| name | sf-datacloud-harmonize |
| description | Salesforce Data Cloud Harmonize phase. TRIGGER when: user works with DMOs, mappings, relationships, identity resolution, unified profiles, data graphs, or universal IDs. DO NOT TRIGGER when: the task is only about streams/DLOs (use sf-datacloud-prepare), segments/insights (use sf-datacloud-segment), retrieval/search (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
|
| license | MIT |
| compatibility | Requires an external community sf data360 CLI plugin and a Data Cloud-enabled org |
| metadata | {"version":"1.0.0","author":"Gnanasekaran Thoppae","phase":"Harmonize"} |
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:
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 ~/.claude/skills/sf-datacloud/scripts/diagnose-org.mjs -o <org> --phase harmonize --json.
- Prefer
dmo list --all when browsing the catalog, but use first-page dmo list for fast readiness checks.
- Use
query describe or dmo get --json instead 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 ~/.claude/skills/sf-datacloud/scripts/diagnose-org.mjs -o <org> --phase harmonize --json
2. Inspect the catalog
sf data360 dmo list --all -o <org> 2>/dev/null
sf data360 identity-resolution list -o <org> 2>/dev/null
3. 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/null
4. 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/null
5. 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 list should usually use --all.- Use
query describe or dmo get --json; there is no dmo describe command.
- 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 list works but identity-resolution list is 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
