data-cloud-segmentation

data-cloud-segmentation is a skill for Claude Code, Codex from BanibrataChatterjee/AwesomeSalesforceSkills. It costs 74 tokens per session (2,914 once invoked), scanned A, original, Apache-2.0.

A guide to building and publishing audience segments in Salesforce Data Cloud. Segments are groups of unified customer profiles selected by filtering their data for use in other systems.

In plain words
What is it for?
Use it to create segment filters, choose segment types and refresh schedules, map fields to activation targets, publish audiences, and investigate missing contacts.
Why use it?
It helps prevent empty audiences, invalid refresh choices, and failed publishing caused by missing identity-resolved data or activation targets. It also covers limits and the differences between segment types.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create segment filters, choose segment types and refresh schedules, map fields to activation targets, publish audiences, and investigate missing contacts.

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Install with agentmods
npx agentmods add skills/banibratachatterjee/awesomesalesforceskills/data-cloud-segmentation
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add BanibrataChatterjee/AwesomeSalesforceSkills --skill data-cloud-segmentation
Clone the repo
git clone --depth 1 https://github.com/BanibrataChatterjee/AwesomeSalesforceSkills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for data-cloud-segmentation

README.md
[![agentmods](https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-segmentation/github.svg)](https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-segmentation)
Your own site
<a href="https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-segmentation"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-segmentation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for data-cloud-segmentation

Your own site · 80×15
<a href="https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-segmentation"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/data-cloud-segmentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,914 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00074 $0.02914
Opus 5 $0.00037 $0.01457
Sonnet 5 $0.00015 $0.00583
Haiku 4.5 $0.00007 $0.00291

Measured 9d ago against content hash 8ba72bd301f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

data-cloud-segmentation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/check_data_cloud_segmentation.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/admin/data-cloud-segmentation/SKILL.md · 204 lines

How it starts

The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Cloud Segmentation

This skill activates when a practitioner needs to create, configure, publish, or troubleshoot audience segments in Salesforce Data Cloud. It covers the full segment lifecycle: building filter logic against Unified Profiles, choosing the right segment type and refresh schedule, mapping attributes to activation targets, and diagnosing why contacts are missing from downstream systems.


Before Starting

Gather this context before working on anything in this domain:

  • Confirm Data Cloud is provisioned and at least one data stream is ingested and identity-resolved. Segments without a populated Unified Individual DMO return empty populations.
  • Know the org's current Rapid Publish segment count. The hard org-wide limit is 20 Rapid Publish segments. Exceeding it silently prevents creation of new Rapid Publish segments without surfacing an obvious error.
  • Identify whether the target activation system (Salesforce CRM, Marketing Cloud Engagement, cloud storage) is already configured as an activation target in Data Cloud setup. Activation cannot proceed without a named target.
  • Clarify the segment's population size expectation. Segments with populations over 10 million Unified Profiles cannot use related attributes in activations.

Core Concepts

Segment Types

Data Cloud supports five segment types, each with different use cases and constraints:

Type Description Key Constraint
Standard Filter-based segment refreshed on a schedule Default; 12–24 hour refresh cycle
Real-Time Evaluated near-continuously for use in real-time personalization Requires real-time data stream; higher processing cost
Waterfall Mutually exclusive priority-ordered buckets Contacts can appear in only one bucket
Dynamic Segment membership driven by changes to a related data object Useful for event-triggered audiences
Data Kit Segments packaged and distributed via Data Kits Cross-org distribution pattern

Read the full file on GitHub · 204 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 204 lines · 74 tokens per session scan A 8ba72bd301f3

Subscribe to this mod's changes

data-cloud-segmentation is a skill published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (3 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 74 tokens to every session and 2,914 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.