/**
 * Local Agent v2 Handler
 * Main orchestrator for tool-based agent mode with parallel execution
 */

import { IpcMainInvokeEvent } from "electron";
import {
  streamText,
  ToolSet,
  stepCountIs,
  hasToolCall,
  ModelMessage,
  type ToolExecutionOptions,
} from "ai";
import log from "electron-log";

import { db } from "@/db";
import { chats, messages } from "@/db/schema";
import { eq } from "drizzle-orm";

import { isDyadProEnabled, isBasicAgentMode } from "@/lib/schemas";
import { readSettings } from "@/main/settings";
import { getDyadAppPath } from "@/paths/paths";
import { detectFrameworkType } from "@/ipc/utils/framework_utils";
import { getModelClient } from "@/ipc/utils/get_model_client";
import { safeSend } from "@/ipc/utils/safe_sender";
import { getMaxTokens, getTemperature } from "@/ipc/utils/token_utils";
import {
  getProviderOptions,
  getAiHeaders,
  DYAD_INTERNAL_REQUEST_ID_HEADER,
} from "@/ipc/utils/provider_options";

import {
  AgentToolName,
  buildAgentToolSet,
  requireAgentToolConsent,
  clearPendingConsentsForChat,
  clearPendingQuestionnairesForChat,
} from "./tool_definitions";
import {
  deployAllFunctionsIfNeeded,
  commitAllChanges,
} from "./processors/file_operations";
import { storeDbTimestampAtCurrentVersion } from "@/ipc/utils/neon_timestamp_utils";
import { mcpManager } from "@/ipc/utils/mcp_manager";
import { mcpServers } from "@/db/schema";
import { requireMcpToolConsent } from "@/ipc/utils/mcp_consent";
import { getAiMessagesJsonIfWithinLimit } from "@/ipc/utils/ai_messages_utils";

import type { ChatStreamParams, ChatResponseEnd } from "@/ipc/types";
import {
  AgentContext,
  parsePartialJson,
  escapeXmlAttr,
  escapeXmlContent,
  UserMessageContentPart,
  FileEditTracker,
} from "./tools/types";
import { sendTelemetryEvent } from "@/ipc/utils/telemetry";
import {
  prepareStepMessages,
  buildTodoReminderMessage,
  hasIncompleteTodos,
  formatTodoSummary,
  ensureToolResultOrdering,
  type InjectedMessage,
} from "./prepare_step_utils";
import { loadTodos } from "./todo_persistence";
import { ensureDyadGitignored } from "@/ipc/handlers/gitignoreUtils";
import { TOOL_DEFINITIONS } from "./tool_definitions";
import {
  parseAiMessagesJson,
  type DbMessageForParsing,
} from "@/ipc/utils/ai_messages_utils";
import { parseMcpToolKey, sanitizeMcpName } from "@/ipc/utils/mcp_tool_utils";
import { addIntegrationTool } from "./tools/add_integration";
import { writePlanTool } from "./tools/write_plan";
import { exitPlanTool } from "./tools/exit_plan";
import {
  appendCancelledResponseNotice,
  filterCancelledMessagePairs,
} from "@/shared/chatCancellation";
import {
  isChatPendingCompaction,
  performCompaction,
  checkAndMarkForCompaction,
} from "@/ipc/handlers/compaction/compaction_handler";
import { getPostCompactionMessages } from "@/ipc/handlers/compaction/compaction_utils";
import { DEFAULT_MAX_TOOL_CALL_STEPS } from "@/constants/settings_constants";
import { DyadError, DyadErrorKind } from "@/errors/dyad_error";
import {
  type RetryReplayEvent,
  maybeCaptureRetryReplayEvent,
  maybeCaptureRetryReplayText,
  maybeAppendRetryReplayForRetry,
} from "./retry_replay_utils";
import { setChatSummaryTool } from "./tools/set_chat_summary";

const logger = log.scope("local_agent_handler");
const PLANNING_QUESTIONNAIRE_TOOL_NAME = "planning_questionnaire";
const MAX_TERMINATED_STREAM_RETRIES = 3;
const STREAM_RETRY_BASE_DELAY_MS = 400;
const STREAM_CONTINUE_MESSAGE =
  "[System] Your previous response stream was interrupted by a transient network error. Continue from exactly where you left off and do not repeat text that has already been sent.";

const RETRYABLE_STREAM_ERROR_STATUS_CODES = new Set([
  408, 429, 500, 502, 503, 504,
]);
const RETRYABLE_STREAM_ERROR_PATTERNS = [
  "server_error",
  "internal server error",
  "service unavailable",
  "bad gateway",
  "gateway timeout",
  "too many requests",
  "rate_limit",
  "overloaded",
  "econnrefused",
  "enotfound",
  "econnreset",
  "epipe",
  "etimedout",
];

// ============================================================================
// Tool Streaming State Management
// ============================================================================

