refactor: update node type registry for per-field _updated_at timestamps

packages/node-type-registry/src/data/data-file-embedding.ts

@@ -177,21 +177,6 @@ export const DataFileEmbedding: NodeTypeDefinition = {
             default: 'generate_chunks'
           }
         }
-      },
-
-      // ── Stale tracking (meaningful in extract mode) ────────────────
-      stale_strategy: {
-        type: 'string',
-        enum: ['column', 'null', 'hash'],
-        description:
-          'Strategy for tracking embedding staleness when extraction is enabled. ' +
-          'column: embedding_stale boolean. null: set embedding to NULL. hash: md5 hash.',
-        default: 'column'
-      },
-      include_stale_field: {
-        type: 'boolean',
-        description: 'Whether to include the embedding_stale boolean field (extract mode)',
-        default: true
       }
     }
   },

packages/node-type-registry/src/data/data-image-embedding.ts

@@ -150,19 +150,6 @@ export const DataImageEmbedding: NodeTypeDefinition = {
           enqueue_chunking_job: { type: 'boolean', default: true },
           chunking_task_name: { type: 'string', default: 'generate_chunks' }
         }
-      },
-
-      // ── Stale tracking (forwarded to DataFileEmbedding) ────────────
-      stale_strategy: {
-        type: 'string',
-        enum: ['column', 'null', 'hash'],
-        description: 'Strategy for tracking embedding staleness in extract mode',
-        default: 'column'
-      },
-      include_stale_field: {
-        type: 'boolean',
-        description: 'Whether to include the embedding_stale boolean field',
-        default: true
       }
     }
   },

packages/node-type-registry/src/data/search-vector.ts

@@ -5,7 +5,7 @@ export const SearchVector: NodeTypeDefinition = {
   slug: 'search_vector',
   category: 'search',
   display_name: 'Vector Search',
-  description: 'Adds a vector embedding column with HNSW or IVFFlat index for similarity search. Supports configurable dimensions, distance metrics (cosine, l2, ip), stale tracking strategies (column, null, hash), and automatic job enqueue triggers for embedding generation.',
+  description: 'Adds a vector embedding column with HNSW or IVFFlat index for similarity search. Supports configurable dimensions, distance metrics (cosine, l2, ip), per-field {field_name}_updated_at timestamp tracking (read-only in GraphQL), and automatic job enqueue triggers for embedding generation.',
   parameter_schema: {
     type: 'object',
     properties: {
@@ -44,11 +44,6 @@ export const SearchVector: NodeTypeDefinition = {
         description: 'Index-specific options. HNSW: {m, ef_construction}. IVFFlat: {lists}.',
         default: {}
       },
-      include_stale_field: {
-        type: 'boolean',
-        description: 'When stale_strategy is column, adds an embedding_stale boolean field',
-        default: true
-      },
       source_fields: {
         type: 'array',
         items: {
@@ -67,16 +62,6 @@ export const SearchVector: NodeTypeDefinition = {
         description: 'Task identifier for the job queue',
         default: 'generate_embedding'
       },
-      stale_strategy: {
-        type: 'string',
-        enum: [
-          'column',
-          'null',
-          'hash'
-        ],
-        description: 'Strategy for tracking embedding staleness. column: embedding_stale boolean. null: set embedding to NULL. hash: md5 hash of source fields.',
-        default: 'column'
-      },
       chunks: {
         type: 'object',
         description: 'Chunking configuration for long-text embedding. Creates an embedding_chunks record that drives automatic text splitting and per-chunk embedding. Omit to skip chunking.',