sshvarzman-salesforce/claude-skills

segmenting-datacloud

Salesforce Data Cloud Segment phase.

查看源码

使用方法

  1. 复制安装命令,在自己的智能体环境安装前先检查源码包。
  2. 从原始文档核对所需工具、凭据和支持的宿主。
  3. 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/sshvarzman-salesforce/claude-skills --skill segmenting-datacloud

开始前需了解

  • 安装不包含模型订阅、API 额度或访问文件的权限。
  • 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
仓库原始内容

按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。

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:


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

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

2. Inspect current state

bash
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

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/null

4. 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/null

5. 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/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

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>

References

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