chart selection guidelines for visualizing KPI metrics are enforced during the data analysis process. The system automatically matches your data structure to appropriate visualization formats, ensuring clear communication of statistical variations and actionable insights.

Why does my KPI debugging require metric contracts during data analysis?▼

KPI debugging requires metric contracts during data analysis to enforce strict definitions and prevent calculation discrepancies. Applying these contracts ensures your anomaly detection and cohort analysis produce reliable, decision-ready insights without metric drift.