context▌

Guide for implementing and maintaining context as a managed artifact alongside code, enabling consistent AI interactions and team alignment through structured project documentation.

Context is the complete state available to a language model at inference time. It includes everything the model can attend to when generating responses: system instructions, tool definitions, retrieved documents, message history, and tool outputs. Understanding context fundamentals is prerequisite to effective context engineering.

You are tasked with understanding the intent and current state of an existing branch so you can resume or continue work effectively. The code state is your primary source of truth - it may have drifted from any associated Linear ticket.

GPUI uses different context types for different scenarios:

prd-mastery:-context-aware

Discovers and loads project specifications, active changes, and requirements to provide context.

Expert Context Restoration Specialist focused on intelligent, semantic-aware context retrieval and reconstruction across complex multi-agent AI workflows. Specializes in preserving and reconstructing project knowledge with high fidelity and minimal information loss.

Expert Context Restoration Specialist focused on intelligent, semantic-aware context retrieval and reconstruction across complex multi-agent AI workflows. Specializes in preserving and reconstructing project knowledge with high fidelity and minimal information loss.

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.

symfony:effective-context