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>

tests/data/test_exercise_picker.gd

@@ -0,0 +1,33 @@
+extends GutTest
+## Tests de ExercisePicker.
+
+var rng := RandomNumberGenerator.new()
+
+
+func before_each() -> void:
+    rng.seed = 42
+
+
+func test_empty_candidates_returns_null() -> void:
+    var candidates: Array[Dictionary] = []
+    assert_null(ExercisePicker.pick(candidates, "", rng))
+
+
+func test_picks_among_candidates() -> void:
+    var candidates: Array[Dictionary] = [{"id": "a"}, {"id": "b"}, {"id": "c"}]
+    var picked: Dictionary = ExercisePicker.pick(candidates, "", rng)
+    var ids: Array = candidates.map(func(c: Dictionary) -> String: return c["id"])
+    assert_true(ids.has(picked["id"]))
+
+
+func test_never_returns_the_excluded_id_when_alternatives_exist() -> void:
+    var candidates: Array[Dictionary] = [{"id": "a"}, {"id": "b"}]
+    for _i in 20:
+        var picked: Dictionary = ExercisePicker.pick(candidates, "a", rng)
+        assert_eq(picked["id"], "b")
+
+
+func test_returns_the_only_candidate_even_if_excluded() -> void:
+    var candidates: Array[Dictionary] = [{"id": "a"}]
+    var picked: Dictionary = ExercisePicker.pick(candidates, "a", rng)
+    assert_eq(picked["id"], "a")