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Skills/jaganpro/sf-skills/sf-datacloud-segment
sf-datacloud-segment logo

sf-datacloud-segment

jaganpro/sf-skills
882 installs418 stars
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Installation

npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-segment

Summary

>

SKILL.md

sf-datacloud-segment: 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 sf-datacloud-segment 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 DMOs, mappings, or identity resolution → sf-datacloud-harmonize
  • activating a segment downstream → sf-datacloud-act
  • writing read-only SQL or search-index queries → sf-datacloud-retrieve

---

Required Context to Gather First

Ask for or infer:

  • target org alias
  • unified DMO 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 before mutating audience assets: node ~/.claude/skills/sf-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 ~/.claude/skills/sf-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>

---

References

  • README.md
  • ../sf-datacloud/assets/definitions/calculated-insight.template.json
  • ../sf-datacloud/assets/definitions/segment.template.json
  • ../sf-datacloud/references/feature-readiness.md
  • ../sf-datacloud/UPSTREAM.md

Score

0–100
55/ 100

Grade

C

Popularity15/30

882 installs — growing adoption.

Completeness19/30

Documented: full SKILL.md body, one-line install. Missing: description, category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Sf Datacloud Segment skill score badge previewScore badge

Markdown

[![Sf Datacloud Segment skill](https://www.remoteopenclaw.com/skills/jaganpro/sf-skills/sf-datacloud-segment/badges/score.svg)](https://www.remoteopenclaw.com/skills/jaganpro/sf-skills/sf-datacloud-segment)

HTML

<a href="https://www.remoteopenclaw.com/skills/jaganpro/sf-skills/sf-datacloud-segment"><img src="https://www.remoteopenclaw.com/skills/jaganpro/sf-skills/sf-datacloud-segment/badges/score.svg" alt="Sf Datacloud Segment skill"/></a>

Sf Datacloud Segment FAQ

How do I install the Sf Datacloud Segment skill?

Run “npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-segment” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Sf Datacloud Segment skill do?

> The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Sf Datacloud Segment skill free?

Yes. Sf Datacloud Segment is a free, open-source skill published from jaganpro/sf-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Sf Datacloud Segment work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Sf Datacloud Segment works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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