Platform Data Manage
forcedotcom/sf-skills
Salesforce data operations with 130-point scoring. An agent skill from forcedotcom/sf-skills.
Salesforce data operations with 130-point scoring. An agent skill from Jaganpro/sf-skills.
Install Sf Data
$ npx skills add Jaganpro/sf-skills --skill sf-data -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Jaganpro/sf-skills sf-data --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Jaganpro/sf-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/sf-data .claude/skills/sf-data && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "sf-data" agent skill from https://github.com/Jaganpro/sf-skills/tree/main/skills/sf-data into .claude/skills/sf-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sf-data", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Jaganpro/sf-skills/tree/main/skills/sf-dataType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Jaganpro/sf-skills --skill sf-data -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Jaganpro/sf-skills sf-data --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jaganpro/sf-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/sf-data .agents/skills/sf-data && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sf-data" agent skill from https://github.com/Jaganpro/sf-skills/tree/main/skills/sf-data into .agents/skills/sf-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sf-data", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Jaganpro/sf-skills --skill sf-data -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Jaganpro/sf-skills sf-data --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jaganpro/sf-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/sf-data .cursor/skills/sf-data && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sf-data" agent skill from https://github.com/Jaganpro/sf-skills/tree/main/skills/sf-data into .cursor/skills/sf-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sf-data", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Jaganpro/sf-skills.git --path skills/sf-data--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Jaganpro/sf-skills --skill sf-data -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Jaganpro/sf-skills sf-data --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jaganpro/sf-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/sf-data .gemini/skills/sf-data && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sf-data" agent skill from https://github.com/Jaganpro/sf-skills/tree/main/skills/sf-data into .gemini/skills/sf-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sf-data", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Jaganpro/sf-skills sf-dataInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Jaganpro/sf-skills --skill sf-data -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Jaganpro/sf-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/sf-data .github/skills/sf-data && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sf-data" agent skill from https://github.com/Jaganpro/sf-skills/tree/main/skills/sf-data into .github/skills/sf-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sf-data", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Jaganpro/sf-skills --skill sf-data -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Jaganpro/sf-skills sf-data --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Jaganpro/sf-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/sf-data .opencode/skills/sf-data && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sf-data" agent skill from https://github.com/Jaganpro/sf-skills/tree/main/skills/sf-data into .opencode/skills/sf-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sf-data", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
sf-data- GitHub stars
- 424
- Token cost
- ~2.1k tokens
- SKILL.md length
- 761 words
- Files
- 54 (incl. references, assets)
- Skills in repo
- 36
- Repo updated
- First seen
- Licence
- MIT
At a glance
Salesforce data operations with 130-point scoring. An agent skill from Jaganpro/sf-skills.
- Works in 7 steps: Verify prerequisites → Run describe-first pre-flight validation… → Choose the smallest correct mechanism → …
- : user creates test data
- SKILL.md covers When This Skill Owns the Task, Important Mode Decision, Required Context to Gather First and Core Operating Rules, plus 7 more sections
- Calls sf and jq; needs INVALID_CROSS_REFERENCE_KEY
What it does
Sf Data is an agent skill from Jaganpro/sf-skills. 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 metadata deployment (use sf-deploy).
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 58 other files, including reference files and assets (for example `CREDITS.md` and `README.md`).
It sits in Testing & QA, covering Test data and fixtures, CRM management and Deployment. It works with Salesforce. The repository describes itself as: [ARCHIVED — migrated to forcedotcom/afv-library] Salesforce Skills for Agentic Coding Tools — Apex, Flow, LWC, SOQL, Agentforce, Data Cloud, OmniStudio. Read-only archive; active… The licence is MIT.
When your agent uses it
- : user creates test data
- Performs bulk import/export
- Uses sf data CLI commands
- Needs data factory patterns for Apex tests
Example prompts
- “/sf-data”
Requirements
- A credential in INVALID_CROSS_REFERENCE_KEY
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 53c9956. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
sfjq
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
INVALID_CROSS_REFERENCE_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Sf Data loads about 2.1k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 761 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from Jaganpro/sf-skills at commit 53c9956, republished under its MIT licence (© Jaganpro). 761 words, ~2,144 tokens.
Download SKILL.mdSave it as
.claude/skills/sf-data/SKILL.md (or your agent's skills folder). This skill also uses 53 other files; get the full folder from GitHub.- name
- sf-data
- description
- 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 metadata deployment (use sf-deploy).
