Initial import of NousResearch/hermes-agent

tests/agent/transports/test_bedrock_transport.py

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+"""Tests for the BedrockTransport."""
+
+import pytest
+from types import SimpleNamespace
+
+from agent.transports import get_transport
+from agent.transports.types import NormalizedResponse
+
+
+@pytest.fixture
+def transport():
+    import agent.transports.bedrock  # noqa: F401
+    return get_transport("bedrock_converse")
+
+
+class TestBedrockBasic:
+
+    def test_api_mode(self, transport):
+        assert transport.api_mode == "bedrock_converse"
+
+    def test_registered(self, transport):
+        assert transport is not None
+
+
+class TestBedrockBuildKwargs:
+
+    def test_basic_kwargs(self, transport):
+        msgs = [{"role": "user", "content": "Hello"}]
+        kw = transport.build_kwargs(model="anthropic.claude-3-5-sonnet-20241022-v2:0", messages=msgs)
+        assert kw["modelId"] == "anthropic.claude-3-5-sonnet-20241022-v2:0"
+        assert kw["__bedrock_converse__"] is True
+        assert kw["__bedrock_region__"] == "us-east-1"
+        assert "messages" in kw
+
+    def test_custom_region(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="anthropic.claude-3-5-sonnet-20241022-v2:0",
+            messages=msgs,
+            region="eu-west-1",
+        )
+        assert kw["__bedrock_region__"] == "eu-west-1"
+
+    def test_max_tokens(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="anthropic.claude-3-5-sonnet-20241022-v2:0",
+            messages=msgs,
+            max_tokens=8192,
+        )
+        assert kw["inferenceConfig"]["maxTokens"] == 8192
+
+
+class TestBedrockConvertTools:
+
+    def test_convert_tools(self, transport):
+        tools = [{
+            "type": "function",
+            "function": {
+                "name": "terminal",
+                "description": "Run commands",
+                "parameters": {"type": "object", "properties": {"command": {"type": "string"}}},
+            }
+        }]
+        result = transport.convert_tools(tools)
+        assert len(result) == 1
+        assert result[0]["toolSpec"]["name"] == "terminal"
+
+
+class TestBedrockValidate:
+
+    def test_none(self, transport):
+        assert transport.validate_response(None) is False
+
+    def test_raw_dict_valid(self, transport):
+        assert transport.validate_response({"output": {"message": {}}}) is True
+
+    def test_raw_dict_invalid(self, transport):
+        assert transport.validate_response({"error": "fail"}) is False
+
+    def test_normalized_valid(self, transport):
+        r = SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content="hi"))])
+        assert transport.validate_response(r) is True
+
+
+class TestBedrockMapFinishReason:
+
+    def test_end_turn(self, transport):
+        assert transport.map_finish_reason("end_turn") == "stop"
+
+    def test_tool_use(self, transport):
+        assert transport.map_finish_reason("tool_use") == "tool_calls"
+
+    def test_max_tokens(self, transport):
+        assert transport.map_finish_reason("max_tokens") == "length"
+
+    def test_guardrail(self, transport):
+        assert transport.map_finish_reason("guardrail_intervened") == "content_filter"
+
+    def test_unknown(self, transport):
+        assert transport.map_finish_reason("unknown") == "stop"
+
+
+class TestBedrockNormalize:
+
+    def _make_bedrock_response(self, text="Hello", tool_calls=None, stop_reason="end_turn"):
+        """Build a raw Bedrock converse response dict."""
+        content = []
+        if text:
+            content.append({"text": text})
+        if tool_calls:
+            for tc in tool_calls:
+                content.append({
+                    "toolUse": {
+                        "toolUseId": tc["id"],
+                        "name": tc["name"],
+                        "input": tc["input"],
+                    }
+                })
+        return {
+            "output": {"message": {"role": "assistant", "content": content}},
+            "stopReason": stop_reason,
+            "usage": {"inputTokens": 10, "outputTokens": 5, "totalTokens": 15},
+        }
+
+    def test_text_response(self, transport):
+        raw = self._make_bedrock_response(text="Hello world")
+        nr = transport.normalize_response(raw)
+        assert isinstance(nr, NormalizedResponse)
+        assert nr.content == "Hello world"
+        assert nr.finish_reason == "stop"
+
+    def test_tool_call_response(self, transport):
+        raw = self._make_bedrock_response(
+            text=None,
+            tool_calls=[{"id": "tool_1", "name": "terminal", "input": {"command": "ls"}}],
+            stop_reason="tool_use",
+        )
+        nr = transport.normalize_response(raw)
+        assert nr.finish_reason == "tool_calls"
+        assert len(nr.tool_calls) == 1
+        assert nr.tool_calls[0].name == "terminal"
+
+    def test_raw_reasoning_content_response(self, transport):
+        raw = {
+            "output": {
+                "message": {
+                    "role": "assistant",
+                    "content": [
+                        {"reasoningContent": {"text": "Let me think..."}},
+                        {"text": "Answer."},
+                    ],
+                }
+            },
+            "stopReason": "end_turn",
+            "usage": {"inputTokens": 10, "outputTokens": 5, "totalTokens": 15},
+        }
+        nr = transport.normalize_response(raw)
+        assert nr.reasoning == "Let me think..."
+        assert nr.content == "Answer."
+
+    def test_already_normalized_response(self, transport):
+        """Test normalize_response handles already-normalized SimpleNamespace (from dispatch site)."""
+        pre_normalized = SimpleNamespace(
+            choices=[SimpleNamespace(
+                message=SimpleNamespace(
+                    content="Hello from Bedrock",
+                    tool_calls=None,
+                    reasoning=None,
+                    reasoning_content=None,
+                ),
+                finish_reason="stop",
+            )],
+            usage=SimpleNamespace(prompt_tokens=10, completion_tokens=5, total_tokens=15),
+        )
+        nr = transport.normalize_response(pre_normalized)
+        assert isinstance(nr, NormalizedResponse)
+        assert nr.content == "Hello from Bedrock"
+        assert nr.finish_reason == "stop"
+        assert nr.usage is not None
+        assert nr.usage.prompt_tokens == 10

