What data format does the skill require?

The scripts primarily use JSON input files for pipeline, forecast, and GTM data to ensure structured and reliable analysis.

What is the Revenue Operations skill for Claude Code?

It is a specialized plugin that provides tools and scripts to analyze sales data, track forecast accuracy, and measure GTM efficiency within the Claude Code environment.

Which SaaS metrics can this skill calculate?

It calculates core metrics including Magic Number, LTV:CAC, Rule of 40, Net Dollar Retention (NDR), and CAC Payback periods.

How does it track forecast accuracy?

It uses Mean Absolute Percentage Error (MAPE) and bias analysis to evaluate the difference between forecasted revenue and actual results over time.

Can I use this for board meetings?

Yes, it includes templates and calculators specifically designed for quarterly business reviews (QBRs) and leadership-level efficiency audits.

Revenue Operations (RevOps) Analyzer

Name: Revenue Operations (RevOps) Analyzer
Author: alirezarezvani

byalirezarezvani

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9,958

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Analíticas y Monitorización

Optimizes SaaS revenue performance through automated pipeline health analysis, forecast accuracy tracking, and GTM efficiency benchmarking.

The Revenue Operations skill empowers SaaS teams and leaders to make data-driven decisions by providing advanced tools for pipeline inspection, forecasting precision, and unit economic evaluation. It automates complex calculations such as sales velocity, MAPE (Mean Absolute Percentage Error), and the Rule of 40, allowing Claude to act as a specialized RevOps consultant. Whether you are preparing for a board meeting, conducting a weekly sales cadence, or auditing go-to-market efficiency, this skill provides the structured frameworks and scripts needed to identify revenue leakage and strategic growth opportunities.

Características Principales

01Forecast Accuracy Tracking using MAPE and Bias Detection

02Multi-format Output support for human-readable text or JSON integrations

03Automated Pipeline Coverage & Health Analysis (3x-4x ratio tracking)

04SaaS GTM Efficiency Metric Calculation (Magic Number, Rule of 40, LTV:CAC)

059,958 GitHub stars

06Industry-standard Benchmarking and Strategic Improvement Recommendations

Casos de Uso

01Auditing sales forecast accuracy to improve predictability and reduce systematic bias

02Automating weekly pipeline reviews to identify aging deals and coverage gaps

03Generating board-ready GTM efficiency reports including CAC payback and Burn Multiples

Características Principales

01Forecast Accuracy Tracking using MAPE and Bias Detection

02Multi-format Output support for human-readable text or JSON integrations

03Automated Pipeline Coverage & Health Analysis (3x-4x ratio tracking)

04SaaS GTM Efficiency Metric Calculation (Magic Number, Rule of 40, LTV:CAC)

059,958 GitHub stars

06Industry-standard Benchmarking and Strategic Improvement Recommendations

Casos de Uso

01Auditing sales forecast accuracy to improve predictability and reduce systematic bias

02Automating weekly pipeline reviews to identify aging deals and coverage gaps

03Generating board-ready GTM efficiency reports including CAC payback and Burn Multiples