Sf Datacloud Harmonize
This handles the schema harmonization and unification layer of Salesforce Data Cloud: building Data Model Objects, mapping fields from Data Lake Objects to canonical models, configuring identity resolution rulesets, and defining data graphs for unified profiles. It's the middle phase between ingestion and segmentation. The skill knows to run readiness checks before mutations, inspect schemas before creating mappings, and treat identity resolution as async. One thing worth noting is it explicitly routes you elsewhere if you're still working on streams or already building segments, which keeps the workflow boundaries clean. Built around the community sf data360 CLI plugin, so you'll need that installed and a Data Cloud enabled org.
- skills.sh installs
- 976
- GitHub stars
- 422
- last updated
- Jul 14, 2026
Install
$ npx -y skills add jaganpro/sf-skills --skill sf-datacloud-harmonize --agent claude-codeInstalls into .claude/skills of the current project.
Files
sf-datacloud-harmonize: 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 sf-datacloud-harmonize 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 → sf-datacloud-prepare
- working on segment logic or calculated insights → sf-datacloud-segment
- running SQL, describe, or search-index workflows → sf-datacloud-retrieve
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
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- Repository
- github.com/jaganpro/sf-skills
- First seen
- May 16, 2026
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