diff --git a/agent/context_compressor.py b/agent/context_compressor.py
index 1cf3bb1e358..4bccda13808 100644
--- a/agent/context_compressor.py
+++ b/agent/context_compressor.py
@@ -1768,7 +1768,15 @@ This compaction should PRIORITISE preserving all information related to the focu
             # retry (_generate_summary recursion) re-enters harmlessly.
             with aux_interrupt_protection():
                 response = call_llm(**call_kwargs)
-            content = response.choices[0].message.content
+            # ``_validate_llm_response`` only guarantees ``choices[0].message``
+            # exists, not that it's an object with ``.content``. Some
+            # OpenAI-compatible proxies / local backends return a dict- or
+            # str-shaped message; coerce defensively instead of crashing.
+            message = response.choices[0].message
+            if isinstance(message, dict):
+                content = message.get("content")
+            else:
+                content = getattr(message, "content", message)
             # Handle cases where content is not a string (e.g., dict from llama.cpp)
             if not isinstance(content, str):
                 content = str(content) if content else ""
diff --git a/tests/agent/test_context_compressor.py b/tests/agent/test_context_compressor.py
index 5edb412e507..cd23d13480c 100644
--- a/tests/agent/test_context_compressor.py
+++ b/tests/agent/test_context_compressor.py
@@ -510,6 +510,24 @@ class TestNonStringContent:
         assert summary is None
         assert c._summary_failure_cooldown_until > 0
 
+    def test_string_message_coerced_to_summary_content(self):
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock()]
+        mock_response.choices[0].message = "plain summary text"
+
+        with patch("agent.context_compressor.get_model_context_length", return_value=100000):
+            c = ContextCompressor(model="test", quiet_mode=True)
+
+        messages = [
+            {"role": "user", "content": "do something"},
+            {"role": "assistant", "content": "ok"},
+        ]
+
+        with patch("agent.context_compressor.call_llm", return_value=mock_response):
+            summary = c._generate_summary(messages)
+
+        assert summary == f"{SUMMARY_PREFIX}\nplain summary text"
+
     def test_summary_call_does_not_force_temperature(self):
         mock_response = MagicMock()
         mock_response.choices = [MagicMock()]