vLLM 도구 호출 스트리밍 실행기와 코워크 루프 실시간 소비 구조 추가

- LlmService에 tool-use 전용 streaming event API를 추가하고 OpenAI vLLM IBM 경로의 partial tool_call 조립을 event 기반으로 재구성함
- Cowork/Code 루프가 streaming event를 직접 소비하도록 바꿔 도구 호출 감지와 진행 표시를 더 빠르게 갱신함
- read-only 도구 조기 실행이 기존 loop와 실제로 이어지도록 정리하고 최종 실행에서는 prefetch 결과를 재사용함
- README와 DEVELOPMENT 문서를 2026-04-08 11:31(KST) 기준으로 갱신함

검증
- dotnet build src/AxCopilot/AxCopilot.csproj -c Release -v minimal -p:OutputPath=bin\verify\ -p:IntermediateOutputPath=obj\verify\
- 경고 0 / 오류 0

README.md

@@ -1488,3 +1488,7 @@ MIT License
   - IBM 배포형 엔드포인트가 `tool_choice`를 400으로 거부하면, `tool_choice`만 제거하고 동일한 강제 지시를 유지한 채 한 번 더 재시도하는 대체 강제 전략을 넣었습니다.
   - OpenAI/vLLM tool-use 응답은 이제 `stream=true` 기반 SSE 수신기로 읽으며, `delta.tool_calls`를 부분 조립해 완성된 도구 호출을 더 빨리 감지합니다.
   - read-only 도구는 조립이 끝나는 즉시 조기 실행을 시작하고, 최종 루프에서는 그 결과를 재사용하도록 바꿔 도구 착수 속도를 끌어올렸습니다.
+- 업데이트: 2026-04-08 11:31 (KST)
+  - `LlmService`에 tool-use 전용 스트리밍 이벤트 API를 추가했습니다. 이제 OpenAI/vLLM/IBM 경로는 텍스트 델타와 완성된 도구 호출을 각각 이벤트로 내보낼 수 있습니다.
+  - `Cowork/Code` 루프도 이 스트리밍 이벤트를 직접 소비하도록 바꿔, 도구 호출이 완성되는 즉시 transcript에 `스트리밍 도구 감지` 진행 표시가 보이고 read-only 도구 조기 실행도 실제 실행 루프와 연결되도록 정리했습니다.
+  - 기존의 `응답 전체 수신 -> tool_calls 파싱 -> 도구 실행` 구조에서 한 단계 더 나아가, `스트리밍 수신 -> partial tool_call 조립 -> 조기 read-only 실행 -> 최종 루프 재사용` 흐름으로 리팩터링했습니다.

docs/DEVELOPMENT.md

@@ -5401,3 +5401,17 @@ ow + toggle ?쒓컖 ?몄뼱濡??ㅼ떆 ?뺣젹?덈떎.
 - [AgentLoopService.cs](/E:/AX%20Copilot%20-%20Codex/src/AxCopilot/Services/Agent/AgentLoopService.cs)
   - 메인 루프의 tool-use 요청 경로에 조기 read-only prefetch callback을 연결했다.
   - 최종 도구 실행 단계에서는 조기 실행이 이미 끝난 도구의 결과를 재사용해 중복 실행을 피하고, transcript에는 `조기 실행 결과 재사용` 힌트를 남기도록 정리했다.
+
+## 2026-04-08 11:31 (KST)
+
+- [LlmService.ToolUse.cs](/E:/AX%20Copilot%20-%20Codex/src/AxCopilot/Services/LlmService.ToolUse.cs)
+  - `ToolStreamEventKind`, `ToolStreamEvent`, `StreamWithToolsAsync(...)`를 추가해 tool-use 응답을 텍스트 델타와 도구 호출 이벤트 단위로 소비할 수 있게 했다.
+  - OpenAI/vLLM/IBM 경로에 `StreamOpenAiToolEventsAsync(...)`를 도입해 `choices[].delta.tool_calls`와 IBM `results`/`choices` 스트림을 직접 읽고, 완성된 tool call을 event로 즉시 방출하도록 리팩터링했다.
+  - 기존 `ReadOpenAiToolBlocksFromStreamAsync(...)`는 이제 streaming event를 집계하는 래퍼로 바뀌어, 기존 반환형 API와 새 streaming API가 같은 파서를 공유한다.
+- [AgentLoopTransitions.Execution.cs](/E:/AX%20Copilot%20-%20Codex/src/AxCopilot/Services/Agent/AgentLoopTransitions.Execution.cs)
+  - `SendWithToolsWithRecoveryAsync(...)`가 streaming event callback을 받을 수 있게 확장했다.
+  - callback이 주어지면 `LlmService.StreamWithToolsAsync(...)`를 직접 소비하면서 텍스트/도구 호출을 집계하도록 조정했다.
+- [AgentLoopService.cs](/E:/AX%20Copilot%20-%20Codex/src/AxCopilot/Services/Agent/AgentLoopService.cs)
+  - Cowork/Code 메인 루프가 tool-use streaming event를 직접 소비하게 바꿨다.
+  - 텍스트 델타가 쌓이면 450ms 주기로 `Thinking` 이벤트에 축약 preview를 갱신하고, 도구 호출이 완성되면 `스트리밍 도구 감지` 진행 메시지를 즉시 띄우도록 연결했다.
+  - read-only 조기 실행과 최종 실행 재사용 흐름이 기존 loop와 실제로 이어지도록 정리했다.

