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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)
npx skills add https://github.com/forcedotcom/afv-library --skill harmonizing-datacloud

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Listed on Skillselion
Installs520
repo stars787
Last updatedAugust 5, 2026
Repositoryforcedotcom/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

SKILL.mdMarkdownGitHub ↗

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

  • 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

Related 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.

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