feat(engine): allow replay tool executor injection

app-instance/backend/beaver/engine/loop.py

@@ -247,6 +247,7 @@ class AgentLoop:
         attempt_index: int | None = None,
         pinned_skill_names: list[str] | None = None,
         pinned_skill_contexts: list[SkillContext] | None = None,
+        tool_executor_override: Any = None,
         allow_candidate_generation: bool = False,
         intent_agent_decision: dict[str, Any] | None = None,
         channel_identity: ChannelIdentity | None = None,
@@ -297,6 +298,7 @@ class AgentLoop:
             attempt_index=attempt_index,
             pinned_skill_names=pinned_skill_names,
             pinned_skill_contexts=pinned_skill_contexts,
+            tool_executor_override=tool_executor_override,
             allow_candidate_generation=allow_candidate_generation,
             intent_agent_decision=intent_agent_decision,
             channel_identity=channel_identity,
@@ -335,6 +337,7 @@ class AgentLoop:
         attempt_index: int | None = None,
         pinned_skill_names: list[str] | None = None,
         pinned_skill_contexts: list[SkillContext] | None = None,
+        tool_executor_override: Any = None,
         allow_candidate_generation: bool = False,
         intent_agent_decision: dict[str, Any] | None = None,
         channel_identity: ChannelIdentity | None = None,
@@ -354,6 +357,7 @@ class AgentLoop:
         tool_registry = self._require_loaded("tool_registry")
         tool_assembler = self._require_loaded("tool_assembler")
         tool_executor = self._require_loaded("tool_executor")
+        effective_tool_executor = tool_executor_override or tool_executor
         skills_loader = self._require_loaded("skills_loader")
         skill_assembler = self._require_loaded("skill_assembler")
         skill_learning_service = self._require_loaded("skill_learning_service")
@@ -789,7 +793,7 @@ class AgentLoop:
 
                 iterations += 1
                 for tool_call in response.tool_calls:
-                    result = await tool_executor.execute_tool_call(tool_call, context=tool_context)
+                    result = await effective_tool_executor.execute_tool_call(tool_call, context=tool_context)
                     session_manager.append_message(
                         resolved_session_id,
                         run_id=resolved_run_id,

app-instance/backend/tests/unit/test_agent_loop_replay_executor.py

@@ -0,0 +1,71 @@
+from __future__ import annotations
+
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+from beaver.engine.loader import EngineLoader
+from beaver.engine.loop import AgentLoop
+from beaver.engine.providers.base import LLMProvider, LLMResponse, ToolCallRequest
+from beaver.engine.providers.factory import ProviderBundle
+from beaver.skills.learning.replay import ReplayToolExecutor, ReplayToolPolicy
+
+
+class ToolCallingProvider(LLMProvider):
+    def __init__(self) -> None:
+        super().__init__()
+        self.calls = 0
+
+    async def chat(
+        self,
+        messages: list[dict],
+        tools: list[dict] | None = None,
+        model: str | None = None,
+        max_tokens: int | None = None,
+        temperature: float = 0.7,
+        thinking_enabled: bool | None = None,
+    ) -> LLMResponse:
+        self.calls += 1
+        if self.calls == 1:
+            return LLMResponse(
+                content="",
+                tool_calls=[
+                    ToolCallRequest(
+                        id="call-1",
+                        name="read_file",
+                        arguments={"path": "README.md"},
+                    )
+                ],
+            )
+        return LLMResponse(content="done")
+
+    def get_default_model(self) -> str:
+        return "stub"
+
+
+@pytest.mark.asyncio
+async def test_process_direct_uses_replay_tool_executor(tmp_path: Path) -> None:
+    loop = AgentLoop(loader=EngineLoader(workspace=tmp_path))
+    loaded = loop.boot()
+    provider = ToolCallingProvider()
+    runtime = SimpleNamespace(model="stub", provider_name="stub")
+    replay_executor = ReplayToolExecutor(
+        loaded.tool_executor,
+        registry=loaded.tool_registry,
+        policy=ReplayToolPolicy(),
+    )
+
+    result = await loop.process_direct(
+        "Read the README.",
+        provider_bundle=ProviderBundle(main_runtime=runtime, main_provider=provider),  # type: ignore[arg-type]
+        include_skill_assembly=False,
+        pinned_skill_names=[],
+        tool_executor_override=replay_executor,
+        max_tool_iterations=2,
+        source="skill_replay_eval",
+    )
+
+    assert result.output_text == "done"
+    assert replay_executor.traces
+    assert replay_executor.traces[0]["tool_name"] == "read_file"