fix(core): recover from hallucinated tool names instead of ending the scan

A tool call for a name Strix does not register raised ModelBehaviorError
from the SDK turn resolver, which nothing retries: the root agent's raise
tore down the whole scan and a sub-agent died before its status was set.
Opt into the SDK's tool_not_found_behavior="return_error_to_model" so the
unknown call comes back as a tool result and the agent self-corrects.

The setting landed in openai-agents 0.19.0, which requires openai>=2.45,
so both pins move.

.pre-commit-config.yaml

@@ -21,7 +21,7 @@ repos:
           fastapi,
           pytest,
           hatchling,
-          "openai-agents[litellm]==0.14.6",
+          "openai-agents[litellm]>=0.19.0,<0.20",
         ]
         args: [--install-types, --non-interactive]
 

pyproject.toml

@@ -33,8 +33,8 @@ classifiers = [
   "Programming Language :: Python :: 3.14",
 ]
 dependencies = [
-  "openai-agents[litellm]==0.14.6",
+  "openai-agents[litellm]>=0.19.0,<0.20",
-  "openai>=2.26.0,<2.45",
+  "openai>=2.45.0,<3",
   "litellm",
   "pydantic>=2.11.3",
   "pydantic-settings>=2.13.0",
@@ -233,6 +233,7 @@ ignore = [
 "strix/interface/auth_cli.py" = ["N802"]
 "tests/test_codex_streaming.py" = ["N802"]
 "tests/test_disable_streaming.py" = ["N802"]
+"tests/test_unknown_tool_recovery.py" = ["N802"]
 "tests/test_report_pdf.py" = ["S105", "S106"]
 # Stdlib HTTP handler overrides (do_GET/do_POST) and lazy imports that avoid a
 # circular dependency with strix.telemetry / strix.interface.viewer.report_pdf.

strix/core/runner.py

@@ -268,6 +268,9 @@ async def run_strix_scan(
             model_settings=model_settings,
             sandbox=SandboxRunConfig(client=bundle["client"], session=bundle["session"]),
             trace_include_sensitive_data=False,
+            # A hallucinated tool name is a recoverable model mistake, not a scan-ending
+            # error: hand it back as a tool result so the agent can correct itself.
+            tool_not_found_behavior="return_error_to_model",
         )
         hooks = ReportUsageHooks(
             model=resolved_model,

tests/test_runner_rate_limit.py

@@ -8,6 +8,7 @@ from typing import Any
 
 import httpx
 import pytest
+from agents import ModelSettings
 from openai import RateLimitError
 
 import strix.tools.notes.tools as notes_tools
@@ -64,7 +65,7 @@ async def test_persistent_rate_limit_stops_gracefully(
 
     monkeypatch.setattr(runner, "build_root_task", lambda _scan_config: "task")
     monkeypatch.setattr(runner, "build_scope_context", lambda _scan_config: "")
-    monkeypatch.setattr(runner, "make_model_settings", lambda *_args, **_kwargs: object())
+    monkeypatch.setattr(runner, "make_model_settings", lambda *_args, **_kwargs: ModelSettings())
     monkeypatch.setattr(runner, "build_strix_agent", lambda **_kwargs: object())
     monkeypatch.setattr(runner, "make_child_factory", lambda **_kwargs: lambda **_k: object())
     monkeypatch.setattr(runner, "open_agent_session", lambda _root_id, _db: object())

tests/test_runner_root_prompt.py

@@ -11,6 +11,7 @@ from typing import Any
 
 import httpx
 import pytest
+from agents import ModelSettings
 from openai import RateLimitError
 
 import strix.tools.notes.tools as notes_tools
@@ -74,7 +75,7 @@ def _patch_engine_scaffold(
 
     monkeypatch.setattr(runner, "build_root_task", lambda _scan_config: "task")
     monkeypatch.setattr(runner, "build_scope_context", lambda _scan_config: scope_context)
-    monkeypatch.setattr(runner, "make_model_settings", lambda *_args, **_kwargs: object())
+    monkeypatch.setattr(runner, "make_model_settings", lambda *_args, **_kwargs: ModelSettings())
 
     captured: dict[str, Any] = {}
 
@@ -87,7 +88,8 @@ def _patch_engine_scaffold(
     monkeypatch.setattr(runner, "make_child_factory", lambda **_kwargs: lambda **_k: object())
     monkeypatch.setattr(runner, "open_agent_session", lambda _root_id, _db: object())
 