tests/agent/transports/test_chat_completions.py

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+"""Tests for the ChatCompletionsTransport."""
+
+import pytest
+from types import SimpleNamespace
+
+from agent.transports import get_transport
+from agent.transports.types import NormalizedResponse
+
+
+@pytest.fixture
+def transport():
+    import agent.transports.chat_completions  # noqa: F401
+    return get_transport("chat_completions")
+
+
+class TestChatCompletionsBasic:
+
+    def test_api_mode(self, transport):
+        assert transport.api_mode == "chat_completions"
+
+    def test_registered(self, transport):
+        assert transport is not None
+
+    def test_convert_tools_identity(self, transport):
+        tools = [{"type": "function", "function": {"name": "test", "parameters": {}}}]
+        assert transport.convert_tools(tools) is tools
+
+    def test_convert_messages_no_codex_leaks(self, transport):
+        msgs = [{"role": "user", "content": "hi"}]
+        result = transport.convert_messages(msgs)
+        assert result is msgs  # no copy needed
+
+    def test_convert_messages_strips_codex_fields(self, transport):
+        msgs = [
+            {"role": "assistant", "content": "ok", "codex_reasoning_items": [{"id": "rs_1"}],
+             "codex_message_items": [{"id": "msg_1", "type": "message"}],
+             "tool_calls": [{"id": "call_1", "call_id": "call_1", "response_item_id": "fc_1",
+                            "type": "function", "function": {"name": "t", "arguments": "{}"}}]},
+        ]
+        result = transport.convert_messages(msgs)
+        assert "codex_reasoning_items" not in result[0]
+        assert "codex_message_items" not in result[0]
+        assert "call_id" not in result[0]["tool_calls"][0]
+        assert "response_item_id" not in result[0]["tool_calls"][0]
+        # Original list untouched (deepcopy-on-demand)
+        assert "codex_reasoning_items" in msgs[0]
+        assert "codex_message_items" in msgs[0]
+
+    def test_convert_messages_strips_tool_name(self, transport):
+        """Internal `tool_name` (used for FTS indexing in the SQLite store) is
+        not part of the OpenAI Chat Completions schema. Strict providers like
+        Moonshot/Kimi reject it with HTTP 400 'Extra inputs are not permitted'.
+        """
+        msgs = [
+            {"role": "user", "content": "hi"},
+            {"role": "assistant", "content": None,
+             "tool_calls": [{"id": "call_1", "type": "function",
+                             "function": {"name": "execute_code", "arguments": "{}"}}]},
+            {"role": "tool", "tool_call_id": "call_1", "tool_name": "execute_code",
+             "content": "result"},
+        ]
+        result = transport.convert_messages(msgs)
+        assert "tool_name" not in result[2]
+        assert result[2]["content"] == "result"
+        assert result[2]["tool_call_id"] == "call_1"
+        # Original list untouched (deepcopy-on-demand)
+        assert msgs[2]["tool_name"] == "execute_code"
+
+    def test_convert_messages_strips_internal_scaffolding_markers(self, transport):
+        """Hermes-internal ``_``-prefixed markers must never reach the wire.
+
+        The empty-response recovery path appends synthetic messages tagged
+        with ``_empty_recovery_synthetic``; permissive providers ignore the
+        unknown key, but strict gateways (opencode-go, codex.nekos.me)
+        reject the request, poisoning every later turn in the session.
+        """
+        msgs = [
+            {"role": "user", "content": "run the task"},
+            {"role": "assistant", "content": "(empty)", "_empty_recovery_synthetic": True},
+            {"role": "user", "content": "continue", "_empty_recovery_synthetic": True},
+            {"role": "assistant", "content": "done", "_thinking_prefill": True,
+             "_empty_terminal_sentinel": True},
+        ]
+        result = transport.convert_messages(msgs)
+        for m in result:
+            assert not any(k.startswith("_") for k in m), m
+        # Visible content preserved
+        assert result[1]["content"] == "(empty)"
+        assert result[2]["content"] == "continue"
+        # Original list untouched (deepcopy-on-demand)
+        assert msgs[1]["_empty_recovery_synthetic"] is True
+
+    def test_convert_messages_clean_list_is_identity(self, transport):
+        """A list with no internal/codex keys is returned as-is (no copy)."""
+        msgs = [
+            {"role": "user", "content": "hi"},
+            {"role": "assistant", "content": "hello"},
+        ]
+        assert transport.convert_messages(msgs) is msgs
+
+
+class TestChatCompletionsBuildKwargs:
+
+    def test_basic_kwargs(self, transport):
+        msgs = [{"role": "user", "content": "Hello"}]
+        kw = transport.build_kwargs(model="gpt-4o", messages=msgs, timeout=30.0)
+        assert kw["model"] == "gpt-4o"
+        assert kw["messages"][0]["content"] == "Hello"
+        assert kw["timeout"] == 30.0
+
+    def test_developer_role_swap(self, transport):
+        msgs = [{"role": "system", "content": "You are helpful"}, {"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(model="gpt-5.4", messages=msgs, model_lower="gpt-5.4")
+        assert kw["messages"][0]["role"] == "developer"
+
+    def test_no_developer_swap_for_non_gpt5(self, transport):
+        msgs = [{"role": "system", "content": "You are helpful"}, {"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(model="claude-sonnet-4", messages=msgs, model_lower="claude-sonnet-4")
+        assert kw["messages"][0]["role"] == "system"
+
+    def test_tools_included(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        tools = [{"type": "function", "function": {"name": "test", "parameters": {}}}]
+        kw = transport.build_kwargs(model="gpt-4o", messages=msgs, tools=tools)
+        assert kw["tools"] == tools
+
+    def test_openrouter_provider_prefs(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("openrouter")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            provider_profile=profile,
+            provider_preferences={"only": ["openai"]},
+        )
+        assert kw["extra_body"]["provider"] == {"only": ["openai"]}
+
+    def test_openrouter_pareto_min_coding_score(self, transport):
+        """Profile path: model=openrouter/pareto-code + score → plugins block."""
+        from providers import get_provider_profile
+        profile = get_provider_profile("openrouter")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="openrouter/pareto-code", messages=msgs,
+            provider_profile=profile,
+            openrouter_min_coding_score=0.65,
+        )
+        assert kw["extra_body"]["plugins"] == [
+            {"id": "pareto-router", "min_coding_score": 0.65}
+        ]
+
+    def test_openrouter_pareto_score_ignored_for_other_models(self, transport):
+        """Score must not be emitted for any model other than openrouter/pareto-code."""
+        from providers import get_provider_profile
+        profile = get_provider_profile("openrouter")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="anthropic/claude-sonnet-4.6", messages=msgs,
+            provider_profile=profile,
+            openrouter_min_coding_score=0.65,
+        )
+        assert "plugins" not in (kw.get("extra_body") or {})
+
+    def test_openrouter_pareto_score_omitted_when_unset(self, transport):
+        """No score → no plugins block (router uses its omission default = strongest coder)."""
+        from providers import get_provider_profile
+        profile = get_provider_profile("openrouter")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="openrouter/pareto-code", messages=msgs,
+            provider_profile=profile,
+            openrouter_min_coding_score=None,
+        )
+        assert "plugins" not in (kw.get("extra_body") or {})
+
+    def test_openrouter_pareto_score_out_of_range_dropped(self, transport):
+        """Out-of-range scores must be silently dropped, not forwarded."""
+        from providers import get_provider_profile
+        profile = get_provider_profile("openrouter")
+        msgs = [{"role": "user", "content": "Hi"}]
+        for bad in (1.5, -0.1, "not-a-number"):
+            kw = transport.build_kwargs(
+                model="openrouter/pareto-code", messages=msgs,
+                provider_profile=profile,
+                openrouter_min_coding_score=bad,
+            )
+            assert "plugins" not in (kw.get("extra_body") or {}), f"bad={bad!r}"
+
+    def test_openrouter_pareto_legacy_path(self, transport):
+        """Legacy flag path (no profile loaded) must also emit the plugins block."""
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="openrouter/pareto-code", messages=msgs,
+            is_openrouter=True,
+            openrouter_min_coding_score=0.8,
+        )
+        assert kw["extra_body"]["plugins"] == [
+            {"id": "pareto-router", "min_coding_score": 0.8}
+        ]
+
+    def test_nous_tags(self, transport):
+        from agent.portal_tags import nous_portal_tags
+        from providers import get_provider_profile
+        profile = get_provider_profile("nous")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(model="gpt-4o", messages=msgs, provider_profile=profile)
+        assert kw["extra_body"]["tags"] == nous_portal_tags()
+
+    def test_reasoning_default(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            supports_reasoning=True,
+        )
+        assert kw["extra_body"]["reasoning"] == {"enabled": True, "effort": "medium"}
+
+    def test_nous_omits_disabled_reasoning(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("nous")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            provider_profile=profile,
+            supports_reasoning=True,
+            reasoning_config={"enabled": False},
+        )
+        # Nous rejects enabled=false; reasoning omitted entirely
+        assert "reasoning" not in kw.get("extra_body", {})
+
+    def test_ollama_num_ctx(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("custom")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="llama3", messages=msgs,
+            provider_profile=profile,
+            ollama_num_ctx=32768,
+        )
+        assert kw["extra_body"]["options"]["num_ctx"] == 32768
+
+    def test_custom_think_false(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("custom")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="qwen3", messages=msgs,
+            provider_profile=profile,
+            reasoning_config={"effort": "none"},
+        )
+        assert kw["extra_body"]["think"] is False
+
+    def test_gemini_native_without_explicit_reasoning_config_keeps_existing_behavior(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-3-flash-preview",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta",
+        )
+        assert "thinking_config" not in kw.get("extra_body", {})
+        assert "google" not in kw.get("extra_body", {})
+        assert "extra_body" not in kw.get("extra_body", {})
+
+    def test_gemini_native_flash_reasoning_maps_to_top_level_thinking_config(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-3-flash-preview",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta",
+            reasoning_config={"enabled": True, "effort": "high"},
+        )
+        assert kw["extra_body"]["thinking_config"] == {
+            "includeThoughts": True,
+            "thinkingLevel": "high",
+        }
+
+    def test_gemini_openai_compat_flash_reasoning_maps_to_nested_google_thinking_config(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-3-flash-preview",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta/openai",
+            reasoning_config={"enabled": True, "effort": "high"},
+        )
+        assert "thinking_config" not in kw["extra_body"]
+        assert kw["extra_body"]["extra_body"]["google"]["thinking_config"] == {
+            "include_thoughts": True,
+            "thinking_level": "high",
+        }
+
+    def test_gemini_native_25_reasoning_only_enables_visible_thoughts(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-2.5-flash",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta",
+            reasoning_config={"enabled": True, "effort": "high"},
+        )
+        assert kw["extra_body"]["thinking_config"] == {
+            "includeThoughts": True,
+        }
+
+    def test_gemini_openai_compat_pro_reasoning_clamps_to_supported_levels(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="google/gemini-3.1-pro-preview",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta/openai",
+            reasoning_config={"enabled": True, "effort": "medium"},
+        )
+        assert kw["extra_body"]["extra_body"]["google"]["thinking_config"] == {
+            "include_thoughts": True,
+            "thinking_level": "low",
+        }
+
+    def test_gemini_native_disabled_reasoning_hides_thoughts(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-3-flash-preview",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta",
+            reasoning_config={"enabled": False},
+        )
+        assert kw["extra_body"]["thinking_config"] == {
+            "includeThoughts": False,
+        }
+
+    def test_gemini_openai_compat_xhigh_clamps_to_high(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-3-flash-preview",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta/openai",
+            reasoning_config={"enabled": True, "effort": "xhigh"},
+        )
+        assert kw["extra_body"]["extra_body"]["google"]["thinking_config"]["thinking_level"] == "high"
+
+    def test_google_gemini_cli_keeps_top_level_thinking_config(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-3-flash-preview",
+            messages=msgs,
+            provider_name="google-gemini-cli",
+            reasoning_config={"enabled": True, "effort": "high"},
+        )
+        assert kw["extra_body"]["thinking_config"] == {
+            "includeThoughts": True,
+            "thinkingLevel": "high",
+        }
+        assert "google" not in kw["extra_body"]
+
+    def test_gemini_flash_minimal_clamps_to_low(self, transport):
+        # Gemini 3 Flash documents low/medium/high; "minimal" isn't accepted,
+        # so clamp it down to "low" rather than forwarding it verbatim.
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemini-3-flash-preview",
+            messages=msgs,
+            provider_name="gemini",
+            base_url="https://generativelanguage.googleapis.com/v1beta/openai",
+            reasoning_config={"enabled": True, "effort": "minimal"},
+        )
+        assert kw["extra_body"]["extra_body"]["google"]["thinking_config"] == {
+            "include_thoughts": True,
+            "thinking_level": "low",
+        }
+
+    def test_gemma_does_not_receive_thinking_config(self, transport):
+        # The `gemini` provider also serves Gemma (e.g. `gemma-4-31b-it`),
+        # but Gemma rejects `thinking_config` with HTTP 400 (#17426). Even
+        # when Hermes has reasoning enabled, the field must be omitted for
+        # non-Gemini models on this provider.
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemma-4-31b-it",
+            messages=msgs,
+            provider_name="gemini",
+            reasoning_config={"enabled": True, "effort": "high"},
+        )
+        assert "thinking_config" not in kw.get("extra_body", {})
+
+    def test_gemma_disabled_reasoning_still_omits_thinking_config(self, transport):
+        # The `Unknown name 'thinking_config': Cannot find field` rejection
+        # fires even on `{"includeThoughts": False}` — the entire field must
+        # be absent, not just disabled. (#17426)
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gemma-4-31b-it",
+            messages=msgs,
+            provider_name="gemini",
+            reasoning_config={"enabled": False},
+        )
+        assert "thinking_config" not in kw.get("extra_body", {})
+
+    def test_google_prefixed_gemma_also_omits_thinking_config(self, transport):
+        # OpenRouter-style `google/gemma-...` IDs hit the same provider path
+        # and must also omit `thinking_config`. The existing `google/`
+        # prefix-stripping must not accidentally classify Gemma as Gemini.
