Build an Agent with Sanity Context

Give AI agents intelligent access to your Sanity content. Unlike embedding-only approaches, Agent Context is schema-aware—agents can reason over your content structure, query with real field values, follow references, and combine structural filters with semantic search.

What this enables:

• Agents understand the relationships between your content types
• Queries use actual schema fields, not just text similarity
• Results respect your content model (categories, tags, references)
• Semantic search is available when needed, layered on structure

Agent Context gives agents your schema and teaches them GROQ, but it can't know your domain. You close that gap through the Instructions field (dataset-specific query guidance) and optionally the system prompt (agent behavior and tone).

Three actors in this workflow:

• You — the agent executing this skill, helping the user set things up
• The user — the human you're working with, who knows their domain and data
• The production agent — the agent being built, which will serve end users