Fix protein midpoint to ~198 g for 230 lb at 1.9 g/kg.

Expose protein_g_mid in the nutrition calculator and align docs, persona prompts, and tests with the corrected midpoint math.

Co-authored-by: Cursor <cursoragent@cursor.com>

docs/nutrition_tools.md

@@ -13,10 +13,10 @@ Deterministic fitness/nutrition math for advisor responses. LLM personas receive
 ## Core formulas (local)
 
 - **Weight:** `kg = lbs × 0.45359237`
-- **Protein (hypertrophy):** `protein_g_min = round(weight_kg × 1.6)`, `protein_g_max = round(weight_kg × 2.2)`
+- **Protein (hypertrophy):** `protein_g_min = round(weight_kg × 1.6)`, `protein_g_mid = round(weight_kg × 1.9)`, `protein_g_max = round(weight_kg × 2.2)`
 - **Meal split:** even distribution with remainder assigned to first meals
 
-Example: **230 lb** → **104.33 kg** → **167–230 g protein/day** (4 meals ≈ 42/42/42/41 g at the low end).
+Example: **230 lb** → **104.33 kg** → **167–230 g protein/day**; midpoint at **1.9 g/kg** ≈ **~198 g/day** (4 meals ≈ 50/50/49/49 g at the midpoint).
 
 ## How calculations reach advisors
 

multi_llm_chatbot_backend/app/core/improved_orchestrator.py

@@ -354,7 +354,7 @@ class ImprovedChatOrchestrator:
             "replies that supply requested data (body weight, schedule, equipment, "
             "experience level) are CLEAR ENOUGH when prior messages asked for that "
             "information or discussed a related topic (e.g. protein question then "
-            "'230 lbs').\n\n"
+            "'230 lbs' → ~198 g/day at 1.9 g/kg midpoint).\n\n"
             "A message NEEDS CLARIFICATION when it:\n"
             "- Expresses confusion or uncertainty without a concrete topic\n"
             "- Is a single generic request like 'help' or 'advice'\n"

multi_llm_chatbot_backend/app/tests/unit/test_nutrition_calculator.py

@@ -28,6 +28,7 @@ class TestProteinTarget(unittest.TestCase):
         protein = protein_target_g(weight_kg)
         self.assertEqual(weight_kg, 104.33)
         self.assertEqual(protein["protein_g_min"], 167)
+        self.assertEqual(protein["protein_g_mid"], 198)
         self.assertEqual(protein["protein_g_max"], 230)
 
 
@@ -72,6 +73,7 @@ class TestProteinAdvisoryContext(unittest.TestCase):
         self.assertIsNotNone(computed)
         self.assertEqual(computed["weight_kg"], 104.33)
         self.assertEqual(computed["protein_g_min"], 167)
+        self.assertEqual(computed["protein_g_mid"], 198)
         self.assertEqual(computed["protein_g_max"], 230)
         self.assertEqual(len(computed["meal_split_min_g"]), 4)
 

multi_llm_chatbot_backend/app/tests/unit/test_nutrition_calculator_tool.py

@@ -16,6 +16,7 @@ class TestNutritionCalculatorTool(unittest.TestCase):
         result = asyncio.run(execute(weight=230, unit="lb", meals=4))
         self.assertEqual(result["weight_kg"], 104.33)
         self.assertEqual(result["protein_g_min"], 167)
+        self.assertEqual(result["protein_g_mid"], 198)
         self.assertEqual(result["protein_g_max"], 230)
         self.assertEqual(sum(result["meal_split_min_g"]), 167)
 

multi_llm_chatbot_backend/app/tools/nutrition_calculator.py

@@ -14,6 +14,8 @@ from typing import Any, Dict, List, Optional, Tuple
 _LB_TO_KG = 0.45359237
 _KG_TO_LB = 1 / _LB_TO_KG
 
+_G_PER_KG_MID = 1.9  # midpoint of 1.6–2.2 g/kg hypertrophy range
+
 _PROTEIN_TOPIC_KEYWORDS = (
     "protein",
     "macro",
@@ -51,10 +53,12 @@ def protein_target_g(
     weight_kg: float,
     g_per_kg_low: float = 1.6,
     g_per_kg_high: float = 2.2,
+    g_per_kg_mid: float = _G_PER_KG_MID,
 ) -> Dict[str, int]:
     """Return rounded daily protein range in grams for hypertrophy."""
     return {
         "protein_g_min": round(weight_kg * g_per_kg_low),
+        "protein_g_mid": round(weight_kg * g_per_kg_mid),
         "protein_g_max": round(weight_kg * g_per_kg_high),
     }
 
