etylsarin/sanity-cms

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Sanity CMS

Generic Sanity CMS development methodology. For project-specific configuration, schemas, plugins, document types, and GROQ examples, see sanity-config.md.

Critical Development Rules

1. Always check the schema before querying — use get_schema to understand document types and field structures before writing GROQ queries
2. Array vs single reference — always verify whether a field is an array of references or a single reference; using the wrong query operator causes silent failures
3. Local schema files are source of truth — never edit deployed schemas directly; always change local files and redeploy
4. Follow defineType and defineField patterns — always use Sanity helpers for type safety and consistency
5. Test GROQ queries in Vision — validate queries against real data in the Vision plugin before deploying
6. Handle draft/publish workflow — always account for the drafts. prefix when querying or mutating documents
7. Keep queries in the shared library — queries belong in a shared queries library, never inline in components

Quick GROQ examples

Fetch published articles with authors populated:

*[_type == "article" && defined(publishedAt)] | order(publishedAt desc) {
	_id,
	title,
	"author": author-> { name, _id },
	body
}

Filter by tag and return first 10:

*[_type == "article" && "tech" in tags[]] | order(_createdAt desc)[0..9] { title, slug }

Example schema (executable)

// schemas/article.js
import { defineType, defineField } from 'sanity'

export default defineType({
	name: 'article',
	title: 'Article',
	type: 'document',
	fields: [
		defineField({ name: 'title', type: 'string', title: 'Title' }),
		defineField({ name: 'slug', type: 'slug', options: { source: 'title' } }),
		defineField({ name: 'author', type: 'reference', to: [{ type: 'author' }] }),
		defineField({ name: 'body', type: 'array', of: [{ type: 'block' }] }),
	],
})

Workflow: change schema → validate → deploy

1. Update local schema files and run sanity start to surface schema errors locally.
2. Run Vision queries to validate GROQ results against local data: execute representative queries (see examples above).
3. Create a migration or dataset export if needed and test changes in a staging project/dataset.
   • Validation checkpoint: run sanity dataset export and sanity dataset import into a temporary dataset and run queries.
4. Deploy the schema to Studio and run end-to-end site builds to confirm runtime behavior.
5. If validation fails at any step, revert schema changes locally, fix, and repeat from step 1.