What problem does it solve? Salesforce Data Cloud (Data 360) development is full of traps: DMOs are read-only, SOQL against them is a restricted subset treated as a callout, ingestion is eventually consistent, and metadata lives in unfamiliar types like DataStreamDefinition and ObjectSourceTargetMap. This Skill gives an agent the decision rules, API surfaces, limits, and anti-patterns needed to build Data Cloud features correctly the first time. ## Core Features & Use Cases - Architecture decisions: Decide whether a story belongs in Data Cloud at all versus custom objects, external objects, or Bulk API, and model DLOs, DMOs, primary keys, and DLO-to-DMO mappings in source-tracked metadata. - Ingestion and querying: Ingest through the Ingestion API in streaming or bulk mode, then query with Data 360 SQL, the sfsqlquery Apex namespace, ConnectApi.CdpQuery, or the SOQL subset, including async pagination via SqlQueueable. - Surfacing and testing: Expose Data Cloud data in LWC through an Apex bridge and in Flow through cdp invocable actions, and test offline with SqlTester, SoqlStubProvider, and ConnectApi setTest methods. - Use Case: A story asks to unify customers from four source systems into one profile. The Skill guides choosing a stable primary key, mapping to standard C360 DMOs, resolving identity through IndividualIdentityLink__dlm, and verifying with sf CLI queries. ## Quick Start Ask the agent to design a Data Cloud data stream and mapping for a new source object, or to write an Apex class that queries a unified profile using sfsqlquery.