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="google/gemma-4-31b-it",
+            messages=msgs,
+            provider_name="gemini",
+            reasoning_config={"enabled": True, "effort": "medium"},
+        )
+        assert "thinking_config" not in kw.get("extra_body", {})
+
+    def test_max_tokens_with_fn(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            max_tokens=4096,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        assert kw["max_tokens"] == 4096
+
+    def test_ephemeral_overrides_max_tokens(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            max_tokens=4096,
+            ephemeral_max_output_tokens=2048,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        assert kw["max_tokens"] == 2048
+
+    def test_nvidia_default_max_tokens(self, transport):
+        """NVIDIA max_tokens=16384 is now set via ProviderProfile, not legacy flag."""
+        from providers import get_provider_profile
+
+        profile = get_provider_profile("nvidia")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="nvidia/llama-3.1-405b-instruct",
+            messages=msgs,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+            provider_profile=profile,
+        )
+        assert kw["max_tokens"] == 16384
+
+    def test_qwen_default_max_tokens(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("qwen-oauth")
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="qwen3-coder-plus", messages=msgs,
+            provider_profile=profile,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        # Qwen default: 65536 from profile.default_max_tokens
+        assert kw["max_tokens"] == 65536
+
+    def test_anthropic_max_output_for_claude_on_aggregator(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="anthropic/claude-sonnet-4.6", messages=msgs,
+            is_openrouter=True,
+            anthropic_max_output=64000,
+        )
+        # Set as plain max_tokens (not via fn) because the aggregator proxies to
+        # Anthropic Messages API which requires the field.
+        assert kw["max_tokens"] == 64000
+
+    def test_request_overrides_last(self, transport):
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            request_overrides={"service_tier": "priority"},
+        )
+        assert kw["service_tier"] == "priority"
+
+    def test_fixed_temperature(self, transport):
+        """Fixed temperature is now set via ProviderProfile.fixed_temperature."""
+        from providers.base import ProviderProfile
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            provider_profile=ProviderProfile(name="_t", fixed_temperature=0.6),
+        )
+        assert kw["temperature"] == 0.6
+
+    def test_omit_temperature(self, transport):
+        """Omit temperature is set via ProviderProfile with OMIT_TEMPERATURE sentinel."""
+        from providers.base import ProviderProfile, OMIT_TEMPERATURE
+        msgs = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-4o", messages=msgs,
+            provider_profile=ProviderProfile(name="_t", fixed_temperature=OMIT_TEMPERATURE),
+        )
+        assert "temperature" not in kw
+
+
+class TestChatCompletionsKimi:
+    """Regression tests for the Kimi/Moonshot quirks migrated into the transport."""
+
+    def test_kimi_max_tokens_default(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("kimi-coding")
+        kw = transport.build_kwargs(
+            model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
+            provider_profile=profile,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        # Kimi CLI default: 32000 from KimiProfile.default_max_tokens
+        assert kw["max_tokens"] == 32000
+
+    def test_kimi_reasoning_effort_top_level(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("kimi-coding")
+        kw = transport.build_kwargs(
+            model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
+            provider_profile=profile,
+            reasoning_config={"effort": "high"},
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        # Kimi requires reasoning_effort as a top-level parameter
+        assert kw["reasoning_effort"] == "high"
+
+    def test_kimi_reasoning_effort_omitted_when_thinking_disabled(self, transport):
+        kw = transport.build_kwargs(
+            model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
+            is_kimi=True,
+            reasoning_config={"enabled": False},
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        # Mirror Kimi CLI: omit reasoning_effort entirely when thinking off
+        assert "reasoning_effort" not in kw
+
+    def test_kimi_thinking_enabled_extra_body(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("kimi-coding")
+        kw = transport.build_kwargs(
+            model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
+            provider_profile=profile,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        assert kw["extra_body"]["thinking"] == {"type": "enabled"}
+
+    def test_kimi_thinking_disabled_extra_body(self, transport):
+        from providers import get_provider_profile
+        profile = get_provider_profile("kimi-coding")
+        kw = transport.build_kwargs(
+            model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
+            provider_profile=profile,
+            reasoning_config={"enabled": False},
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        assert kw["extra_body"]["thinking"] == {"type": "disabled"}
+
+    def test_moonshot_tool_schemas_are_sanitized_by_model_name(self, transport):
+        """Aggregator routes (Nous, OpenRouter) hit Moonshot by model name, not base URL."""
+        tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": "search",
+                    "description": "Search",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "q": {"description": "query"},  # missing type
+                        },
+                    },
+                },
+            },
+        ]
+        kw = transport.build_kwargs(
+            model="moonshotai/kimi-k2.6",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=tools,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        assert kw["tools"][0]["function"]["parameters"]["properties"]["q"]["type"] == "string"
+
+    def test_non_moonshot_tools_are_not_mutated(self, transport):
+        """Other models don't go through the Moonshot sanitizer."""
+        original_params = {
+            "type": "object",
+            "properties": {"q": {"description": "query"}},  # missing type
+        }
+        tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": "search",
+                    "description": "Search",
+                    "parameters": original_params,
+                },
+            },
+        ]
+        kw = transport.build_kwargs(
+            model="anthropic/claude-sonnet-4.6",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=tools,
+            max_tokens_param_fn=lambda n: {"max_tokens": n},
+        )
+        # The parameters dict is passed through untouched (no synthetic type)
+        assert "type" not in kw["tools"][0]["function"]["parameters"]["properties"]["q"]
+
+
+class TestChatCompletionsLmStudioReasoning:
+    """LM Studio publishes per-model reasoning ``allowed_options``. When the
+    user requests an effort the model can't honor (e.g. ``high`` on a
+    toggle-style ``["off","on"]`` model), the transport omits
+    ``reasoning_effort`` so LM Studio falls back to the model's default —
+    silently downgrading "high" to "low" would mislead the user.
+    """
+
+    def test_omits_effort_when_high_not_allowed_toggle(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-oss", messages=[{"role": "user", "content": "Hi"}],
+            is_lmstudio=True,
+            supports_reasoning=True,
+            reasoning_config={"effort": "high"},
+            lmstudio_reasoning_options=["off", "on"],
+        )
+        assert "reasoning_effort" not in kw
+
+    def test_omits_effort_when_high_not_allowed_minimal_low(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-oss", messages=[{"role": "user", "content": "Hi"}],
+            is_lmstudio=True,
+            supports_reasoning=True,
+            reasoning_config={"effort": "high"},
+            lmstudio_reasoning_options=["off", "minimal", "low"],
+        )
+        assert "reasoning_effort" not in kw
+
+    def test_passes_through_when_effort_allowed(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-oss", messages=[{"role": "user", "content": "Hi"}],
+            is_lmstudio=True,
+            supports_reasoning=True,
+            reasoning_config={"effort": "high"},
+            lmstudio_reasoning_options=["off", "low", "medium", "high"],
+        )
+        assert kw["reasoning_effort"] == "high"
+
+    def test_passes_through_aliased_on_for_toggle(self, transport):
+        # User has reasoning enabled at the default "medium"; toggle model
+        # publishes ["off","on"] which aliases to {"none","medium"}, so the
+        # default request is honorable and gets sent.
+        kw = transport.build_kwargs(
+            model="gpt-oss", messages=[{"role": "user", "content": "Hi"}],
+            is_lmstudio=True,
+            supports_reasoning=True,
+            reasoning_config={"effort": "medium"},
+            lmstudio_reasoning_options=["off", "on"],
+        )
+        assert kw["reasoning_effort"] == "medium"
+
+    def test_disabled_keeps_none_when_off_allowed(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-oss", messages=[{"role": "user", "content": "Hi"}],
+            is_lmstudio=True,
+            supports_reasoning=True,
+            reasoning_config={"enabled": False},
+            lmstudio_reasoning_options=["off", "on"],
+        )
+        assert kw["reasoning_effort"] == "none"
+
+    def test_no_options_falls_back_to_legacy_behavior(self, transport):
+        # When the probe failed or returned nothing, allowed_options is unknown;
+        # send whatever the user picked rather than blocking the request.
+        kw = transport.build_kwargs(
+            model="gpt-oss", messages=[{"role": "user", "content": "Hi"}],
+            is_lmstudio=True,
+            supports_reasoning=True,
+            reasoning_config={"effort": "high"},
+            lmstudio_reasoning_options=None,
+        )
+        assert kw["reasoning_effort"] == "high"
+
+
+class TestChatCompletionsValidate:
+
+    def test_none(self, transport):
+        assert transport.validate_response(None) is False
+
+    def test_no_choices(self, transport):
+        r = SimpleNamespace(choices=None)
+        assert transport.validate_response(r) is False
+
+    def test_empty_choices(self, transport):
+        r = SimpleNamespace(choices=[])
+        assert transport.validate_response(r) is False
+
+    def test_valid(self, transport):
+        r = SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content="hi"))])
+        assert transport.validate_response(r) is True
+
+
+class TestChatCompletionsNormalize:
+
+    def test_text_response(self, transport):
+        r = SimpleNamespace(
+            choices=[SimpleNamespace(
+                message=SimpleNamespace(content="Hello", tool_calls=None, reasoning_content=None),
+                finish_reason="stop",
+            )],
+            usage=SimpleNamespace(prompt_tokens=10, completion_tokens=5, total_tokens=15),
+        )
+        nr = transport.normalize_response(r)
+        assert isinstance(nr, NormalizedResponse)
+        assert nr.content == "Hello"
+        assert nr.finish_reason == "stop"
+        assert nr.tool_calls is None
+
+    def test_tool_call_response(self, transport):
+        tc = SimpleNamespace(
+            id="call_123",
+            function=SimpleNamespace(name="terminal", arguments='{"command": "ls"}'),
+        )
+        r = SimpleNamespace(
+            choices=[SimpleNamespace(
+                message=SimpleNamespace(content=None, tool_calls=[tc], reasoning_content=None),
+                finish_reason="tool_calls",
+            )],
+            usage=SimpleNamespace(prompt_tokens=10, completion_tokens=20, total_tokens=30),
+        )
+        nr = transport.normalize_response(r)
+        assert len(nr.tool_calls) == 1
+        assert nr.tool_calls[0].name == "terminal"
+        assert nr.tool_calls[0].id == "call_123"
+
+    def test_tool_call_extra_content_preserved(self, transport):
+        """Gemini 3 thinking models attach extra_content with thought_signature
+        on tool_calls.  Without this replay on the next turn, the API rejects
+        the request with 400.  The transport MUST surface extra_content so the
+        agent loop can write it back into the assistant message."""
+        tc = SimpleNamespace(
+            id="call_gem",
+            function=SimpleNamespace(name="terminal", arguments='{"command": "ls"}'),
+            extra_content={"google": {"thought_signature": "SIG_ABC123"}},
+        )
+        r = SimpleNamespace(
+            choices=[SimpleNamespace(
+                message=SimpleNamespace(content=None, tool_calls=[tc], reasoning_content=None),
+                finish_reason="tool_calls",
+            )],
+            usage=None,
+        )
+        nr = transport.normalize_response(r)
+        assert nr.tool_calls[0].provider_data == {
+            "extra_content": {"google": {"thought_signature": "SIG_ABC123"}}
+        }
+
+    def test_reasoning_content_preserved_separately(self, transport):
+        """DeepSeek/Moonshot use reasoning_content distinct from reasoning.
+        Don't merge them — the thinking-prefill retry check reads each field
+        separately."""
+        r = SimpleNamespace(
+            choices=[SimpleNamespace(
+                message=SimpleNamespace(
+                    content=None, tool_calls=None,
+                    reasoning="summary text",
+                    reasoning_content="detailed scratchpad",
+                ),
+                finish_reason="stop",
+            )],
+            usage=None,
+        )
+        nr = transport.normalize_response(r)
+        assert nr.reasoning == "summary text"
+        assert nr.provider_data == {"reasoning_content": "detailed scratchpad"}
+
+    def test_empty_reasoning_content_preserved(self, transport):
+        """DeepSeek can require an explicit empty reasoning_content replay field."""
+        r = SimpleNamespace(
+            choices=[SimpleNamespace(
+                message=SimpleNamespace(
+                    content=None,
+                    tool_calls=None,
+                    reasoning=None,
+                    reasoning_content="",
+                ),
+                finish_reason="stop",
+            )],
+            usage=None,
+        )
+        nr = transport.normalize_response(r)
+        assert nr.provider_data == {"reasoning_content": ""}
+        assert nr.reasoning_content == ""
+
+    def test_reasoning_content_preserved_from_model_extra(self, transport):
+        """OpenAI SDK can expose provider-specific DeepSeek fields via model_extra."""
+        r = SimpleNamespace(
+            choices=[SimpleNamespace(
+                message=SimpleNamespace(
+                    content=None,
+                    tool_calls=None,
+                    reasoning=None,
+                    model_extra={"reasoning_content": "model-extra scratchpad"},
+                ),
+                finish_reason="stop",
+            )],
+            usage=None,
+        )
+        nr = transport.normalize_response(r)
+        assert nr.provider_data == {"reasoning_content": "model-extra scratchpad"}
+
+
+class TestChatCompletionsCacheStats:
+
+    def test_no_usage(self, transport):
+        r = SimpleNamespace(usage=None)
+        assert transport.extract_cache_stats(r) is None
+
+    def test_no_details(self, transport):
+        r = SimpleNamespace(usage=SimpleNamespace(prompt_tokens_details=None))
+        assert transport.extract_cache_stats(r) is None
+
+    def test_with_cache(self, transport):
+        details = SimpleNamespace(cached_tokens=500, cache_write_tokens=100)
+        r = SimpleNamespace(usage=SimpleNamespace(prompt_tokens_details=details))
+        result = transport.extract_cache_stats(r)
+        assert result == {"cached_tokens": 500, "creation_tokens": 100}