@@ -136,6 +140,7 @@ def compute_protein_advisory_context(
     weight_kg = weight_info["weight_kg"]
     protein = protein_target_g(weight_kg, g_per_kg_low, g_per_kg_high)
     split_min = meal_split(protein["protein_g_min"], meals=meals)
+    split_mid = meal_split(protein["protein_g_mid"], meals=meals)
     split_max = meal_split(protein["protein_g_max"], meals=meals)
 
     return {
@@ -147,9 +152,12 @@ def compute_protein_advisory_context(
         },
         "weight_kg": weight_kg,
         "protein_g_min": protein["protein_g_min"],
+        "protein_g_mid": protein["protein_g_mid"],
         "protein_g_max": protein["protein_g_max"],
         "g_per_kg_range": [g_per_kg_low, g_per_kg_high],
+        "g_per_kg_mid": _G_PER_KG_MID,
         "meal_split_min_g": split_min["per_meal_g"],
+        "meal_split_mid_g": split_mid["per_meal_g"],
         "meal_split_max_g": split_max["per_meal_g"],
         "meals": meals,
         "formula": "protein_g = weight_kg × g_per_kg (Mifflin-independent; hypertrophy range 1.6–2.2 g/kg)",
@@ -215,6 +223,7 @@ async def execute(
         weight_kg = bodyweight_to_kg(float(weight), unit)
         protein = protein_target_g(weight_kg)
         split_min = meal_split(protein["protein_g_min"], meals=max(1, int(meals)))
+        split_mid = meal_split(protein["protein_g_mid"], meals=max(1, int(meals)))
         split_max = meal_split(protein["protein_g_max"], meals=max(1, int(meals)))
     except (TypeError, ValueError) as exc:
         return {"error": str(exc)}
@@ -222,9 +231,12 @@ async def execute(
     return {
         "weight_kg": weight_kg,
         "protein_g_min": protein["protein_g_min"],
+        "protein_g_mid": protein["protein_g_mid"],
         "protein_g_max": protein["protein_g_max"],
         "g_per_kg_range": [1.6, 2.2],
+        "g_per_kg_mid": _G_PER_KG_MID,
         "meal_split_min_g": split_min["per_meal_g"],
+        "meal_split_mid_g": split_mid["per_meal_g"],
         "meal_split_max_g": split_max["per_meal_g"],
         "meals": max(1, int(meals)),
     }

muscle_growth_config.yaml

@@ -123,7 +123,7 @@ personas:
     - Read the full chat history before responding.
     - Never re-ask for information the user already provided in earlier messages.
     - When the user supplies follow-up data (body weight, schedule, equipment, experience), apply it immediately to the question they asked earlier in the thread.
-    - Perform unit conversions and arithmetic when you have enough inputs (e.g. lbs→kg, protein g/day at 1.6–2.2 g/kg).
+    - Perform unit conversions and arithmetic when you have enough inputs (e.g. lbs→kg, protein g/day at 1.6–2.2 g/kg; 230 lb ≈ ~198 g/day at 1.9 g/kg midpoint).
     - Default training and nutrition goal to muscle gain / hypertrophy unless the user specifies otherwise.
   personas_dir: "personas/fitness_advisors"
 

personas/fitness_advisors/nutrition_strategist.yaml

@@ -23,6 +23,6 @@ persona_prompt: |
   - If the user asked about protein and then provides body weight (e.g. "230 lbs", "I'm 180"), calculate immediately:
     - Convert lbs to kg: divide by 2.205 (230 lbs ≈ 104.3 kg)
     - Hypertrophy protein target: 1.6–2.2 g/kg/day
-    - Show the math briefly and give a rounded daily gram target (e.g. 167–230 g/day)
+    - Show the math briefly and give a rounded daily gram target (e.g. 167–230 g/day; ~198 g/day at 1.9 g/kg midpoint)
   - Default goal to muscle gain / hypertrophy when not specified
   - Only ask for missing inputs that are still unknown after reading the thread