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thats-my-quant

Analyze financial and RevOps data with structured workflows and Excel reports.

11|4|Updated Jan 20, 2026
Search Tags:#financial modeling#data analysis#excel#pdf extraction#saas metrics#revops#dashboarding
One-click install
npx skills add https://github.com/Casper-Studios/casper-marketplace --skill thats-my-quant
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: thats-my-quant
Source: https://github.com/Casper-Studios/casper-marketplace/tree/main/thats-my-quant
Command: npx skills add https://github.com/Casper-Studios/casper-marketplace --skill thats-my-quant

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires marimo, matplotlib, numpy, openpyxl, pandas, python-pptx, seaborn, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of transforming raw financial, SaaS, and RevOps data into reliable, actionable insights. It provides structured workflows to ensure analytical rigor, transparency, and bias awareness, helping users make data-driven decisions without falling prey to common analytical pitfalls or messy data.

Core Features & Use Cases

  • Comprehensive Data Analysis: Follows a structured 7-phase workflow for data ingestion, exploration, modeling, and interpretation, ensuring a robust analytical process.
  • Bias-Aware Interpretation & Validation: Integrates decision logging, bias checklists (e.g., survivorship, Simpson's paradox), and a "bullshit detector" to ensure findings are trustworthy and appropriately hedged.
  • Flexible Output & Reporting: Generates progressive disclosure reports (slide decks, detailed reports, Marimo notebooks) and exports to Excel with proper financial formatting and formulas.
  • Dashboarding & Data Cleaning: Scaffolds interactive Marimo dashboards and provides tools for data quality profiling and cleaning messy datasets.

Quick Start

Analyze our ARR trends by segment and identify drivers of growth/churn.

Frequently Asked Questions about thats-my-quant

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

FAQPage Schema
How do I build a SaaS dashboard for revenue forecasting and churn modeling?▼

This Skill scaffolds interactive Marimo dashboards for revenue forecasting and churn modeling by applying a structured 7-phase workflow for data ingestion, exploration, and modeling.

Can I export financial data analysis results to Excel with proper formulas?▼

Yes, you can export financial data analysis results to Excel with proper formulas. The Skill generates structured outputs and exports directly to Excel, ensuring analytical findings are formatted correctly for financial reporting and decision-making.

What is the best way to profile and clean messy RevOps datasets before analysis?▼

The best way to clean messy RevOps datasets is using a structured data quality profiling workflow within the ingestion phase, which applies validation checks to ensure reliable, actionable insights before modeling begins.

Does this approach help identify bias in financial data interpretation?▼

Yes, this approach helps identify bias in financial data interpretation by integrating decision logging, bias checklists for survivorship and Simpson's paradox, and a validation mechanism to ensure findings are trustworthy and appropriately hedged.

What formats are supported for generating financial reporting outputs?▼

Supported formats for financial reporting outputs include slide decks via python-pptx, detailed PDF reports, interactive Marimo notebooks, and Excel spreadsheets with financial formatting and formulas for progressive disclosure.

Do I need Python and pandas to analyze ARR trends by segment?▼

Yes, you need a Python environment with pandas, numpy, and openpyxl to analyze ARR trends by segment, as the Skill relies on these dependencies to ingest raw data, perform modeling, and export structured reports.

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