harmonizing-datacloud
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).
What this skill does
# 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](../preparing-datacloud/SKILL.md) - working on segment logic or calculated insights → [segmenting-datacloud](../segmenting-datacloud/SKILL.md) - running SQL, describe, or search-index workflows → [retrieving-datacloud](../retrieving-datacloud/SKILL.md) --- ## 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/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 ```bash node ~/.claude/skills/orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase harmonize --json ``` ### 2. Inspect the catalog ```bash 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 ```bash 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 ```bash 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 ```bash 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 ```text 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](README.md) - [../orchestrating-datacloud/assets/definitions/dmo.template.json](../orchestrating-datacloud/assets/definitions/dmo.template.json) - [../orchestrating-datacloud/assets/definitions/mapping.template.json](../orchestrating-datacloud/assets/definitions/mapping.template.json) - [../orchestrating-datacloud/assets/definitions/relationship.template.json](../orchestrating-datacloud/assets/definitions/relationship.template.json) - [../orchestrating-datacloud/assets/definitions/identity-resolution.template.json](../orchestrating-datacloud/assets/definitions/identity-resolution.template.json) - [../orchestrating-datacloud/assets/definitions/data-graph.template.json](../orchestrating-datacloud/assets/definitions/data-graph.template.json) - [../orchestrating-datacloud/references/feature-readiness.md](../orchestrating-datacloud/references/feature-readiness.md)
Related in Cloud & DevOps
appbuilder-action-scaffolder
IncludedCreate, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
orchestrating-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. Use this skill when the user needs a multi-step Data Cloud pipeline, cross-phase troubleshooting, or data space and data kit management. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase sf data360 workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching phase-specific skill), the task is STDM/session tracing/parquet telemetry (use observing-agentforce), standard CRM SOQL (use querying-soql), or Apex implementation (use generating-apex).
github-project-automation
IncludedAutomate GitHub repository setup with CI/CD workflows, issue templates, Dependabot, and CodeQL security scanning. Includes 12 production-tested workflows and prevents 18 errors: YAML syntax, action pinning, and configuration. Use when: setting up GitHub Actions CI/CD, creating issue/PR templates, enabling Dependabot or CodeQL scanning, deploying to Cloudflare Workers, implementing matrix testing, or troubleshooting YAML indentation, action version pinning, secrets syntax, runner versions, or CodeQL configuration. Keywords: github actions, github workflow, ci/cd, issue templates, pull request templates, dependabot, codeql, security scanning, yaml syntax, github automation, repository setup, workflow templates, github actions matrix, secrets management, branch protection, codeowners, github projects, continuous integration, continuous deployment, workflow syntax error, action version pinning, runner version, github context, yaml indentation error
sf-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
fabric-cli
IncludedUse this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
lark
IncludedLark/Feishu CLI skills: lark-cli operations for docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, event. Use when the user needs to operate Lark/Feishu resources via lark-cli, send messages, manage documents, spreadsheets, calendars, tasks, OKRs, deploy web pages, or any Feishu/Lark workspace operations.