fix(anthropic): prepend user turn when compaction leaves a leading assistant message

Anthropic extracts the system prompt into a separate `system` field and
requires messages[0] to be role="user"; a leading assistant turn is rejected
with HTTP 400. After a second context compaction the only surviving leading
anchor is the system prompt, so a summary/handoff message emitted as
role="assistant" becomes the first messages entry once the system prompt is
extracted. Anthropic reports this with a misleading error —
`messages.N: tool_use ids were found without tool_result blocks immediately
after: toolu_...` — even when every tool_use/tool_result pair is adjacent and
matched; the real structural defect is the leading assistant role (#52160).

This is engine-agnostic: it fires for any producer of a leading-assistant
transcript (built-in compressor, the DAG/LCM context engine, session
truncation), unlike the compressor-scoped fix in #52167. The native Bedrock
Converse adapter already guards the same invariant
(convert_messages_to_converse); this mirrors it for the native Anthropic path.

Add _ensure_leading_user_turn() to the convert_messages_to_anthropic
post-processing chain, scoped to the system-extracted case (the production
trigger) so bare assistant-only unit fixtures are unaffected. Adds regression
tests (leading-assistant, leading-assistant-with-adjacent-tool_use, and a
no-op negative control).

agent/anthropic_adapter.py

@@ -2412,6 +2412,12 @@ def _evict_old_screenshots(result: List[Dict[str, Any]]) -> None:
                 ]
 
 
+def _ensure_leading_user_turn(result: List[Dict[str, Any]], system: Any) -> None:
+    """Anthropic requires messages[0] to be user when system is extracted."""
+    if system is not None and result and result[0].get("role") != "user":
+        result.insert(0, {"role": "user", "content": [{"type": "text", "text": " "}]})
+
+
 def convert_messages_to_anthropic(
     messages: List[Dict],
     base_url: str | None = None,
@@ -2470,6 +2476,7 @@ def convert_messages_to_anthropic(
 
     _strip_orphaned_tool_blocks(result)
     result = _merge_consecutive_roles(result)
+    _ensure_leading_user_turn(result, system)
     _manage_thinking_signatures(result, base_url, model)
     _evict_old_screenshots(result)
 

tests/agent/test_anthropic_adapter.py

@@ -1121,7 +1121,8 @@ class TestConvertMessages:
         ])
 
         _, result = convert_messages_to_anthropic(messages)
-        assistant_blocks = result[0]["content"]
+        assistant_msg = next(m for m in result if m["role"] == "assistant")
+        assistant_blocks = assistant_msg["content"]
 
         assert assistant_blocks[0]["type"] == "text"
         assert assistant_blocks[0]["text"] == "Hello from assistant"
@@ -1207,7 +1208,12 @@ class TestConvertMessages:
         ], native_anthropic=True)
 
         _, result = convert_messages_to_anthropic(messages)
-        user_msg = [m for m in result if m["role"] == "user"][0]
+        user_msg = next(
+            m for m in result
+            if m["role"] == "user"
+            and isinstance(m["content"], list)
+            and any(b.get("type") == "tool_result" for b in m["content"])
+        )
         tool_block = user_msg["content"][0]
 
         assert tool_block["type"] == "tool_result"
@@ -1356,6 +1362,69 @@ class TestConvertMessages:
         assert isinstance(result[0]["content"], list)
         assert result[0]["content"] == [{"type": "text", "text": "(empty message)"}]
 
+    def test_leading_assistant_after_compaction_gets_user_turn_prepended(self):
+        """The adapter backstops compactors that emit a leading assistant summary."""
+        messages = [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "assistant", "content": "[Context compaction summary] earlier work…"},
+            {"role": "user", "content": "continue"},
+        ]
+
+        system, result = convert_messages_to_anthropic(messages)
+
+        assert system == "You are helpful."
+        assert result[0]["role"] == "user"
+        assert result[0]["content"] == [{"type": "text", "text": " "}]
+        assert result[1]["role"] == "assistant"
+        assert any(
+            m["role"] == "assistant" and "Context compaction summary" in str(m["content"])
+            for m in result
+        )
+
+    def test_leading_user_message_is_not_modified(self):
+        """A normal transcript that already starts with user must be untouched."""
+        messages = [
+            {"role": "system", "content": "sys"},
+            {"role": "user", "content": "hello"},
+            {"role": "assistant", "content": "hi"},
+        ]
+
+        _, result = convert_messages_to_anthropic(messages)
+
+        assert len(result) == 2
+        assert result[0]["role"] == "user"
+        assert result[0]["content"] == "hello"
+
+    def test_leading_assistant_with_tool_use_after_compaction_is_repaired(self):
+        """Repair the leading role without disturbing adjacent tool pairs."""
+        messages = [
+            {"role": "system", "content": "sys"},
+            {
+                "role": "assistant",
+                "content": "running it",
+                "tool_calls": [
+                    {"id": "toolu_1", "function": {"name": "terminal", "arguments": "{}"}},
+                ],
+            },
+            {"role": "tool", "tool_call_id": "toolu_1", "content": "ok"},
+            {"role": "user", "content": "next"},
+        ]
+
+        _, result = convert_messages_to_anthropic(messages)
+
+        assert result[0]["role"] == "user"
+        asst_idx = next(
+            i for i, m in enumerate(result)
+            if m["role"] == "assistant"
+            and any(b.get("type") == "tool_use" for b in m["content"] if isinstance(b, dict))
+        )
+        nxt = result[asst_idx + 1]
+        assert nxt["role"] == "user"
+        assert any(
+            isinstance(b, dict) and b.get("type") == "tool_result" and b.get("tool_use_id") == "toolu_1"
+            for b in nxt["content"]
+        )
+
 
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