Salesforce Data Cloud Retrieve phase. TRIGGER when: user runs Data Cloud SQL, describe, async queries, vector search, search-index workflows, or metadata introspection for Data Cloud objects. DO NOT TRIGGER when: the task is standard CRM SOQL (use sf-soql), segment creation or calculated insight des

sf datacloud retrieve: Data Cloud Retrieve Phase Use this skill when the user needs query, search, and metadata introspection for Data Cloud: sync SQL, paginated SQL, async query workflows, table describe, vector search, hybrid search, or search index operations. When This Skill Owns the Task Use sf datacloud retrieve when the work involves: sf data360 query sf data360 search index sf data360 metadata sf data360 profile or sf data360 insight inspection understanding Data Cloud SQL results or query shape Delegate elsewhere when the user is: writing standard CRM SOQL only → [sf soql](../sf soql/SKILL.md) designing segment or calculated insight assets → [sf datacloud segment](../sf datacloud segment/SKILL.md) analyzing STDM/session tracing/parquet telemetry → [sf ai agentforce observability](../sf ai agentforce observability/SKILL.md) Required Context to Gather First Ask for or infer: target org alias whether the user needs quick count, medium result set, large export, schema inspection, or semantic search table/index name if known whether the task is read only SQL or search index lifecycle management Core Operating Rules Treat Data Cloud SQL as its own query language, not SOQL. Run the shared readiness classifier before relying on query/search surfaces: node ~/.claude/skills/sf datacloud/scripts/diagnose org.mjs o <org phase retrieve json . Use describe before guessing columns. Prefer sqlv2 or async query flows for larger result sets. Use vector search or hybrid search only when the search index lifecycle is healthy. Keep STDM/parquet/session tracing workflows out of this skill family. Recommended Workflow 1. Classify readiness for retrieve work 2. Choose the smallest correct query shape 3. Use describe before guessing fields 4. Use vector or hybrid search only when an index exists 5. Reuse curated search index examples when creating indexes Use the phase owned examples instead of inventing JSON from scratch: examples/search indexes/vector knowledge.json examples/search indexes/hybrid structured.json High Signal Gotchas Data Cloud SQL is not SOQL. Table names should be double quoted in SQL. sqlv2 is better than ad hoc OFFSET paging for medium result sets. async query is preferable for large results. search index operations and vector/hybrid queries depend on the index lifecycle being healthy. Hybrid search can use prefilter , but only on fields configured as prefilter capable when the search index was created. HNSW index parameters are typically read only on create; leave userValues: [] unless the platform explicitly documents otherwise. query describe is not a universal tenant probe; only run it with a known DMO or DLO table after broader readiness has been confirmed. Output Format References [README.md](README.md) [examples/search indexes/vector knowledge.json](examples/search indexes/vector knowledge.json) [examples/search indexes/hybrid structured.json](examples/search indexes/hybrid structured.json) [../sf datacloud/assets/definitions/search index.template.json](../sf datacloud/assets/definitions/search index.template.json) [../sf datacloud/references/plugin setup.md](../sf datacloud/references/plugin setup.md) [../sf datacloud/references/feature readiness.md](../sf datacloud/references/feature readiness.md)

sf-datacloud-retrieve