sf-datacloud-segment
Salesforce Data Cloud Segment phase. 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 sf-datacloud-harmonize), activation work (use sf-datacloud-act), query/search-index work (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-segment- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads sf-datacloud-segment automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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 64.0when 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
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 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
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
FAQ
What does the sf-datacloud-segment skill do?
Salesforce Data Cloud Segment phase. 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 sf-datacloud-harmonize), activation work (use sf-datacloud-act), query/search-index work (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
How do I install sf-datacloud-segment?
Run npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-segment in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/sf-datacloud-segment/ (personal) or .claude/skills/sf-datacloud-segment/ (project).
Which AI agents can use sf-datacloud-segment?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is sf-datacloud-segment safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains sf-datacloud-segment?
It is published by jaganpro in jaganpro/sf-skills. It has 976 recorded installs.
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