sf-datacloud-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:

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

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

3. Inspect schema before mapping

4. Create or review mappings intentionally

5. Run IR only after mappings are trustworthy

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

References

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

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

3. Inspect schema before mapping

4. Create or review mappings intentionally

5. Run IR only after mappings are trustworthy

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.

sf-datacloud-harmonize

Documentation

Documentation

sf-datacloud-harmonize: Data Cloud Harmonize Phase

When This Skill Owns the Task

Required Context to Gather First

Core Operating Rules

Recommended Workflow

1. Classify readiness for harmonize work

2. Inspect the catalog

3. Inspect schema before mapping

4. Create or review mappings intentionally

5. Run IR only after mappings are trustworthy

High-Signal Gotchas

Output Format

References

Documentation

sf-datacloud-harmonize

Documentation

sf-datacloud-harmonize: Data Cloud Harmonize Phase

When This Skill Owns the Task

Required Context to Gather First

Core Operating Rules

Recommended Workflow

1. Classify readiness for harmonize work

2. Inspect the catalog

3. Inspect schema before mapping

4. Create or review mappings intentionally

5. Run IR only after mappings are trustworthy

High-Signal Gotchas

Output Format

References