feat(fifa17): apply the rare all-six training card

Passes a null attribute slot for the rare card -- Core reads absence as
"every slot", so sending 0 would silently train pace alone -- and declares
the per-family ceiling rather than a single constant.

Tests pin the null-slot serialisation, both ceilings, and that all 36
single-attribute plus all 6 rare cards resolve.

openfut-utas-host/src/lib.rs

@@ -91,7 +91,7 @@ use openfut_adapter_fifa17::fut::store_session::{
     validate_capability, SessionStore, StoreMode, SENTINEL_PACK_ID,
 };
 use openfut_adapter_fifa17::fut::training_cards::{
-    class_accepts_position, training_effect, TRAINING_MAX_AMOUNT,
+    ceiling_for, class_accepts_position, training_effect,
 };
 use openfut_identity::ExternalIdentityStore;
 use rand::{Rng, SeedableRng};
@@ -1316,7 +1316,8 @@ pub enum ApplyEffect {
     /// out of `cardsubtypeid` by the adapter — Core is never told a FIFA
     /// attribute name.
     ApplyTraining {
-        attribute_index: i64,
+        /// `None` = the rare card that boosts all six attributes.
+        attribute_index: Option<i64>,
         amount: i64,
         max_amount: i64,
     },
@@ -1344,6 +1345,9 @@ impl ApplyEffect {
                 amount,
                 max_amount,
             } => json!({
+                // `attribute_index` is deliberately null for the rare all-six
+                // card: Core reads absence as "every slot", so omitting the key
+                // or sending 0 would silently train pace only.
                 "kind": "apply_training",
                 "attribute_index": attribute_index,
                 "amount": amount,
@@ -5087,10 +5091,14 @@ impl Server {
                 );
                 return error_response(409, "training_target_class_mismatch");
             }
+            // The ceiling is per-family: 15 for a single attribute, 10 for the
+            // rare all-six card. Sending the single-attribute ceiling for an
+            // all-six card would let Core accept a +15 all-six boost that EA
+            // never authored.
             let effect = ApplyEffect::ApplyTraining {
                 attribute_index: t.attribute_index,
                 amount: t.amount,
-                max_amount: TRAINING_MAX_AMOUNT,
+                max_amount: ceiling_for(&t),
             };
             return self.finish_consumable_apply(
                 econ,