-    async def _raise_rate_limit(*_args: Any, **_kwargs: Any) -> None:
+    async def _raise_rate_limit(*_args: Any, **kwargs: Any) -> None:
+        captured["run_config"] = kwargs.get("run_config")
         raise _make_rate_limit_error()
 
     monkeypatch.setattr(runner, "run_agent_loop", _raise_rate_limit)
@@ -176,3 +178,21 @@ async def test_root_prompt_options_default_to_none(
     kwargs = captured["kwargs"]
     assert kwargs["instructions_override"] is None
     assert kwargs["system_prompt_context"] == {"scope": "built-in"}
+
+
+@pytest.mark.asyncio
+async def test_unknown_tool_calls_are_returned_to_the_model(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Any,
+) -> None:
+    """A hallucinated tool name must not end the scan."""
+    captured = _patch_engine_scaffold(monkeypatch, tmp_path, {})
+
+    await runner.run_strix_scan(
+        scan_config={"targets": [], "scan_mode": "deep"},
+        scan_id="scan-unknown-tool",
+        image="img",
+        coordinator=AgentCoordinator(),
+    )
+
+    assert captured["run_config"].tool_not_found_behavior == "return_error_to_model"

tests/test_unknown_tool_recovery.py

@@ -0,0 +1,155 @@
+"""Tests for surviving a hallucinated tool name.
+
+Models regularly invent tool names that Strix does not register (``read_file``
+is a common one, borrowed from other agent frameworks). The SDK's default is to
+raise ``ModelBehaviorError``, which ends the whole run: nothing in Strix retries
+it, so one bad token discards a scan. The runner therefore opts into
+``tool_not_found_behavior="return_error_to_model"`` so the unknown call comes
+back as a tool result and the agent corrects itself on the next turn.
+"""
+
+from __future__ import annotations
+
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+from typing import TYPE_CHECKING, Any
+
+import pytest
+from agents import Agent, Runner, function_tool
+from agents.exceptions import ModelBehaviorError
+from agents.models.interface import Model, ModelProvider
+from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel
+from agents.run import RunConfig
+from openai import AsyncOpenAI
+
+from strix.config.models import _NonStreamingModel
+
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+
+_TURNS: list[dict[str, Any]] = []
+
+
+def _unknown_tool_call_completion() -> dict[str, Any]:
+    return {
+        "id": "chatcmpl-1",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "gw-model",
+        "choices": [
+            {
+                "index": 0,
+                "finish_reason": "tool_calls",
+                "message": {
+                    "role": "assistant",
+                    "content": None,
+                    "tool_calls": [
+                        {
+                            "id": "call_1",
+                            "type": "function",
+                            "function": {
+                                "name": "read_file",
+                                "arguments": '{"path": "/etc/passwd"}',
+                            },
+                        }
+                    ],
+                },
+            }
+        ],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 2, "total_tokens": 7},
+    }
+
+
+def _text_completion(text: str) -> dict[str, Any]:
+    return {
+        "id": "chatcmpl-2",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "gw-model",
+        "choices": [
+            {"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": text}}
+        ],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8},
+    }
+
+
+class _Handler(BaseHTTPRequestHandler):
+    """Calls an unregistered tool on turn 1, then answers on turn 2."""
+
+    def log_message(self, *args: Any) -> None:
+        pass
+
+    def do_POST(self) -> None:
+        length = int(self.headers.get("Content-Length", 0))
+        _TURNS.append(json.loads(self.rfile.read(length) or b"{}"))
+        completion = (
+            _unknown_tool_call_completion() if len(_TURNS) == 1 else _text_completion("recovered")
+        )
+        payload = json.dumps(completion).encode()
+        self.send_response(200)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(payload)))
+        self.end_headers()
+        self.wfile.write(payload)
+
+
+@pytest.fixture
+def gateway_url() -> Iterator[str]:
+    _TURNS.clear()
+    server = HTTPServer(("127.0.0.1", 0), _Handler)
+    thread = threading.Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    try:
+        yield f"http://127.0.0.1:{server.server_address[1]}/v1"
+    finally:
+        server.shutdown()
+        server.server_close()
+
+
+def _agent() -> Agent[Any]:
+    @function_tool
+    def real_tool(n: int) -> str:
+        return f"did {n}"
+
+    return Agent(name="Strix", instructions="test", tools=[real_tool], model="gw-model")
+
+
+def _run_config(base_url: str, **kwargs: Any) -> RunConfig:
+    class _Provider(ModelProvider):
+        def get_model(self, model_name: str | None) -> Model:  # noqa: ARG002
+            client = AsyncOpenAI(api_key="tok", base_url=base_url)
+            return _NonStreamingModel(OpenAIChatCompletionsModel("gw-model", openai_client=client))
+
+    return RunConfig(model_provider=_Provider(), **kwargs)
+
+
+@pytest.mark.asyncio
+async def test_unknown_tool_call_is_returned_to_the_model(gateway_url: str) -> None:
+    result = Runner.run_streamed(
+        _agent(),
+        input="go",
+        run_config=_run_config(gateway_url, tool_not_found_behavior="return_error_to_model"),
+    )
+    async for _ in result.stream_events():
+        pass
+
+    assert result.final_output == "recovered"
+    # The second turn carries the error back to the model as a tool result.
+    tool_results = [
+        item
+        for item in _TURNS[1]["messages"]
+        if item.get("role") == "tool" and item.get("tool_call_id") == "call_1"
+    ]
+    assert tool_results
+    assert "read_file" in str(tool_results[0]["content"])
+
+
+@pytest.mark.asyncio
+async def test_unknown_tool_call_kills_the_run_without_the_setting(gateway_url: str) -> None:
+    result = Runner.run_streamed(_agent(), input="go", run_config=_run_config(gateway_url))
+    with pytest.raises(ModelBehaviorError, match="read_file"):
+        async for _ in result.stream_events():
+            pass