src/AxCopilot/Services/Agent/AgentLoopService.cs

@@ -2,6 +2,7 @@
 using System.Diagnostics;
 using System.Collections.Concurrent;
 using System.IO;
+using System.Text;
 using System.Text.Json;
 using AxCopilot.Models;
 using AxCopilot.Services;
@@ -548,6 +549,8 @@ public partial class AgentLoopService
                     var (_, currentModel) = _llm.GetCurrentModelInfo();
                     WorkflowLogService.LogLlmRequest(_conversationId, _currentRunId, iteration,
                         currentModel, sendMessages.Count, activeTools.Count, forceFirst);
+                    var streamedTextPreview = new StringBuilder();
+                    var lastStreamUiUpdateAt = DateTime.MinValue;
 
                     blocks = await SendWithToolsWithRecoveryAsync(
                         sendMessages,
@@ -560,7 +563,39 @@ public partial class AgentLoopService
                             block,
                             activeTools,
                             context,
-                            ct));
+                            ct),
+                        onStreamEventAsync: async evt =>
+                        {
+                            switch (evt.Kind)
+                            {
+                                case LlmService.ToolStreamEventKind.TextDelta:
+                                    if (!string.IsNullOrWhiteSpace(evt.Text))
+                                    {
+                                        streamedTextPreview.Append(evt.Text);
+                                        var now = DateTime.UtcNow;
+                                        if ((now - lastStreamUiUpdateAt).TotalMilliseconds >= 450 && streamedTextPreview.Length > 0)
+                                        {
+                                            var preview = streamedTextPreview.ToString();
+                                            preview = preview.Length > 140 ? preview[..140] + "…" : preview;
+                                            EmitEvent(AgentEventType.Thinking, "", preview);
+                                            lastStreamUiUpdateAt = now;
+                                        }
+                                    }
+                                    break;
+                                case LlmService.ToolStreamEventKind.ToolCallReady:
+                                    if (evt.ToolCall != null)
+                                    {
+                                        EmitEvent(
+                                            AgentEventType.Thinking,
+                                            evt.ToolCall.ToolName,
+                                            $"스트리밍 도구 감지: {FormatToolCallSummary(evt.ToolCall)}");
+                                    }
+                                    break;
+                                case LlmService.ToolStreamEventKind.Completed:
+                                    await Task.CompletedTask;
+                                    break;
+                            }
+                        });
                     runState.ContextRecoveryAttempts = 0;
                     llmCallSw.Stop();
                     runState.TransientLlmErrorRetries = 0;

src/AxCopilot/Services/Agent/AgentLoopTransitions.Execution.cs

@@ -3,6 +3,7 @@ using AxCopilot.Services;
 using System.Text.Json;
 
 using System.Diagnostics;
+using System.Text;
 
 namespace AxCopilot.Services.Agent;
 
