사용 방법
- 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
- 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
- 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/sshvarzman-salesforce/claude-skills --skill segmenting-datacloud시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
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-datacloudskill 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 64.0when 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 memberswhen readable member details are needed.
Recommended Workflow
1. Classify readiness for segment work
bash
node ../orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase segment --json2. Inspect current state
bash
sf data360 segment list -o <org> 2>/dev/null
sf data360 calculated-insight list -o <org> 2>/dev/null3. Create with reusable JSON definitions
bash
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/null4. Publish or run explicitly
bash
sf data360 segment publish -o <org> --name My_Segment 2>/dev/null
sf data360 calculated-insight run -o <org> --name Lifetime_Value 2>/dev/null5. Verify with counts or SQL
bash
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/nullHigh-Signal Gotchas
- Segment creation can require
--api-version 64.0. segment membersreturns 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
text
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>
