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Sf Datacloud Segment

  • 934 installs
  • 423 repo stars
  • Updated April 27, 2026
  • jaganpro/sf-skills

sf-datacloud-segment is a Claude Code skill that connects AI agents to Salesforce Data Cloud for audience segmentation and insight retrieval for developers building CRM-integrated agent features.

About

sf-datacloud-segment is a skill from jaganpro/sf-skills in the sf-datacloud-* family that enables AI agents to query Salesforce Data Cloud for audience segmentation and customer insight retrieval. The skill shares attribution and upstream maintenance notes with sibling sf-datacloud skills via CREDITS.md and UPSTREAM.md, with primary contributor Gnanasekaran Thoppae and MIT License copyright 2024-2025 Jag Valaiyapathy. Reach for sf-datacloud-segment when building agents that need Data Cloud segment definitions, audience filters, or insight queries inside Salesforce-connected workflows rather than generic CRM CRUD or unrelated Salesforce modules.

  • Connects directly to Salesforce Data Cloud APIs for real-time audience and insight data
  • Provides structured workflows for segmentation and customer data activation
  • Enables AI agents to query and act on unified customer profiles
  • Part of the sf-datacloud family with shared upstream maintenance
  • MIT licensed with full source transparency

Sf Datacloud Segment by the numbers

  • 934 all-time installs (skills.sh)
  • +4 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #419 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-segment

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Listed on Skillselion
Installs934
repo stars423
Security audit2 / 3 scanners passed
Last updatedApril 27, 2026
Repositoryjaganpro/sf-skills

How do you connect agents to Salesforce Data Cloud segments?

Connect their AI agent to Salesforce Data Cloud for audience segmentation and insight retrieval.

Who is it for?

Developers building Salesforce-integrated AI agents who need Data Cloud audience segmentation and insight retrieval APIs.

Skip if: Non-Salesforce CRM integrations, Salesforce modules outside Data Cloud, or teams without Data Cloud licensing and access.

When should I use this skill?

The user connects an AI agent to Salesforce Data Cloud, queries audience segments, retrieves customer insights, or works within the sf-datacloud-* skill family.

What you get

Salesforce Data Cloud segment queries, audience filter results, and customer insight data wired into agent workflows.

  • segment query results
  • audience insight data
  • agent-to-Data Cloud integration

By the numbers

  • Part of the sf-datacloud-* skill family in jaganpro/sf-skills
  • MIT License copyright 2024-2025 Jag Valaiyapathy

Files

SKILL.mdMarkdownGitHub ↗

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

Related skills

How it compares

Use sf-datacloud-segment for Data Cloud audience queries; use other sf-skills modules for Salesforce objects outside the Data Cloud segment domain.

FAQ

What does sf-datacloud-segment integrate with?

sf-datacloud-segment connects AI agents to Salesforce Data Cloud for audience segmentation and insight retrieval. Developers use it when agent workflows need segment definitions, audience filters, or customer data from Data Cloud APIs.

How does sf-datacloud-segment relate to other sf-skills?

sf-datacloud-segment is part of the sf-datacloud-* family in jaganpro/sf-skills. Shared attribution and upstream source mapping live in sibling CREDITS.md and UPSTREAM.md files maintained across the Data Cloud skill set.

Is Sf Datacloud Segment safe to install?

skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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