Tighten LLM proposal schema

src/aituner/llm.py

@@ -31,7 +31,9 @@ def build_prompt(
         "You are tuning an OpenAI-compatible serving engine.",
         "Return exactly one JSON object with keys: observation, diagnosis, config_patch, expected_effects, why_not_previous_failures.",
         "config_patch must contain env_patch and flag_patch.",
+        "expected_effects must be a JSON array of short strings, not an object.",
         "Only use allowed tunable env keys and allowed tunable flag keys.",
+        "Do not wrap the JSON in markdown fences or any extra text.",
         "",
         "Study stack:",
         json.dumps(

src/aituner/spec.py

@@ -398,6 +398,17 @@ class Proposal:
         expected_effects = data.get("expected_effects")
         if isinstance(expected_effects, str):
             expected_effects_value = [expected_effects.strip()] if expected_effects.strip() else []
+        elif isinstance(expected_effects, Mapping):
+            expected_effects_value = []
+            for key, value in expected_effects.items():
+                key_text = str(key).strip()
+                value_text = str(value).strip()
+                if key_text and value_text:
+                    expected_effects_value.append(f"{key_text}: {value_text}")
+                elif key_text:
+                    expected_effects_value.append(key_text)
+                elif value_text:
+                    expected_effects_value.append(value_text)
         else:
             expected_effects_value = _coerce_str_list(
                 expected_effects, context="proposal.expected_effects"