fix(auto-router): omit Claude Code system text from classifier (#40655)

Co-authored-by: Claude Code <noreply@anthropic.com>

litellm/router_strategy/complexity_router/README.md

@@ -455,6 +455,13 @@ If 2+ reasoning markers are detected in the user message, the request is promote
 
 Reasoning markers in the system prompt do **not** trigger the reasoning override. This prevents system prompts like "Think step by step before answering" from forcing all requests to the reasoning tier.
 
+For requests identified by a `claude-cli/` or `claude-code/` user agent, the LLM classifier omits caller system
+text to avoid classifying environment, agent, and skill catalogs. The current ask, configured prior-turn context,
+and trajectory signal remain unchanged. The routed completion still receives the original system text. This
+also excludes genuine task constraints supplied only in Claude Code system messages. Other clients keep the
+existing system-context behavior. The browser routing preview has no client-identity field and retains that
+generic behavior; use the real client when checking Claude Code routing.
+
 ### Harness Reminder Blocks
 
 Agent harnesses inject their own context into the conversation as ordinary message text. That text is plumbing, not something a human asked for, so the router strips complete reminder blocks before classifying and picking a tier. A turn that is nothing but a reminder block strips to empty and is skipped, and the router falls back to the last real ask instead

litellm/router_strategy/complexity_router/complexity_router.py

@@ -48,6 +48,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
     request_contains_image_content,
 )
 from litellm.litellm_core_utils.sensitive_data_masker import mask_credentials_in_payload
+from litellm.llms.anthropic.common_utils import is_claude_code_user_agent
 from litellm.llms.base_llm.base_utils import type_to_response_format_param
 from litellm.router_strategy.adaptive_router.classifier import classify_prompt
 from litellm.router_strategy.complexity_router.tier_predictor import (
@@ -1993,8 +1994,7 @@ class ComplexityRouter(CustomLogger):
 
         Args:
             prompt: The current user ask text (already extracted as the real human ask, not tool results)
-            system_prompt: The caller's system prompt (task constraints), always included so later
-                turns never lose it
+            system_prompt: Caller task constraints, omitted from classification for Claude Code requests
             request_kwargs: Request metadata for spend attribution
             messages: Full message history for extracting prior turns and the trajectory signal
         """
@@ -2027,9 +2027,18 @@ class ComplexityRouter(CustomLogger):
         )
 
         encrypted_task: Final = _encrypted_classifier_task(request_kwargs, marker_pairs)
+        caller_system_prompt: Final = (
+            None
+            if any(
+                is_claude_code_user_agent(user_agent)
+                for metadata in (self._iter_metadata_dicts(request_kwargs) if request_kwargs is not None else ())
+                if isinstance(user_agent := metadata.get("user_agent"), str)
+            )
+            else system_prompt
+        )
         user_payload: Final = self._build_classifier_user_payload(
             prompt="The delegated task in the following agent_message." if encrypted_task is not None else prompt,
-            system_prompt=system_prompt,
+            system_prompt=caller_system_prompt,
             prior_turns=prior_turns,
             messages=messages,
             has_prior_conversation=has_prior_conversation,