tests/agent/transports/test_codex_app_server_runtime.py

@@ -0,0 +1,298 @@
+"""Tests for the optional codex app-server runtime gate.
+
+These are unit tests for the api_mode rewriter and the wire-level transport
+module. They do NOT require the `codex` CLI to be installed — that's
+covered by a separate live test gated on `codex --version`.
+"""
+
+from __future__ import annotations
+
+import pytest
+
+from hermes_cli.runtime_provider import (
+    _VALID_API_MODES,
+    _maybe_apply_codex_app_server_runtime,
+)
+
+
+class TestApiModeRegistration:
+    """The new api_mode must be registered or downstream parsing rejects it."""
+
+    def test_codex_app_server_is_a_valid_api_mode(self) -> None:
+        assert "codex_app_server" in _VALID_API_MODES
+
+    def test_existing_api_modes_still_present(self) -> None:
+        # Regression guard: don't accidentally delete other api_modes when
+        # touching this set.
+        for mode in (
+            "chat_completions",
+            "codex_responses",
+            "anthropic_messages",
+            "bedrock_converse",
+        ):
+            assert mode in _VALID_API_MODES
+
+
+class TestMaybeApplyCodexAppServerRuntime:
+    """The opt-in helper that rewrites api_mode → codex_app_server."""
+
+    @pytest.mark.parametrize(
+        "model_cfg",
+        [
+            None,
+            {},
+            {"openai_runtime": ""},
+            {"openai_runtime": "auto"},
+            {"openai_runtime": "AUTO"},
+            {"other_key": "codex_app_server"},  # wrong key
+        ],
+    )
+    def test_default_off_for_openai(self, model_cfg) -> None:
+        """Default behavior is preserved when the flag is unset/auto."""
+        got = _maybe_apply_codex_app_server_runtime(
+            provider="openai", api_mode="chat_completions", model_cfg=model_cfg
+        )
+        assert got == "chat_completions"
+
+    def test_opt_in_rewrites_openai(self) -> None:
+        got = _maybe_apply_codex_app_server_runtime(
+            provider="openai",
+            api_mode="chat_completions",
+            model_cfg={"openai_runtime": "codex_app_server"},
+        )
+        assert got == "codex_app_server"
+
+    def test_opt_in_rewrites_openai_codex(self) -> None:
+        got = _maybe_apply_codex_app_server_runtime(
+            provider="openai-codex",
+            api_mode="codex_responses",
+            model_cfg={"openai_runtime": "codex_app_server"},
+        )
+        assert got == "codex_app_server"
+
+    def test_case_insensitive(self) -> None:
+        got = _maybe_apply_codex_app_server_runtime(
+            provider="openai",
+            api_mode="chat_completions",
+            model_cfg={"openai_runtime": "Codex_App_Server"},
+        )
+        assert got == "codex_app_server"
+
+    @pytest.mark.parametrize(
+        "provider",
+        [
+            "anthropic",
+            "openrouter",
+            "xai",
+            "qwen-oauth",
+            "google-gemini-cli",
+            "opencode-zen",
+            "bedrock",
+            "",
+        ],
+    )
+    def test_other_providers_never_rerouted(self, provider) -> None:
+        """Non-OpenAI providers MUST NOT be rerouted even with the flag set —
+        codex's app-server can only run OpenAI/Codex auth flows."""
+        got = _maybe_apply_codex_app_server_runtime(
+            provider=provider,
+            api_mode="anthropic_messages",
+            model_cfg={"openai_runtime": "codex_app_server"},
+        )
+        assert got == "anthropic_messages", (
+            f"provider={provider!r} should not be rerouted to codex_app_server"
+        )
+
+
+class TestCodexAppServerModule:
+    """Module-surface tests for the JSON-RPC speaker. Don't require codex CLI."""
+
+    def test_module_imports(self) -> None:
+        from agent.transports import codex_app_server
+
+        assert codex_app_server.MIN_CODEX_VERSION >= (0, 1, 0)
+        assert callable(codex_app_server.parse_codex_version)
+        assert callable(codex_app_server.check_codex_binary)
+
+    def test_parse_codex_version_valid(self) -> None:
+        from agent.transports.codex_app_server import parse_codex_version
+
+        assert parse_codex_version("codex-cli 0.130.0") == (0, 130, 0)
+        assert parse_codex_version("codex-cli 1.2.3 (extra metadata)") == (1, 2, 3)
+        assert parse_codex_version("codex 99.0.1\n") == (99, 0, 1)
+
+    def test_parse_codex_version_invalid(self) -> None:
+        from agent.transports.codex_app_server import parse_codex_version
+
+        assert parse_codex_version("nope") is None
+        assert parse_codex_version("") is None
+        assert parse_codex_version(None) is None  # type: ignore[arg-type]
+
+    def test_check_binary_handles_missing_executable(self) -> None:
+        from agent.transports.codex_app_server import check_codex_binary
+
+        ok, msg = check_codex_binary(codex_bin="/nonexistent/codex/binary/path")
+        assert ok is False
+        assert "not found" in msg.lower() or "no such" in msg.lower()
+
+    def test_codex_error_class_is_runtimeerror(self) -> None:
+        from agent.transports.codex_app_server import CodexAppServerError
+
+        err = CodexAppServerError(code=-32600, message="boom")
+        assert isinstance(err, RuntimeError)
+        assert "boom" in str(err)
+        assert "-32600" in str(err)
+
+
+class TestSpawnEnvIsolation:
+    """The codex spawn must NOT rewrite HOME — codex's shell tool spawns
+    subprocesses (gh, git, npm, aws, gcloud, ...) that need to find their
+    config in the real user $HOME. CODEX_HOME isolates codex's own state,
+    HOME stays unchanged.
+
+    OpenClaw hit this footgun (openclaw/openclaw#81562) — they were
+    rewriting HOME to a synthetic per-agent dir alongside CODEX_HOME,
+    and then `gh auth status` / git config / etc. all broke inside codex
+    shell calls. We avoid the same bug by only overlaying CODEX_HOME and
+    RUST_LOG on top of os.environ.copy().
+    """
+
+    def test_spawn_env_preserves_HOME(self, monkeypatch):
+        """The spawn env must contain the parent process's HOME unchanged.
+        Verifies via a subprocess-monkey-patch."""
+        import subprocess
+        from agent.transports import codex_app_server as cas
+
+        captured = {}
+
+        class FakePopen:
+            def __init__(self, cmd, *args, **kwargs):
+                captured["env"] = kwargs.get("env", {}).copy()
+                # Provide minimal Popen surface so __init__ doesn't crash
+                # on attribute access during construction.
+                self.stdin = None
+                self.stdout = None
+                self.stderr = None
+                self.pid = 1
+                self.returncode = None
+
+            def poll(self):
+                return None
+
+            def terminate(self):
+                pass
+
+            def wait(self, timeout=None):
+                return 0
+
+            def kill(self):
+                pass
+
+        monkeypatch.setattr(subprocess, "Popen", FakePopen)
+        monkeypatch.setenv("HOME", "/users/alice")
+
+        client = cas.CodexAppServerClient(codex_bin="codex")
+        client._closed = True  # so close() is a no-op
+
+        # The spawn env must have HOME=/users/alice unchanged
+        assert captured["env"].get("HOME") == "/users/alice", (
+            f"HOME got rewritten in codex spawn env: "
+            f"{captured['env'].get('HOME')!r}. Codex's shell tool's "
+            "subprocesses (gh, git, aws, npm) need the user's real HOME."
+        )
+
+    def test_spawn_env_sets_CODEX_HOME_when_provided(self, monkeypatch):
+        """CODEX_HOME isolation must still work — that's the whole point
+        of the codex_home arg."""
+        import subprocess
+        from agent.transports import codex_app_server as cas
+
+        captured = {}
+
+        class FakePopen:
+            def __init__(self, cmd, *args, **kwargs):
+                captured["env"] = kwargs.get("env", {}).copy()
+                self.stdin = None
+                self.stdout = None
+                self.stderr = None
+                self.pid = 1
+                self.returncode = None
+
+            def poll(self):
+                return None
+
+            def terminate(self):
+                pass
+
+            def wait(self, timeout=None):
+                return 0
+
+            def kill(self):
+                pass
+
+        monkeypatch.setattr(subprocess, "Popen", FakePopen)
+        monkeypatch.setenv("HOME", "/users/alice")
+
+        client = cas.CodexAppServerClient(
+            codex_bin="codex", codex_home="/tmp/profile/codex"
+        )
+        client._closed = True
+
+        assert captured["env"].get("CODEX_HOME") == "/tmp/profile/codex"
+        # And HOME still passes through unchanged
+        assert captured["env"].get("HOME") == "/users/alice"
+
+    def test_kanban_worker_adds_only_kanban_writable_root(self, monkeypatch):
+        """Codex-runtime Kanban workers need to write board state outside
+        their scratch/worktree workspace, but should not fall back to
+        danger-full-access. Hermes passes a narrow app-server config override
+        for the Kanban root only.
+        """
+        import subprocess
+        from agent.transports import codex_app_server as cas
+
+        captured = {}
+
+        class FakePopen:
+            def __init__(self, cmd, *args, **kwargs):
+                captured["cmd"] = list(cmd)
+                captured["env"] = kwargs.get("env", {}).copy()
+                self.stdin = None
+                self.stdout = None
+                self.stderr = None
+                self.pid = 1
+                self.returncode = None
+
+            def poll(self):
+                return None
+
+            def terminate(self):
+                pass
+
+            def wait(self, timeout=None):
+                return 0
+
+            def kill(self):
+                pass
+
+        monkeypatch.setattr(subprocess, "Popen", FakePopen)
+        monkeypatch.setenv("HOME", "/users/alice")
+        monkeypatch.setenv("HERMES_HOME", "/users/alice/.hermes/profiles/backend-worker")
+        monkeypatch.setenv("HERMES_KANBAN_TASK", "t_smoke")
+        monkeypatch.setenv(
+            "HERMES_KANBAN_DB",
+            "/users/alice/.hermes/kanban/boards/smoke/kanban.db",
+        )
+
+        client = cas.CodexAppServerClient(codex_bin="codex")
+        client._closed = True
+
+        cmd = captured["cmd"]
+        assert cmd[:2] == ["codex", "app-server"]
+        assert 'sandbox_mode="workspace-write"' in cmd
+        assert (
+            'sandbox_workspace_write.writable_roots=["/users/alice/.hermes/kanban/boards/smoke"]'
+            in cmd
+        )
+        assert "sandbox_workspace_write.network_access=false" in cmd
+        assert all("danger" not in part for part in cmd)

tests/agent/transports/test_codex_event_projector.py

@@ -0,0 +1,302 @@
+"""Tests for CodexEventProjector — codex item/* events → Hermes messages list.
+
+Drives projection against fixture notifications captured from codex 0.130.0
+plus synthetic ones for item types we couldn't auth-test live."""
+
+from __future__ import annotations
+
+import json
+
+import pytest
+
+from agent.transports.codex_event_projector import (
+    CodexEventProjector,
+    _deterministic_call_id,
+    _format_tool_args,
+)
+
+
+# --- Fixture: real `commandExecution` notification captured from codex 0.130.0
+COMMAND_EXEC_COMPLETED = {
+    "method": "item/completed",
+    "params": {
+        "item": {
