Automate Salesforce data access with SOQL, SOSL, and Bulk API 2.0.
npx skills add https://github.com/tomz/agent-skills --skill sf-data-tomz
Please help me install this Agent Skill. Skill: sf-data Source: https://github.com/tomz/agent-skills/tree/main/sf-data Command: npx skills add https://github.com/tomz/agent-skills --skill sf-data-tomz
Salesforce data management tasks are complex due to layered security (OWD, sharing rules, and FLS), multiple data-access patterns (SOQL, SOSL, and Bulk API), and the need for reliable data movement during exports and imports.
Query your Salesforce org with the sf data CLI to fetch a sample set of Account records.
High-intent search queries and answers about installing and using this skill.
Exporting large Salesforce data volumes with Bulk API 2.0 enables scalable data movement for backups. This approach supports bulk queries across standard objects like Accounts, Contacts, and Opportunities while respecting org-wide defaults and sharing rules.
SOQL retrieves precise records from single objects like Accounts or Opportunities, while SOSL searches text across multiple objects simultaneously. Both methods respect field-level security and sharing rules during data access in Salesforce.
Loading data with Record Types and Field-Level Security (FLS) requires mapping records to correct types and respecting field accessibility. Data Loader workflows validate FLS permissions during upserts to ensure secure, error-free imports across objects.
Data Loader supports upsert operations across standard objects like Accounts, Contacts, and Opportunities. Proper load ordering is essential when importing related records, and error handling ensures data integrity during the process.
Correct load ordering imports parent objects like Accounts before dependent Contacts or Opportunities. This sequence maintains referential integrity during data loading, and error handling catches failures before they cascade across related records.
Salesforce data exports fail when Field-Level Security (FLS) blocks access to specific fields. Secure data handling requires checking FLS and org-wide defaults before querying or exporting, ensuring only accessible fields are retrieved.
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