feat(keyboard): expand contextual skills and managed flows

Add local clipboard intent recommendations, webpage and phone actions, and safer host handoffs. Refine managed gateway, catalog refresh, onboarding, and adaptive polish behavior.

ModelTraining/ClipboardSemantics/README.md

@@ -5,17 +5,19 @@ for OSGKeyboard's fully local clipboard analyzer.
 
 ## Scope
 
-The model suite predicts four independent intents (`task`, `question`,
-`invitation`, and `complaint`) plus three-way sentiment. Apple data detectors
-remain responsible for dates, addresses, phone numbers, and URLs; `NLTagger`
-provides best-effort person and organization names.
+The model suite predicts five independent intents (`task`, `question`,
+`invitation`, `complaint`, and `replyableMessage`) plus three-way sentiment.
+`replyableMessage` distinguishes messages that invite a response from terminal
+acknowledgments, personal notes, quoted questions, and factual notices. Apple
+data detectors remain responsible for dates, addresses, phone numbers, and
+URLs; `NLTagger` provides best-effort person and organization names.
 
-The corpus contains 6,334 Chinese and English records:
+The corpus contains 7,272 Chinese and English records:
 
-- 4,100 generated training records
-- 1,080 generated validation records
-- 1,080 template-held-out test records
-- 74 manually authored golden records
+- 4,660 generated training records
+- 1,260 generated validation records
+- 1,260 template-held-out test records
+- 92 manually authored golden records
 
 No user clipboard content is included.
 
@@ -38,11 +40,12 @@ transfer models depend on `NLContextualEmbedding` assets that are not guaranteed
 to exist in a simulator or keyboard-extension runtime, so they remain evaluation
 candidates only.
 
-The selected task, question, and invitation models passed the automatic-routing
-precision gates. The complaint model is packaged for further evaluation but its
-automatic-routing flag remains disabled because golden-set precision is 88.89%,
-below the 90% release gate. Sentiment returns `unknown` unless confidence and
-top-two margin checks both pass.
+The selected intent models passed the automatic-routing precision gates. The
+replyable-message model reached 100% test precision and 97.96% golden precision;
+its measured recall remains part of release monitoring. The complaint model is
+also high precision but remains conservative because golden recall is limited.
+Sentiment returns `unknown` unless confidence and top-two margin checks both
+pass.
 
 Synthetic results are not treated as production truth. Real opt-in, anonymized
 or manually reviewed examples are still required before widening labels or

ModelTraining/ClipboardSemantics/corpus-summary.json

@@ -1,8 +1,10 @@
 {
   "containsUserClipboardData": false,
   "families": {
+    "acknowledgment": 388,
     "complaint_request": 546,
     "complaint_statement": 546,
+    "conversational_message": 550,
     "event_statement": 544,
     "information_question": 544,
     "invitation_question": 548,
@@ -15,26 +17,27 @@
     "task_statement": 548
   },
   "languages": {
-    "en": 3167,
-    "zh-Hans": 3167
+    "en": 3636,
+    "zh-Hans": 3636
   },
   "positiveIntentLabels": {
     "complaint": 1092,
     "invitation": 548,
     "question": 2182,
+    "replyable": 4374,
     "task": 1094
   },
   "seed": 20260821,
   "sentiments": {
     "negative": 1578,
-    "neutral": 4210,
+    "neutral": 5148,
     "positive": 546
   },
   "splits": {
-    "golden": 74,
-    "test": 1080,
-    "train": 4100,
-    "validation": 1080
+    "golden": 92,
+    "test": 1260,
+    "train": 4660,
+    "validation": 1260
   },
-  "total": 6334
+  "total": 7272
 }