litellm/router_strategy/complexity_router/config.py

@@ -971,9 +971,11 @@ class ComplexityRouterConfig(BaseModel):
             "classified against what it refers to. Counts turns of both roles when "
             "classifier_context_include_assistant_turns is enabled. These turns are sent to the classifier "
             "model, which may "
-            "be a different deployment or provider than the routed completion model; that call already "
-            "carries the current user ask and the caller's system prompt in full. Set to 0 to send neither "
-            "prior turns nor any conversation context beyond the current ask. Only applies when "
+            "be a different deployment or provider than the routed completion model; that call carries "
+            "the current user ask and, except for Claude Code requests, the extracted system-role text in full. "
+            "Claude Code system text is omitted to avoid classifying harness instructions; the routed "
+            "completion still receives it. Set to 0 to send neither prior turns nor "
+            "any conversation context beyond the current ask. Only applies when "
             "classifier_type is 'llm'."
         ),
     )
@@ -985,9 +987,9 @@ class ComplexityRouterConfig(BaseModel):
             "context window, per classification call. Turns are taken newest first and quoted whole "
             "while they fit, so a conversation small enough to quote entirely is never cut; once the "
             "budget runs out the older turns are dropped whole and only the turn straddling the "
-            "boundary is truncated, into whatever space is left. The current ask and the caller's "
-            "system prompt sit outside this budget and are always sent in full, as does the numbering "
-            "each quoted turn carries. A budget under 120 leaves no room to quote a turn and "
+            "boundary is truncated, into whatever space is left. The current ask and, except for Claude "
+            "Code requests, the extracted system-role text sit outside this budget and are sent in full, as does "
+            "the numbering each quoted turn carries. A budget under 120 leaves no room to quote a turn and "
             "suppresses the block; set classifier_context_window_size to 0 to turn context off "
             "deliberately. Only applies when classifier_type is 'llm'."
         ),

tests/test_litellm/router_strategy/test_complexity_router.py

@@ -2676,6 +2676,26 @@ class TestEncryptedTaskClassifier:
         assert "source-secret" not in json.dumps(call)
         assert "originating_request_masked" not in call["proxy_server_request"]["body"]
 
+    @pytest.mark.asyncio
+    async def test_claude_code_encrypted_task_omits_caller_instructions(self):
+        router, dependency = _native_classifier_router()
+        task: Final = _encrypted_agent_task()
+        request: Final = {
+            "input": [task],
+            "instructions": "CLAUDE_CODE_SYSTEM",
+            "litellm_metadata": {"user_agent": "claude-cli/2.1.233"},
+        }
+        original: Final = deepcopy(request)
+
+        result: Final = await router.async_pre_routing_hook(model="encrypted-router", request_kwargs=request)
+
+        assert result.routing_decision["cause"] == "llm_classifier"
+        assert request == original
+        call: Final = dependency.aresponses.call_args.kwargs
+        assert call["instructions"] == classification_system_prompt(router.config.classifier_context_window_size)
+        assert "CLAUDE_CODE_SYSTEM" not in json.dumps(call["input"][:-1])
+        assert call["input"][-1] == task
+
     @pytest.mark.asyncio
     @pytest.mark.parametrize(
         "items",
@@ -7994,6 +8014,113 @@ _CODEX_ENVELOPES: Final = (
 class TestContextAwareClassifier:
     """Test the new classifier context window and trajectory signals."""
 
