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Handling Sf Data

  • 2.4k installs
  • 763 repo stars
  • Updated July 24, 2026
  • forcedotcom/sf-skills

handling-sf-data is a Salesforce skill for org data CRUD, bulk import/export, test data factories, and cleanup via sf data CLI.

About

The handling-sf-data skill covers Salesforce data operations with sf data CLI commands, bulk import and export, test data generation, cleanup scripts, and Apex anonymous seeding for validating Flow, Apex, and integration behavior. It owns record CRUD, tree import, factory patterns, and org cleanup while delegating pure SOQL writing, Apex test execution, and metadata deployment to sibling skills. A required mode decision distinguishes script generation from remote execution in a real org. Operating rules demand describe-first preflight when schema is uncertain, synthetic non-PII test data, cleanup planning before large seeds, and preferring 251 plus records when bulk behavior matters. The workflow verifies prerequisites, chooses the smallest correct mechanism from single-record sf data through Bulk API 2.0 and tree import, executes or generates assets from built-in templates, verifies counts and relationships, applies bounded retries, and leaves cleanup guidance after creation.

  • Owns sf data CLI CRUD, bulk import/export, and Apex data seeding workflows.
  • Confirm script generation vs remote org execution before starting.
  • Describe-first preflight validates required fields and picklist values.
  • Prefer 251 plus records when bulk automation behavior must be tested.
  • Always leave cleanup commands after creating test or migration data.

Handling Sf Data by the numbers

  • 2,402 all-time installs (skills.sh)
  • +7 installs in the week ending Jul 28, 2026 (Skillselion tracking)
  • Ranked #216 of 4,386 Backend & APIs skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

handling-sf-data capabilities & compatibility

Capabilities
sf data single record and bulk cli command patte · tree import for parent child seed datasets · describe first schema preflight validation · anonymous apex factory and cleanup templates · mode decision between script generation and remo
Works with
salesforce
Use cases
database · testing · api development
From the docs

What handling-sf-data says it does

Do not assume remote execution if the user may only want scripts.
SKILL.md
Plan cleanup before creating large or noisy datasets
SKILL.md
npx skills add https://github.com/forcedotcom/sf-skills --skill handling-sf-data

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Listed on Skillselion
Installs2.4k
repo stars763
Security audit3 / 3 scanners passed
Last updatedJuly 24, 2026
Repositoryforcedotcom/sf-skills

How do I seed, bulk import, or clean Salesforce records in a dev org using sf data CLI?

Create, bulk import, export, seed, and clean Salesforce org records using sf data CLI and anonymous Apex patterns.

Who is it for?

Salesforce developers creating test data, bulk imports, or cleanup scripts in authenticated orgs.

Skip if: Skip for SOQL-only queries, metadata deployment, or Connected App OAuth configuration.

When should I use this skill?

User needs sf data commands, bulk import, test data factory, or org record cleanup in Salesforce.

What you get

Verified records with counts, relationships, cleanup commands, and reusable factory or CSV assets.

  • CSV bulk files
  • sf bulk import commands
  • populated test org data

By the numbers

  • Designed for bulk insert of 10,000+ Salesforce records
  • Recommends sf data import bulk with CSV over Anonymous Apex

Files

SKILL.mdMarkdownGitHub ↗

Salesforce Data Operations Expert (handling-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 handling-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 → querying-soql
  • running or repairing Apex tests → running-apex-tests
  • deploying metadata first → deploying-metadata
  • creating or modifying custom objects / fields → generating-custom-object or generating-custom-field

---

Important Mode Decision

Confirm which mode the user wants:

ModeUse when
Script generationthey want reusable .apex, CSV, or JSON assets without touching an org yet
Remote executionthey 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

  • handling-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.
  • Plan cleanup before creating large or noisy datasets — untracked records accumulate across runs and pollute org state.
  • Use synthetic, non-identifying data in test records — real PII creates compliance risk and cannot be safely removed after bulk import.
  • 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:

  • generating-custom-object or generating-custom-field to create the missing schema, then deploying-metadata to deploy it before retrying the data operation

---

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

See references/sf-cli-data-commands.md for the sf sobject describe command and jq filter patterns for inspecting fields, picklist values, and createable constraints.