- license
- MIT
- metadata.version
- 1.2.0
- metadata.author
- Jag Valaiyapathy
- metadata.scoring
- 130 points across 7 categories
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 dataCLI 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
- running or repairing Apex tests → sf-testing
- deploying metadata first → sf-deploy
- discovering schema / field definitions → sf-metadata
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-dataacts 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:
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:
sf sobject describe --sobject ObjectName --target-org <alias> --jsonHelpful filters:
# Required + createable fields
jq '.result.fields[] | select(.nillable==false and .createable==true) | {name, type}'
# Valid picklist values for one field
jq '.result.fields[] | select(.name=="StageName") | .picklistValues[].value'
# Fields that cannot be set on create
jq '.result.fields[] | select(.createable==false) | .name'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:
- try the primary CLI shape once
- retry once with corrected parameters
- re-run describe / validate assumptions
- pivot to a different mechanism or provide a manual workaround
Do not repeat the same failing command indefinitely.
Show full SKILL.md (305 more words)Show less
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:
- Operation performed
- Objects and counts
- Target org or local artifact path
- Record IDs / output files
- Verification result
- 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
| Need | Delegate to | Reason |
|---|---|---|
| discover object / field structure | sf-metadata | accurate schema grounding |
| run bulk-sensitive Apex validation | sf-testing | test execution and coverage |
| deploy missing schema first | sf-deploy | metadata readiness |
| implement production logic consuming the data | sf-apex or sf-flow | behavior implementation |
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
- 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 |
© Jaganpro, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 53 other files (references, assets) in skills/sf-data of Jaganpro/sf-skills.
- SKILL.md
- CREDITS.md
- README.md
- assets/bulk/bulk-insert-10000.apex
- assets/bulk/bulk-insert-200.apex
- assets/bulk/bulk-insert-500.apex
- assets/bulk/bulk-upsert-external-id.apex
- assets/cleanup/delete-by-created-date.apex
- assets/cleanup/delete-by-name.apex
- assets/cleanup/delete-test-data.apex
- assets/cleanup/rollback-transaction.apex
- assets/csv/account-import.csv
- assets/csv/contact-import.csv
- assets/csv/custom-object-import.csv
- assets/csv/opportunity-import.csv
- assets/factories/account-factory.apex
- … and 38 more
Open the folder on GitHubat commit 53c9956
Compare with similar skills
Sf Data next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Sf Data this skillJaganpro/sf-skills | 424 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Platform Data Manageforcedotcom/sf-skills | 1.1k | — | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Soql Lib Testingbeyond-the-cloud-dev/soql-lib | 154 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Platform Flexipage Generateforcedotcom/sf-skills | 1.1k | — | ~5.1k | Automated safety check: Notes | Apache-2.0 | |
| Service Omni Channel Setup Coordinateforcedotcom/sf-skills | 1.1k | — | ~5.5k | Automated safety check: Notes | Apache-2.0 | |
| Consumer Goods Accruals Datakit Deployforcedotcom/sf-skills | 1.1k | — | ~4.8k | Automated safety check: Pass | Apache-2.0 |
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Related
Works with
Categories
Questions about Sf Data
What does Sf Data do?
Salesforce data operations with 130-point scoring. An agent skill from Jaganpro/sf-skills. Sf Data is an agent skill from Jaganpro/sf-skills. Salesforce data operations with 130-point scoring.
When should I use Sf Data?
Sf Data fits situations like: : user creates test data; performs bulk import/export; uses sf data CLI commands; needs data factory patterns for Apex tests.
How do I install Sf Data in Claude Code?
Run `npx skills add Jaganpro/sf-skills --skill sf-data -a claude-code`. Or copy the skill folder (skills/sf-data in Jaganpro/sf-skills) into .claude/skills/sf-data in your project. Claude Code loads it when a task matches its description.
How do I install Sf Data in Codex?
Run `npx skills add Jaganpro/sf-skills --skill sf-data -a codex`. Or copy the skill folder (skills/sf-data in Jaganpro/sf-skills) into .agents/skills/sf-data in your project. Codex loads it when a task matches its description.
Can I use Sf Data in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Jaganpro/sf-skills --skill sf-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sf-data, .gemini/skills/sf-data, .github/skills/sf-data and .opencode/skills/sf-data in your project.
What does Sf Data need to run?
Going by SKILL.md and its folder, Sf Data needs the command-line tools its instructions call (sf and jq) and credentials named INVALID_CROSS_REFERENCE_KEY. Our summary lists: A credential in INVALID_CROSS_REFERENCE_KEY.
Does Sf Data access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Sf Data safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Sf Data use?
Sf Data is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Sf Data use?
About 2.1k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 14k tokens, read only when the agent opens those files.
What are the alternatives to Sf Data?
Skills that share tags, products or a category with Sf Data: Platform Data Manage (forcedotcom/sf-skills, 1.1k stars), Soql Lib Testing (beyond-the-cloud-dev/soql-lib, 154 stars), Platform Flexipage Generate (forcedotcom/sf-skills, 1.1k stars) and Service Omni Channel Setup Coordinate (forcedotcom/sf-skills, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sf Data?
Jaganpro (a GitHub user) maintains it in Jaganpro/sf-skills, which has 424 GitHub stars. The repository holds 36 skills in this directory. The repository was last updated on April 27, 2026.
Source: Jaganpro/sf-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.