@@ -1164,7 +1165,8 @@ public partial class AgentLoopService
         string phaseLabel,
         RunState? runState = null,
         bool forceToolCall = false,
-        Func<LlmService.ContentBlock, Task<LlmService.ToolPrefetchResult?>>? prefetchToolCallAsync = null)
+        Func<LlmService.ContentBlock, Task<LlmService.ToolPrefetchResult?>>? prefetchToolCallAsync = null,
+        Func<LlmService.ToolStreamEvent, Task>? onStreamEventAsync = null)
     {
         var transientRetries = runState?.TransientLlmErrorRetries ?? 0;
         var contextRecoveryRetries = runState?.ContextRecoveryAttempts ?? 0;
@@ -1172,7 +1174,30 @@ public partial class AgentLoopService
         {
             try
             {
-                return await _llm.SendWithToolsAsync(messages, tools, ct, forceToolCall, prefetchToolCallAsync);
+                if (onStreamEventAsync == null)
+                    return await _llm.SendWithToolsAsync(messages, tools, ct, forceToolCall, prefetchToolCallAsync);
+
+                var blocks = new List<LlmService.ContentBlock>();
+                var textBuilder = new StringBuilder();
+                await foreach (var evt in _llm.StreamWithToolsAsync(messages, tools, forceToolCall, prefetchToolCallAsync, ct).WithCancellation(ct))
+                {
+                    await onStreamEventAsync(evt);
+                    if (evt.Kind == LlmService.ToolStreamEventKind.TextDelta && !string.IsNullOrWhiteSpace(evt.Text))
+                    {
+                        textBuilder.Append(evt.Text);
+                    }
+                    else if (evt.Kind == LlmService.ToolStreamEventKind.ToolCallReady && evt.ToolCall != null)
+                    {
+                        blocks.Add(evt.ToolCall);
+                    }
+                }
+
+                var result = new List<LlmService.ContentBlock>();
+                var text = textBuilder.ToString().Trim();
+                if (!string.IsNullOrWhiteSpace(text))
+                    result.Add(new LlmService.ContentBlock { Type = "text", Text = text });
+                result.AddRange(blocks);
+                return result;
             }
             catch (Exception ex)
             {

src/AxCopilot/Services/LlmService.ToolUse.cs

@@ -32,6 +32,18 @@ public partial class LlmService
         long ElapsedMilliseconds,
         string? ResolvedToolName = null);
 
+    public enum ToolStreamEventKind
+    {
+        TextDelta,
+        ToolCallReady,
+        Completed
+    }
+
+    public sealed record ToolStreamEvent(
+        ToolStreamEventKind Kind,
+        string Text = "",
+        ContentBlock? ToolCall = null);
+
     /// <summary>도구 정의를 포함하여 LLM에 요청하고, 텍스트 + tool_use 블록을 파싱하여 반환합니다.</summary>
     /// <param name="forceToolCall">
     /// true이면 <c>tool_choice: "required"</c>를 요청에 추가하여 모델이 반드시 도구를 호출하도록 강제합니다.
@@ -56,6 +68,51 @@ public partial class LlmService
         };
     }
 