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "request_metadata,forwards_system",
+        [
+            ({"metadata": {"user_agent": "claude-cli/2.1.233"}}, False),
+            ({"litellm_metadata": {"user_agent": "claude-code/2.1.233"}}, False),
+            ({"metadata": {"user_agent": "curl/8.7.1"}}, True),
+            ({"litellm_metadata": {}}, True),
+            (
+                {"metadata": {"user_agent": "claude-cli/2.1.233"}, "litellm_metadata": {"user_agent": "curl/8.7.1"}},
+                False,
+            ),
+            ({"metadata": {"user_agent": "Claude-Code/2.1.233"}}, True),
+        ],
+    )
+    async def test_claude_code_classifier_omits_harness_system_prompt(
+        self,
+        llm_classifier_config: dict[str, object],
+        request_metadata: dict[str, object],
+        forwards_system: bool,
+    ) -> None:
+        dependency: Final = MagicMock(acompletion=AsyncMock(return_value=_llm_response('{"tier": "COMPLEX"}')))
+        router: Final = ComplexityRouter(
+            "test-complexity-router",
+            dependency,
+            {
+                **llm_classifier_config,
+                "classifier_context_include_assistant_turns": True,
+            },
+        )
+        messages: Final = [
+            {"role": "user", "content": "Design the retry state machine"},
+            {"role": "assistant", "content": "The design needs a lease and fencing token"},
+            {"role": "user", "content": "Now prove it cannot livelock"},
+            {
+                "role": "system",
+                "content": [{"type": "text", "text": "ENVIRONMENT_CATALOG\nAGENT_CATALOG\nSKILL_CATALOG"}],
+            },
+        ]
+        top_level_system: Final = [{"type": "text", "text": "TOP_LEVEL_HARNESS_SYSTEM"}]
+        claude_kwargs: Final = {
+            "metadata": {"user_agent": "claude-cli/2.1.233"},
+            "system": top_level_system,
+            "proxy_server_request": {"body": {"system": top_level_system}},
+        }
+        compared_kwargs: Final = {
+            **request_metadata,
+            "system": top_level_system,
+            "proxy_server_request": {"body": {"system": top_level_system}},
+        }
+        original_messages: Final = deepcopy(messages)
+        original_kwargs: Final = deepcopy((claude_kwargs, compared_kwargs))
+        results: Final = (
+            await router.async_pre_routing_hook("test-complexity-router", claude_kwargs, messages),
+            await router.async_pre_routing_hook("test-complexity-router", compared_kwargs, messages),
+        )
+
+        assert all(result is not None and result.routing_decision["cause"] == "llm_classifier" for result in results)
+        assert all(result is not None and result.messages == original_messages for result in results)
+        assert messages == original_messages
+        assert (claude_kwargs, compared_kwargs) == original_kwargs
+        calls: Final = tuple(call.kwargs["messages"] for call in dependency.acompletion.await_args_list)
+        assert calls[0][0]["content"] == calls[1][0]["content"] == classification_system_prompt(
+            router.config.classifier_context_window_size
+        )
+        payloads: Final = (calls[0][1]["content"], calls[1][1]["content"])
+        for payload, expected_system in zip(payloads, (False, forwards_system)):
+            assert payload.endswith("Classify this message:\nNow prove it cannot livelock")
+            assert ("ENVIRONMENT_CATALOG" in payload) is expected_system
+            assert ("AGENT_CATALOG" in payload) is expected_system
+            assert ("SKILL_CATALOG" in payload) is expected_system
+            assert "Design the retry state machine" in payload
+            assert "lease and fencing token" in payload
+            assert "TOP_LEVEL_HARNESS_SYSTEM" not in payload
+            assert "Conversation so far: ~35 tokens across the request" in payload
+
+    @pytest.mark.asyncio
+    async def test_claude_code_first_turn_without_context_omits_harness_system_prompt(
+        self, llm_classifier_config: dict[str, object]
+    ) -> None:
+        dependency: Final = MagicMock(acompletion=AsyncMock(return_value=_llm_response('{"tier": "SIMPLE"}')))
+        router: Final = ComplexityRouter(
+            "test-complexity-router",
+            dependency,
+            {**llm_classifier_config, "classifier_context_window_size": 0},
+        )
+        messages: Final = [
+            {"role": "user", "content": "What is two plus two?"},
+            {
+                "role": "system",
+                "content": [{"type": "text", "text": "ENVIRONMENT_CATALOG\nAGENT_CATALOG\nSKILL_CATALOG"}],
+            },
+        ]
+        request_kwargs: Final = {"litellm_metadata": {"user_agent": "claude-code/2.1.233"}}
+        original: Final = deepcopy((messages, request_kwargs))
+
+        result: Final = await router.async_pre_routing_hook("test-complexity-router", request_kwargs, messages)
+
+        assert result is not None and result.routing_decision["cause"] == "llm_classifier"
+        assert result.messages == messages == original[0]
+        assert request_kwargs == original[1]
+        classifier_messages: Final = dependency.acompletion.call_args.kwargs["messages"]
+        assert classifier_messages[0]["content"] == classification_system_prompt(
+            router.config.classifier_context_window_size
+        )
+        assert classifier_messages[1]["content"].strip() == "Classify this message:\nWhat is two plus two?"
+
     @pytest.mark.parametrize(
         "tail,expected",
         (