
Harmonizing Datacloud
- 520 installs
- 787 repo stars
- Updated August 5, 2026
- forcedotcom/afv-library
This is a copy of harmonizing-datacloud by forcedotcom - installs and ranking accrue to the original listing.
harmonizing-datacloud is an agent skill that provides context-aware guidance for Salesforce Data Cloud Harmonize tasks involving DMOs, mappings, identity resolution, and unified profiles for developers integrating custom
About
harmonizing-datacloud is a skill from forcedotcom/afv-library for the Salesforce Data Cloud Harmonize phase. It assists developers working with Data Model Objects (DMOs), field mappings, relationships, identity resolution rules, unified profiles, data graphs, and universal IDs. The skill requires an external community sf data360 CLI plugin and a Data Cloud-enabled Salesforce org. Developers reach for harmonizing-datacloud when harmonizing customer data—not when tasks are limited to streams/DLOs, segments, insights, retrieval search, or STDM session tracing covered by sibling skills. It targets build-stage integration work for enterprise data unification on Salesforce Data Cloud.
- Triggers exclusively on DMO, mapping, relationship, identity resolution, unified profile, data graph, and universal ID t
- Delegates streams/DLO work to preparing-datacloud and segment work to segmenting-datacloud
- Requires sf data360 CLI plugin and a Data Cloud-enabled org
- Provides specialized commands for sf data360 dmo *, identity-resolution *, data-graph *, profile *, and universal-id loo
- Maintains clean separation of concerns across the five Data Cloud skill set
Harmonizing Datacloud by the numbers
- 520 all-time installs (skills.sh)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 520 |
|---|---|
| repo stars | ★ 787 |
| Last updated | August 5, 2026 |
| Repository | forcedotcom/afv-library ↗ |
How do you harmonize Salesforce Data Cloud DMO mappings?
Get precise, context-aware assistance when working with Salesforce Data Cloud harmonization tasks involving DMOs, mappings, identity resolution, and unified profi
Who is it for?
Salesforce developers harmonizing Data Cloud DMOs, mappings, and identity resolution in a Data Cloud-enabled org with the sf data360 CLI.
Skip if: Tasks limited to Data Cloud streams, DLO preparation, segmentation, insights, or Agentforce session tracing covered by other afv-library skills.
When should I use this skill?
The user works with Salesforce DMOs, mappings, relationships, identity resolution, unified profiles, data graphs, or universal IDs in Data Cloud.
What you get
DMO mapping configs, identity resolution rules, unified profile definitions, and data graph relationship documentation.
- DMO mapping configurations
- Identity resolution setup
- Unified profile definitions
Files
harmonizing-datacloud: Data Cloud Harmonize Phase
Use this skill when the user needs schema harmonization and unification work: DMOs, field mappings, relationships, identity resolution, unified profiles, data graphs, or universal ID lookup.
When This Skill Owns the Task
Use harmonizing-datacloud when the work involves:
sf data360 dmo *sf data360 identity-resolution *sf data360 data-graph *sf data360 profile *sf data360 universal-id lookup
Delegate elsewhere when the user is:
- still ingesting streams or building DLOs → preparing-datacloud
- working on segment logic or calculated insights → segmenting-datacloud
- running SQL, describe, or search-index workflows → retrieving-datacloud
---
Required Context to Gather First
Ask for or infer:
- source DLO and target DMO names
- whether the task is schema creation, mapping, IR, or graph-related
- target org alias
- whether a ruleset already exists
- the user’s desired unified entity model
---
Core Operating Rules
- Inspect DMO schema before creating mappings.
- Run the shared readiness classifier before mutating harmonization assets:
node ../orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase harmonize --json. - Prefer
dmo list --allwhen browsing the catalog, but use first-pagedmo listfor fast readiness checks. - Use
query describeordmo get --jsoninstead of inventing unsupported describe flows. - Treat identity resolution runs as asynchronous and verify results after execution.
- Keep unified-profile work separate from STDM/session tracing work.
---
Recommended Workflow
1. Classify readiness for harmonize work
node ../orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase harmonize --json2. Inspect the catalog
sf data360 dmo list --all -o <org> 2>/dev/null
sf data360 identity-resolution list -o <org> 2>/dev/null3. Inspect schema before mapping
sf data360 query describe -o <org> --table ssot__Individual__dlm 2>/dev/null
sf data360 dmo get -o <org> --name ssot__Individual__dlm --json 2>/dev/null4. Create or review mappings intentionally
sf data360 dmo mapping-list -o <org> --source Contact_Home__dll --target ssot__Individual__dlm 2>/dev/null
sf data360 dmo map-to-canonical -o <org> --dlo Contact_Home__dll --dmo ssot__Individual__dlm --dry-run 2>/dev/null5. Run IR only after mappings are trustworthy
sf data360 identity-resolution create -o <org> -f ir-ruleset.json 2>/dev/null
sf data360 identity-resolution run -o <org> --name Main 2>/dev/null---
High-Signal Gotchas
dmo listshould usually use--all.- Use
query describeordmo get --json; there is nodmo describecommand. - Mapping and related commands can be sensitive to API-version differences.
- Unified DMO names are ruleset-specific rather than generic.
- Data graph definitions are sensitive to field selection and relationship shape.
- If
dmo listworks butidentity-resolution listis gated, treat that as a phase-specific gap rather than a full Data Cloud outage.
---
Output Format
Harmonize task: <dmo / mapping / relationship / ir / data-graph>
Source/target: <dlo → dmo or ruleset/graph names>
Target org: <alias>
Artifacts: <json files / commands>
Verification: <passed / partial / blocked>
Next step: <segment / retrieve / follow-up>---
References
- README.md
- ../orchestrating-datacloud/assets/definitions/dmo.template.json
- ../orchestrating-datacloud/assets/definitions/mapping.template.json
- ../orchestrating-datacloud/assets/definitions/relationship.template.json
- ../orchestrating-datacloud/assets/definitions/identity-resolution.template.json
- ../orchestrating-datacloud/assets/definitions/data-graph.template.json
- ../orchestrating-datacloud/references/feature-readiness.md
Credits & Acknowledgments
This skill is part of the *-datacloud family of skills covering the Data Cloud lifecycle: ingestion, harmonization, segmentation, and retrieval.
harmonizing-datacloud
Schema harmonization and unification workflows for Salesforce Data Cloud.
Use this skill for
- DMOs (Data Model Objects)
- Field mappings
- Relationships
- Identity resolution
- Unified profiles
- Data graphs
- Universal ID lookup
Example requests
"Map this DLO to ssot__Individual__dlm"
"Help me create an identity resolution ruleset"
"Why are unified profiles not appearing?"
"Show me the DMO fields before I create mappings"Common commands
sf data360 dmo list --all -o myorg 2>/dev/null
sf data360 query describe -o myorg --table ssot__Individual__dlm 2>/dev/null
sf data360 dmo mapping-list -o myorg --source Contact_Home__dll --target ssot__Individual__dlm 2>/dev/null
sf data360 identity-resolution list -o myorg 2>/dev/nullRelated skills
FAQ
What does harmonizing-datacloud help with?
harmonizing-datacloud helps with Salesforce Data Cloud Harmonize tasks including DMOs, field mappings, relationships, identity resolution, unified profiles, data graphs, and universal IDs. The skill delivers context-aware guidance for developers integrating and unifying customer
What prerequisites does harmonizing-datacloud require?
harmonizing-datacloud requires an external community sf data360 CLI plugin and a Salesforce org with Data Cloud enabled. Without those prerequisites, developers should complete org setup and CLI installation before harmonization work.