3. Choose the smallest correct mechanism

NeedDefault approach
small one-off CRUDsf data single-record commands
large import/exportBulk API 2.0 via sf data ... bulk
parent-child seed settree import/export
reusable test datasetfactory / anonymous Apex script
reversible experimentcleanup 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

ErrorLikely causeDefault fix direction
INVALID_FIELDwrong field API name or FLS issueverify schema and access
REQUIRED_FIELD_MISSINGmandatory field omittedinclude required values from describe data
INVALID_CROSS_REFERENCE_KEYbad parent IDcreate / verify parent first
FIELD_CUSTOM_VALIDATION_EXCEPTIONvalidation rule blocked the recorduse valid test data or adjust setup
invalid picklist valueguessed value instead of describe-backed valueinspect picklist values first
non-writeable field errorfield is not createable / updateableremove it from the payload
bulk limits / timeoutswrong tool for the volumeswitch 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:

Data operation: <create / update / delete / export / seed>
Objects: <object + counts>
Target: <org alias or local path>
Artifacts: <record ids / csv / apex / json files>
Verification: <passed / partial / failed>
Cleanup: <exact delete or rollback guidance>

---

Cross-Skill Integration

NeedDelegate toReason
create missing custom objectsgenerating-custom-objectschema must exist before data operations
create missing custom fieldsgenerating-custom-fieldfield-level schema must exist before data creation
run bulk-sensitive Apex validationrunning-apex-teststest execution and coverage
deploy missing schema firstdeploying-metadatametadata readiness
implement production Apex logic consuming the datagenerating-apexApex class / trigger authoring
implement Flow logic consuming the datagenerating-flowFlow authoring and automation

---

Reference Map

Start here

  • references/sf-cli-data-commands.md
  • references/test-data-best-practices.md
  • references/orchestration.md
  • references/test-data-patterns.md
  • references/test-data-factory-usage.md

Query / bulk / cleanup

  • references/soql-relationship-guide.md
  • references/relationship-query-examples.md
  • references/bulk-operations-guide.md
  • references/cleanup-rollback-guide.md
  • references/cleanup-rollback-example.md

Examples / limits

  • references/crud-workflow-example.md
  • references/bulk-testing-example.md
  • references/anonymous-apex-guide.md
  • references/governor-limits-reference.md

Validation scripts

  • scripts/soql_validator.py — validate SOQL queries before execution
  • scripts/validate_data_operation.py — pre-flight check for data operations (required fields, picklist values, createable fields)

Asset templates

  • assets/factories/ — Apex test data factory scripts (account, contact, opportunity, lead, user, etc.)
  • assets/bulk/ — Bulk API 2.0 Apex templates (insert 200, 500, 10000 records; upsert by external ID)
  • assets/cleanup/ — Cleanup and rollback scripts (delete by name, date, pattern; transaction rollback)
  • assets/soql/ — SOQL query templates (aggregate, subquery, parent-to-child, child-to-parent, polymorphic)
  • assets/csv/ — CSV import templates for Account, Contact, Opportunity, custom objects
  • assets/json/ — JSON tree import templates (account-contact, account-opportunity, full hierarchy)

---

Score Guide

ScoreMeaning
117+strong production-safe data workflow
104–116good operation with minor improvements possible
91–103acceptable but review advised
78–90partial / risky patterns present
< 78blocked until corrected

Related skills

Forks & variants (1)

Handling Sf Data has 1 known copy in the catalog totaling 532 installs. They canonicalize to this original listing.

How it compares

Use handling-sf-data for CLI-driven 10k+ Salesforce bulk loads; use small Apex scripts only when record counts stay within governor limits.

FAQ

When should I use anonymous Apex instead of sf data?

Use Apex when the operation needs server-side orchestration; prefer CLI for straightforward CRUD.

How many records for bulk behavior testing?

Prefer 251 or more records when bulk automation behavior matters for Flow or Apex.

What if required objects or fields are missing?

Stop and hand off to generating-custom-object or deploying-metadata skills before data creation.

Is Handling Sf Data safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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