+    public async IAsyncEnumerable<ToolStreamEvent> StreamWithToolsAsync(
+        List<ChatMessage> messages,
+        IReadOnlyCollection<IAgentTool> tools,
+        bool forceToolCall = false,
+        Func<ContentBlock, Task<ToolPrefetchResult?>>? prefetchToolCallAsync = null,
+        [EnumeratorCancellation] CancellationToken ct = default)
+    {
+        var activeService = ResolveService();
+        EnsureOperationModeAllowsLlmService(activeService);
+
+        switch (NormalizeServiceName(activeService))
+        {
+            case "ollama":
+            case "vllm":
+                await foreach (var evt in StreamOpenAiToolEventsAsync(messages, tools, ct, forceToolCall, prefetchToolCallAsync).WithCancellation(ct))
+                    yield return evt;
+                yield break;
+
+            case "sigmoid":
+                foreach (var block in await SendSigmoidWithToolsAsync(messages, tools, ct))
+                {
+                    if (block.Type == "text" && !string.IsNullOrWhiteSpace(block.Text))
+                        yield return new ToolStreamEvent(ToolStreamEventKind.TextDelta, block.Text);
+                    else if (block.Type == "tool_use")
+                        yield return new ToolStreamEvent(ToolStreamEventKind.ToolCallReady, ToolCall: block);
+                }
+                yield return new ToolStreamEvent(ToolStreamEventKind.Completed);
+                yield break;
+
+            case "gemini":
+                foreach (var block in await SendGeminiWithToolsAsync(messages, tools, ct))
+                {
+                    if (block.Type == "text" && !string.IsNullOrWhiteSpace(block.Text))
+                        yield return new ToolStreamEvent(ToolStreamEventKind.TextDelta, block.Text);
+                    else if (block.Type == "tool_use")
+                        yield return new ToolStreamEvent(ToolStreamEventKind.ToolCallReady, ToolCall: block);
+                }
+                yield return new ToolStreamEvent(ToolStreamEventKind.Completed);
+                yield break;
+
+            default:
+                throw new NotSupportedException($"서비스 '{activeService}'는 아직 Function Calling 스트리밍을 지원하지 않습니다.");
+        }
+    }
+
     /// <summary>도구 실행 결과를 LLM에 피드백하기 위한 메시지를 생성합니다.</summary>
     public static ChatMessage CreateToolResultMessage(string toolId, string toolName, string result)
     {
@@ -909,14 +966,127 @@ public partial class LlmService
         bool usesIbmDeploymentApi,
         Func<ContentBlock, Task<ToolPrefetchResult?>>? prefetchToolCallAsync,
         CancellationToken ct)
+    {
+        var blocks = new List<ContentBlock>();
+        var textBuilder = new StringBuilder();
+
+        await foreach (var evt in StreamOpenAiToolEventsAsync(resp, usesIbmDeploymentApi, prefetchToolCallAsync, ct).WithCancellation(ct))
+        {
+            if (evt.Kind == ToolStreamEventKind.TextDelta && !string.IsNullOrWhiteSpace(evt.Text))
+            {
+                textBuilder.Append(evt.Text);
+            }
+            else if (evt.Kind == ToolStreamEventKind.ToolCallReady && evt.ToolCall != null)
+            {
+                blocks.Add(evt.ToolCall);
+            }
+        }
+
+        var text = textBuilder.ToString().Trim();
+        var result = new List<ContentBlock>();
+        if (!string.IsNullOrWhiteSpace(text))
+            result.Add(new ContentBlock { Type = "text", Text = text });
+        result.AddRange(blocks);
+
+        if (!result.Any(b => b.Type == "tool_use"))
+        {
+            var textBlock = result.FirstOrDefault(b => b.Type == "text" && !string.IsNullOrWhiteSpace(b.Text));
+            if (textBlock != null)
+            {
+                var extracted = TryExtractToolCallsFromText(textBlock.Text);
+                if (extracted.Count > 0)
+                {
+                    foreach (var block in extracted)
+                    {
+                        if (prefetchToolCallAsync != null)
+                            block.PrefetchedExecutionTask = prefetchToolCallAsync(block);