+            "type": "commandExecution",
+            "id": "f8a75c66-a89e-4fd7-8bcf-2d58e664fa9e",
+            "command": "/bin/bash -lc 'echo hello && ls /tmp | head -3'",
+            "cwd": "/tmp",
+            "processId": None,
+            "source": "userShell",
+            "status": "completed",
+            "commandActions": [
+                {"type": "listFiles", "command": "ls /tmp", "path": "tmp"}
+            ],
+            "aggregatedOutput": "hello\naa_lang.json\n",
+            "exitCode": 0,
+            "durationMs": 10,
+        },
+        "threadId": "019e1a94-352b-71e1-b214-e5c67c9ec190",
+        "turnId": "019e1a94-3553-7940-8af3-4ca57142deb7",
+        "completedAtMs": 1778562381151,
+    },
+}
+
+
+class TestProjectionInvariants:
+    """Universal invariants that must hold across all projection paths."""
+
+    def test_streaming_deltas_dont_materialize(self) -> None:
+        p = CodexEventProjector()
+        for delta_method in (
+            "item/commandExecution/outputDelta",
+            "item/agentMessage/delta",
+            "item/reasoning/delta",
+        ):
+            r = p.project({"method": delta_method, "params": {"delta": "x"}})
+            assert r.messages == [], (
+                f"{delta_method} should NOT produce messages — only "
+                f"item/completed materializes"
+            )
+            assert r.is_tool_iteration is False
+            assert r.final_text is None
+
+    def test_turn_started_and_completed_are_silent(self) -> None:
+        p = CodexEventProjector()
+        for method in ("turn/started", "turn/completed", "thread/started"):
+            r = p.project({"method": method, "params": {}})
+            assert r.messages == []
+
+    def test_unknown_method_silent(self) -> None:
+        p = CodexEventProjector()
+        r = p.project({"method": "totally/unknown", "params": {}})
+        assert r.messages == []
+
+
+class TestCommandExecutionProjection:
+    """Real captured notification → assistant tool_call + tool result."""
+
+    def test_command_completed_produces_two_messages(self) -> None:
+        p = CodexEventProjector()
+        r = p.project(COMMAND_EXEC_COMPLETED)
+        assert len(r.messages) == 2
+        assert r.is_tool_iteration is True
+
+    def test_first_message_is_assistant_tool_call(self) -> None:
+        p = CodexEventProjector()
+        msgs = p.project(COMMAND_EXEC_COMPLETED).messages
+        assistant = msgs[0]
+        assert assistant["role"] == "assistant"
+        assert assistant["content"] is None
+        assert len(assistant["tool_calls"]) == 1
+        tc = assistant["tool_calls"][0]
+        assert tc["type"] == "function"
+        assert tc["function"]["name"] == "exec_command"
+        args = json.loads(tc["function"]["arguments"])
+        assert "echo hello" in args["command"]
+        assert args["cwd"] == "/tmp"
+
+    def test_second_message_is_tool_result_correlating_by_id(self) -> None:
+        p = CodexEventProjector()
+        msgs = p.project(COMMAND_EXEC_COMPLETED).messages
+        assistant, tool = msgs
+        assert tool["role"] == "tool"
+        assert tool["tool_call_id"] == assistant["tool_calls"][0]["id"]
+        assert "hello" in tool["content"]
+
+    def test_nonzero_exit_code_annotated_in_tool_result(self) -> None:
+        item = {**COMMAND_EXEC_COMPLETED["params"]["item"], "exitCode": 2,
+                "aggregatedOutput": "boom"}
+        notif = {
+            "method": "item/completed",
+            "params": {**COMMAND_EXEC_COMPLETED["params"], "item": item},
+        }
+        p = CodexEventProjector()
+        msgs = p.project(notif).messages
+        assert "[exit 2]" in msgs[1]["content"]
+        assert "boom" in msgs[1]["content"]
+
+    def test_deterministic_call_id_across_replay(self) -> None:
+        # Same item id → same call_id (prefix cache must stay valid).
+        p1 = CodexEventProjector()
+        p2 = CodexEventProjector()
+        a = p1.project(COMMAND_EXEC_COMPLETED).messages
+        b = p2.project(COMMAND_EXEC_COMPLETED).messages
+        assert a[0]["tool_calls"][0]["id"] == b[0]["tool_calls"][0]["id"]
+
+
+class TestAgentMessageProjection:
+    """assistant text → final_text + assistant message."""
+
+    def test_agent_message_projects_to_assistant(self) -> None:
+        p = CodexEventProjector()
+        r = p.project({
+            "method": "item/completed",
+            "params": {"item": {"type": "agentMessage", "id": "x",
+                                "text": "hi there"}},
+        })
+        assert r.final_text == "hi there"
+        assert r.messages == [{"role": "assistant", "content": "hi there"}]
+        assert r.is_tool_iteration is False
+
+    def test_pending_reasoning_attaches_to_next_assistant_message(self) -> None:
+        p = CodexEventProjector()
+        # First a reasoning item lands
+        r1 = p.project({
+            "method": "item/completed",
+            "params": {"item": {"type": "reasoning", "id": "r1",
+                                "summary": ["thinking..."],
+                                "content": ["step 1", "step 2"]}},
+        })
+        assert r1.messages == []  # reasoning alone produces no message
+        # Then the assistant message
+        r2 = p.project({
+            "method": "item/completed",
+            "params": {"item": {"type": "agentMessage", "id": "a1",
+                                "text": "ok"}},
+        })
+        assistant = r2.messages[0]
+        assert "reasoning" in assistant
+        assert "thinking" in assistant["reasoning"]
+        assert "step 1" in assistant["reasoning"]
+
+    def test_reasoning_consumed_after_attaching(self) -> None:
+        p = CodexEventProjector()
+        p.project({"method": "item/completed", "params": {"item": {
+            "type": "reasoning", "id": "r1", "summary": ["once"], "content": []}}})
+        first = p.project({"method": "item/completed", "params": {"item": {
+            "type": "agentMessage", "id": "a", "text": "first"}}}).messages[0]
+        second = p.project({"method": "item/completed", "params": {"item": {
+            "type": "agentMessage", "id": "b", "text": "second"}}}).messages[0]
+        assert "reasoning" in first
+        assert "reasoning" not in second
+
+
+class TestFileChangeProjection:
+    def test_file_change_summary_no_inlined_content(self) -> None:
+        item = {
+            "type": "fileChange",
+            "id": "fc1",
+            "status": "applied",
+            "changes": [
+                {"kind": {"type": "add"}, "path": "/tmp/new.py"},
+                {"kind": {"type": "update"}, "path": "/tmp/old.py"},
+            ],
+        }
+        p = CodexEventProjector()
+        msgs = p.project({"method": "item/completed",
+                          "params": {"item": item}}).messages
+        assert len(msgs) == 2
+        tc = msgs[0]["tool_calls"][0]
+        assert tc["function"]["name"] == "apply_patch"
+        args = json.loads(tc["function"]["arguments"])
+        assert len(args["changes"]) == 2
+        assert all("kind" in c and "path" in c for c in args["changes"])
+        assert "applied" in msgs[1]["content"]
+
+
+class TestMcpToolCallProjection:
+    def test_mcp_tool_call_namespaced(self) -> None:
+        item = {
+            "type": "mcpToolCall",
+            "id": "m1",
+            "server": "obsidian",
+            "tool": "search_notes",
+            "status": "completed",
+            "arguments": {"query": "hermes"},
+            "result": {"content": [{"text": "found"}]},
+            "error": None,
+        }
+        msgs = CodexEventProjector().project(
+            {"method": "item/completed", "params": {"item": item}}
+        ).messages
+        assert msgs[0]["tool_calls"][0]["function"]["name"] == "mcp.obsidian.search_notes"
+        assert "found" in msgs[1]["content"]
+
+    def test_mcp_error_surfaced(self) -> None:
+        item = {
+            "type": "mcpToolCall", "id": "m2",
+            "server": "x", "tool": "y", "status": "failed",
+            "arguments": {}, "result": None,
+            "error": {"code": -1, "message": "no"},
+        }
+        msgs = CodexEventProjector().project(
+            {"method": "item/completed", "params": {"item": item}}
+        ).messages
+        assert "error" in msgs[1]["content"]
+
+
+class TestUserAndOpaqueProjection:
+    def test_user_message_text_fragments_only(self) -> None:
+        item = {
+            "type": "userMessage", "id": "u1",
+            "content": [
+                {"type": "text", "text": "hello"},
+                {"type": "image", "url": "http://x/y"},
+                {"type": "text", "text": "world"},
+            ],
+        }
+        msgs = CodexEventProjector().project(
+            {"method": "item/completed", "params": {"item": item}}
+        ).messages
+        assert msgs[0]["role"] == "user"
+        assert "hello" in msgs[0]["content"]
+        assert "world" in msgs[0]["content"]
+
+    def test_opaque_item_recorded_without_fabricated_tool_calls(self) -> None:
+        item = {"type": "plan", "id": "p1", "text": "do the thing"}
+        msgs = CodexEventProjector().project(
+            {"method": "item/completed", "params": {"item": item}}
+        ).messages
+        assert len(msgs) == 1
+        assert msgs[0]["role"] == "assistant"
+        assert "plan" in msgs[0]["content"].lower()
+        assert "tool_calls" not in msgs[0]
+
+
+class TestHelpers:
+    def test_deterministic_call_id_stable(self) -> None:
+        assert _deterministic_call_id("exec", "abc") == _deterministic_call_id("exec", "abc")
+        assert _deterministic_call_id("exec", "abc") != _deterministic_call_id("exec", "xyz")
+
+    def test_deterministic_call_id_handles_missing_id(self) -> None:
+        # Should not raise, should be stable for same item type
+        a = _deterministic_call_id("exec", "")
+        b = _deterministic_call_id("exec", "")
+        assert a == b
+        assert "exec" in a
+
+    def test_format_tool_args_sorted_keys(self) -> None:
+        # Sorted keys = deterministic across replays = prefix cache stays valid
+        a = _format_tool_args({"b": 1, "a": 2})
+        b = _format_tool_args({"a": 2, "b": 1})
+        assert a == b
+
+
+class TestRoleAlternationInvariant:
+    """The project must never emit two assistant messages back-to-back from
+    one item — that breaks Hermes' message alternation invariant."""
+
+    @pytest.mark.parametrize(
+        "item",
+        [
+            {"type": "commandExecution", "id": "c1", "command": "x",
+             "cwd": "/", "status": "completed", "aggregatedOutput": "",
+             "exitCode": 0, "commandActions": []},
+            {"type": "fileChange", "id": "f1", "status": "applied",
+             "changes": []},
+            {"type": "mcpToolCall", "id": "m1", "server": "s", "tool": "t",
+             "status": "completed", "arguments": {}, "result": None,
+             "error": None},
+            {"type": "dynamicToolCall", "id": "d1", "tool": "x",
+             "arguments": {}, "status": "completed",
+             "contentItems": [], "success": True},
+        ],
+    )
+    def test_tool_items_emit_assistant_then_tool(self, item) -> None:
+        msgs = CodexEventProjector().project(
+            {"method": "item/completed", "params": {"item": item}}
+        ).messages
+        assert len(msgs) == 2
+        assert msgs[0]["role"] == "assistant"
+        assert msgs[1]["role"] == "tool"
+        assert msgs[1]["tool_call_id"] == msgs[0]["tool_calls"][0]["id"]

