harmonizing-datacloud | SkillBundle

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SKILL.md

Salesforce Data Cloud Harmonize phase. Use this skill when the user works with DMOs, mappings, relationships, identity resolution, unified profiles, data graphs, or universal IDs. 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 preparing-datacloud), segments/insights (use segmenting-datacloud), retrieval/search (use retrieving-datacloud), or STDM/session tracing (use observing-agentforce).

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npx skills add forcedotcom/sf-skills --skill harmonizing-datacloud

Documentation

SKILL.md

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 --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 ../orchestrating-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