+                    }
+                    result.AddRange(extracted);
+                    LogService.Debug($"[ToolUse] 텍스트에서 도구 호출 {extracted.Count}건 추출 (SSE 폴백 파싱)");
+                }
+            }
+        }
+
+        return result;
+    }
+
+    private async IAsyncEnumerable<ToolStreamEvent> StreamOpenAiToolEventsAsync(
+        List<ChatMessage> messages,
+        IReadOnlyCollection<IAgentTool> tools,
+        [EnumeratorCancellation] CancellationToken ct,
+        bool forceToolCall = false,
+        Func<ContentBlock, Task<ToolPrefetchResult?>>? prefetchToolCallAsync = null)
+    {
+        var activeService = ResolveService();
+        var (resolvedEp, _, allowInsecureTls) = ResolveServerInfo();
+        var endpoint = string.IsNullOrEmpty(resolvedEp)
+            ? ResolveEndpointForService(activeService)
+            : resolvedEp;
+        var registered = GetActiveRegisteredModel();
+        var isIbmDeployment = UsesIbmDeploymentChatApi(activeService, registered, endpoint);
+
+        var body = isIbmDeployment
+            ? BuildIbmToolBody(messages, tools, forceToolCall)
+            : BuildOpenAiToolBody(messages, tools, forceToolCall);
+
+        string url;
+        if (isIbmDeployment)
+            url = BuildIbmDeploymentChatUrl(endpoint, stream: true);
+        else if (activeService.Equals("ollama", StringComparison.OrdinalIgnoreCase))
+            url = endpoint.TrimEnd('/') + "/api/chat";
+        else
+            url = endpoint.TrimEnd('/') + "/v1/chat/completions";
+        var json = JsonSerializer.Serialize(body);
+
+        using var req = new HttpRequestMessage(HttpMethod.Post, url)
+        {
+            Content = new StringContent(json, Encoding.UTF8, "application/json")
+        };
+        await ApplyAuthHeaderAsync(req, ct);
+        using var resp = await SendWithTlsAsync(req, allowInsecureTls, ct, HttpCompletionOption.ResponseHeadersRead);
+        if (!resp.IsSuccessStatusCode)
+        {
+            var errBody = await resp.Content.ReadAsStringAsync(ct);
+            var detail = ExtractErrorDetail(errBody);
+            if (isIbmDeployment && forceToolCall && (int)resp.StatusCode == 400)
+            {
+                var fallbackBody = BuildIbmToolBody(messages, tools, forceToolCall: true, useToolChoice: false);
+                var fallbackJson = JsonSerializer.Serialize(fallbackBody);
+                using var retryReq = new HttpRequestMessage(HttpMethod.Post, url)
+                {
+                    Content = new StringContent(fallbackJson, Encoding.UTF8, "application/json")
+                };
+                await ApplyAuthHeaderAsync(retryReq, ct);
+                using var retryResp = await SendWithTlsAsync(retryReq, allowInsecureTls, ct, HttpCompletionOption.ResponseHeadersRead);
+                if (!retryResp.IsSuccessStatusCode)
+                    throw new ToolCallNotSupportedException($"{activeService} API 오류 ({retryResp.StatusCode}): {detail}");
+
+                await foreach (var evt in StreamOpenAiToolEventsAsync(retryResp, true, prefetchToolCallAsync, ct).WithCancellation(ct))
+                    yield return evt;
+                yield break;
+            }
+
+            if ((int)resp.StatusCode == 400)
+                throw new ToolCallNotSupportedException($"{activeService} API 오류 ({resp.StatusCode}): {detail}");
+
+            throw new HttpRequestException($"{activeService} API 오류 ({resp.StatusCode}): {detail}");
+        }
+
+        await foreach (var evt in StreamOpenAiToolEventsAsync(resp, isIbmDeployment, prefetchToolCallAsync, ct).WithCancellation(ct))
+            yield return evt;
+    }
+
+    private async IAsyncEnumerable<ToolStreamEvent> StreamOpenAiToolEventsAsync(
+        HttpResponseMessage resp,
+        bool usesIbmDeploymentApi,
+        Func<ContentBlock, Task<ToolPrefetchResult?>>? prefetchToolCallAsync,
+        [EnumeratorCancellation] CancellationToken ct)
     {
         using var stream = await resp.Content.ReadAsStreamAsync(ct);
         using var reader = new StreamReader(stream);
 
