feat(R04): run every Cowork turn through ConversationApplicationService

R04-T03 — the turn lifecycle, extracted from `core/chat_agent.py::run_cowork`
into `application/conversations/`. The 260-line body mixed the lifecycle (step
budget, cancel checks, guard -> preview -> gate -> execute ordering, sandbox
tidy-up) with the machinery doing each step, and reaching any of it meant
standing up a Qt widget and a worker thread. It is now a plain object driven
through two Protocols and six callables (`turn_runtime.py`), with the concrete
`core/*` wiring confined to `core_runtime_adapter.py` — the same shape R03 used
for routing. Faithful port, not an improvement pass: where the original had a
quirk (the step-ceiling note only merges into the answer when the last message
is the assistant's) the quirk is preserved and commented.

R04-T04 — `ui/cowork_tab.py::build_job` no longer calls run_cowork. It captures
the widget's state at submit time, builds the request via the new
`cowork_turn_request.py` and executes it. `execute(..., messages=...)` hands the
widget's own list over because `_reattach_running_turn` replays from it WHILE
the worker appends and `_finalize_turn` slices it afterwards — a private list
would break both silently.

R04-T05 — `core/task_executors.py`'s cowork branch shares the same engine. All
five unattended-run behaviours stay put (plan reminder, history_ready, History
autosave per assistant message, timeout notice, plan_incomplete_reason), and
`_unattended_prompt` now expresses the load-bearing prefix order in one
readable call instead of three successive rebindings.

Verification: 74 new tests (364 passed, 1 skipped overall; check_imports PASS).
The two that matter most:
- `test_conversation_service_parity.py` runs the same scripted turn through
  run_cowork AND the service and compares the event stream, the resulting
  conversation and the advertised tool list across 7 scenarios;
- `test_task_executor_turn.py` was written BEFORE the migration and passed 8/8
  against the old code, then unchanged against the new.

Known: `ui/cowork_tab.py` (416 -> 455) and `core/task_executors.py` (476 -> 524)
stay above the 400-LOC limit. Both were already over it before this change;
bringing them under needs the R08 / R07 decompositions.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

