Sf Datacloud Retrieve

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/rule file)
• designing segment or calculated insight assets → [sf-datacloud-segment](../sf-datacloud-segment/rule file)
• analyzing STDM/session tracing/parquet telemetry → [sf-ai-agentforce-observability](../sf-ai-agentforce-observability/rule file)

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 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

node skills/sf-datacloud/scripts/diagnose-org.mjs -o <org> --phase retrieve --json
# optional query-plane probe, only with a real table name
node skills/sf-datacloud/scripts/diagnose-org.mjs -o <org> --phase retrieve --describe-table MyDMO__dlm --json

2. Choose the smallest correct query shape

sf data360 query sql -o <org> --sql 'SELECT COUNT(*) FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query sqlv2 -o <org> --sql 'SELECT * FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query async-create -o <org> --sql 'SELECT * FROM "ssot__Individual__dlm"' 2>/dev/null

3. Use describe before guessing fields

sf data360 query describe -o <org> --table ssot__Individual__dlm 2>/dev/null

4. Use vector or hybrid search only when an index exists

sf data360 search-index list -o <org> 2>/dev/null
sf data360 query vector -o <org> --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o <org> --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o <org> --index Insurance_Index --query "weather damage coverage" --prefilter "Type_of_Insurance__c='Home'" --limit 10 2>/dev/null

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

Retrieve task: <sql / sqlv2 / async / describe / vector / search-index>
Target org: <alias>
Target object: <table or index>
Commands: <key commands run>
Verification: <query rows / schema / status>
Next step: <segment / harmonize / follow-up>

References

• README.md
• examples/search-indexes/vector-knowledge.json
• examples/search-indexes/hybrid-structured.json
• ../sf-datacloud/assets/definitions/search-index.template.json
• ../sf-datacloud/references/plugin-setup.md
• ../sf-datacloud/references/feature-readiness.md