sf-datacloud-retrieve

安装量: 455
排名: #4872

安装

npx skills add https://github.com/jaganpro/sf-skills --skill 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 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 --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: Target org: Target object:

Commands: Verification: Next step: 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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