Add the playable scene loop: boot through mission to reward

Wires every autoload up to a real UI: boot -> profile select/create
-> world map (three mission markers, positioned from data, not
hardcoded pixels) -> mission intro (narrative from data/missions/,
a new data type with its own schema) -> rule panel -> exercise host
-> one of the three exercise type scenes -> feedback panel -> reward
screen -> back to the map.

exercise_host is the only piece with real orchestration logic: picks
exercises via ExerciseEngine (now fully implemented, validating at
load like make validate-data does), validates answers through the
pure AnswerValidator/DictationAnalyzer, escalates aid over 3 attempts
via AttemptFlow, feeds DifficultyManager so adaptive difficulty is
actually wired in rather than dead code, and records every attempt
through ProgressManager. Every exercise-type scene (multiple_choice,
sentence_correction, dictation) only emits its answer by signal, per
the architecture invariant.

All child-facing text now comes from data/localization/fr.json via
UIText, not hardcoded in scripts or scenes. Getting that right
required extending SchemaValidator to support "additionalProperties"
as a schema (dynamic keys), which also closed a real gap: save.skills
was previously unvalidated against SkillState's actual shape.

16 new headless tests, including two integration tests that instance
exercise_host.tscn directly and drive it by emitting child-scene
signals, stopping short of the final scene transition (which would
tear down the test runner's own tree). Everything that needs a
screen -- layout at different sizes, touch, virtual keyboard, actual
audio playback (no .ogg files exist yet) -- is listed in the new
docs/testing/manual-checklist.md instead of claimed as verified.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

data/schemas/save.schema.json

@@ -18,7 +18,36 @@
     "school_level": { "type": "string", "enum": ["CE1", "CE2"] },
     "session_count": { "type": "integer", "minimum": 0 },
     "unlocked_regions": { "type": "array", "items": { "type": "string" } },
-    "skills": { "type": "object" },
+    "skills": {
+      "type": "object",
+      "additionalProperties": {
+        "type": "object",
+        "required": [
+          "status",
+          "recent_results",
+          "recent_hint_used",
+          "sessions_succeeded",
+          "formats_succeeded",
+          "last_session_practiced",
+          "review_interval_index",
+          "next_review_session"
+        ],
+        "additionalProperties": false,
+        "properties": {
+          "status": {
+            "type": "string",
+            "enum": ["decouverte", "en_acquisition", "en_consolidation", "acquise", "a_reviser"]
+          },
+          "recent_results": { "type": "array", "items": { "type": "boolean" } },
+          "recent_hint_used": { "type": "array", "items": { "type": "boolean" } },
+          "sessions_succeeded": { "type": "array", "items": { "type": "integer" } },
+          "formats_succeeded": { "type": "array", "items": { "type": "string" } },
+          "last_session_practiced": { "type": "integer" },
+          "review_interval_index": { "type": "integer" },
+          "next_review_session": { "type": "integer" }
+        }
+      }
+    },
     "rewards": {
       "type": "object",
       "required": ["stars", "items"],