tests/fakes/turn_runtime_fakes.py

@@ -0,0 +1,141 @@
+"""Offline test doubles for the R04 turn runtime seams.
+
+Sits beside ``fake_provider.py``/``fake_tool_executor.py`` (R01-T02) and plays
+the same role one level up: those fake a *provider*, these fake the ports
+``ConversationApplicationService`` is driven through
+(``application/conversations/turn_runtime.py``).
+
+Deliberately dumb — they record what they were asked and return canned answers.
+A failing test then points at the service under test rather than at a mock
+framework's configuration.
+"""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional, Tuple
+
+from cowork_local.domain.agents.agent_event import ToolPreview
+from cowork_local.domain.agents.conversation_execution_request import (
+    ConversationExecutionRequest,
+)
+
+
+class FakeSpec:
+    """An advertised tool. The service only ever reads ``.name`` off a spec."""
+
+    def __init__(self, name: str) -> None:
+        self.name = name
+
+
+class FakeReply:
+    """One programmed provider answer."""
+
+    def __init__(self, content: str = "", tool_calls=None, chunks=None, reasoning: str = ""):
+        self.content = content
+        self.tool_calls = tool_calls or []
+        # Default to streaming the whole content as a single chunk, which is what
+        # a non-streaming gateway effectively does.
+        self.chunks = chunks if chunks is not None else ([content] if content else [])
+        self.reasoning = reasoning
+
+
+class FakeModelCall:
+    """:class:`ModelCallPort` returning programmed replies in order.
+
+    A programmed entry may be an exception instead of a reply, which is how a
+    test simulates the gateway dying mid-turn.
+    """
+
+    def __init__(self, replies: List[Any]) -> None:
+        self.replies = list(replies)
+        self.calls: List[Dict[str, Any]] = []
+
+    def call(self, messages, tools, on_text=None, on_reasoning=None, cancel=None):
+        # Snapshot the messages: the service keeps mutating its own list, so
+        # storing it by reference would make every recorded call look identical.
+        self.calls.append({"messages": [dict(m) for m in messages],
+                           "tool_names": [getattr(t, "name", "") for t in tools]})
+        reply = self.replies.pop(0) if self.replies else FakeReply(content="(default)")
+        if isinstance(reply, BaseException):
+            raise reply
+        if reply.reasoning and on_reasoning:
+            on_reasoning(reply.reasoning)
+        for chunk in reply.chunks:
+            if on_text and chunk:
+                on_text(chunk)
+        assistant: Dict[str, Any] = {"role": "assistant", "content": reply.content}
+        if reply.tool_calls:
+            assistant["tool_calls"] = reply.tool_calls
+        return assistant
+
+
+class FakeToolRuntime:
+    """:class:`ToolRuntimePort` over an imaginary output folder."""
+
+    def __init__(self, specs=("save_file", "run_command", "update_plan"),
+                 results: Optional[Dict[str, Dict[str, Any]]] = None,
+                 removed: Tuple[str, ...] = (), added: Tuple[str, ...] = ()) -> None:
+        self._specs = [FakeSpec(n) for n in specs]
+        self._results = results or {}
+        self._removed, self._added = removed, added
+        self.executed: List[Tuple[str, Dict[str, Any]]] = []
+        self.finalize_calls: List[Dict[str, Any]] = []
+        # When set, every executed tool streams this string through ``on_output``.
+        self.emit_output: Optional[str] = None
+
+    def specs(self, allowed_tools=None):
+        if allowed_tools is None:
+            return list(self._specs)
+        return [s for s in self._specs if s.name in allowed_tools]
+
+    def preview(self, name, args):
+        return ToolPreview(kind="info", title=name, text=str(args))
+
+    def execute(self, name, args, on_output=None, cancel=None):
+        self.executed.append((name, dict(args)))
+        if self.emit_output and on_output:
+            on_output(self.emit_output)
+        return dict(self._results.get(name, {"ok": True, "output": f"{name} ok"}))
+
+    def snapshot(self):
+        return "before"
+
+    def finalize(self, before, cancelled=False):
+        self.finalize_calls.append({"before": before, "cancelled": cancelled})
+        return list(self._removed), list(self._added)
+
+
+# --------------------------------------------------------------------------- #
+# Small helpers shared by the turn tests.
+# --------------------------------------------------------------------------- #
+def make_request(**overrides) -> ConversationExecutionRequest:
+    """A minimal valid request; each test overrides only what it exercises."""
+    base: Dict[str, Any] = {"turn_id": "t1", "session_id": "s1", "prompt": "do it"}
+    base.update(overrides)
+    return ConversationExecutionRequest(**base)
+
+
+def run_turn(service, request=None, cancel=None):
+    """Execute a turn and return ``(result, events)``."""
+    events: List[Any] = []
+    result = service.execute(request or make_request(), events.append, cancel=cancel)
+    return result, events
+
+
+def events_of_type(events, cls):
+    """Every emitted event of one type, in order."""
+    return [e for e in events if isinstance(e, cls)]
+
+
+def tool_turn(tool_name: str = "save_file", args=None, **tool_kwargs):
+    """A turn that calls one tool and then answers — ``(model, tools)``."""
+    calls = [{"id": "c1", "name": tool_name, "arguments": args or {"filename": "a.md"}}]
+    model = FakeModelCall([FakeReply(content="working", tool_calls=calls),
+                           FakeReply(content="done")])
+    return model, FakeToolRuntime(**tool_kwargs)
+
+
+__all__ = [
+    "FakeSpec", "FakeReply", "FakeModelCall", "FakeToolRuntime",
+    "make_request", "run_turn", "events_of_type", "tool_turn",
+]