cot

app.py

@@ -547,22 +547,20 @@ def _parse_s3(text):
 PROMPT_BULLETS = {
     1: [
         "Extract objective factual features from the agent's mobility trajectory <b>without any interpretation</b>",
-        "Location inventory: list all visited POIs with visit counts and apparent price tier (budget / mid-range / high-end)",
-        "Temporal patterns: time-of-day distribution, weekday vs. weekend split, and regularity of routines",
-        "Spatial characteristics: activity radius, average movement distance between locations",
-        "Sequence observations: common location transitions and typical daily activity chains",
+        "Location inventory: list all visited POIs...",
+        "Temporal patterns: time-of-day distribution, weekday vs. weekend split...",
+        "Spatial characteristics: activity radius...",
+        "Sequence observations: common location transitions...",
     ],
     2: [
         "Perform behavioral abstraction across four dimensions based on Step 1 features",
-        "Routine &amp; Schedule: infer work schedule type (fixed hours, flexible, shift work, etc.) and daily structure",
-        "Economic Behavior: assess spending tier from venue choices, transportation costs, and lifestyle signals",
-        "Social &amp; Lifestyle: identify social engagement patterns, leisure activities, and community involvement",
-        "Routine Stability: evaluate consistency and regularity of movement patterns over the observation period",
+        "Routine &amp; Schedule: infer work schedule type (fixed hours, flexible, shift work, etc.)...",
+        "Economic Behavior: assess spending tier from venue choices...",
+        "Social &amp; Lifestyle: identify social engagement patterns, leisure activities...",
+        "Routine Stability: evaluate consistency and regularity of movement patterns...",
     ],
     3: [
-        "Synthesize factual features (Step 1) and behavioral patterns (Step 2) to infer household income bracket",
-        "Score location economic indicators: luxury / mid-range / budget venue distribution",
-        "Consider transportation mode signals, activity diversity, and temporal flexibility as income proxies",
+        "Synthesize factual features (Step 1) and behavioral patterns (Step 2) to infer household income bracket...",
         "Output: <code>INCOME_REASONING</code> — evidence-grounded justification referencing specific mobility observations",
     ],
 }