tests/agent/transports/test_codex_transport.py

@@ -0,0 +1,657 @@
+"""Tests for the ResponsesApiTransport (Codex)."""
+
+import json
+import pytest
+from types import SimpleNamespace
+
+from agent.transports import get_transport
+from agent.transports.types import NormalizedResponse
+
+
+@pytest.fixture
+def transport():
+    import agent.transports.codex  # noqa: F401
+    return get_transport("codex_responses")
+
+
+class TestCodexTransportBasic:
+
+    def test_api_mode(self, transport):
+        assert transport.api_mode == "codex_responses"
+
+    def test_registered_on_import(self, transport):
+        assert transport is not None
+
+    def test_convert_tools(self, transport):
+        tools = [{
+            "type": "function",
+            "function": {
+                "name": "terminal",
+                "description": "Run a command",
+                "parameters": {"type": "object", "properties": {"command": {"type": "string"}}},
+            }
+        }]
+        result = transport.convert_tools(tools)
+        assert len(result) == 1
+        assert result[0]["type"] == "function"
+        assert result[0]["name"] == "terminal"
+
+
+class TestCodexBuildKwargs:
+
+    def test_basic_kwargs(self, transport):
+        messages = [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "user", "content": "Hello"},
+        ]
+        kw = transport.build_kwargs(
+            model="gpt-5.4",
+            messages=messages,
+            tools=[],
+        )
+        assert kw["model"] == "gpt-5.4"
+        assert kw["instructions"] == "You are helpful."
+        assert "input" in kw
+        assert kw["store"] is False
+
+    def test_system_extracted_from_messages(self, transport):
+        messages = [
+            {"role": "system", "content": "Custom system prompt"},
+            {"role": "user", "content": "Hi"},
+        ]
+        kw = transport.build_kwargs(model="gpt-5.4", messages=messages, tools=[])
+        assert kw["instructions"] == "Custom system prompt"
+
+    def test_no_system_uses_default(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(model="gpt-5.4", messages=messages, tools=[])
+        assert kw["instructions"]  # should be non-empty default
+
+    def test_reasoning_config(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-5.4", messages=messages, tools=[],
+            reasoning_config={"effort": "high"},
+        )
+        assert kw.get("reasoning", {}).get("effort") == "high"
+
+    def test_reasoning_disabled(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-5.4", messages=messages, tools=[],
+            reasoning_config={"enabled": False},
+        )
+        assert "reasoning" not in kw or kw.get("include") == []
+
+    def test_session_id_sets_cache_key(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-5.4", messages=messages, tools=[],
+            session_id="test-session-123",
+        )
+        assert kw.get("prompt_cache_key") == "test-session-123"
+
+    def test_github_responses_no_cache_key(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-5.4", messages=messages, tools=[],
+            session_id="test-session",
+            is_github_responses=True,
+        )
+        assert "prompt_cache_key" not in kw
+
+    def test_xai_responses_sends_cache_key_via_extra_body(self, transport):
+        """xAI's Responses API documents ``prompt_cache_key`` as the
+        body-level cache-routing key (the ``x-grok-conv-id`` header is
+        Chat-Completions-only). Passing it via ``extra_body`` is robust
+        against openai SDK builds whose ``Responses.stream()`` kwarg
+        signature ever drops the field — the body field still serializes
+        and reaches xAI either way. The ``x-grok-conv-id`` header is kept
+        as a belt-and-braces fallback so cache routing survives even
+        when the body field would be stripped by an intermediate proxy.
+        Ref: https://docs.x.ai/developers/advanced-api-usage/prompt-caching/maximizing-cache-hits
+        """
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-4.3", messages=messages, tools=[],
+            session_id="conv-xai-1",
+            is_xai_responses=True,
+        )
+        assert "prompt_cache_key" not in kw
+        assert kw.get("extra_body", {}).get("prompt_cache_key") == "conv-xai-1"
+        assert kw.get("extra_headers", {}).get("x-grok-conv-id") == "conv-xai-1"
+
+    def test_xai_responses_extra_body_preserves_caller_fields(self, transport):
+        """When the caller already supplies ``extra_body`` (e.g. via
+        request_overrides), the xAI cache-key injection must merge into
+        the existing dict instead of overwriting it. Caller-supplied
+        ``prompt_cache_key`` wins (setdefault semantics) so user overrides
+        aren't silently clobbered by the transport."""
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-4.3", messages=messages, tools=[],
+            session_id="conv-xai-1",
+            is_xai_responses=True,
+            request_overrides={"extra_body": {"prompt_cache_key": "caller-override", "other_field": 42}},
+        )
+        eb = kw.get("extra_body", {})
+        assert eb.get("prompt_cache_key") == "caller-override"
+        assert eb.get("other_field") == 42
+
+    def test_max_tokens(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-5.4", messages=messages, tools=[],
+            max_tokens=4096,
+        )
+        assert kw.get("max_output_tokens") == 4096
+
+    def test_codex_backend_no_max_output_tokens(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-5.4", messages=messages, tools=[],
+            max_tokens=4096,
+            is_codex_backend=True,
+        )
+        assert "max_output_tokens" not in kw
+
+    def test_xai_headers(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-3", messages=messages, tools=[],
+            session_id="conv-123",
+            is_xai_responses=True,
+        )
+        assert kw.get("extra_headers", {}).get("x-grok-conv-id") == "conv-123"
+
+    def test_xai_headers_preserve_request_override_headers(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-3", messages=messages, tools=[],
+            session_id="conv-123",
+            is_xai_responses=True,
+            request_overrides={"extra_headers": {"X-Test": "1", "X-Trace": "abc"}},
+        )
+        assert kw.get("extra_headers") == {
+            "X-Test": "1",
+            "X-Trace": "abc",
+            "x-grok-conv-id": "conv-123",
+        }
+
+    def test_minimal_effort_clamped(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="gpt-5.4", messages=messages, tools=[],
+            reasoning_config={"effort": "minimal"},
+        )
+        # "minimal" should be clamped to "low"
+        assert kw.get("reasoning", {}).get("effort") == "low"
+
+    def test_xai_reasoning_effort_passed(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-4.3", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"effort": "high"},
+        )
+        # xAI Responses receives reasoning.effort on the allowlisted models.
+        assert kw.get("reasoning") == {"effort": "high"}
+        # As of May 2026 (post-revert of PR #26644) we DO request
+        # reasoning.encrypted_content back from xAI so we can replay it
+        # across turns for cross-turn coherence — xAI explicitly relies
+        # on this for their partnership integration.  See
+        # tests/run_agent/test_codex_xai_oauth_recovery.py for the
+        # full history.
+        assert "reasoning.encrypted_content" in kw.get("include", [])
+
+    def test_xai_reasoning_disabled_no_reasoning_key(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-4.3", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"enabled": False},
+        )
+        # When reasoning is disabled, do not send the reasoning key at all
+        assert "reasoning" not in kw
+
+    def test_xai_minimal_effort_clamped(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-4.3", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"effort": "minimal"},
+        )
+        # "minimal" should be clamped to "low" for xAI as well
+        assert kw.get("reasoning", {}).get("effort") == "low"
+
+    # --- Grok reasoning-effort capability allowlist ---
+    # api.x.ai 400s with "Model X does not support parameter reasoningEffort"
+    # on grok-4 / grok-4-fast / grok-3 / grok-code-fast / grok-4.20-0309-*.
+    # Those models reason natively but don't expose the dial. The transport
+    # must omit the `reasoning` key for them.  As of May 2026 we DO request
+    # ``reasoning.encrypted_content`` back from xAI on every model —
+    # see test_xai_reasoning_effort_passed for the rationale.
+
+    def test_xai_grok_4_omits_reasoning_effort(self, transport):
+        """grok-4 / grok-4-0709 reject reasoning.effort with HTTP 400."""
+        messages = [{"role": "user", "content": "Hi"}]
+        for model in ("grok-4", "grok-4-0709"):
+            kw = transport.build_kwargs(
+                model=model, messages=messages, tools=[],
+                is_xai_responses=True,
+                reasoning_config={"effort": "high"},
+            )
+            assert "reasoning" not in kw, (
+                f"{model} must not receive a reasoning key (xAI rejects it)"
+            )
+            # Even without the effort dial we still ask xAI to echo back
+            # encrypted reasoning content so it can be replayed next turn.
+            assert "reasoning.encrypted_content" in kw.get("include", [])
+
+    def test_xai_grok_4_fast_omits_reasoning_effort(self, transport):
+        """grok-4-fast and grok-4-1-fast variants reject reasoning.effort."""
+        messages = [{"role": "user", "content": "Hi"}]
+        for model in (
+            "grok-4-fast-reasoning",
+            "grok-4-fast-non-reasoning",
+            "grok-4-1-fast-reasoning",
+            "grok-4-1-fast-non-reasoning",
+        ):
+            kw = transport.build_kwargs(
+                model=model, messages=messages, tools=[],
+                is_xai_responses=True,
+                reasoning_config={"effort": "low"},
+            )
+            assert "reasoning" not in kw, (
+                f"{model} must not receive a reasoning key (xAI rejects it)"
+            )
+
+    def test_xai_grok_3_non_mini_omits_reasoning_effort(self, transport):
+        """Plain grok-3 rejects reasoning.effort — only grok-3-mini accepts it."""
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-3", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"effort": "medium"},
+        )
+        assert "reasoning" not in kw
+
+    def test_xai_grok_3_mini_keeps_reasoning_effort(self, transport):
+        """grok-3-mini and -fast variants do accept the effort dial."""
+        messages = [{"role": "user", "content": "Hi"}]
+        for model in ("grok-3-mini", "grok-3-mini-fast"):
+            kw = transport.build_kwargs(
+                model=model, messages=messages, tools=[],
+                is_xai_responses=True,
+                reasoning_config={"effort": "high"},
+            )
+            assert kw.get("reasoning") == {"effort": "high"}
+
+    def test_xai_grok_4_20_0309_variants_omit_reasoning_effort(self, transport):
+        """grok-4.20-0309-(non-)reasoning reject the effort dial.
+
+        Counterintuitively, only grok-4.20-multi-agent-0309 accepts it.
+        """
+        messages = [{"role": "user", "content": "Hi"}]
+        for model in ("grok-4.20-0309-reasoning", "grok-4.20-0309-non-reasoning"):
+            kw = transport.build_kwargs(
+                model=model, messages=messages, tools=[],
+                is_xai_responses=True,
+                reasoning_config={"effort": "high"},
+            )
+            assert "reasoning" not in kw, f"{model} must not receive reasoning"
+
+    def test_xai_grok_4_20_multi_agent_keeps_reasoning_effort(self, transport):
+        """grok-4.20-multi-agent-0309 is the one grok-4.20 variant that accepts effort."""
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-4.20-multi-agent-0309", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"effort": "low"},
+        )
+        assert kw.get("reasoning") == {"effort": "low"}
+
+    def test_xai_grok_code_fast_omits_reasoning_effort(self, transport):
+        """grok-code-fast-1 rejects reasoning.effort."""
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="grok-code-fast-1", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"effort": "high"},
+        )
+        assert "reasoning" not in kw
+
+    def test_xai_aggregator_prefix_stripped(self, transport):
+        """`x-ai/grok-3-mini` (OpenRouter-style slug) still resolves correctly."""
+        messages = [{"role": "user", "content": "Hi"}]
+        # Effort-capable
+        kw = transport.build_kwargs(
+            model="x-ai/grok-3-mini", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"effort": "high"},
+        )
+        assert kw.get("reasoning") == {"effort": "high"}
+        # Effort-incapable
+        kw = transport.build_kwargs(
+            model="x-ai/grok-4-0709", messages=messages, tools=[],
+            is_xai_responses=True,
+            reasoning_config={"effort": "high"},
+        )
+        assert "reasoning" not in kw
+
+
+class TestCodexValidateResponse:
+
+    def test_none_response(self, transport):
+        assert transport.validate_response(None) is False
+
+    def test_empty_output(self, transport):
+        r = SimpleNamespace(output=[], output_text=None)
+        assert transport.validate_response(r) is False
+
+    def test_valid_output(self, transport):
+        r = SimpleNamespace(output=[{"type": "message", "content": []}])
+        assert transport.validate_response(r) is True
+
+    def test_output_text_fallback_not_valid(self, transport):
+        """validate_response is strict — output_text doesn't make it valid.
+        The caller handles output_text fallback with diagnostic logging."""
+        r = SimpleNamespace(output=None, output_text="Some text")
+        assert transport.validate_response(r) is False
+
+
+class TestCodexMapFinishReason:
+
+    def test_completed(self, transport):
+        assert transport.map_finish_reason("completed") == "stop"
+
+    def test_incomplete(self, transport):
+        assert transport.map_finish_reason("incomplete") == "length"
+
+    def test_failed(self, transport):
+        assert transport.map_finish_reason("failed") == "stop"
+
+    def test_unknown(self, transport):
+        assert transport.map_finish_reason("unknown_status") == "stop"
+
+
+class TestCodexNormalizeResponse:
+
+    def test_text_response(self, transport):
+        """Normalize a simple text Codex response."""
+        r = SimpleNamespace(
+            output=[
+                SimpleNamespace(
+                    type="message",
+                    role="assistant",
+                    content=[SimpleNamespace(type="output_text", text="Hello world")],
+                    status="completed",
+                ),
+            ],
+            status="completed",
+            incomplete_details=None,
+            usage=SimpleNamespace(input_tokens=10, output_tokens=5,
+                                  input_tokens_details=None, output_tokens_details=None),
+        )
+        nr = transport.normalize_response(r)
+        assert isinstance(nr, NormalizedResponse)
+        assert nr.content == "Hello world"
+        assert nr.finish_reason == "stop"
+
+    def test_message_items_preserved_in_provider_data(self, transport):
+        """Codex assistant message item ids/phases must survive transport normalization."""
+        r = SimpleNamespace(
+            output=[
+                SimpleNamespace(
+                    type="message",
+                    role="assistant",
+                    id="msg_abc",
+                    phase="final_answer",
+                    content=[SimpleNamespace(type="output_text", text="Hello world")],
+                    status="completed",
+                ),
+            ],
+            status="completed",
+            incomplete_details=None,
+            usage=SimpleNamespace(input_tokens=10, output_tokens=5,
+                                  input_tokens_details=None, output_tokens_details=None),
+        )
+        nr = transport.normalize_response(r)
+        assert nr.codex_message_items == [
+            {
+                "type": "message",
+                "role": "assistant",
+                "status": "completed",
+                "content": [{"type": "output_text", "text": "Hello world"}],
+                "id": "msg_abc",
+                "phase": "final_answer",
+            }
+        ]
+
+    def test_tool_call_response(self, transport):
+        """Normalize a Codex response with tool calls."""
+        r = SimpleNamespace(
+            output=[
+                SimpleNamespace(
+                    type="function_call",
+                    call_id="call_abc123",
+                    name="terminal",
+                    arguments=json.dumps({"command": "ls"}),
+                    id="fc_abc123",
+                    status="completed",
+                ),
+            ],
+            status="completed",
+            incomplete_details=None,
+            usage=SimpleNamespace(input_tokens=10, output_tokens=20,
+                                  input_tokens_details=None, output_tokens_details=None),
+        )
+        nr = transport.normalize_response(r)
+        assert nr.finish_reason == "tool_calls"
+        assert len(nr.tool_calls) == 1
+        tc = nr.tool_calls[0]
+        assert tc.name == "terminal"
+        assert '"command"' in tc.arguments
+
+
+
+class TestCodexTransportTimeout:
+    """Forward per-request timeout from build_kwargs to the SDK kwargs."""
+
+    def test_positive_timeout_preserved(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            timeout=600.0,
+        )
+        assert kw.get("timeout") == 600.0
+
+    def test_zero_timeout_dropped(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            timeout=0,
+        )
+        assert "timeout" not in kw
+
+    def test_none_timeout_omitted(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            timeout=None,
+        )
+        assert "timeout" not in kw
+
+    def test_inf_timeout_dropped(self, transport):
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            timeout=float("inf"),
+        )
+        assert "timeout" not in kw
+
+    def test_bool_timeout_dropped(self, transport):
+        """``True`` is technically int but must not survive — caller bug guard."""
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            timeout=True,
+        )
+        assert "timeout" not in kw
+
+    def test_request_overrides_can_supply_timeout(self, transport):
+        """request_overrides["timeout"] is honored when no explicit kwarg passed."""
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            request_overrides={"timeout": 450.0},
+        )
+        assert kw.get("timeout") == 450.0
+
+
+class TestCodexTransportXaiServiceTierStrip:
+    """xAI Responses API rejects ``service_tier`` (#28490).
+
+    ``resolve_fast_mode_overrides`` only returns ``service_tier`` for
+    OpenAI fast-eligible models, so on paper the field should never
+    reach a Grok request.  But ``self.service_tier`` lingers across
+    model switches and can also be set directly via ``agent.service_tier``
+    in config.yaml — both leak paths plumb through ``request_overrides``
+    and would 400 against xAI's ``/v1/responses``.
+    Strip defensively when targeting xAI.
+    """
+
+    @pytest.fixture
+    def transport(self):
+        from agent.transports.codex import ResponsesApiTransport
+        return ResponsesApiTransport()
+
+    def test_xai_strips_service_tier_from_request_overrides(self, transport):
+        """Headline #28490 case: service_tier=priority leaks through
+        request_overrides, must not reach the xAI request body."""
+        kw = transport.build_kwargs(
+            model="grok-4.3",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            is_xai_responses=True,
+            request_overrides={"service_tier": "priority"},
+        )
+        assert "service_tier" not in kw, (
+            f"service_tier must be stripped on xAI requests, "
+            f"got {kw.get('service_tier')!r}"
+        )
+
+    def test_non_xai_codex_preserves_service_tier(self, transport):
+        """The strip is xAI-only — native Codex DOES accept
+        service_tier=priority (OpenAI Priority Processing).  Stripping
+        it elsewhere would silently disable the user's fast-mode opt-in.
+        """
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            is_xai_responses=False,
+            is_codex_backend=True,
+            request_overrides={"service_tier": "priority"},
+        )
+        assert kw.get("service_tier") == "priority", (
+            "non-xAI codex_responses providers must keep service_tier"
+        )
+
+    def test_github_responses_preserves_service_tier(self, transport):
+        """GitHub Models (Copilot) is another codex_responses surface
+        that should not be affected by the xAI strip."""
+        kw = transport.build_kwargs(
+            model="gpt-5.5",
+            messages=[{"role": "user", "content": "hi"}],
+            tools=[],
+            is_github_responses=True,
+            request_overrides={"service_tier": "priority"},
+        )
+        assert kw.get("service_tier") == "priority"
+
+
+class TestPreflightSlashEnumStrip:
+    """xAI Responses safety-net: strip slash-containing enum values
+    when the model name indicates a Grok target (#28490).
+
+    Native Codex accepts ``/``-containing enums; xAI rejects them with
+    HTTP 400 "Invalid arguments passed to the model".  The main agent
+    loop and the auxiliary client already sanitize at request-build
+    time; this preflight catches any future code path that bypasses
+    those — gated on model name so we don't unnecessarily strip on
+    non-xAI providers.
+    """
+
+    def _make_kwargs(self, model: str, enum_values: list[str]) -> dict:
+        return {
+            "model": model,
+            "instructions": "test",
+            "input": [{"role": "user", "content": "hi"}],
+            "tools": [
+                {
+                    "type": "function",
+                    "name": "pick_model",
+                    "description": "pick a model",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "model_id": {
+                                "type": "string",
+                                "enum": enum_values,
+                            },
+                        },
+                    },
+                },
+            ],
+        }
+
+    def test_grok_model_strips_slash_enum_values(self):
+        """When the model name is Grok-family, slash-containing enum
+        values are stripped so xAI doesn't 400 on the tool schema."""
+        from agent.codex_responses_adapter import _preflight_codex_api_kwargs
+        kwargs = self._make_kwargs(
+            "grok-4.3",
+            ["Qwen/Qwen3.5-0.8B", "openai/gpt-oss-20b", "plain-id"],
+        )
+        result = _preflight_codex_api_kwargs(kwargs)
+        # The enum keyword itself is stripped (per strip_slash_enum's
+        # semantics — it removes the constraint entirely when any value
+        # contains /).
+        params = result["tools"][0]["parameters"]
+        assert "enum" not in params["properties"]["model_id"], (
+            "slash-containing enum must be stripped on Grok"
+        )
+
+    def test_aggregator_prefixed_grok_also_strips(self):
+        """Aggregator-prefixed (x-ai/grok-*) names hit the same path."""
+        from agent.codex_responses_adapter import _preflight_codex_api_kwargs
+        kwargs = self._make_kwargs(
+            "x-ai/grok-4.3",
+            ["Qwen/Qwen3.5-0.8B"],
+        )
+        result = _preflight_codex_api_kwargs(kwargs)
+        assert "enum" not in result["tools"][0]["parameters"]["properties"]["model_id"]
+
+    def test_non_grok_model_preserves_slash_enum_values(self):
+        """Native Codex / GitHub Models DO accept slash-containing
+        enums.  The safety-net must NOT strip there or we silently
+        degrade tool-schema constraints on every codex_responses
+        provider that isn't xAI."""
+        from agent.codex_responses_adapter import _preflight_codex_api_kwargs
+        kwargs = self._make_kwargs(
+            "gpt-5.5",
+            ["Qwen/Qwen3.5-0.8B", "plain-id"],
+        )
+        result = _preflight_codex_api_kwargs(kwargs)
+        params = result["tools"][0]["parameters"]
+        # The enum must survive on non-xAI providers.
+        assert params["properties"]["model_id"].get("enum") == [
+            "Qwen/Qwen3.5-0.8B", "plain-id"
+        ]

