
Generating Custom Field
- 2.5k installs
- 763 repo stars
- Updated July 24, 2026
- forcedotcom/sf-skills
generating-custom-field is a Salesforce skill that emits validated CustomField metadata XML with relationship, formula, and roll-up constraints.
About
Generating Custom Field is a Salesforce metadata skill focused on deployment-safe CustomField XML with emphasis on high-failure field types. Every field requires fullName derived from label, label, description stating business purpose, and inlineHelpText with actionable guidance beyond the label. Precision and scale rules cap totals at eighteen digits with scale less than or equal to precision, and TextArea types need length two fifty five per API quirks. Roll-up Summary and Master-Detail sections document format errors, attribute restrictions, and lookup filter constraints called out as critical focus areas. External ID configuration triggers on integration or import keywords for Text, Number, and Email types. Agents verify universal mandatory attributes and type-specific requirements before output. Use it when creating fields, relationship lookups, formula or picklist metadata, or troubleshooting field deployment errors especially for roll-ups and Master-Detail relationships.
- Universal mandatory fullName, label, description, and inlineHelpText on every field.
- Precision, scale, and TextArea length rules to prevent Metadata API failures.
- Critical focus on Roll-up Summary format and Master-Detail attribute restrictions.
- External ID configuration for integration and import scenarios.
- Lookup and Master-Detail relationship metadata with deleteConstraint guidance.
Generating Custom Field by the numbers
- 2,526 all-time installs (skills.sh)
- +7 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Ranked #205 of 4,386 Backend & APIs skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
generating-custom-field capabilities & compatibility
- Capabilities
- customfield universal mandatory attribute enforc · precision, scale, and textarea length validation · roll up summary and master detail constraint che · lookup relationship and deleteconstraint configu · external id and formula field metadata generatio
- Works with
- salesforce
- Use cases
- api development · database
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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 generate Salesforce field metadata that survives deployment, especially for roll-ups and Master-Detail?
Generate and validate Salesforce Custom Field metadata XML including relationships, formulas, and roll-up summary constraints.
Who is it for?
Salesforce developers creating or troubleshooting custom field and relationship metadata.
Skip if: Skip for custom object shell creation only; use generating-custom-object first.
When should I use this skill?
User creates custom fields, mentions field types, roll-up summary, Master-Detail, lookup filters, or field deployment errors.
What you get
Deployment-ready field XML with mandatory descriptions, correct precision, and relationship attributes.
- CustomField metadata XML
By the numbers
- Skill metadata version 1.0
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 Custom Field has 1 known copy in the catalog totaling 1.6k installs. They canonicalize to this original listing.
- forcedotcom - 1.6k installs
How it compares
Use generating-custom-field for individual fields; use generating-custom-object when defining a new Salesforce object shell.
FAQ
What attributes are mandatory on every field?
fullName, label, description, and inlineHelpText with actionable guidance.
What are the precision rules?
precision must be at most 18 and scale must be less than or equal to precision.
When should externalId be true?
When integration, import, or unique external system ID requirements are mentioned.
Is Generating Custom Field safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.