added type family support

GEMINI.md

@@ -10,7 +10,29 @@ This document outlines the purpose of the `jspg` project, its architecture, and
 
 The extension is designed for high-performance scenarios where schemas are defined once and used many times for validation. It achieves this through an in-memory cache.
 
-1.  **Caching:** A user first calls the `cache_json_schemas(enums, types, puncs)` SQL function. This function takes arrays of JSON objects representing different kinds of schemas within a larger application framework. It uses the vendored `boon` crate to compile all these schemas into an efficient internal format and stores them in a static, in-memory `SCHEMA_CACHE`. This cache is managed by a `RwLock` to allow concurrent reads during validation.
+1.  **Caching and Pre-processing:** A user first calls the `cache_json_schemas(enums, types, puncs)` SQL function. This function takes arrays of JSON objects representing different kinds of schemas:
+    -   `enums`: Standalone enum schemas (e.g., for a `task_priority` list).
+    -   `types`: Schemas for core application data models (e.g., `person`, `organization`). These may contain a `hierarchy` array for inheritance information.
+    -   `puncs`: Schemas for API/function-specific requests and responses.
+
+    Before compiling, `jspg` performs a crucial **pre-processing step** for type hierarchies. It inspects each definition in the `types` array. If a type includes a `hierarchy` array (e.g., a `person` type with `["entity", "organization", "user", "person"]`), `jspg` uses this to build a map of "type families."
+
+    From this map, it generates new, virtual schemas on the fly. For example, for the `organization` type, it will generate a schema with `$id: "organization.family"` that contains an `enum` of all its descendant types, such as `["organization", "user", 'person"]`.
+
+    This allows developers to write more flexible schemas. Instead of strictly requiring a `const` type, you can validate against an entire inheritance chain:
+
+    ```json
+    // In an "organization" schema definition
+    "properties": {
+      "type": {
+        // Allows the 'type' field to be "organization", "user", or "person"
+        "$ref": "organization.family",
+        "override": true
+      }
+    }
+    ```
+
+    Finally, all user-defined schemas and the newly generated `.family` schemas are passed to the vendored `boon` crate, compiled into an efficient internal format, and stored in a static, in-memory `SCHEMA_CACHE`. This cache is managed by a `RwLock` to allow for high-performance, concurrent reads during validation.
 
 2.  **Validation:** The `validate_json_schema(schema_id, instance)` SQL function is then used to validate a JSONB `instance` against a specific, pre-cached schema identified by its `$id`. This function looks up the compiled schema in the cache and runs the validation, returning a success response or a detailed error report.