How does it improve Salesforce formula development?

The skill provides safe patterns for null handling, prevents common errors when referencing picklist fields, and helps manage cross-object relationship limits.

Can it help prevent deployment failures?

Yes, it includes a pre-deployment checklist that checks for field history tracking limits, Apex code coverage requirements, and common blockers like missing dependencies.

What naming conventions does this skill support?

It provides specific patterns for Objects (BusinessName__c), Fields (DescriptiveName__c), Flows ({Object}_{Action}_{Trigger}), and Validation Rules to ensure consistency across the org.

Does it support different types of Salesforce Flows?

Yes, it offers distinct naming and design patterns for Record-Triggered, Screen, Autolaunched, and Scheduled flows.

Salesforce Metadata Standards

Name: Salesforce Metadata Standards
Author: RevPalSFDC

byRevPalSFDC

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Database Management

Enforces Salesforce metadata best practices and naming conventions for objects, fields, flows, and validation rules.

This skill acts as a RevOps CoPilot by providing a comprehensive framework for Salesforce metadata design and architectural consistency. It guides the creation of custom objects and fields using standardized naming patterns, optimizes complex formula logic to avoid common pitfalls, and provides pre-deployment checklists to ensure compliance with platform limits. By integrating these standards directly into the development workflow, it helps maintain a scalable, high-quality Salesforce environment while reducing deployment errors and technical debt.

Key Features

01Provides optimized formula patterns for picklists, null handling, and cross-object references.

02Identifies common deployment blockers including missing dependencies and FLS restrictions.

03Standardizes naming conventions for objects, fields, junction objects, and flows.

04Enforces naming patterns for record-triggered, screen, scheduled, and autolaunched flows.

051 GitHub stars

06Validates metadata against platform limits like field history tracking and validation rule counts.

Use Cases

01Refactoring legacy validation rules and formulas for better performance and readability.

02Conducting pre-deployment audits to ensure metadata quality and platform limit compliance.

03Defining architectural standards for new custom objects and complex field relationships.

Key Features

01Provides optimized formula patterns for picklists, null handling, and cross-object references.

02Identifies common deployment blockers including missing dependencies and FLS restrictions.

03Standardizes naming conventions for objects, fields, junction objects, and flows.

04Enforces naming patterns for record-triggered, screen, scheduled, and autolaunched flows.

051 GitHub stars

06Validates metadata against platform limits like field history tracking and validation rule counts.

Use Cases

01Refactoring legacy validation rules and formulas for better performance and readability.

02Conducting pre-deployment audits to ensure metadata quality and platform limit compliance.

03Defining architectural standards for new custom objects and complex field relationships.