Replace the M3 stub in `agents session tell` with real orchestrator actor
invocation via `SessionWorkflow.tell()`. The stub echoed a canned
`Acknowledged: ...` response without calling any LLM or actor; this
commit wires up the full pipeline:

Architecture:
- New `SessionWorkflow` (Application layer) orchestrates LLM invocation
  for session tell. Accepts a `ProviderRegistry` and `ToolRegistry`;
  falls back to `FakeListLLM` when no provider is configured.
- `LangChainSessionCaller` implements the `LLMCaller` protocol, building
  history-aware LangChain message lists from the session conversation and
  invoking the LLM via `ToolCallingRuntime.run_tool_loop()`.
- `TellResult` (Pydantic BaseModel) carries the assistant response plus
  token usage (input_tokens, output_tokens, cost_usd, duration_ms).

Domain / service layer:
- `SessionActorNotConfiguredError` added to the session domain model;
  raised when tell is invoked with no actor on the session and no
  `--actor` override. Clear message; CLI exits with code 1.
- `SessionService.get_messages()` abstract method added (+ implementation
  in `PersistentSessionService`) to load ordered message history.

A2A facade:
- `A2aLocalFacade` gains `message/send` and `message/stream` standard
  A2A operation handlers that route to `SessionWorkflow.tell()`.
  Total supported operations count: 42 → 44.

CLI:
- `session tell` command delegates to `_build_session_workflow()`
  (patchable factory) instead of directly calling `SessionService`.
- Non-streaming: `SessionWorkflow.tell()` returns `TellResult`; output
  includes a Usage panel (Rich/Plain) or a `usage` object (JSON/YAML).
- Streaming: `SessionWorkflow.tell_stream()` yields tokens; CLI prints
  them via `console.print` (not raw `sys.stdout.write`).
- Token usage recorded via `SessionService.update_token_usage()` in
  both paths.

Tests:
- New Behave feature `session_tell_llm.feature` (4 scenarios): real LLM
  response persisted; streaming yields tokens; no-actor exits code 1;
  `--actor` override resolves correctly.
- New Robot suite `session_tell_llm.robot` (4 tests): end-to-end with
  stub LLM injected via monkey-patching `_resolve_llm`.
- Updated all existing `session tell` test steps to patch
  `_build_session_workflow` returning a mock `TellResult` so tests
  remain isolated from the LLM layer.
- Updated operation-count assertions (42 → 44) in
  `a2a_cli_facade_integration`, `consolidated_misc`,
  `m6_autonomy_acceptance` feature files and steps.

ISSUES CLOSED: #5784

@@ -0,0 +1,688 @@
+"""Session workflow — orchestrator actor invocation for ``agents session tell``.

@@ -0,0 +327,4 @@
+
+class SessionWorkflow:
+    """Orchestrates ``agents session tell`` — real LLM actor invocation.
+

@@ -0,0 +516,4 @@
+        input_tokens, output_tokens = self._estimate_tokens(prompt, full_content)
+        cost = _estimate_cost(input_tokens, output_tokens)
+        self._session_service.update_token_usage(
+            session_id=session_id,

@@ -90,0 +116,4 @@
+
+        return get_provider_registry()
+    except Exception:
+        return None

@@ -0,0 +1,832 @@
+"""Session workflow — orchestrator actor invocation for ``agents session tell``.

@@ -917,0 +1018,4 @@
+        # TODO(#5784-C3): Route through A2aLocalFacade once the DI wiring
+        # supports test-patchable facade services.
+        result = workflow.tell(
+            session_id=session_id,

@@ -0,0 +1,802 @@
+"""Session workflow — orchestrator actor invocation for ``agents session tell``.

@@ -0,0 +1,802 @@
+"""Session workflow — orchestrator actor invocation for ``agents session tell``.

@@ -0,0 +1,802 @@
+"""Session workflow — orchestrator actor invocation for ``agents session tell``.

@@ -0,0 +7,4 @@
+
+In local mode the call chain is::
+
+    tell CLI  ──▸  A2aLocalFacade.dispatch("message/send")

@@ -0,0 +94,4 @@
+    Returns an ordered list of LangChain message objects, empty if
+    no history is available.
+    """
+    from langchain_core.messages import (

@@ -0,0 +406,4 @@
+        Used by ``tell_stream()`` to avoid the duplicate-user-message bug (C1).
+        The caller controls when history is sampled.
+        """
+        from langchain_core.messages import HumanMessage, SystemMessage