Stage 1: project setup, Exercise Library, both Mode designs and the Mode switch

- Flutter Android app on CookIT's stack (provider, shared_preferences, gen-l10n)
- tools/exercise-import turns free-exercise-db into 876 bundled Exercises
  with 1,746 WebP images (20 MB); stretching -> Stretching, rest -> Workout
- ZenStyle tokens per Mode: calm rounded sage/teal with breath ripples vs.
  dark ember-to-red with floor-tape slashes; the theme morphs at each
  Mode's own pace
- Remembered global Mode switch, Plans / Library / History tabs

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tools/exercise-import/README.md

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+# Exercise import
+
+Builds the bundled Exercise Library in `assets/exercises/` from
+[free-exercise-db](https://github.com/yuhonas/free-exercise-db) (Unlicense).
+
+```sh
+git clone --depth 1 https://github.com/yuhonas/free-exercise-db.git <somewhere outside the repo>
+python -m venv .venv
+.venv/Scripts/python -m pip install -r requirements.txt
+.venv/Scripts/python convert.py <somewhere outside the repo>/free-exercise-db
+.venv/Scripts/python -m pytest
+```
+
+The script slims `dist/exercises.json`, assigns each Exercise its Mode (`stretching` category →
+Stretching, everything else → Workout) and converts every image to a WebP of at most 480 px,
+flattened to `images/<id>_<n>.webp`. Rerunning it replaces the previous output.

tools/exercise-import/convert.py

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+"""Usage: python convert.py <free-exercise-db checkout> [output folder]
+
+The output folder defaults to the app's assets/exercises.
+"""
+
+import collections
+import sys
+from pathlib import Path
+
+from exercise_import import run
+
+
+def main() -> None:
+    if len(sys.argv) < 2:
+        sys.exit(__doc__)
+    source = Path(sys.argv[1])
+    output = Path(sys.argv[2]) if len(sys.argv) > 2 else Path(__file__).resolve().parents[2] / "assets" / "exercises"
+    exercises = run(source, output)
+    modes = collections.Counter(e["mode"] for e in exercises)
+    size = sum(f.stat().st_size for f in (output / "images").glob("*.webp"))
+    print(f"{len(exercises)} Exercises ({dict(modes)}), images {size / 1_000_000:.1f} MB -> {output}")
+
+
+if __name__ == "__main__":
+    main()

tools/exercise-import/exercise_import.py

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+"""Turns a checkout of free-exercise-db into ZenXercise's bundled Exercise Library.
+
+Writes `exercises.json` (slimmed, with each Exercise's Mode) and one WebP per
+image into the output folder, flattened to `images/<id>_<n>.webp` because
+Flutter assets are declared per folder.
+"""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+from PIL import Image
+
+STRETCHING_CATEGORY = "stretching"
+MAX_EDGE = 480
+WEBP_QUALITY = 72
+
+
+def mode_of(category: str) -> str:
+    """Category `stretching` belongs to Stretching Mode, everything else to Workout Mode."""
+    return "stretching" if category == STRETCHING_CATEGORY else "workout"
+
+
+def slim(exercise: dict) -> dict:
+    """The fields the app needs, with images reduced to a count."""
+    return {
+        "id": exercise["id"],
+        "name": exercise["name"],
+        "mode": mode_of(exercise["category"]),
+        "category": exercise["category"],
+        "level": exercise["level"],
+        "equipment": exercise.get("equipment"),
+        "force": exercise.get("force"),
+        "mechanic": exercise.get("mechanic"),
+        "primaryMuscles": exercise["primaryMuscles"],
+        "secondaryMuscles": exercise["secondaryMuscles"],
+        "instructions": [line.strip() for line in exercise["instructions"] if line.strip()],
+        "imageCount": len(exercise["images"]),
+    }
+
+
+def image_name(exercise_id: str, index: int) -> str:
+    return f"{exercise_id}_{index}.webp"
+
+
+def convert_image(source: Path, target: Path) -> None:
+    with Image.open(source) as image:
+        image = image.convert("RGB")
+        image.thumbnail((MAX_EDGE, MAX_EDGE))
+        image.save(target, "WEBP", quality=WEBP_QUALITY, method=6)
+
+
+def run(source_root: Path, output_root: Path) -> list[dict]:
+    exercises = json.loads((source_root / "dist" / "exercises.json").read_text(encoding="utf-8"))
+    images = output_root / "images"
+    images.mkdir(parents=True, exist_ok=True)
+    for stale in images.glob("*.webp"):
+        stale.unlink()
+
+    slimmed = sorted((slim(e) for e in exercises), key=lambda e: e["name"].lower())
+    for exercise in exercises:
+        for index, relative in enumerate(exercise["images"]):
+            convert_image(source_root / "exercises" / relative, images / image_name(exercise["id"], index))
+
+    (output_root / "exercises.json").write_text(
+        json.dumps(slimmed, ensure_ascii=False, separators=(",", ":")), encoding="utf-8"
+    )
+    return slimmed

tools/exercise-import/pytest.ini

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+[pytest]
+testpaths = tests
+pythonpath = .

tools/exercise-import/requirements.txt

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+Pillow>=11
+pytest>=8

tools/exercise-import/tests/test_exercise_import.py

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+import json
+
+from PIL import Image
+
+from exercise_import import mode_of, run, slim
+
+RAW = {
+    "id": "Calf_Stretch",
+    "name": "Calf Stretch",
+    "force": "static",
+    "level": "beginner",
+    "mechanic": None,
+    "equipment": "body only",
+    "primaryMuscles": ["calves"],
+    "secondaryMuscles": [],
+    "instructions": ["Stand tall. ", "", "Lean forward."],
+    "category": "stretching",
+    "images": ["Calf_Stretch/0.jpg", "Calf_Stretch/1.jpg"],
+}
+
+
+def test_stretching_category_is_stretching_mode_and_others_workout():
+    assert mode_of("stretching") == "stretching"
+    for category in ["strength", "plyometrics", "cardio", "powerlifting"]:
+        assert mode_of(category) == "workout"
+
+
+def test_slim_keeps_needed_fields_and_cleans_instructions():
+    result = slim(RAW)
+    assert result["mode"] == "stretching"
+    assert result["instructions"] == ["Stand tall.", "Lean forward."]
+    assert result["imageCount"] == 2
+    assert "images" not in result
+
+
+def test_run_writes_json_and_flattened_small_webps(tmp_path):
+    source = tmp_path / "db"
+    (source / "dist").mkdir(parents=True)
+    (source / "exercises" / "Calf_Stretch").mkdir(parents=True)
+    (source / "dist" / "exercises.json").write_text(json.dumps([RAW]), encoding="utf-8")
+    for i in range(2):
+        Image.new("RGB", (850, 567), "white").save(source / "exercises" / "Calf_Stretch" / f"{i}.jpg")
+
+    out = tmp_path / "out"
+    run(source, out)
+
+    written = json.loads((out / "exercises.json").read_text(encoding="utf-8"))
+    assert [e["id"] for e in written] == ["Calf_Stretch"]
+    with Image.open(out / "images" / "Calf_Stretch_1.webp") as image:
+        assert max(image.size) == 480