Salesforce Org Analysis Kit

Automated framework for Salesforce org analysis, designed for merger/acquisition due diligence and technical health assessments. This kit combines metadata extraction with AI-driven analysis to identify technical debt, automation conflicts, and migration blockers.

---

Overview

Merging Salesforce orgs requires deep visibility into what exists, what is used, and what is broken. This toolkit provides the raw data and structured AI prompts to turn a black-box org into a clear migration plan.

Key Capabilities

Feature	Description
Data Inventory	Catalog record counts, identify empty tables, and calculate field usage statistics (population %).
Metadata Analysis	Detect "ghost metadata" (fields in XML but 0% usage), hard-coded IDs, and dormant automations.
Security Audit	Analyze Profile complexity, Permission Sets, and Sharing Models to assess access risks.
Process Mapping	Reverse-engineer sales and delivery processes based on Record Types and Stage history.
Risk Assessment	Flag critical migration blockers: Validation Rules, cross-object formulas, and dependencies.

---

Workflow

graph LR
    A[Setup Project] --> B[Retrieve Metadata]
    B --> C[Export Data & Stats]
    C --> D[AI Analysis]
    D --> E[Final Reports]
    
    style A fill:#f9f9f9,stroke:#333,stroke-width:2px
    style B fill:#f9f9f9,stroke:#333,stroke-width:2px
    style C fill:#f9f9f9,stroke:#333,stroke-width:2px
    style D fill:#e1f5fe,stroke:#01579b,stroke-width:2px
    style E fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px

Loading

1. Retrieve: Pull XML metadata using the Salesforce CLI.
2. Export: Run Python scripts to sample data and calculate field population stats.
3. Analyze: Feed the metadata and stats into an AI assistant using the provided prompts.

---

Prerequisites

• Salesforce CLI (sf)
• Python 3.x
• Git

---

Installation

1. Clone the repository

   git clone https://github.com/designthynk/salesforce-org-analysis-kit.git
   cd salesforce-org-analysis-kit

2. Initialize the Project Run the setup script with your target org alias (from sf org list).

   ./setup.sh [ORG_ALIAS]
   # Example: ./setup.sh my-org-prod

   Creates directory structure, installs Python requirements, and generates custom scripts.

---

Usage Guide

1. Retrieve Metadata

Pull the specific metadata needed for analysis. The included package manifest focuses on high-value components.

sf project retrieve start --manifest templates/package.xml --target-org [ORG_ALIAS] --output-dir force-app/[ORG_ALIAS]

2. Export Data & Statistics

Run the generated Python script to export samples and calculate field usage.

• Input: Org connection
• Output: CSV samples and field_stats.csv in scripts/data/

python scripts/export_[ORG_ALIAS].py

3. Generate Analysis Reports

Open docs/PROMPTS.md. This file contains a sequence of prompts to feed into your AI assistant (ChatGPT, Claude, Cursor).

Analysis Sequence:

1. Setup: Contextualize the AI with Prompt 0.
2. Task 1: Data Summary: Inventory records and overall health.
3. Task 1.5: Security: Analyze profiles and sharing rules.
4. Task 2: Data Model: Map objects and business processes.
5. Task 3: Automation: Audit flows, triggers, and validations.
6. Task 4: Tech Debt: Identify unused fields and integrations.
7. Task 5: Final Report: Generate the executive summary.

---

Project Structure

.
├── docs/
│   ├── PROMPTS.md          # Structured prompts for AI analysis
│   └── ai-instructions.md  # System context for the AI
├── templates/
│   ├── export_data.py      # Python script for data export & stats
│   ├── extract_metadata.py # XML parsing utility
│   └── package.xml         # Retrieval manifest
├── force-app/              # (Created) Storage for retrieved metadata
├── scripts/                # (Created) Storage for generated scripts & data
├── setup.sh                # Initialization script
└── requirements.txt        # Python dependencies

License

This project is licensed under the MIT License - see the LICENSE file for details.