         var firstChunkReceived = false;
-        var textBuilder = new StringBuilder();
         var toolAccumulators = new Dictionary<int, ToolCallAccumulator>();
-        var emittedTools = new List<ContentBlock>();
         var lastIbmGeneratedText = "";
 
         while (!reader.EndOfStream && !ct.IsCancellationRequested)
@@ -952,8 +1122,21 @@ public partial class LlmService
                 throw new ToolCallNotSupportedException(detail ?? "IBM vLLM 도구 호출 응답 오류");
             }
 
-            if (TryExtractMessageToolBlocks(root, textBuilder, emittedTools))
+            if (TryExtractMessageToolBlocks(root, out var messageText, out var directToolBlocks))
+            {
+                if (!string.IsNullOrWhiteSpace(messageText))
+                    yield return new ToolStreamEvent(ToolStreamEventKind.TextDelta, messageText);
+                if (directToolBlocks.Count > 0)
+                {
+                    foreach (var toolBlock in directToolBlocks)
+                    {
+                        if (prefetchToolCallAsync != null)
+                            toolBlock.PrefetchedExecutionTask = prefetchToolCallAsync(toolBlock);
+                        yield return new ToolStreamEvent(ToolStreamEventKind.ToolCallReady, ToolCall: toolBlock);
+                    }
+                }
                 continue;
+            }
 
             if (usesIbmDeploymentApi &&
                 root.TryGetProperty("results", out var resultsEl) &&
@@ -970,13 +1153,15 @@ public partial class LlmService
                 {
                     if (generatedText.StartsWith(lastIbmGeneratedText, StringComparison.Ordinal))
                     {
-                        textBuilder.Append(generatedText[lastIbmGeneratedText.Length..]);
+                        var delta = generatedText[lastIbmGeneratedText.Length..];
+                        if (!string.IsNullOrEmpty(delta))
+                            yield return new ToolStreamEvent(ToolStreamEventKind.TextDelta, delta);
                         lastIbmGeneratedText = generatedText;
                     }
                     else
                     {
-                        textBuilder.Clear();
-                        textBuilder.Append(generatedText);
+                        if (!string.IsNullOrEmpty(generatedText))
+                            yield return new ToolStreamEvent(ToolStreamEventKind.TextDelta, generatedText);
                         lastIbmGeneratedText = generatedText;
                     }
                 }
@@ -994,7 +1179,7 @@ public partial class LlmService
                     {
                         var chunk = contentEl.GetString();
                         if (!string.IsNullOrEmpty(chunk))
-                            textBuilder.Append(chunk);
+                            yield return new ToolStreamEvent(ToolStreamEventKind.TextDelta, chunk);
                     }
 
                     if (deltaEl.TryGetProperty("tool_calls", out var toolCallsEl) &&
@@ -1030,53 +1215,50 @@ public partial class LlmService
                                 }
                             }
 
-                            await TryEmitCompletedToolCallAsync(acc, emittedTools, prefetchToolCallAsync).ConfigureAwait(false);
+                            var emittedBlock = await TryCreateCompletedToolCallAsync(acc, prefetchToolCallAsync).ConfigureAwait(false);
+                            if (emittedBlock != null)
+                                yield return new ToolStreamEvent(ToolStreamEventKind.ToolCallReady, ToolCall: emittedBlock);
                         }
                     }
                 }
 
                 if (firstChoice.TryGetProperty("message", out var messageEl))
-                    TryExtractMessageToolBlocks(messageEl, textBuilder, emittedTools);
-            }
-        }
-
-        foreach (var acc in toolAccumulators.Values.OrderBy(a => a.Index))
-            await TryEmitCompletedToolCallAsync(acc, emittedTools, prefetchToolCallAsync, forceEmit: true).ConfigureAwait(false);
-
-        var blocks = new List<ContentBlock>();
-        var text = textBuilder.ToString().Trim();
-        if (!string.IsNullOrWhiteSpace(text))
-            blocks.Add(new ContentBlock { Type = "text", Text = text });
-
-        blocks.AddRange(emittedTools);
-
-        if (!blocks.Any(b => b.Type == "tool_use"))
-        {
-            var textBlock = blocks.FirstOrDefault(b => b.Type == "text" && !string.IsNullOrWhiteSpace(b.Text));
-            if (textBlock != null)
-            {
-                var extracted = TryExtractToolCallsFromText(textBlock.Text);
-                if (extracted.Count > 0)
                 {
-                    foreach (var block in extracted)
+                    if (TryExtractMessageToolBlocks(messageEl, out var messageText2, out var directToolBlocks2))
                     {
-                        if (prefetchToolCallAsync != null)
-                            block.PrefetchedExecutionTask = prefetchToolCallAsync(block);
+                        if (!string.IsNullOrWhiteSpace(messageText2))
+                            yield return new ToolStreamEvent(ToolStreamEventKind.TextDelta, messageText2);
+                        if (directToolBlocks2.Count > 0)
+                        {
+                            foreach (var toolBlock in directToolBlocks2)
+                            {
+                                if (prefetchToolCallAsync != null)
+                                    toolBlock.PrefetchedExecutionTask = prefetchToolCallAsync(toolBlock);
+                                yield return new ToolStreamEvent(ToolStreamEventKind.ToolCallReady, ToolCall: toolBlock);
+                            }
+                        }
                     }
-                    blocks.AddRange(extracted);
-                    LogService.Debug($"[ToolUse] 텍스트에서 도구 호출 {extracted.Count}건 추출 (SSE 폴백 파싱)");
                 }
             }
         }
 
