MCPInstall

sf-datacloud-harmonize

by jaganproDevOps & Cloud

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).

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-harmonize
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads sf-datacloud-harmonize automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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 --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
  • ../sf-datacloud/assets/definitions/dmo.template.json
  • ../sf-datacloud/assets/definitions/mapping.template.json
  • ../sf-datacloud/assets/definitions/relationship.template.json
  • ../sf-datacloud/assets/definitions/identity-resolution.template.json
  • ../sf-datacloud/assets/definitions/data-graph.template.json
  • ../sf-datacloud/references/feature-readiness.md

FAQ

What does the sf-datacloud-harmonize skill do?

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).

How do I install sf-datacloud-harmonize?

Run npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-harmonize in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/sf-datacloud-harmonize/ (personal) or .claude/skills/sf-datacloud-harmonize/ (project).

Which AI agents can use sf-datacloud-harmonize?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is sf-datacloud-harmonize safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains sf-datacloud-harmonize?

It is published by jaganpro in jaganpro/sf-skills. It has 973 recorded installs.

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