tests/agent/transports/test_hermes_tools_mcp_server.py

@@ -0,0 +1,133 @@
+"""Tests for the hermes-tools-as-MCP server module surface.
+
+We don't run a live MCP session in unit tests — that requires the codex
+subprocess + client + an event loop. These tests pin the static
+contract: the module imports, the EXPOSED_TOOLS list is sane, and the
+build helper assembles a server when the SDK is present.
+"""
+
+from __future__ import annotations
+
+
+
+
+class TestModuleSurface:
+    def test_module_imports_clean(self):
+        from agent.transports import hermes_tools_mcp_server as m
+        assert callable(m.main)
+        assert callable(m._build_server)
+        assert isinstance(m.EXPOSED_TOOLS, tuple)
+        assert len(m.EXPOSED_TOOLS) > 0
+
+    def test_exposed_tools_are_safe_subset(self):
+        """We MUST NOT expose tools codex already has, because codex'
+        own builtins are better-integrated with its sandbox + approvals.
+        Specifically: no terminal/shell, no read_file/write_file, no
+        patch — those are codex's built-in tools."""
+        from agent.transports.hermes_tools_mcp_server import EXPOSED_TOOLS
+        forbidden = {
+            "terminal", "shell", "read_file", "write_file", "patch",
+            "search_files", "process",
+        }
+        leaked = forbidden & set(EXPOSED_TOOLS)
+        assert not leaked, (
+            f"these tools must NOT be exposed via the codex callback "
+            f"because codex has built-in equivalents: {leaked}"
+        )
+
+    def test_expected_hermes_specific_tools_listed(self):
+        """The Hermes-specific tools should be present so users on the
+        codex runtime keep access to them."""
+        from agent.transports.hermes_tools_mcp_server import EXPOSED_TOOLS
+        for required in (
+            "web_search",
+            "web_extract",
+            "browser_navigate",
+            "vision_analyze",
+            "image_generate",
+            "skill_view",
+        ):
+            assert required in EXPOSED_TOOLS, f"missing {required!r}"
+
+    def test_agent_loop_tools_not_exposed(self):
+        """delegate_task / memory / session_search / todo require the
+        running AIAgent context to dispatch, so a stateless MCP callback
+        can't drive them. They must NOT be in EXPOSED_TOOLS."""
+        from agent.transports.hermes_tools_mcp_server import EXPOSED_TOOLS
+        for agent_loop_tool in ("delegate_task", "memory", "session_search", "todo"):
+            assert agent_loop_tool not in EXPOSED_TOOLS, (
+                f"{agent_loop_tool!r} requires the agent loop context "
+                "and can't be reached through a stateless MCP callback"
+            )
+
+    def test_kanban_worker_tools_exposed(self):
+        """Kanban workers run as `hermes chat -q` subprocesses; if they
+        come up on the codex_app_server runtime, the worker can do the
+        actual work via codex's shell but needs the kanban tools through
+        the MCP callback to report back to the kernel. Without these
+        tools available, the worker would hang at completion time."""
+        from agent.transports.hermes_tools_mcp_server import EXPOSED_TOOLS
+        # Worker handoff tools — every dispatched worker uses at least
+        # one of {complete, block, comment} to close out its task.
+        for worker_tool in (
+            "kanban_complete",
+            "kanban_block",
+            "kanban_comment",
+            "kanban_heartbeat",
+        ):
+            assert worker_tool in EXPOSED_TOOLS, (
+                f"{worker_tool!r} missing from codex callback — kanban "
+                "workers on codex_app_server runtime would hang"
+            )
+
+    def test_kanban_orchestrator_tools_exposed(self):
+        """Orchestrator agents need to dispatch new tasks, query the
+        board, and unblock/link tasks. Exposed so an orchestrator on
+        codex_app_server can do its job."""
+        from agent.transports.hermes_tools_mcp_server import EXPOSED_TOOLS
+        for orch_tool in (
+            "kanban_create",
+            "kanban_show",
+            "kanban_list",
+            "kanban_unblock",
+            "kanban_link",
+        ):
+            assert orch_tool in EXPOSED_TOOLS, (
+                f"{orch_tool!r} missing from codex callback"
+            )
+
+
+class TestMain:
+    def test_main_returns_2_when_mcp_unavailable(self, monkeypatch):
+        """When the mcp package isn't installed, main() should exit
+        cleanly with code 2 and an install hint, not crash."""
+        import agent.transports.hermes_tools_mcp_server as m
+
+        def boom_build(*a, **kw):
+            raise ImportError("mcp not installed")
+
+        monkeypatch.setattr(m, "_build_server", boom_build)
+        rc = m.main(["--verbose"])
+        assert rc == 2
+
+    def test_main_handles_keyboard_interrupt(self, monkeypatch):
+        import agent.transports.hermes_tools_mcp_server as m
+
+        class FakeServer:
+            def run(self):
+                raise KeyboardInterrupt()
+
+        monkeypatch.setattr(m, "_build_server", lambda: FakeServer())
+        rc = m.main([])
+        assert rc == 0
+
+    def test_main_returns_1_on_runtime_error(self, monkeypatch):
+        import agent.transports.hermes_tools_mcp_server as m
+
+        class CrashingServer:
+            def run(self):
+                raise RuntimeError("boom")
+
+        monkeypatch.setattr(m, "_build_server", lambda: CrashingServer())
+        rc = m.main([])
+        assert rc == 1

tests/agent/transports/test_transport.py

@@ -0,0 +1,234 @@
+"""Tests for the transport ABC, registry, and AnthropicTransport."""
+
+import pytest
+from types import SimpleNamespace
+
+from agent.transports.base import ProviderTransport
+from agent.transports.types import NormalizedResponse
+from agent.transports import get_transport, register_transport, _REGISTRY
+
+
+# ── ABC contract tests ──────────────────────────────────────────────────
+
+class TestProviderTransportABC:
+    """Verify the ABC contract is enforceable."""
+
+    def test_cannot_instantiate_abc(self):
+        with pytest.raises(TypeError):
+            ProviderTransport()
+
+    def test_concrete_must_implement_all_abstract(self):
+        class Incomplete(ProviderTransport):
+            @property
+            def api_mode(self):
+                return "test"
+        with pytest.raises(TypeError):
+            Incomplete()
+
+    def test_minimal_concrete(self):
+        class Minimal(ProviderTransport):
+            @property
+            def api_mode(self):
+                return "test_minimal"
+            def convert_messages(self, messages, **kw):
+                return messages
+            def convert_tools(self, tools):
+                return tools
+            def build_kwargs(self, model, messages, tools=None, **params):
+                return {"model": model, "messages": messages}
+            def normalize_response(self, response, **kw):
+                return NormalizedResponse(content="ok", tool_calls=None, finish_reason="stop")
+
+        t = Minimal()
+        assert t.api_mode == "test_minimal"
+        assert t.validate_response(None) is True  # default
+        assert t.extract_cache_stats(None) is None  # default
+        assert t.map_finish_reason("end_turn") == "end_turn"  # default passthrough
+
+
+# ── Registry tests ───────────────────────────────────────────────────────
+
+class TestTransportRegistry:
+
+    def test_get_unregistered_returns_none(self):
+        assert get_transport("nonexistent_mode") is None
+
+    def test_anthropic_registered_on_import(self):
+        import agent.transports.anthropic  # noqa: F401
+        t = get_transport("anthropic_messages")
+        assert t is not None
+        assert t.api_mode == "anthropic_messages"
+
+    def test_discovers_missing_transport_when_registry_partially_populated(self):
+        """Importing one transport directly must not hide other valid api_modes."""
+        import agent.transports.chat_completions  # noqa: F401
+        t = get_transport("codex_responses")
+        assert t is not None
+        assert t.api_mode == "codex_responses"
+
+    def test_register_and_get(self):
+        class DummyTransport(ProviderTransport):
+            @property
+            def api_mode(self):
+                return "dummy_test"
+            def convert_messages(self, messages, **kw):
+                return messages
+            def convert_tools(self, tools):
+                return tools
+            def build_kwargs(self, model, messages, tools=None, **params):
+                return {}
+            def normalize_response(self, response, **kw):
+                return NormalizedResponse(content=None, tool_calls=None, finish_reason="stop")
+
+        register_transport("dummy_test", DummyTransport)
+        t = get_transport("dummy_test")
+        assert t.api_mode == "dummy_test"
+        # Cleanup
+        _REGISTRY.pop("dummy_test", None)
+
+
+# ── AnthropicTransport tests ────────────────────────────────────────────
+
+class TestAnthropicTransport:
+
+    @pytest.fixture
+    def transport(self):
+        import agent.transports.anthropic  # noqa: F401
+        return get_transport("anthropic_messages")
+
+    def test_api_mode(self, transport):
+        assert transport.api_mode == "anthropic_messages"
+
+    def test_convert_tools_simple(self, transport):
+        tools = [{
+            "type": "function",
+            "function": {
+                "name": "test_tool",
+                "description": "A test",
+                "parameters": {"type": "object", "properties": {}},
+            }
+        }]
+        result = transport.convert_tools(tools)
+        assert len(result) == 1
+        assert result[0]["name"] == "test_tool"
+        assert "input_schema" in result[0]
+
+    def test_validate_response_none(self, transport):
+        assert transport.validate_response(None) is False
+
+    def test_validate_response_empty_content(self, transport):
+        r = SimpleNamespace(content=[])
+        assert transport.validate_response(r) is False
+
+    def test_validate_response_empty_content_with_end_turn_is_valid(self, transport):
+        r = SimpleNamespace(content=[], stop_reason="end_turn")
+        assert transport.validate_response(r) is True
+
+    def test_validate_response_empty_content_with_tool_use_is_invalid(self, transport):
+        r = SimpleNamespace(content=[], stop_reason="tool_use")
+        assert transport.validate_response(r) is False
+
+    def test_validate_response_valid(self, transport):
+        r = SimpleNamespace(content=[SimpleNamespace(type="text", text="hello")])
+        assert transport.validate_response(r) is True
+
+    def test_map_finish_reason(self, transport):
+        assert transport.map_finish_reason("end_turn") == "stop"
+        assert transport.map_finish_reason("tool_use") == "tool_calls"
+        assert transport.map_finish_reason("max_tokens") == "length"
+        assert transport.map_finish_reason("stop_sequence") == "stop"
+        assert transport.map_finish_reason("refusal") == "content_filter"
+        assert transport.map_finish_reason("model_context_window_exceeded") == "length"
+        assert transport.map_finish_reason("unknown") == "stop"
+
+    def test_extract_cache_stats_none_usage(self, transport):
+        r = SimpleNamespace(usage=None)
+        assert transport.extract_cache_stats(r) is None
+
+    def test_extract_cache_stats_with_cache(self, transport):
+        usage = SimpleNamespace(cache_read_input_tokens=100, cache_creation_input_tokens=50)
+        r = SimpleNamespace(usage=usage)
+        result = transport.extract_cache_stats(r)
+        assert result == {"cached_tokens": 100, "creation_tokens": 50}
+
+    def test_extract_cache_stats_zero(self, transport):
+        usage = SimpleNamespace(cache_read_input_tokens=0, cache_creation_input_tokens=0)
+        r = SimpleNamespace(usage=usage)
+        assert transport.extract_cache_stats(r) is None
+
+    def test_normalize_response_text(self, transport):
+        """Test normalization of a simple text response."""
+        r = SimpleNamespace(
+            content=[SimpleNamespace(type="text", text="Hello world")],
+            stop_reason="end_turn",
+            usage=SimpleNamespace(input_tokens=10, output_tokens=5),
+            model="claude-sonnet-4-6",
+        )
+        nr = transport.normalize_response(r)
+        assert isinstance(nr, NormalizedResponse)
+        assert nr.content == "Hello world"
+        assert nr.tool_calls is None or nr.tool_calls == []
+        assert nr.finish_reason == "stop"
+
+    def test_normalize_response_tool_calls(self, transport):
+        """Test normalization of a tool-use response."""
+        r = SimpleNamespace(
+            content=[
+                SimpleNamespace(
+                    type="tool_use",
+                    id="toolu_123",
+                    name="terminal",
+                    input={"command": "ls"},
+                ),
+            ],
+            stop_reason="tool_use",
+            usage=SimpleNamespace(input_tokens=10, output_tokens=20),
+            model="claude-sonnet-4-6",
+        )
+        nr = transport.normalize_response(r)
+        assert nr.finish_reason == "tool_calls"
+        assert len(nr.tool_calls) == 1
+        tc = nr.tool_calls[0]
+        assert tc.name == "terminal"
+        assert tc.id == "toolu_123"
+        assert '"command"' in tc.arguments
+
+    def test_normalize_response_thinking(self, transport):
+        """Test normalization preserves thinking content."""
+        r = SimpleNamespace(
+            content=[
+                SimpleNamespace(type="thinking", thinking="Let me think..."),
+                SimpleNamespace(type="text", text="The answer is 42"),
+            ],
+            stop_reason="end_turn",
+            usage=SimpleNamespace(input_tokens=10, output_tokens=15),
+            model="claude-sonnet-4-6",
+        )
+        nr = transport.normalize_response(r)
+        assert nr.content == "The answer is 42"
+        assert nr.reasoning == "Let me think..."
+
+    def test_build_kwargs_returns_dict(self, transport):
+        """Test build_kwargs produces a usable kwargs dict."""
+        messages = [{"role": "user", "content": "Hello"}]
+        kw = transport.build_kwargs(
+            model="claude-sonnet-4-6",
+            messages=messages,
+            max_tokens=1024,
+        )
+        assert isinstance(kw, dict)
+        assert "model" in kw
+        assert "max_tokens" in kw
+        assert "messages" in kw
+
+    def test_convert_messages_extracts_system(self, transport):
+        """Test convert_messages separates system from messages."""
+        messages = [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "user", "content": "Hi"},
+        ]
+        system, msgs = transport.convert_messages(messages)
+        # System should be extracted
+        assert system is not None
+        # Messages should only have user
+        assert len(msgs) >= 1