-        return blocks;
+        foreach (var acc in toolAccumulators.Values.OrderBy(a => a.Index))
+        {
+            var emittedBlock = await TryCreateCompletedToolCallAsync(acc, prefetchToolCallAsync, forceEmit: true).ConfigureAwait(false);
+            if (emittedBlock != null)
+                yield return new ToolStreamEvent(ToolStreamEventKind.ToolCallReady, ToolCall: emittedBlock);
+        }
+
+        yield return new ToolStreamEvent(ToolStreamEventKind.Completed);
     }
 
     private static bool TryExtractMessageToolBlocks(
         JsonElement messageOrRoot,
-        StringBuilder textBuilder,
-        List<ContentBlock> emittedTools)
+        out string text,
+        out List<ContentBlock> toolBlocks)
     {
+        text = "";
+        toolBlocks = new List<ContentBlock>();
         JsonElement message = messageOrRoot;
         if (messageOrRoot.TryGetProperty("message", out var nestedMessage))
             message = nestedMessage;
@@ -1085,10 +1267,10 @@ public partial class LlmService
         if (message.TryGetProperty("content", out var contentEl) &&
             contentEl.ValueKind == JsonValueKind.String)
         {
-            var text = contentEl.GetString();
-            if (!string.IsNullOrWhiteSpace(text))
+            var parsedText = contentEl.GetString();
+            if (!string.IsNullOrWhiteSpace(parsedText))
             {
-                textBuilder.Append(text);
+                text = parsedText;
                 consumed = true;
             }
         }
@@ -1119,7 +1301,7 @@ public partial class LlmService
                     }
                 }
 
-                emittedTools.Add(new ContentBlock
+                toolBlocks.Add(new ContentBlock
                 {
                     Type = "tool_use",
                     ToolName = functionEl.TryGetProperty("name", out var nameEl) ? nameEl.GetString() ?? "" : "",
@@ -1154,21 +1336,20 @@ public partial class LlmService
         }
     }
 
-    private static async Task TryEmitCompletedToolCallAsync(
+    private static async Task<ContentBlock?> TryCreateCompletedToolCallAsync(
         ToolCallAccumulator acc,
-        List<ContentBlock> emittedTools,
         Func<ContentBlock, Task<ToolPrefetchResult?>>? prefetchToolCallAsync,
         bool forceEmit = false)
     {
         if (acc.Emitted || string.IsNullOrWhiteSpace(acc.Name))
-            return;
+            return null;
 
         var argsJson = acc.Arguments.ToString().Trim();
         JsonElement? parsedArgs = null;
         if (!string.IsNullOrEmpty(argsJson))
         {
             if (!forceEmit && !LooksLikeCompleteJson(argsJson))
-                return;
+                return null;
 
             try
             {
@@ -1178,7 +1359,7 @@ public partial class LlmService
             catch
             {
                 if (!forceEmit)
-                    return;
+                    return null;
             }
         }
 
@@ -1193,8 +1374,8 @@ public partial class LlmService
         if (prefetchToolCallAsync != null)
             block.PrefetchedExecutionTask = prefetchToolCallAsync(block);
 
-        emittedTools.Add(block);
         acc.Emitted = true;
+        return block;
     }
 
     // ─── 공통 헬퍼 ─────────────────────────────────────────────────────