
Generating Flexipage
- 2.5k installs
- 763 repo stars
- Updated July 24, 2026
- forcedotcom/sf-skills
data360-query is a Salesforce Data Cloud skill for SQL, async queries, vector search, and search-index retrieve workflows via sf data360 CLI.
About
data360-query covers the Salesforce Data Cloud retrieve phase for query, search, and metadata introspection tasks. Use it when work involves sf data360 query commands, search-index lifecycle operations, metadata inspection, or profile and insight reads. Treat Data Cloud SQL as its own language, not standard CRM SOQL, and run the diagnose-org readiness classifier before relying on query surfaces. Start with describe before guessing columns, prefer sqlv2 or async flows for larger result sets, and reserve vector or hybrid search for healthy search indexes. Core commands include sql counts, sqlv2 pagination, async-create exports, table describe, search-index list, and vector or hybrid queries with optional prefilter fields. Curated search-index JSON examples ship for vector knowledge and hybrid structured indexes. High-signal gotchas cover double-quoted table names, HNSW parameter defaults, and keeping STDM parquet tracing in agentforce-observe instead of this skill.
- Data Cloud SQL, sqlv2, and async query workflows.
- describe before guessing columns on DMO tables.
- Vector and hybrid search when indexes are healthy.
- diagnose-org readiness classifier before retrieve work.
- Curated search-index JSON examples for vector and hybrid.
Generating Flexipage by the numbers
- 2,462 all-time installs (skills.sh)
- +7 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Ranked #43 of 923 Databases skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
generating-flexipage capabilities & compatibility
- Capabilities
- data cloud sql, sqlv2, and async query commands · table describe before field selection · vector and hybrid search with index lifecycle ch · search index list and curated json examples · diagnose org retrieve phase readiness classifier
- Works with
- salesforce
- Use cases
- database · data analysis · web search
- Pricing
- Free
What generating-flexipage says it does
Treat Data Cloud SQL as its own query language, not SOQL.
Use describe before guessing columns.
sf data360 query vector -o <org> --index Knowledge_Index
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| Installs | 2.5k |
|---|---|
| repo stars | ★ 763 |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 24, 2026 |
| Repository | forcedotcom/sf-skills ↗ |
How do I query Data Cloud tables, run vector search, or inspect search indexes with the sf data360 CLI?
Run Data Cloud SQL, async queries, vector search, and search-index workflows with the sf data360 CLI plugin.
Who is it for?
Salesforce developers running Data Cloud SQL, async exports, or vector and hybrid search against enabled orgs.
Skip if: Skip for standard CRM SOQL only, segment creation, calculated insights, or STDM parquet session tracing.
When should I use this skill?
User runs sf data360 query, search-index, metadata, profile, or insight commands for Data Cloud objects.
What you get
Correct Data Cloud SQL or search command with describe-verified schema and readiness checks.
- FlexiPage metadata XML
- Validated Lightning page layouts
By the numbers
- Skill metadata version 1.0
- Covers 3 FlexiPage types: RecordPage, AppPage, and HomePage
Files
data360-query: 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 data360-query when the work involves:
sf data360 query *sf data360 search-index *sf data360 metadata *sf data360 profile *orsf data360 insight *inspection- understanding Data Cloud SQL results or query shape
Delegate elsewhere when the user is:
- writing standard CRM SOQL only → platform-soql-query
- designing segment or calculated insight assets → data360-segment
- analyzing STDM/session tracing/parquet telemetry → agentforce-observe
---
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 ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --json. - Use describe before guessing columns.
- Prefer
sqlv2or 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 ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --json
# optional query-plane probe, only with a real table name
node ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --describe-table MyDMO__dlm --json2. 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/null3. Use describe before guessing fields
sf data360 query describe -o <org> --table ssot__Individual__dlm 2>/dev/null4. 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/null5. Reuse curated search-index examples when creating indexes
Use the phase-owned examples instead of inventing JSON from scratch:
examples/search-indexes/vector-knowledge.jsonexamples/search-indexes/hybrid-structured.json
---
High-Signal Gotchas
- Data Cloud SQL is not SOQL.
