Data Cloud Data Model Objects includes pricing or quota commentary. At roughly 1,585 words the SKILL.md is on the longer end of the catalog distribution.
Data Cloud Data Model Objects sits in the General category under the general-misc sub-topic in the ClaudSkills catalog. There are 10 related skills indexed alongside it; comparing a few before installing usually reveals which fits your workflow best.
These notes are auto-generated from features detected in the SKILL.md file and from this catalog's structure — they aren't part of the source repository.
This skill activates when a practitioner needs to design or manage Data Model Objects (DMOs) in Salesforce Data Cloud. DMOs are the semantic layer of the Customer 360 Data Model — they are logical groupings of data stored in Data Lake Objects (DLOs) and organized into subject areas. This skill covers DMO schema design, mandatory DMOs for identity resolution, the XMD (extended metadata) layer for field formatting, and the data transform types that can create or populate DMOs.
Data Cloud Data Model Objects is a community-contributed Claude Code skill in the general-misc sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/data-cloud-data-model-objects/ and loads when your prompt matches the skill's trigger.
When to invoke it: Use when designing or managing Data Model Objects (DMOs) in Salesforce Data Cloud — covers DMO schema design, subject area governance, data relationships between DMOs, XMD (extended metadata) layer management, data transforms (streaming vs. batch), and mandatory DMO requirements for identity resolution.
The Data Cloud Data Model Objects Claude Code skill is built for Claude Code users and developers across all disciplines looking for general-purpose AI assistance. It's part of ClaudSkills (also referred to as Claude Skills or Claude Code Skills) — the open community-curated registry of 116,000+ SKILL.md files for Anthropic's Claude Code agent and the wider Claude ecosystem (Claude API, Claude Agent SDK).
mkdir -p ~/.claude/skills/data-cloud-data-model-objects curl -L https://claudskills.com/skills/data-cloud-data-model-objects/SKILL.md \ -o ~/.claude/skills/data-cloud-data-model-objects/SKILL.md
Or just download SKILL.md directly and drop it into ~/.claude/skills/data-cloud-data-model-objects/. Claude Code auto-discovers it on next session.
Skills live at ~/.claude/skills/data-cloud-data-model-objects/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\data-cloud-data-model-objects\SKILL.md on Windows. See the full install guide for step-by-step instructions.
Open @claudskills_bot on Telegram, tap Open Desktop App, and the desktop app installs this skill for you. Or share the bot link with a colleague — they get the same one-tap install. Learn more →
The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.
For the full experience including quality scoring and one-click install features for each skill — upgrade to Pro.
SKILL.md from the source repository to ~/.claude/skills/data-cloud-data-model-objects/SKILL.md and restart Claude Code. Both flows are detailed at claudskills.com/install/.SKILL.md file that lives under ~/.claude/skills/<name>/ and tells the Claude Code CLI agent how to perform a specific task (instructions, prompts, allowed tools). Skills are auto-discovered at session start. Data Cloud Data Model Objects is one of 67,000+ skills indexed in the open ClaudSkills catalog, classified under the General category. Learn more at /learn/what-is-a-claude-skill/.If you reference this skill in a blog post, paper, or documentation, you can cite it as:
@misc{data-cloud-data-model-objects-2026,
author = {Pranav Nagrecha},
title = {Data Cloud Data Model Objects [Claude Code skill]},
year = {2026},
publisher = {ClaudSkills},
url = {https://claudskills.com/skills/data-cloud-data-model-objects/}
}Browse all General skills in the ClaudSkills registry, or explore these other picks from the same category:
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SKILL.md files, not affiliated with, endorsed by, or sponsored by Anthropic.