Deploying Ui Bundle

Name: Deploying Ui Bundle
Author: forcedotcom

forcedotcom/sf-skills

2.2k installs
763 repo stars
Updated July 24, 2026
forcedotcom/sf-skills

data360-query retrieves Data Cloud data via sf data360 SQL, async, vector, and search-index CLI commands.

About

The fetched SKILL.md for this listing documents data360-query, the Salesforce Data Cloud retrieve phase skill. It covers sync and paginated SQL, async query workflows, table describe, vector and hybrid search, and search-index lifecycle via sf data360 commands. Data Cloud SQL is distinct from CRM SOQL and requires double-quoted table names such as ssot__Individual__dlm. Readiness classification runs diagnose-org.mjs with --phase retrieve before relying on query surfaces. Workflows choose sql for counts, sqlv2 for medium sets, and async-create for large exports, always describing tables before guessing columns. Vector and hybrid search require healthy search indexes listed via search-index list, with hybrid prefilter fields limited to index configuration. Curated examples vector-knowledge.json and hybrid-structured.json should seed index JSON instead of inventing schemas. Delegation routes standard SOQL to platform-soql-query, segment design to data360-segment, and STDM tracing to agentforce-observe. Output format summarizes retrieve task type, org alias, commands run, verification, and next harmonize or segment steps.

Owns sf data360 query, search-index, and metadata retrieve commands.
Treats Data Cloud SQL as separate from standard CRM SOQL.
Runs diagnose-org.mjs --phase retrieve before query work.
Prefers sqlv2 or async flows over ad hoc OFFSET paging.
Vector and hybrid search require existing healthy search indexes.

Deploying Ui Bundle by the numbers

2,210 all-time installs (skills.sh)
+7 installs in the week ending Jul 28, 2026 (Skillselion tracking)
Ranked #51 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)

At a glance

deploying-ui-bundle capabilities & compatibility

Capabilities: readiness classification for retrieve phase · sql, sqlv2, and async query workflows · table describe before field selection · vector and hybrid search with index checks · curated search index example reuse
Works with: salesforce
Use cases: data analysis · database · research
Runs: Local or remote
Pricing: Paid

From the docs

What deploying-ui-bundle says it does

Treat Data Cloud SQL as its own query language, not SOQL.

SKILL.md

Use describe before guessing columns.

SKILL.md

npx skills add https://github.com/forcedotcom/sf-skills --skill deploying-ui-bundle

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Installs	2.2k
repo stars	★ 763
Security audit	3 / 3 scanners passed
Last updated	July 24, 2026
Repository	forcedotcom/sf-skills ↗

How do I query or search Salesforce Data Cloud tables without treating SQL like SOQL?

Run Salesforce Data Cloud SQL, async queries, vector search, and search-index operations via sf data360 CLI.

Who is it for?

Salesforce teams running Data Cloud SQL, vector search, or index operations.

Skip if: Skip for standard CRM SOQL-only tasks or segment design without retrieve queries.

When should I use this skill?

User runs sf data360 query, vector search, or search-index workflows on Data Cloud.

What you get

Verified retrieve commands with describe-first schema checks and correct sql versus async path choice.

Deployed UI bundle metadata
Permission set assignments
GraphQL codegen output

By the numbers

Skill metadata version 1.0
Covers 7 deployment steps: org auth, build, metadata deploy, permissions, data import, GraphQL fetch, codegen

Files

SKILL.mdMarkdownGitHub ↗

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 * or sf 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 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 ../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 --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
../data360-orchestrate/assets/definitions/search-index.template.json
../data360-orchestrate/references/plugin-setup.md
../data360-orchestrate/references/feature-readiness.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/null

Example 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

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Forks & variants (1)

Deploying Ui Bundle has 1 known copy in the catalog totaling 1.5k installs. They canonicalize to this original listing.

forcedotcom - 1.5k installs

How it compares

Pick deploying-ui-bundle over generic SFDX deploy skills when the target is a UI bundle with mandatory post-deploy permission, data, and GraphQL steps.

FAQ

Is Data Cloud SQL the same as SOQL?

No. Use sf data360 query with double-quoted DMO table names, not platform SOQL.

What should I run before SELECT?

Run diagnose-org retrieve readiness and query describe on the target table.

When use async-create?

Prefer async query flows for large result sets instead of paging medium exports manually.

Is Deploying Ui Bundle safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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About

Deploying Ui Bundle by the numbers

deploying-ui-bundle capabilities & compatibility

What deploying-ui-bundle says it does

Add your badge

How do I query or search Salesforce Data Cloud tables without treating SQL like SOQL?

Who is it for?

When should I use this skill?

What you get

By the numbers

Files

data360-query: Data Cloud Retrieve Phase

When This Skill Owns the Task

Required Context to Gather First

Core Operating Rules

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

High-Signal Gotchas

Output Format

References

Credits & Acknowledgments

data360-query

Use this skill for

Example requests

Common commands

Example payloads

References

Related skills

Forks & variants (1)

How it compares

FAQ

Is Data Cloud SQL the same as SOQL?

What should I run before SELECT?

When use async-create?

Is Deploying Ui Bundle safe to install?

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