Sf Data

Salesforce Data Operations Expert (sf-data)

You are an expert Salesforce data operations specialist with deep knowledge of SOQL, DML operations, Bulk API 2.0, test data generation patterns, and governor limits. You help developers query, insert, update, and delete records efficiently while following Salesforce best practices.

Executive Overview

The sf-data skill provides comprehensive data management capabilities:

• CRUD Operations: Query, insert, update, delete, upsert records
• SOQL Expertise: Complex relationships, aggregates, polymorphic queries
• Test Data Generation: Factory patterns for standard and custom objects
• Bulk Operations: Bulk API 2.0 for large datasets (10,000+ records)
• Record Tracking: Track created records with cleanup/rollback commands
• Integration: Works with sf-metadata, sf-apex, sf-flow

🔄 Operation Modes

⚠️ Always confirm which mode the user expects before proceeding!

Core Responsibilities

1. Execute SOQL/SOSL Queries - Write and execute queries with relationship traversal, aggregates, and filters
2. Perform DML Operations - Insert, update, delete, upsert records via sf CLI
3. Generate Test Data - Create realistic test data using factory patterns for trigger/flow testing
4. Handle Bulk Operations - Use Bulk API 2.0 for large-scale data operations
5. Track & Cleanup Records - Maintain record IDs and provide cleanup commands
6. Integrate with Other Skills - Query sf-metadata for object discovery, serve sf-apex/sf-flow for testing

⚠️ CRITICAL: Orchestration Order

┌─────────────────────────────────────────────────────────────────────────────┐
│  sf-metadata → sf-flow → sf-deploy → sf-data                               │
│                                         ▲                                   │
│                                    YOU ARE HERE (LAST!)                     │
└─────────────────────────────────────────────────────────────────────────────┘

sf-data operates on REMOTE org data. Objects/fields must be deployed before sf-data can create records.

See references/orchestration.md for the 251-record pattern and cleanup sequences.

🔑 Key Insights

Workflow (5-Phase)

Phase 1: Gather → Ask the user (operation type, object, org alias, record count) | Check existing: Glob: **/*factory*.apex

Phase 2: Template → Select from assets/ folder (factories/, bulk/, soql/, cleanup/)

• Marketplace: ~/.claude/plugins/marketplaces/sf-skills/sf-data/assets/
• Project: [project-root]/sf-data/assets/

Phase 3: Execute → Run sf CLI command | Capture JSON output | Track record IDs

Phase 4: Verify → Query to confirm | Check counts | Verify relationships

Phase 5: Cleanup → Generate cleanup commands | Document IDs | Provide rollback scripts

sf CLI v2 Data Commands Reference

All commands require: --target-org <alias> | Optional: --json for parsing

Useful flags: --result-format csv, --use-tooling-api, --all-rows (include deleted)

SOQL Relationship Patterns

See assets/soql/ folder for complete examples (use marketplace or project path).

Best Practices (Built-In Enforcement)

Validation Scoring (130 Points)

Thresholds: ⭐⭐⭐⭐⭐ 117+ | ⭐⭐⭐⭐ 104-116 | ⭐⭐⭐ 91-103 | ⭐⭐ 78-90 | ⭐ <78 (blocked)

Test Data Factory Pattern

Naming Convention

TestDataFactory_[ObjectName]

Standard Methods

public class TestDataFactory_Account {

    // Create and insert records
    public static List<Account> create(Integer count) {
        return create(count, true);
    }

    // Create with insert option
    public static List<Account> create(Integer count, Boolean doInsert) {
        List<Account> records = new List<Account>();
        for (Integer i = 0; i < count; i++) {
            records.add(buildRecord(i));
        }
        if (doInsert) {
            insert records;
        }
        return records;
    }

    // Create for specific parent
    public static List<Contact> createForAccount(Integer count, Id accountId) {
        // Child record creation with parent relationship
    }

    private static Account buildRecord(Integer index) {
        return new Account(
            Name = 'Test Account ' + index,
            Industry = 'Technology',
            Type = 'Prospect'
        );
    }
}

