Salesforce 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).
--- name: orchestrating-datacloud description: "Salesforce 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)." license: MIT compatibility: "Requires an external community sf data360 CLI plugin and a Data Cloud-enabled org" metadata: version: "1.0" --- # orchestrating-datacloud: Salesforce Data Cloud Orchestrator Use this skill when the user needs **product-level Data Cloud workflow guidance** rather than a single isolated command family: pipeline setup, cross-phase troubleshooting, data spaces, data kits, or deciding whether a task belongs in Connect, Prepare, Harmonize, Segment, Act, or Retrieve. This skill intentionally follows sf-skills house style while using the external `sf data360` command surface as the runtime. The plugin is **not vendored into this repo**. --- ## When This Skill Owns the Task Use `orchestrating-datacloud` when the work involves: - multi-phase Data Cloud setup or remediation - data spaces (`sf data360 data-space *`) - data kits (`sf data360 data-kit *`) - health checks (`sf data360 doctor`) - CRM-to-unified-profile pipeline design - deciding how to move from ingestion → harmonization → segmentation → activation - cross-phase troubleshooting where the root cause is not yet clear Delegate to a phase-specific skill when the user is focused on one area: | Phase | Use this skill | Typical scope | |---|---|---| | Connect | [connecting-datacloud](../connecting-datacloud/SKILL.md) | connections, connectors, source discovery | | Prepare | [preparing-datacloud](../preparing-datacloud/SKILL.md) | data streams, DLOs, transforms, DocAI | | Harmonize | [harmonizing-datacloud](../harmonizing-datacloud/SKILL.md) | DMOs, mappings, identity resolution, data graphs | | Segment | [segmenting-datacloud](../segmenting-datacloud/SKILL.md) | segments, calculated insights | | Act | [activating-datacloud](../activating-datacloud/SKILL.md) | activations, activation targets, data actions | | Retrieve | [retrieving-datacloud](../retrieving-datacloud/SKILL.md) | SQL, search indexes, vector search, async query | Delegate outside the family when the user is: - extracting Session Tracing / STDM telemetry → [observing-agentforce](../observing-agentforce/SKILL.md) - writing CRM SOQL only → [querying-soql](../querying-soql/SKILL.md) - loading CRM source data → [handling-sf-data](../handling-sf-data/SKILL.md) - creating missing CRM schema → [generating-custom-object](../generating-custom-object/SKILL.md) or [generating-custom-field](../generating-custom-field/SKILL.md) - implementing downstream Apex or Flow logic → [generating-apex](../generating-apex/SKILL.md), [generating-flow](../generating-flow/SKILL.md) --- ## Required Context to Gather First Ask for or infer: - target org alias - whether the plugin is already installed and linked - whether the user wants design guidance, read-only inspection, or live mutation - data sources involved: CRM objects, external databases, file ingestion, knowledge, etc. - desired outcome: unified profiles, segments, activations, vector search, analytics, or troubleshooting - whether the user is working in the default data space or a custom one - whether the org has already been classified with `scripts/diagnose-org.mjs` - which command family is failing today, if any If plugin availability or org readiness is uncertain, start with: - [references/plugin-setup.md](references/plugin-setup.md) - [references/feature-readiness.md](references/feature-readiness.md) - `scripts/verify-plugin.sh` - `scripts/diagnose-org.mjs` - `scripts/bootstrap-plugin.sh` --- ## Core Operating Rules - Use the external `sf data360` plugin runtime; do **not** reimplement or vendor the command layer. - Prefer the smallest phase-specific skill once the task is localized. - Run readiness classification before mutation-heavy work. Prefer `scripts/diagnose-org.mjs` over guessing from one failing command. - For `sf data360` commands, suppress linked-plugin warning noise with `2>/dev/null` unless the stderr output is needed for debugging. - Distinguish **Data Cloud SQL** from CRM SOQL. - Do **not** treat `sf data360 doctor` as a full-product readiness check; the current upstream command only checks the search-index surface. - Do **not** treat `query describe` as a universal tenant probe; only use it with a known DMO/DLO table after broader readiness is confirmed. - Preserve Data Cloud-specific API-version workarounds when they matter. - Prefer generic, reusable JSON definition files over org-specific workshop payloads. --- ## Recommended Workflow ### 1. Verify the runtime and auth Confirm: - `sf` is installed - the community Data Cloud plugin is linked - the target org is authenticated Recommended checks: ```bash sf data360 man sf org display -o <alias> bash ~/.claude/skills/orchestrating-datacloud/scripts/verify-plugin.sh <alias> ``` Treat `sf data360 doctor` as a broad health signal, not the sole gate. On partially provisioned orgs it can fail even when read-only command families like connectors, DMOs, or segments still work. ### 2. Classify readiness before changing anything Run the shared classifier first: ```bash node ~/.claude/skills/orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --json ``` Only use a query-plane probe after you know the table name is real: ```bash node ~/.claude/skills/orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase retrieve --describe-table MyDMO__dlm --json ``` Use the classifier to distinguish: - empty-but-enabled modules - feature-gated modules - query-plane issues - runtime/auth failures ### 3. Discover existing state with read-only commands Use targeted inspection after classification: ```bash sf data360 doctor -o <org> 2>/dev/null sf data360 data-space list -o <org> 2>/dev/null sf data360 data-stream list -o <org> 2>/dev/null sf data360 dmo list -o <org> 2>/dev/null sf data360 identity-resolution list -o <org> 2>/dev/null sf data360 segment list -o <org> 2>/dev/null sf data360 activation platforms -o <org> 2>/dev/null ``` ### 4. Localize the phase Route the task: - source/connector issue → Connect - ingestion/DLO/stream issue → Prepare - mapping/IR/unified profile issue → Harmonize - audience or insight issue → Segment - downstream push issue → Act - SQL/search/index issue → Retrieve ### 5. Choose deterministic artifacts when possible Prefer JSON definition files and repeatable scripts over one-off manual steps. Generic templates live in: - `assets/definitions/data-stream.template.json` - `assets/definitions/dmo.template.json` - `assets/definitions/mapping.template.json` - `assets/definitions/relationship.template.json` - `assets/definitions/identity-resolution.template.json` - `assets/definitions/data-graph.template.json` - `assets/definitions/calculated-insight.template.json` - `assets/definitions/segment.template.json` - `assets/definitions/activation-target.template.json` - `assets/definitions/activation.template.json` - `assets/definitions/data-action-target.template.json` - `assets/definitions/data-action.template.json` - `assets/definitions/search-index.template.json` ### 6. Verify after each phase Typical verification: - stream/DLO exists - DMO/mapping exists - identity resolution run completed - unified records or segment counts look correct - activation/search index status is healthy --- ## High-Signal Gotchas - `connection list` requires `--connector-type`. - `dmo list --all` is useful when you need the full catalog, but first-page `dmo list` is often enough for readiness checks and much faster. - Segment creation may need `--api-version 64.0`. - `segment members` returns opaque IDs; use SQL joins for human-readable details. - `sf data360 doctor` can fail on partially provisioned orgs even when some read-only commands still work; fall back to targeted smoke checks. - `query describe` errors such as `Couldn't find CDP tenant ID` or `DataModelEntity ... not found` are query-plane clues, not automatic proof that the whole product is disabled. - Many long-running jobs are asynchronous in practice even when the command returns quickly. - Some Data Cloud operations still require UI setup outside the CLI runtime. --- ## Output Format When finishing, report in this order: 1. **Task classification** 2. **Runtime status** 3. **Readiness classification** 4. **Phase(s) involved** 5. **Commands or artifacts used** 6. **Verification result** 7. **Next recommended step** Suggested shape: ```text Data Cloud task: <setup / inspect / troubleshoot / migrate> Runtime: <plugin ready / missing / partially verified> Readiness: <ready / ready_empty / partial / feature_gated / blocked> Phases: <connect / prepare / harmonize / segment / act / retrieve> Artifacts: <json files, commands, scripts> Verification: <passed / partial / blocked> Next step: <next phase, setup guidance, or cross-skill handoff> ``` --- ## Cross-Skill Integration | Need | Delegate to | Reason | |---|---|---| | load or clean CRM source data | [handling-sf-data](../handling-sf-data/SKILL.md) | seed or fix source records before ingestion | | create missing CRM schema | [generating-custom-object](../generating-custom-object/SKILL.md), [generating-custom-field](../generating-custom-field/SKILL.md) | Data Cloud expects existing objects/fields | | deploy permissions or bundles | [deploying-metadata](../deploying-metadata/SKILL.md) | environment preparation | | write Apex against Data Cloud outputs | [generating-apex](../generating-apex/SKILL.md) | code implementation | | Flow automation after segmentation/activation | [generating-flow](../generating-flow/SKILL.md) | declarative orchestration | | session tracing / STDM / parquet analysis | [observing-agentforce](../observing-agentforce/SKILL.md) | different Data Cloud use case | --- ## Reference Map ### Start here - [README.md](README.md) - [references/plugin-setup.md](references/plugin-setup.md) - [references/feature-readiness.md](references/feature-readiness.md) - [UPSTREAM.md](UPSTREAM.md) ### Phase skills - [connecting-datacloud](../connecting-datacloud/SKILL.md) - [preparing-datacloud](../preparing-datacloud/SKILL.md) - [harmonizing-datacloud](../harmonizing-datacloud/SKILL.md) - [segmenting-datacloud](../segmenting-datacloud/SKILL.md) - [activating-datacloud](../activating-datacloud/SKILL.md) - [retrieving-datacloud](../retrieving-datacloud/SKILL.md) ### Deterministic helpers - [scripts/bootstrap-plugin.sh](scripts/bootstrap-plugin.sh) - [scripts/verify-plugin.sh](scripts/verify-plugin.sh) - [scripts/diagnose-org.mjs](scripts/diagnose-org.mjs) - [assets/definitions/](assets/definitions/)
Creator's repository · forcedotcom/sf-skills
License: MIT