- Table names should be double-quoted in SQL.
sqlv2is 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 describeis 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
- ../data360-orchestrate/assets/definitions/search-index.template.json
- ../data360-orchestrate/references/plugin-setup.md
- ../data360-orchestrate/references/feature-readiness.md
Credits & Acknowledgments
Primary contributor: Gnanasekaran Thoppae
This skill is part of the *-datacloud family. Shared attribution, upstream source mapping, and maintenance notes live in:
- ../data360-orchestrate/CREDITS.md
- ../data360-orchestrate/UPSTREAM.md
{
"label": "<INDEX_NAME>",
"developerName": "<INDEX_NAME>",
"description": "Hybrid search index on a structured Data Cloud DMO",
"sourceDmoDeveloperName": "<SOURCE_DMO>__dlm",
"chunkDmoName": "<INDEX_NAME> chunk",
"chunkDmoDeveloperName": "<INDEX_NAME>_chunk",
"vectorDmoName": "<INDEX_NAME> index",
"vectorDmoDeveloperName": "<INDEX_NAME>_index",
"searchType": "HYBRID",
"vectorEmbedding": {
"vectorEmbeddingRelatedFields": []
},
"rankingConfigurations": [],
"chunkingConfiguration": {
"fieldLevelConfigurations": [
{
"sourceDmoDeveloperName": "<SOURCE_DMO>__dlm",
"sourceDmoFieldDeveloperName": "<TEXT_FIELD>__c",
"config": {
"id": "passage_extraction",
"userValues": [
{ "id": "max_tokens", "value": "512" },
{ "id": "strip_html", "value": "true" }
]
}
}
]
},
"vectorEmbeddingConfiguration": {
"embeddingModel": {
"id": "e5_large_v2",
"userValues": [
{ "id": "dimension", "value": "1024" },
{ "id": "max_token_limit", "value": "512" }
]
},
"index": {
"id": "HNSW",
"userValues": []
},
"similarityMetric": "COSINE"
}
}
{
"label": "My_kav",
"developerName": "My_kav",
"sourceDmoDeveloperName": "ssot__KnowledgeArticleVersion__dlm",
"chunkDmoName": "My_kav chunk",
"chunkDmoDeveloperName": "My_kav_chunk",
"vectorDmoName": "My_kav index",
"vectorDmoDeveloperName": "My_kav_index",
"searchType": "VECTOR",
"vectorEmbedding": {
"vectorEmbeddingRelatedFields": []
},
"chunkingConfiguration": {
"fieldLevelConfigurations": [
{
"sourceDmoDeveloperName": "ssot__KnowledgeArticleVersion__dlm",
"sourceDmoFieldDeveloperName": "ssot__Name__c",
"config": {
"id": "passage_extraction",
"userValues": [
{ "id": "strip_html", "value": "true" },
{ "id": "max_tokens", "value": "512" }
]
}
}
]
},
"vectorEmbeddingConfiguration": {
"embeddingModel": {
"id": "e5_large_v2",
"userValues": [
{ "id": "dimension", "value": "1024" },
{ "id": "max_token_limit", "value": "512" }
]
},
"index": {
"id": "HNSW",
"userValues": []
},
"similarityMetric": "COSINE"
},
"rankingConfigurations": []
}
data360-query
Query and search workflows for Salesforce Data Cloud.
Use this skill for
- quick SQL counts
- paginated SQL (
sqlv2) - async query lifecycles
- table describe
- vector search
- hybrid search with optional prefilter
- search index inspection and lifecycle work
Example requests
"Run a Data Cloud SQL query against unified profiles"
"Describe this Data Cloud table before I write SQL"
"Help me troubleshoot vector search in Data Cloud"
"Run a hybrid search with a prefilter in Data Cloud"
"Create and inspect a search index"Common commands
sf data360 query sql -o myorg --sql 'SELECT COUNT(*) FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query describe -o myorg --table ssot__Individual__dlm 2>/dev/null
sf data360 search-index list -o myorg 2>/dev/null
sf data360 query vector -o myorg --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o myorg --index Knowledge_Index --query "reset password" --limit 5 2>/dev/nullExample payloads
- examples/search-indexes/vector-knowledge.json
- examples/search-indexes/hybrid-structured.json
References
- SKILL.md
- ../data360-orchestrate/assets/definitions/search-index.template.json
- CREDITS.md
Related skills
Forks & variants (1)
Generating Flexipage has 1 known copy in the catalog totaling 1.6k installs. They canonicalize to this original listing.
- forcedotcom - 1.6k installs
How it compares
Pick generating-flexipage over generic Salesforce metadata help when FlexiPage XML structure, component regions, or Lightning page deploy errors are the blocker.
FAQ
Is Data Cloud SQL the same as SOQL?
No. Data Cloud SQL is separate; delegate standard CRM SOQL to platform-soql-query.
When use sqlv2 or async?
sqlv2 suits medium sets; async-create is preferable for large result exports.
When run describe?
Before guessing columns on a known DMO or DLO table after broader readiness passes.
Is Generating Flexipage safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.