Salesforce data operations with 130-point scoring. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, or needs data factory patterns for Apex tests. DO NOT TRIGGER when: SOQL query writing only (use sf-soql), Apex test execution (use sf-testing), or metadat

Salesforce Data Operations Expert (sf data) Use this skill when the user needs Salesforce data work : record CRUD, bulk import/export, test data generation, cleanup scripts, or data factory patterns for validating Apex, Flow, or integration behavior. When This Skill Owns the Task Use sf data when the work involves: sf data CLI commands record creation, update, delete, upsert, export, or tree import/export realistic test data generation bulk data operations and cleanup Apex anonymous scripts for data seeding / rollback Delegate elsewhere when the user is: writing SOQL only → [sf soql](../sf soql/SKILL.md) running or repairing Apex tests → [sf testing](../sf testing/SKILL.md) deploying metadata first → [sf deploy](../sf deploy/SKILL.md) discovering schema / field definitions → [sf metadata](../sf metadata/SKILL.md) Important Mode Decision Confirm which mode the user wants: Mode Use when Script generation they want reusable .apex , CSV, or JSON assets without touching an org yet Remote execution they want records created / changed in a real org now Do not assume remote execution if the user may only want scripts. Required Context to Gather First Ask for or infer: target object(s) org alias, if remote execution is required operation type: query, create, update, delete, upsert, import, export, cleanup expected volume whether this is test data, migration data, or one off troubleshooting data any parent child relationships that must exist first Core Operating Rules sf data acts on remote org data unless the user explicitly wants local script generation. Objects and fields must already exist before data creation. For automation testing, prefer 251+ records when bulk behavior matters. Always think about cleanup before creating large or noisy datasets. Never use real PII in generated test data. Prefer CLI first for straightforward CRUD; use anonymous Apex when the operation truly needs server side orchestration. If metadata is missing, stop and hand off to: [sf metadata](../sf metadata/SKILL.md) or [sf deploy](../sf deploy/SKILL.md) Recommended Workflow 1. Verify prerequisites Confirm object / field availability, org auth, and required parent records. 2. Run describe first pre flight validation when schema is uncertain Before creating or updating records, use object describe data to validate: required fields createable vs non createable fields picklist values relationship fields and parent requirements Example pattern: Helpful filters: 3. Choose the smallest correct mechanism Need Default approach small one off CRUD sf data single record commands large import/export Bulk API 2.0 via sf data ... bulk parent child seed set tree import/export reusable test dataset factory / anonymous Apex script reversible experiment cleanup script or savepoint based approach 4. Execute or generate assets Use the built in templates under assets/ when they fit: assets/factories/ assets/bulk/ assets/cleanup/ assets/soql/ assets/csv/ assets/json/ 5. Verify results Check counts, relationships, and record IDs after creation or update. 6. Apply a bounded retry strategy If creation fails: 1. try the primary CLI shape once 2. retry once with corrected parameters 3. re run describe / validate assumptions 4. pivot to a different mechanism or provide a manual workaround Do not repeat the same failing command indefinitely. 7. Leave cleanup guidance Provide exact cleanup commands or rollback assets whenever data was created. High Signal Rules Bulk safety use bulk operations for large volumes test automation sensitive behavior with 251+ records where appropriate avoid one record at a time patterns for bulk scenarios Data integrity include required fields validate picklist values before creation verify parent IDs and relationship integrity account for validation rules and duplicate constraints exclude non createable fields from input payloads Cleanup discipline Prefer one of: delete by ID delete by pattern delete by created date window rollback / savepoint patterns for script based test runs Common Failure Patterns Error Likely cause Default fix direction INVALID FIELD wrong field API name or FLS issue verify schema and access REQUIRED FIELD MISSING mandatory field omitted include required values from describe data INVALID CROSS REFERENCE KEY bad parent ID create / verify parent first FIELD CUSTOM VALIDATION EXCEPTION validation rule blocked the record use valid test data or adjust setup invalid picklist value guessed value instead of describe backed value inspect picklist values first non writeable field error field is not createable / updateable remove it from the payload bulk limits / timeouts wrong tool for the volume switch to bulk / staged import Output Format When finishing, report in this order: 1. Operation performed 2. Objects and counts 3. Target org or local artifact path 4. Record IDs / output files 5. Verification result 6. Cleanup instructions Suggested shape: Cross Skill Integration Need Delegate to Reason discover object / field structure [sf metadata](../sf metadata/SKILL.md) accurate schema grounding run bulk sensitive Apex validation [sf testing](../sf testing/SKILL.md) test execution and coverage deploy missing schema first [sf deploy](../sf deploy/SKILL.md) metadata readiness implement production logic consuming the data [sf apex](../sf apex/SKILL.md) or [sf flow](../sf flow/SKILL.md) behavior implementation Reference Map Start here [references/sf cli data commands.md](references/sf cli data commands.md) [references/test data best practices.md](references/test data best practices.md) [references/orchestration.md](references/orchestration.md) [references/test data patterns.md](references/test data patterns.md) [references/test data factory usage.md](references/test data factory usage.md) Query / bulk / cleanup [references/soql relationship guide.md](references/soql relationship guide.md) [references/relationship query examples.md](references/relationship query examples.md) [references/bulk operations guide.md](references/bulk operations guide.md) [references/cleanup rollback guide.md](references/cleanup rollback guide.md) [references/cleanup rollback example.md](references/cleanup rollback example.md) Examples / limits [references/crud workflow example.md](references/crud workflow example.md) [references/bulk testing example.md](references/bulk testing example.md) [references/anonymous apex guide.md](references/anonymous apex guide.md) [references/governor limits reference.md](references/governor limits reference.md) [assets/](assets/) Score Guide Score Meaning 117+ strong production safe data workflow 104–116 good operation with minor improvements possible 91–103 acceptable but review advised 78–90 partial / risky patterns present < 78 blocked until corrected

sf-data