feat(executor,llm): LocalRunner agent-channel via OpenAI tool-use (Phase 5)

LocalRunner previously ignored the AgentChannel and produced a single
fire-and-forget completion. It now declares the four agent back-channel tools
(ask_user/report_summary/spawn_subtask/record_progress) as OpenAI
function-calling definitions and runs a tool-use loop: each turn feeds tool
results back as message history (re-feed) until the model stops calling tools,
bounded by maxLocalToolTurns. ask_user converts a buffered question into a
*BlockedError so the task blocks like the container runners.

Adds tool-use support to the llm client (Tool/ToolCall/ToolFunction types,
Tools on ChatRequest, ToolCalls on ChatResponse + wire request/response). The
loop uses non-streaming Chat (tool_calls don't stream cleanly); assistant text
is still written to stdout.log in the Claude stream-json envelope so summary/
changestats parsing is unchanged.

Fully tested against a mock OpenAI endpoint + storeChannel: spawn/summary/
progress dispatch, ask_user blocking, token accumulation, and the llm tools
round-trip. NOTE: local resume re-feeds conversation state (Decision #8) — not
yet wired, so a blocked local task resumes fresh for now.

https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39

1 files changed, 40 insertions, 0 deletions

diff --git a/internal/llm/client_test.go b/internal/llm/client_test.go
index 8257836..7533a8a 100644
--- a/internal/llm/client_test.go
+++ b/internal/llm/client_test.go
@@ -157,3 +157,43 @@ func TestErrFromStatus_RateLimitMarker(t *testing.T) {
 		t.Errorf("error should embed retry-after, got: %v", err)
 	}
 }
+
+func TestChat_ToolsRoundTrip(t *testing.T) {
+	srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		var body openAIRequest
+		if err := json.NewDecoder(r.Body).Decode(&body); err != nil {
+			t.Fatalf("decode body: %v", err)
+		}
+		if len(body.Tools) != 1 || body.Tools[0].Function.Name != "do_thing" {
+			t.Errorf("tools not forwarded in request: %+v", body.Tools)
+		}
+		w.Header().Set("Content-Type", "application/json")
+		fmt.Fprintln(w, `{
+			"model": "m",
+			"choices": [{"message": {"role": "assistant", "content": "",
+				"tool_calls": [{"id": "call_1", "type": "function",
+					"function": {"name": "do_thing", "arguments": "{\"x\":1}"}}]},
+				"finish_reason": "tool_calls"}],
+			"usage": {"prompt_tokens": 3, "completion_tokens": 4}
+		}`)
+	}))
+	defer srv.Close()
+
+	c := &Client{Endpoint: srv.URL + "/v1", Model: "m"}
+	resp, err := c.Chat(context.Background(), ChatRequest{
+		Messages: []Message{{Role: "user", Content: "go"}},
+		Tools: []Tool{{Type: "function", Function: ToolFunction{
+			Name: "do_thing", Description: "d", Parameters: map[string]any{"type": "object"},
+		}}},
+	})
+	if err != nil {
+		t.Fatalf("Chat: %v", err)
+	}
+	if len(resp.ToolCalls) != 1 {
+		t.Fatalf("expected 1 tool call, got %d", len(resp.ToolCalls))
+	}
+	tc := resp.ToolCalls[0]
+	if tc.ID != "call_1" || tc.Function.Name != "do_thing" || tc.Function.Arguments != `{"x":1}` {
+		t.Errorf("unexpected tool call parsed: %+v", tc)
+	}
+}