What specific metrics does the health score include?

The health score is a weighted average of GTM Architecture (20%), Pipeline Health (25%), Data Quality (20%), Automation efficiency (15%), and Forecasting accuracy (20%).

Can this be used on Salesforce Sandboxes?

Yes, it automatically detects sandbox environments and switches to a metadata-focused analysis approach to provide value even when production data is not present.

Is the data analysis based on real-time queries?

Yes, the framework enforces real-query execution via Salesforce MCP tools and explicitly fails if queries cannot be verified, ensuring recommendations are based on factual data rather than simulations.

How does the framework handle custom Salesforce fields?

The skill includes a revenue context detector that automatically identifies custom revenue fields (like ARR__c) and maps them to assessment metrics, ensuring compatibility with bespoke orgs.

RevOps Assessment Framework for Salesforce

Name: RevOps Assessment Framework for Salesforce
Author: RevPalSFDC

byRevPalSFDC

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Analytics & Monitoring

Audits and optimizes Salesforce Revenue Operations through automated health scoring, pipeline analysis, and data-driven GTM recommendations.

The RevOps Assessment Framework is a specialized Claude Code skill designed to evaluate and enhance Salesforce Go-to-Market (GTM) architectures. It automates the complex process of auditing pipeline health, sales process efficiency, and forecast accuracy using statistical analysis and industry benchmarks. By detecting instance types and identifying custom revenue fields or sales processes, it provides precise health scores across five key categories—GTM Architecture, Pipeline Health, Data Quality, Automation, and Forecasting—delivering actionable insights and verified recommendations for revenue leaders and Salesforce administrators.

Key Features

011 GitHub stars

02Deep pipeline analysis including stage conversion, velocity, and aging

03Automated RevOps health scoring across five key GTM categories

04Intelligent detection of custom revenue fields and multi-sales process configurations

05Context-aware instance detection for metadata-focused or data-driven auditing

06Statistical sampling and real-query validation for maximum data integrity

Use Cases

01Performing comprehensive pipeline audits to identify sales bottlenecks and leakage

02Evaluating GTM architecture alignment during organizational restructuring or mergers

03Assessing data quality and field utilization to improve forecast accuracy

Key Features

011 GitHub stars

02Deep pipeline analysis including stage conversion, velocity, and aging

03Automated RevOps health scoring across five key GTM categories

04Intelligent detection of custom revenue fields and multi-sales process configurations

05Context-aware instance detection for metadata-focused or data-driven auditing

06Statistical sampling and real-query validation for maximum data integrity

Use Cases

01Performing comprehensive pipeline audits to identify sales bottlenecks and leakage

02Evaluating GTM architecture alignment during organizational restructuring or mergers

03Assessing data quality and field utilization to improve forecast accuracy