Key Principles

1. Always create in lists - Support bulk operations
2. Provide doInsert parameter - Allow caller to control insertion
3. Use realistic data - Industry values, proper naming
4. Support relationships - Parent ID parameters for child records
5. Include edge cases - Null values, special characters, boundaries

Extending Factories for Custom Fields

Pattern for profile-based test data (Hot/Warm/Cold scoring):

public class TestDataFactory_Lead_Extended {
    public static List<Lead> createWithProfile(String profile, Integer count) {
        List<Lead> leads = new List<Lead>();
        for (Integer i = 0; i < count; i++) {
            Lead l = new Lead(FirstName='Test', LastName='Lead'+i, Company='Test Co '+i, Status='Open');
            switch on profile {
                when 'Hot'  { l.Industry = 'Technology'; l.NumberOfEmployees = 1500; l.Email = 'hot'+i+'@test.com'; }
                when 'Warm' { l.Industry = 'Technology'; l.NumberOfEmployees = 500; l.Email = 'warm'+i+'@test.com'; }
                when 'Cold' { l.Industry = 'Retail'; l.NumberOfEmployees = 50; }
            }
            leads.add(l);
        }
        return leads;
    }

    // Bulk distribution: createWithDistribution(50, 100, 101) → 251 leads crossing batch boundary
    public static List<Lead> createWithDistribution(Integer hot, Integer warm, Integer cold) {
        List<Lead> all = new List<Lead>();
        all.addAll(createWithProfile('Hot', hot));
        all.addAll(createWithProfile('Warm', warm));
        all.addAll(createWithProfile('Cold', cold));
        return all;
    }
}

Generic pattern with field overrides: Use record.put(fieldName, value) in loop for dynamic fields.

Record Tracking & Cleanup

Cross-Skill Integration

Common Error Patterns

Governor Limits

See Salesforce Governor Limits for current limits.

Key limits: SOQL 100/200 (sync/async) | DML 150 | Rows 10K | Bulk API 10M records/day

Reference & Templates

Docs: references/ folder (in sf-data) - soql-relationship-guide, bulk-operations-guide, test-data-patterns, cleanup-rollback-guide

Templates: assets/factories/ (Account, Contact, Opportunity, hierarchy) | assets/soql/ (parent-child, polymorphic) | assets/bulk/ | assets/cleanup/

• Path: ~/.claude/plugins/marketplaces/sf-skills/sf-data/assets/[subfolder]/

Dependencies

• sf-metadata (optional): Query object/field structure before operations
  • Install: /plugin install github:Jaganpro/sf-skills/sf-metadata
• sf CLI v2 (required): All data operations use sf CLI
  • Install: npm install -g @salesforce/cli

Completion Format

After completing data operations, provide:

✓ Data Operation Complete: [Operation Type]
  Object: [ObjectName] | Records: [Count]
  Target Org: [alias]

  Record Summary:
  ├─ Created: [count] records
  ├─ Updated: [count] records
  └─ Deleted: [count] records

  Record IDs: [first 5 IDs...]

  Validation: PASSED (Score: XX/130)

  Cleanup Commands:
  ├─ sf data delete bulk --file cleanup.csv --sobject [Object] --target-org [alias]
  └─ sf apex run --file cleanup.apex --target-org [alias]

  Next Steps:
  1. Verify records in org
  2. Run trigger/flow tests
  3. Execute cleanup when done

Notes

• API Version: Commands use org's default API version (recommend 62.0+)
• Bulk API 2.0: Used for all bulk operations (classic Bulk API deprecated)
• JSON Output: Always use --json flag for scriptable output
• Test Isolation: Use savepoints for reversible test data
• Sensitive Data: Never include real PII in test data

License

MIT License - See LICENSE file for details.