Sf Datacloud Prepare
This is the ingestion and lake prep layer of Salesforce Data Cloud. You'll use it when you're setting up data streams, managing Data Lake Objects, configuring transforms, or handling Document AI pipelines after your connectors are already wired up. The skill includes a readiness classifier that checks org state before mutating ingestion assets, which is helpful because Data Cloud's CLI behavior varies wildly depending on connector type. Unstructured sources like SharePoint often need UI setup first, and the stream refresh commands don't always do what you'd expect from their names. It hands off to harmonize once your DLOs are healthy and queryable.
- skills.sh installs
- 982
- GitHub stars
- 422
- last updated
- Jul 14, 2026
Install
$ npx -y skills add jaganpro/sf-skills --skill sf-datacloud-prepare --agent claude-codeInstalls into .claude/skills of the current project.
Files
sf-datacloud-prepare: Data Cloud Prepare Phase
Use this skill when the user needs ingestion and lake preparation work: data streams, Data Lake Objects (DLOs), transforms, Document AI, unstructured ingestion, or the handoff from connector setup into a live stream.
When This Skill Owns the Task
Use sf-datacloud-prepare when the work involves:
sf data360 data-stream *sf data360 dlo *sf data360 transform *sf data360 docai *- choosing how data should enter Data Cloud
- rerunning or rescanning ingestion after a source update
- preparing Ingestion API-backed streams after connector setup is complete
Delegate elsewhere when the user is:
- still creating/testing source connections → sf-datacloud-connect
- mapping to DMOs or designing IR/data graphs → sf-datacloud-harmonize
- querying ingested data → sf-datacloud-retrieve
Required Context to Gather First
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- Repository
- github.com/jaganpro/sf-skills
- First seen
- May 16, 2026
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