# Graph Query Language

Curiosity Workspace provides a graph query interface used by connectors, endpoints, and (in limited form) front-ends to traverse and filter the knowledge graph.

This page describes the concepts and common patterns you’ll see in Curiosity queries. The exact API surface can vary by environment/version, but the building blocks remain consistent.

• StartAt(...): defines the starting set of nodes (by type, key, or UID).
• Out(...) / In(...): traverses edges to neighboring nodes.
• Where(...): filters nodes by predicate (properties, timestamp, type).
• Take(...) / Skip(...) / TakeAll(): pagination and bounded reads.
• Emit(...): returns results (nodes, aggregates, summaries).

Most queries follow:

1. Choose a starting set
2. Traverse edges
3. Filter
4. Paginate
5. Emit output

// Return 10 nodes of a given type
return Q().StartAt("Device").Take(10).Emit("N");

// Starting from a manufacturer node (by key), return related devices
return Q().StartAt("Manufacturer", "Apple")
          .Out("Device")
          .Take(50)
          .Emit("N");

// Return recent cases (sorted by timestamp if available)
return Q().StartAt("SupportCase")
          .SortByTimestamp(oldestFirst: false)
          .Take(10)
          .Emit("N");

// Summarize the graph or neighborhood
return Q().EmitSummary();

// Summarize neighbors for a type
return Q().StartAt("Part").EmitNeighborsSummary();

• Bound traversal: always use Take(...)/pagination unless you truly need TakeAll().
• Model for queries: if queries are complex, the schema likely needs another edge or entity.
• Prefer deterministic computation in queries/endpoints: use LLMs for narration, not graph computation.

• Search queries: Search DSL
• Schema concepts: Schema Reference