
Deploying Ui Bundle
- 1.5k installs
- 763 repo stars
- Updated July 24, 2026
- forcedotcom/afv-library
This is a copy of deploying-ui-bundle by forcedotcom - installs and ranking accrue to the original listing.
deploying-ui-bundle is a Salesforce deployment agent skill that runs the ordered push sequence for UI bundle apps—including org auth, build, metadata deploy, permission sets, data import, and GraphQL codegen—for develope
About
deploying-ui-bundle is a forcedotcom/afv-library agent skill (metadata version 1.0) that enforces the correct order of operations when shipping a UI bundle app to a Salesforce org. It activates when uiBundles/*/src/, *.uibundle-meta.xml, or sfdx-project.json exist and the task involves deploying, pushing, or post-deploy setup. The workflow spans org authentication, pre-deploy build, metadata deployment, permission set assignment, data import, GraphQL schema fetch, and codegen. Developers reach for deploying-ui-bundle when a UI bundle push fails from skipped steps or when onboarding a fresh org requires the full post-deploy chain. Output is a deployed org with permissions, imported data, and generated client code aligned to the fetched Graphically.
- Activates automatically when uiBundles/*/src/ or sfdx-project.json is present and the task mentions deploy, push or org
- Orchestrates the full canonical sequence: org authentication, pre-deploy build, metadata deployment, permission set assi
- Checks for manifest/package.xml and falls back to deploying all metadata when absent
- Ensures dist/ is built before any UI bundle metadata is pushed
- Prevents schema fetch until after metadata deployment completes
Deploying Ui Bundle by the numbers
- 1,491 all-time installs (skills.sh)
- +1 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| Installs | 1.5k |
|---|---|
| repo stars | ★ 763 |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 24, 2026 |
| Repository | forcedotcom/afv-library ↗ |
How do you deploy a Salesforce UI bundle?
Reliably push Salesforce UI bundles and all related metadata to an org without missing any step in the deployment sequence.
Who is it for?
Salesforce developers shipping uiBundles apps who need the complete ordered deployment and post-deploy setup without missing CLI steps.
Skip if: Skip deploying-ui-bundle for non-UI-bundle Salesforce metadata changes or scratch-org creation tasks that do not involve uiBundles/*/src/ directories.
When should I use this skill?
Project contains uiBundles/*/src/ or sfdx-project.json and user mentions deploying, pushing to org, or post-deploy setup.
What you get
Deployed UI bundle metadata, assigned permission sets, imported data, and generated GraphQL client code
- Deployed metadata
- Generated GraphQL client code
By the numbers
- Metadata version 1.0 in forcedotcom/afv-library skill manifest
- Covers 7 deployment phases from org auth through GraphQL codegen
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
FAQ
What files trigger deploying-ui-bundle?
deploying-ui-bundle activates when the project has uiBundles/*/src/, *.uibundle-meta.xml, or sfdx-project.json and the user mentions deploying, pushing to an org, or post-deploy tasks.
What steps does deploying-ui-bundle include after metadata push?
deploying-ui-bundle covers permission set assignment, data import, GraphQL schema fetch, and codegen after metadata deployment. Skipping steps in this order commonly causes incomplete org setup.
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.