# Content Modeling Best Practices

> Structured content modeling principles with Sanity-specific guidance. Use when designing or reviewing content schemas, document types, field structures, or content architecture — including decisions around references vs embedding, content reuse, taxonomy, page builders, multi-channel delivery, or refactoring existing schemas. Trigger when the user mentions schema design, content model, document types, content structure, headless CMS architecture, or asks how to model any content type.

- Skill: `majiayu000/content-modeling-best-practices-2` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/content-modeling-best-practices-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/content-modeling-best-practices-2/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: MIT
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/majiayu000/content-modeling-best-practices-2

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# Content Modeling Best Practices

Principles for designing structured content that's flexible, reusable, and maintainable. These concepts apply to any headless CMS but include Sanity-specific implementation notes.

## When to Apply

Reference these guidelines when:
- Starting a new project and designing the content model
- Evaluating whether content should be structured or free-form
- Deciding between references and embedded content
- Planning for multi-channel content delivery
- Refactoring existing content structures

## Core Principles

1. **Content is data, not pages** — Structure content for meaning, not presentation
2. **Single source of truth** — Avoid content duplication
3. **Future-proof** — Design for channels that don't exist yet
4. **Editor-centric** — Optimize for the people creating content

## Resources

See `resources/` for detailed guidance on specific topics:
- Separation of content and presentation
- Reference vs embedding strategies
- Content reuse patterns
- Taxonomy and classification