tests/agent/transports/test_types.py

@@ -0,0 +1,283 @@
+"""Tests for agent/transports/types.py — dataclass construction + helpers."""
+
+import json
+
+from agent.transports.types import (
+    NormalizedResponse,
+    ToolCall,
+    Usage,
+    build_tool_call,
+    map_finish_reason,
+)
+
+
+# ---------------------------------------------------------------------------
+# ToolCall
+# ---------------------------------------------------------------------------
+
+class TestToolCall:
+    def test_basic_construction(self):
+        tc = ToolCall(id="call_abc", name="terminal", arguments='{"cmd": "ls"}')
+        assert tc.id == "call_abc"
+        assert tc.name == "terminal"
+        assert tc.arguments == '{"cmd": "ls"}'
+        assert tc.provider_data is None
+
+    def test_none_id(self):
+        tc = ToolCall(id=None, name="read_file", arguments="{}")
+        assert tc.id is None
+
+    def test_provider_data(self):
+        tc = ToolCall(
+            id="call_x",
+            name="t",
+            arguments="{}",
+            provider_data={"call_id": "call_x", "response_item_id": "fc_x"},
+        )
+        assert tc.provider_data["call_id"] == "call_x"
+        assert tc.provider_data["response_item_id"] == "fc_x"
+
+
+# ---------------------------------------------------------------------------
+# Usage
+# ---------------------------------------------------------------------------
+
+class TestUsage:
+    def test_defaults(self):
+        u = Usage()
+        assert u.prompt_tokens == 0
+        assert u.completion_tokens == 0
+        assert u.total_tokens == 0
+        assert u.cached_tokens == 0
+
+    def test_explicit(self):
+        u = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150, cached_tokens=80)
+        assert u.total_tokens == 150
+
+
+# ---------------------------------------------------------------------------
+# NormalizedResponse
+# ---------------------------------------------------------------------------
+
+class TestNormalizedResponse:
+    def test_text_only(self):
+        r = NormalizedResponse(content="hello", tool_calls=None, finish_reason="stop")
+        assert r.content == "hello"
+        assert r.tool_calls is None
+        assert r.finish_reason == "stop"
+        assert r.reasoning is None
+        assert r.usage is None
+        assert r.provider_data is None
+
+    def test_with_tool_calls(self):
+        tcs = [ToolCall(id="call_1", name="terminal", arguments='{"cmd":"pwd"}')]
+        r = NormalizedResponse(content=None, tool_calls=tcs, finish_reason="tool_calls")
+        assert r.finish_reason == "tool_calls"
+        assert len(r.tool_calls) == 1
+        assert r.tool_calls[0].name == "terminal"
+
+    def test_with_reasoning(self):
+        r = NormalizedResponse(
+            content="answer",
+            tool_calls=None,
+            finish_reason="stop",
+            reasoning="I thought about it",
+        )
+        assert r.reasoning == "I thought about it"
+
+    def test_with_provider_data(self):
+        r = NormalizedResponse(
+            content=None,
+            tool_calls=None,
+            finish_reason="stop",
+            provider_data={"reasoning_details": [{"type": "thinking", "thinking": "hmm"}]},
+        )
+        assert r.provider_data["reasoning_details"][0]["type"] == "thinking"
+
+
+# ---------------------------------------------------------------------------
+# build_tool_call
+# ---------------------------------------------------------------------------
+
+class TestBuildToolCall:
+    def test_dict_arguments_serialized(self):
+        tc = build_tool_call(id="call_1", name="terminal", arguments={"cmd": "ls"})
+        assert tc.arguments == json.dumps({"cmd": "ls"})
+        assert tc.provider_data is None
+
+    def test_string_arguments_passthrough(self):
+        tc = build_tool_call(id="call_2", name="read_file", arguments='{"path": "/tmp"}')
+        assert tc.arguments == '{"path": "/tmp"}'
+
+    def test_provider_fields(self):
+        tc = build_tool_call(
+            id="call_3",
+            name="terminal",
+            arguments="{}",
+            call_id="call_3",
+            response_item_id="fc_3",
+        )
+        assert tc.provider_data == {"call_id": "call_3", "response_item_id": "fc_3"}
+
+    def test_none_id(self):
+        tc = build_tool_call(id=None, name="t", arguments="{}")
+        assert tc.id is None
+
+
+# ---------------------------------------------------------------------------
+# map_finish_reason
+# ---------------------------------------------------------------------------
+
+class TestMapFinishReason:
+    ANTHROPIC_MAP = {
+        "end_turn": "stop",
+        "tool_use": "tool_calls",
+        "max_tokens": "length",
+        "stop_sequence": "stop",
+        "refusal": "content_filter",
+    }
+
+    def test_known_reason(self):
+        assert map_finish_reason("end_turn", self.ANTHROPIC_MAP) == "stop"
+        assert map_finish_reason("tool_use", self.ANTHROPIC_MAP) == "tool_calls"
+        assert map_finish_reason("max_tokens", self.ANTHROPIC_MAP) == "length"
+        assert map_finish_reason("refusal", self.ANTHROPIC_MAP) == "content_filter"
+
+    def test_unknown_reason_defaults_to_stop(self):
+        assert map_finish_reason("something_new", self.ANTHROPIC_MAP) == "stop"
+
+    def test_none_reason(self):
+        assert map_finish_reason(None, self.ANTHROPIC_MAP) == "stop"
+
+
+# ---------------------------------------------------------------------------
+# Backward-compat property tests
+# ---------------------------------------------------------------------------
+
+class TestToolCallBackwardCompat:
+    """Test duck-typing properties that let ToolCall pass through code expecting
+    the old SimpleNamespace(id, type, function=SimpleNamespace(name, arguments)) shape."""
+
+    def test_type_is_function(self):
+        tc = ToolCall(id="1", name="search", arguments='{"q":"test"}')
+        assert tc.type == "function"
+
+    def test_function_returns_self(self):
+        tc = ToolCall(id="1", name="search", arguments='{"q":"test"}')
+        assert tc.function is tc
+
+    def test_function_name_matches(self):
+        tc = ToolCall(id="1", name="search", arguments='{"q":"test"}')
+        assert tc.function.name == "search"
+        assert tc.function.name == tc.name
+
+    def test_function_arguments_matches(self):
+        tc = ToolCall(id="1", name="search", arguments='{"q":"test"}')
+        assert tc.function.arguments == '{"q":"test"}'
+        assert tc.function.arguments == tc.arguments
+
+    def test_call_id_from_provider_data(self):
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data={"call_id": "c1"})
+        assert tc.call_id == "c1"
+
+    def test_call_id_none_when_no_provider_data(self):
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data=None)
+        assert tc.call_id is None
+
+    def test_response_item_id_from_provider_data(self):
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data={"response_item_id": "r1"})
+        assert tc.response_item_id == "r1"
+
+    def test_response_item_id_none_when_missing(self):
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data={"call_id": "c1"})
+        assert tc.response_item_id is None
+
+    def test_getattr_pattern_matches_agent_loop(self):
+        """run_agent.py uses getattr(tool_call, 'call_id', None) — verify it works."""
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data={"call_id": "c1"})
+        assert getattr(tc, "call_id", None) == "c1"
+        tc_no_pd = ToolCall(id="1", name="fn", arguments="{}")
+        assert getattr(tc_no_pd, "call_id", None) is None
+
+    def test_extra_content_from_provider_data(self):
+        """Gemini thought_signature stored in provider_data is exposed via property."""
+        ec = {"google": {"thought_signature": "SIG_ABC123"}}
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data={"extra_content": ec})
+        assert tc.extra_content == ec
+
+    def test_extra_content_none_when_no_provider_data(self):
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data=None)
+        assert tc.extra_content is None
+
+    def test_extra_content_none_when_key_absent(self):
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data={"call_id": "c1"})
+        assert tc.extra_content is None
+
+    def test_extra_content_getattr_pattern(self):
+        """_build_assistant_message uses getattr(tc, 'extra_content', None).
+
+        This is the exact pattern that was broken before the extra_content
+        property was added — ToolCall lacked the property so getattr always
+        returned None, silently dropping the Gemini thought_signature and
+        causing HTTP 400 on subsequent turns (issue #14488).
+        """
+        ec = {"google": {"thought_signature": "SIG_ABC123"}}
+        tc = ToolCall(id="1", name="fn", arguments="{}", provider_data={"extra_content": ec})
+        assert getattr(tc, "extra_content", None) == ec
+
+        tc_no_extra = ToolCall(id="1", name="fn", arguments="{}")
+        assert getattr(tc_no_extra, "extra_content", None) is None
+
+
+class TestNormalizedResponseBackwardCompat:
+    """Test properties that replaced _nr_to_assistant_message() shim."""
+
+    def test_reasoning_content_from_provider_data(self):
+        nr = NormalizedResponse(
+            content="hi", tool_calls=None, finish_reason="stop",
+            provider_data={"reasoning_content": "thought process"},
+        )
+        assert nr.reasoning_content == "thought process"
+
+    def test_reasoning_content_none_when_absent(self):
+        nr = NormalizedResponse(content="hi", tool_calls=None, finish_reason="stop")
+        assert nr.reasoning_content is None
+
+    def test_reasoning_details_from_provider_data(self):
+        details = [{"type": "thinking", "thinking": "hmm"}]
+        nr = NormalizedResponse(
+            content="hi", tool_calls=None, finish_reason="stop",
+            provider_data={"reasoning_details": details},
+        )
+        assert nr.reasoning_details == details
+
+    def test_reasoning_details_none_when_no_provider_data(self):
+        nr = NormalizedResponse(
+            content="hi", tool_calls=None, finish_reason="stop",
+            provider_data=None,
+        )
+        assert nr.reasoning_details is None
+
+    def test_codex_reasoning_items_from_provider_data(self):
+        items = ["item1", "item2"]
+        nr = NormalizedResponse(
+            content="hi", tool_calls=None, finish_reason="stop",
+            provider_data={"codex_reasoning_items": items},
+        )
+        assert nr.codex_reasoning_items == items
+
+    def test_codex_reasoning_items_none_when_absent(self):
+        nr = NormalizedResponse(content="hi", tool_calls=None, finish_reason="stop")
+        assert nr.codex_reasoning_items is None
+
+    def test_codex_message_items_from_provider_data(self):
+        items = [{"id": "msg_1", "type": "message"}]
+        nr = NormalizedResponse(
+            content="hi", tool_calls=None, finish_reason="stop",
+            provider_data={"codex_message_items": items},
+        )
+        assert nr.codex_message_items == items
+
+    def test_codex_message_items_none_when_absent(self):
+        nr = NormalizedResponse(content="hi", tool_calls=None, finish_reason="stop")
+        assert nr.codex_message_items is None