feat: add metadata and tags fields to the Variant model

packages/dash_evals/src/dash_evals/runner/tasks/task_helpers.py

@@ -90,9 +90,17 @@ def append_context_injection(solver_chain: list, config: dict) -> None:
 
     Args:
         solver_chain: The solver chain list to append to.
-        config: Task manifest entry with 'variant' key.
+        config: Task manifest entry with 'variant' key or 'metadata' key.
     """
-    variant = config.get("variant", {})
+    metadata = config.get("metadata", {})
+    variant = metadata.get("variant_config")
+    if variant is None:
+        variant = config.get("variant", {})
+
+    # If variant is still just a name string, we can't extract files from it.
+    if isinstance(variant, str):
+        return
+
     # Support both old "context_files" and new "files" key
     context_files = variant.get("files") or variant.get("context_files", [])
     if context_files:
@@ -109,12 +117,18 @@ def append_model_interaction(
 
     Args:
         solver_chain: The solver chain list to append to.
-        config: Task manifest entry with 'variant' key.
+        config: Task manifest entry with 'variant' key or 'metadata' key.
         extra_tools: Additional tools to include alongside MCP (optional).
     """
     tools: list[Tool | MCPServer] = []
-    variant = config.get("variant", {})
-    mcp_servers_config = variant.get("mcp_servers", [])
+    metadata = config.get("metadata", {})
+    variant = metadata.get("variant_config")
+    if variant is None:
+        variant = config.get("variant", {})
+
+    mcp_servers_config = []
+    if not isinstance(variant, str):
+        mcp_servers_config = variant.get("mcp_servers", [])
 
     if mcp_servers_config:
         sandbox_type = config.get("sandbox_type", "local")

packages/dataset_config_dart/lib/src/models/task.dart

@@ -121,7 +121,32 @@ sealed class Task with _$Task {
     Map<String, dynamic>? metadata,
   }) = _Task;
 
+  const Task._();
+
   factory Task.fromJson(Map<String, dynamic> json) => _$TaskFromJson(json);
+
+  /// Get a job-level task argument.
+  Object? getArg(String key, [Object? defaultValue]) {
+    final args = metadata?['args'] as Map<String, dynamic>?;
+    return args?[key] ?? defaultValue;
+  }
+
+  /// Hydrate and return MCP servers defined in the variant.
+  ///
+  /// This is a convenience method that returns the raw config maps.
+  /// In Dart, hydration happens in the Python runner, so we return
+  /// the config maps that the runner will use.
+  List<Map<String, dynamic>> getMcp() {
+    final vcfg = metadata?['variant_config'] as Map<String, dynamic>?;
+    return (vcfg?['mcp_servers'] as List?)?.cast<Map<String, dynamic>>() ??
+        const [];
+  }
+
+  /// Return the skill paths defined in the variant.
+  List<String> getSkills() {
+    final vcfg = metadata?['variant_config'] as Map<String, dynamic>?;
+    return (vcfg?['skills'] as List?)?.cast<String>() ?? const [];
+  }
 }
 
 class TaskMetadata {

packages/dataset_config_dart/lib/src/models/variant.dart

@@ -53,6 +53,12 @@ sealed class Variant with _$Variant {
     @JsonKey(name: 'task_parameters')
     @Default({})
     Map<String, dynamic> taskParameters,
+
+    /// Optional metadata for the variant.
+    @JsonKey(name: 'metadata') @Default({}) Map<String, dynamic> metadata,
+
+    /// Optional tags for the variant.
+    @JsonKey(name: 'tags') @Default([]) List<String> tags,
   }) = _Variant;
 
   const Variant._();