Fix remaining prefix cache review issues

scripts/compare_prefix_cache.py

@@ -216,6 +216,18 @@ def parse_provider_spec(raw: str) -> ProviderSpec:
         )
     label, provider_model = raw.split("=", 1)
     provider, model = provider_model.split(":", 1)
+    if not label:
+        raise ValueError(
+            f"Invalid provider spec {raw!r}. Label must not be empty."
+        )
+    if not provider:
+        raise ValueError(
+            f"Invalid provider spec {raw!r}. Provider must not be empty."
+        )
+    if not model:
+        raise ValueError(
+            f"Invalid provider spec {raw!r}. Model must not be empty."
+        )
     return ProviderSpec(label=label, provider=provider, model=model)
 
 

src/deriver/prompts.py

@@ -20,6 +20,7 @@ Analyze messages from {peer_id} to extract **explicit atomic facts** about them.
 [EXPLICIT] DEFINITION: Facts about {peer_id} that can be derived directly from their messages.
    - Transform statements into one or multiple conclusions
    - Each conclusion must be self-contained with enough context
+   - Do not infer unstated background facts or implications
    - Use absolute dates/times when possible (e.g. "June 26, 2025" not "yesterday")
 
 RULES:
@@ -29,9 +30,9 @@ RULES:
 - Contextualize each observation sufficiently (e.g. "Ann is nervous about the job interview at the pharmacy" not just "Ann is nervous")
 
 EXAMPLES:
-- EXPLICIT: "I just had my 25th birthday last Saturday" → "{peer_id} is 25 years old", "{peer_id}'s birthday is June 21st"
-- EXPLICIT: "I took my dog for a walk in NYC" → "{peer_id} has a dog", "{peer_id} lives in NYC"
-- EXPLICIT: "{peer_id} attended college" + general knowledge → "{peer_id} completed high school or equivalent"
+- EXPLICIT: "I just had my 25th birthday last Saturday" → "{peer_id} is 25 years old", "{peer_id} celebrated their birthday last Saturday"
+- EXPLICIT: "I took my dog for a walk in NYC" → "{peer_id} has a dog", "{peer_id} said they took their dog for a walk in NYC"
+- EXPLICIT: "{peer_id} attended college" → "{peer_id} said they attended college"
 """
     )
 
@@ -78,5 +79,5 @@ def estimate_minimal_deriver_prompt_tokens() -> int:
             ]
         )
         return estimate_tokens(prompt)
-    except Exception:
+    except ValueError:
         return 300

src/utils/clients.py

@@ -137,6 +137,12 @@ def _build_gemini_contents_from_messages(
         if role == "system":
             if isinstance(msg.get("content"), str):
                 system_instruction_parts.append(msg["content"])
+            elif isinstance(msg.get("content"), list):
+                for block in cast(list[dict[str, Any]], msg["content"]):
+                    if block.get("type") == "text" and isinstance(
+                        block.get("text"), str
+                    ):
+                        system_instruction_parts.append(block["text"])
             continue
 
         if role == "assistant":
@@ -1535,6 +1541,7 @@ async def honcho_llm_call(
                 True,  # type: ignore[arg-type]
                 converted_tools,
                 tool_choice,
+                messages,
             )
         else:
             return await honcho_llm_call_inner(
@@ -1552,6 +1559,7 @@ async def honcho_llm_call(
                 False,  # type: ignore[arg-type]
                 converted_tools,
                 tool_choice,
+                messages,
             )
 
     decorated = _call_with_provider_selection

tests/utils/test_clients.py

@@ -101,6 +101,22 @@ class TestLLMCallResponse:
         assert cache_creation == 0
         assert cache_read == 321
 
+    def test_extract_gemini_cache_tokens_none_metadata(self):
+        """Missing Gemini usage metadata should return zero cache tokens."""
+        cache_creation, cache_read = extract_gemini_cache_tokens(None)
+
+        assert cache_creation == 0
+        assert cache_read == 0
+
+    def test_extract_gemini_cache_tokens_missing_attribute(self):
+        """Gemini usage metadata without the cached token field should return zeroes."""
+        usage_metadata = Mock(spec=[])
+
+        cache_creation, cache_read = extract_gemini_cache_tokens(usage_metadata)
+
+        assert cache_creation == 0
+        assert cache_read == 0
+
 
 @pytest.mark.asyncio
 class TestAnthropicClient:
@@ -836,6 +852,59 @@ class TestGoogleClient:
         assert config["response_schema"] == PromptRepresentation
         assert config["response_mime_type"] == "application/json"
 
+    async def test_google_preserves_list_form_system_messages(self):
+        """Gemini should preserve text blocks from list-form system content."""
+        from google import genai
+
+        mock_client = Mock(spec=genai.Client)
+        mock_response = Mock()
+        mock_part = Mock()
+        mock_part.text = "ok"
+        mock_part.function_call = None
+        mock_content = Mock()
+        mock_content.parts = [mock_part]
+        mock_finish_reason = Mock()
+        mock_finish_reason.name = "STOP"
+        mock_candidate = Mock()
+        mock_candidate.content = mock_content
+        mock_candidate.finish_reason = mock_finish_reason
+        mock_response.candidates = [mock_candidate]
+        mock_usage_metadata = Mock()
+        mock_usage_metadata.prompt_token_count = 10
+        mock_usage_metadata.candidates_token_count = 5
+        mock_response.usage_metadata = mock_usage_metadata
+        mock_aio = Mock()
+        mock_aio.models.generate_content = AsyncMock(return_value=mock_response)
+        mock_client.aio = mock_aio
+
+        with patch.dict(CLIENTS, {"google": mock_client}):
+            await honcho_llm_call_inner(
+                provider="google",
+                model="gemini-1.5-pro",
+                prompt="ignored",
+                max_tokens=100,
+                messages=[
+                    {
+                        "role": "system",
+                        "content": [
+                            {"type": "text", "text": "stable instructions"},
+                            {
+                                "type": "text",
+                                "text": "rolling session context",
+                                "cache_control": {"type": "ephemeral"},
+                            },
+                        ],
+                    },
+                    {"role": "user", "content": "Hello"},
+                ],
+            )
+
+        call_args = mock_aio.models.generate_content.call_args
+        assert call_args is not None
+        assert call_args.kwargs["config"]["system_instruction"] == (
+            "stable instructions\n\nrolling session context"
+        )
+
     async def test_google_streaming(self):
         """Test Google/Gemini streaming response"""
         from google import genai