
Generating Custom Object
- 1.6k installs
- 763 repo stars
- Updated July 24, 2026
- forcedotcom/afv-library
This is a copy of generating-custom-object by forcedotcom - installs and ranking accrue to the original listing.
generating-custom-object is a Salesforce agent skill that generates and validates Custom Object metadata XML—including sharing models, name fields, and validation rules—so deployments succeed without errors.
About
generating-custom-object is version 1.0 skill from forcedotcom/afv-library for creating, generating, and validating Salesforce Custom Object metadata. Agents produce accurate .object XML covering sharing models, name fields, Master-Detail relationships, and object-level validation rules that deploy through Metadata API or SFDX without common deployment failures. The skill triggers on phrases like "create a custom object," ".object files," or troubleshooting sharing-model and Master-Detail errors. Developers reach for generating-custom-object when bootstrapping new Salesforce data models, fixing object deployment errors, or scaffolding objects before Apex triggers and Lightning pages.
- Generates valid .object-meta.xml files for any custom object
- Enforces sharing models, Master-Detail relationships, and name fields
- Validates security settings and object capabilities before output
- Troubleshoots deployment errors related to custom objects
- Always triggered on mentions of custom objects or object metadata
Generating Custom Object by the numbers
- 1,556 all-time installs (skills.sh)
- +2 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 | 1.6k |
|---|---|
| repo stars | ★ 763 |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 24, 2026 |
| Repository | forcedotcom/afv-library ↗ |
How do you generate Salesforce Custom Object metadata XML?
Generate accurate Salesforce Custom Object metadata XML that deploys without errors.
Who is it for?
Salesforce developers or integration engineers authoring new custom objects who need error-free metadata XML before Apex or Flow work.
Skip if: Teams only editing existing Apex or LWC without any custom object schema changes or metadata deployment needs.
When should I use this skill?
The user mentions custom objects, .object files, object metadata, sharing models, Master-Detail relationships, or object deployment errors.
What you get
Valid .object metadata XML files with sharing model, fields, relationships, and validation rules ready for SFDX or Metadata API deploy.
- .object metadata XML
- sharing model configuration
- validation rule definitions
By the numbers
- Skill metadata version 1.0 in forcedotcom/afv-library manifest
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
How it compares
Use for Custom Object metadata XML; use separate Salesforce skills for Apex classes, Flows, or LWC when schema is already deployed.
FAQ
What does generating-custom-object produce?
generating-custom-object produces Salesforce Custom Object metadata as .object XML, including sharing models, name fields, relationships, and validation rules formatted for Metadata API or SFDX deployment at version 1.0.
When should I use generating-custom-object?
Use generating-custom-object when creating new Salesforce custom objects, generating .object files, or fixing deployment errors around sharing models and Master-Detail relationships before Apex or UI development.
Is Generating Custom Object safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.