uv.lock

@@ -1384,7 +1384,7 @@ wheels = [
 
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+version = "2.53.0"
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+    { url = "https://files.pythonhosted.org/packages/78/0f/cc6afea3542a5142c5d8fc8211c5e059a8375105d004a41dfa2c7948dbb0/openai-2.53.0-py3-none-any.whl", hash = "sha256:c694ffc747a3c4d1663ef2b07b811315a476164ee5efa3a993967349ebca7618", size = 1659829, upload-time = "2026-08-03T21:41:59.581Z" },
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 [[package]]
 name = "openai-agents"
-version = "0.14.6"
+version = "0.19.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "griffelib" },
@@ -1411,13 +1411,12 @@ dependencies = [
     { name = "openai" },
     { name = "pydantic" },
     { name = "requests" },
-    { name = "types-requests" },
     { name = "typing-extensions" },
     { name = "websockets" },
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+    { url = "https://files.pythonhosted.org/packages/3b/3a/bac1aa3405c0f11b4334ac999e881d08fa40fad1f3b7229a1ca222ada489/openai_agents-0.19.0-py3-none-any.whl", hash = "sha256:25392cff993eca7c75b0679ec8d0111faef20c517222c0193111097d0f70db7a", size = 928463, upload-time = "2026-07-27T22:49:24.405Z" },
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 [package.optional-dependencies]
@@ -2426,8 +2425,8 @@ requires-dist = [
     { name = "docker", specifier = ">=7.1.0" },
     { name = "google-auth", marker = "extra == 'vertex'", specifier = ">=2.0.0" },
     { name = "litellm" },
-    { name = "openai", specifier = ">=2.26.0,<2.45" },
+    { name = "openai", specifier = ">=2.45.0,<3" },
-    { name = "openai-agents", extras = ["litellm"], specifier = "==0.14.6" },
+    { name = "openai-agents", extras = ["litellm"], specifier = ">=0.19.0,<0.20" },
     { name = "pydantic", specifier = ">=2.11.3" },
     { name = "pydantic-settings", specifier = ">=2.13.0" },
     { name = "pypdf", specifier = ">=5.0" },
@@ -2550,18 +2549,6 @@ wheels = [
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