Generating List View

Name: Generating List View
Author: forcedotcom

forcedotcom/sf-skills

2.4k installs
763 repo stars
Updated July 24, 2026
forcedotcom/sf-skills

data360-query is a Salesforce skill for Data Cloud SQL, async queries, vector search, and metadata describe via sf data360 CLI.

About

data360-query owns the Salesforce Data Cloud retrieve phase for query, search, and metadata introspection using the external sf data360 CLI plugin on Data Cloud enabled orgs. It covers sync SQL, paginated sqlv2, async query workflows, table describe, vector search, hybrid search, and search index operations. Core rules treat Data Cloud SQL as distinct from CRM SOQL, run diagnose-org readiness with --phase retrieve, describe tables before guessing columns, and prefer sqlv2 or async flows for larger result sets. Vector and hybrid search require healthy search index lifecycle with list and prefilter constraints documented in curated examples. Delegation routes standard SOQL to platform-soql-query, segments to data360-segment, and STDM tracing to agentforce-observe. Recommended workflow classifies org readiness, chooses the smallest correct query shape, describes fields, then runs vector or hybrid queries only when indexes exist. High-signal gotchas include double-quoted table names, async preference for large exports, and HNSW index parameter defaults. Output format reports retrieve task type, org alias, commands, verification, and next steps.

Data Cloud SQL distinct from standard CRM SOQL.
diagnose-org retrieve readiness before query surfaces.
sql, sqlv2, async-create, and describe command patterns.
Vector and hybrid search with index lifecycle checks.
Curated search-index JSON examples for index creation.

Generating List View by the numbers

2,424 all-time installs (skills.sh)
+7 installs in the week ending Jul 28, 2026 (Skillselion tracking)
Ranked #41 of 2,066 Data Science & ML 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

generating-list-view capabilities & compatibility

Capabilities: retrieve phase org readiness diagnosis · sync, sqlv2, and async data cloud sql execution · table describe before column guessing · vector and hybrid search index operations · search index curated example reuse · delegation rules to sibling sf skills families
Works with: salesforce
Use cases: data analysis · research
Pricing: Free

From the docs

What generating-list-view says it does

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

SKILL.md

Use describe before guessing columns.

SKILL.md

async query is preferable for large results.

SKILL.md

npx skills add https://github.com/forcedotcom/sf-skills --skill generating-list-view

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Installs	2.4k
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, and inspect schema without treating SQL as SOQL?

Run Data Cloud SQL, async queries, vector search, and metadata describe via sf data360 CLI retrieve workflows.

Who is it for?

Salesforce developers running Data Cloud SQL, hybrid search, or search-index lifecycle tasks.

Skip if: Skip for standard CRM SOQL only, segment design, or STDM session tracing workflows.

When should I use this skill?

User runs sf data360 query, search-index, metadata, or Data Cloud SQL and vector search tasks.

What you get

Readiness-checked retrieve commands with correct SQL shape, describe output, and verified search index usage.

ListView XML metadata
Filter criteria definitions
Column configuration

By the numbers

Skill metadata version is 1.0

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)

Generating List View has 1 known copy in the catalog totaling 1.5k installs. They canonicalize to this original listing.

forcedotcom - 1.5k installs

How it compares

Use generating-list-view for ListView XML metadata; use page layout or report skills when the UI need is record forms or analytics instead of filtered object lists.

FAQ

Data Cloud SQL or SOQL?

Data Cloud SQL is its own language; delegate standard CRM SOQL to platform-soql-query.

sql or sqlv2 for medium sets?

Prefer sqlv2 over ad hoc OFFSET paging for medium result sets.

When use hybrid prefilter?

Only on fields configured as prefilter-capable when the search index was created.

Is Generating List View safe to install?

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

Data Science & MLanalyticsdatabases

About

Generating List View by the numbers

generating-list-view capabilities & compatibility

What generating-list-view says it does

Add your badge

How do I query Data Cloud tables, run vector search, and inspect schema without treating SQL as 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

Data Cloud SQL or SOQL?

sql or sqlv2 for medium sets?

When use hybrid prefilter?

Is Generating List View safe to install?

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