segmenting-datacloud

name: segmenting-datacloud description: "Salesforce Data Cloud Segment phase. Use this skill when the user creates or publishes segments, manages calculated insights, or troubleshoots audience SQL in Data Cloud. TRIGGER when: user creates or publishes segments, manages calculated insights, inspects segment counts or membership, or troubleshoots audience SQL in Data Cloud. DO NOT TRIGGER when: the task is DMO/mapping/identity-resolution work (use harmonizing-datacloud), activation work (use activating-datacloud), query/search-index work (use retrieving-datacloud), or Standard Data Model (STDM)/session tracing (use observing-agentforce)." license: MIT compatibility: "Requires an external community sf data360 CLI plugin and a Data Cloud-enabled org" metadata: version: "1.0"

segmenting-datacloud: Data Cloud Segment Phase

Use this skill when the user needs audience and insight work: segments, calculated insights, publish workflows, member counts, or troubleshooting Data Cloud segment SQL.

When This Skill Owns the Task

Use segmenting-datacloud when the work involves:

sf data360 segment *
sf data360 calculated-insight *
segment publish workflows
member counts and segment troubleshooting
calculated insight execution and verification

Delegate elsewhere when the user is:

still building Data Model Objects (DMOs), mappings, or identity resolution → harmonizing-datacloud
activating a segment downstream → activating-datacloud
writing read-only SQL or search-index queries → retrieving-datacloud

Required Context to Gather First

Ask for or infer:

target org alias
unified DMO (Data Model Object) or base entity name
whether the user wants create, publish, inspect, or troubleshoot
whether the asset is a segment or calculated insight
expected success metric: member count, aggregate value, or publish status

Core Operating Rules

Treat Data Cloud segment SQL as distinct from CRM SOQL.
Run the shared readiness classifier from the orchestrating-datacloud skill before mutating audience assets: node ../orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase segment --json.
Prefer reusable JSON definitions for repeatable segment and CI creation.
Use --api-version 64.0 when segment creation behavior is unstable on newer defaults.
Verify with counts or SQL after publish/run steps instead of assuming success.
Use SQL joins rather than segment members when readable member details are needed.

Recommended Workflow

1. Classify readiness for segment work

node ../orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase segment --json

2. Inspect current state

sf data360 segment list -o <org> 2>/dev/null
sf data360 calculated-insight list -o <org> 2>/dev/null

3. Create with reusable JSON definitions

sf data360 segment create -o <org> -f segment.json --api-version 64.0 2>/dev/null
sf data360 calculated-insight create -o <org> -f ci.json 2>/dev/null

4. Publish or run explicitly

sf data360 segment publish -o <org> --name My_Segment 2>/dev/null
sf data360 calculated-insight run -o <org> --name Lifetime_Value 2>/dev/null

5. Verify with counts or SQL

sf data360 segment count -o <org> --name My_Segment 2>/dev/null
sf data360 query sql -o <org> --sql 'SELECT COUNT(*) FROM "UnifiedssotIndividualMain__dlm"' 2>/dev/null

High-Signal Gotchas

Segment creation can require --api-version 64.0.
segment members returns opaque IDs; use SQL joins when human-readable member details are needed.
Segment SQL is not SOQL.
Calculated insight assets and segment SQL have different limitations.
Publish/run steps may kick off asynchronous work even when the command returns quickly.
An empty segment or calculated-insight list usually means the module is reachable but unconfigured, not unavailable.

Output Format

Segment task: <segment / calculated-insight>
Action: <create / publish / inspect / troubleshoot>
Target org: <alias>
Artifacts: <definition files / commands>
Verification: <member count / query result / publish state>
Next step: <act / retrieve / follow-up>