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Installation

npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-retrieve

Summary

>

SKILL.md

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
  • designing segment or calculated insight assets → sf-datacloud-segment
  • analyzing STDM/session tracing/parquet telemetry → sf-ai-agentforce-observability

---

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

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

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