/**
 * Track streaming state per tool call ID
 */
interface ToolStreamingEntry {
  toolName: string;
  argsAccumulated: string;
}
const toolStreamingEntries = new Map<string, ToolStreamingEntry>();

function getOrCreateStreamingEntry(
  id: string,
  toolName?: string,
): ToolStreamingEntry | undefined {
  let entry = toolStreamingEntries.get(id);
  if (!entry && toolName) {
    entry = {
      toolName,
      argsAccumulated: "",
    };
    toolStreamingEntries.set(id, entry);
  }
  return entry;
}

function cleanupStreamingEntry(id: string): void {
  toolStreamingEntries.delete(id);
}

function findToolDefinition(toolName: string) {
  return TOOL_DEFINITIONS.find((t) => t.name === toolName);
}

function buildChatMessageHistory(
  chatMessages: Array<
    DbMessageForParsing & {
      isCompactionSummary: boolean | null;
      createdAt: Date;
    }
  >,
  options?: { excludeMessageIds?: Set<number> },
): ModelMessage[] {
  const excludedIds = options?.excludeMessageIds;
  const relevantMessages = getPostCompactionMessages(chatMessages);
  const reorderedMessages = [...relevantMessages];

  // For mid-turn compaction, keep the summary immediately after the triggering
  // user message so subsequent turns reflect that compaction happened before
  // post-compaction tool-loop steps.
  for (const summary of [...reorderedMessages].filter(
    (message) => message.isCompactionSummary,
  )) {
    const summaryIndex = reorderedMessages.findIndex(
      (m) => m.id === summary.id,
    );
    if (summaryIndex < 0) {
      continue;
    }

    const triggeringUser = [...reorderedMessages]
      .filter((m) => m.role === "user" && m.id < summary.id)
      .sort((a, b) => b.id - a.id)[0];
    if (!triggeringUser) {
      continue;
    }

    const triggeringUserIndex = reorderedMessages.findIndex(
      (m) => m.id === triggeringUser.id,
    );
    if (triggeringUserIndex < 0) {
      continue;
    }

    const isMidTurnSummary =
      summary.createdAt.getTime() >= triggeringUser.createdAt.getTime();
    if (!isMidTurnSummary || summaryIndex === triggeringUserIndex + 1) {
      continue;
    }

    reorderedMessages.splice(summaryIndex, 1);
    const targetIndex = Math.min(
      triggeringUserIndex + 1,
      reorderedMessages.length,
    );
    reorderedMessages.splice(targetIndex, 0, summary);
  }

  const filtered = reorderedMessages
    .filter((msg) => !excludedIds?.has(msg.id))
    .filter((msg) => msg.content || msg.aiMessagesJson);

  // Filter out cancelled message pairs (user prompt + cancelled assistant response)
  // so the AI doesn't try to reconcile cancelled/incorrect prompts with new ones.
  return filterCancelledMessagePairs(filtered).flatMap((msg) =>
    parseAiMessagesJson(msg),
  );
}

function getMidTurnCompactionSummaryIds(
  chatMessages: Array<{
    id: number;
    role: string;
    createdAt: Date;
    isCompactionSummary: boolean | null;
  }>,
): Set<number> {
  const hiddenIds = new Set<number>();

  for (const summary of chatMessages.filter((m) => m.isCompactionSummary)) {
    const triggeringUserMessage = [...chatMessages]
      .filter((m) => m.role === "user" && m.id < summary.id)
      .sort((a, b) => b.id - a.id)[0];

    if (!triggeringUserMessage) {
      continue;
    }

    if (
      summary.createdAt.getTime() >= triggeringUserMessage.createdAt.getTime()
    ) {
      hiddenIds.add(summary.id);
    }
  }

  return hiddenIds;
}

/**
 * Handle a chat stream in local-agent mode
 */
export async function handleLocalAgentStream(
  event: IpcMainInvokeEvent,
  req: ChatStreamParams,
  abortController: AbortController,
  {
    placeholderMessageId,
    systemPrompt,
    dyadRequestId,
    readOnly = false,
    planModeOnly = false,
    messageOverride,
  }: {
    placeholderMessageId: number;
    systemPrompt: string;
    dyadRequestId: string;
    /**
     * If true, the agent operates in read-only mode (e.g., ask mode).
     * State-modifying tools are disabled, and no commits/deploys are made.
     */
    readOnly?: boolean;
    /**
     * If true, only include tools allowed in plan mode.
     * This includes read-only exploration tools and planning-specific tools.
     */
    planModeOnly?: boolean;
    /**
     * If provided, use these messages instead of fetching from the database.
     * Used for summarization where messages need to be transformed.
     */
    messageOverride?: ModelMessage[];
  },
): Promise<boolean> {
  const settings = readSettings();
  const maxToolCallSteps =
    settings.maxToolCallSteps ?? DEFAULT_MAX_TOOL_CALL_STEPS;
  let fullResponse = "";
  let streamingPreview = ""; // Temporary preview for current tool, not persisted
  let activeRetryReplayEvents: RetryReplayEvent[] | null = null;
  // Mid-turn compaction inserts a DB summary row for LLM history, but we render
  // the user-facing compaction indicator inline in the active assistant turn.
  const hiddenMessageIdsForStreaming = new Set<number>();
  let postMidTurnCompactionStartStep: number | null = null;

  const appendInlineCompactionToTurn = async (
    summary?: string,
    backupPath?: string,
  ) => {
    const summaryText =
      summary && summary.trim().length > 0
        ? summary
        : "Conversation compacted.";
    const inlineCompaction = `<dyad-compaction title="Conversation compacted" state="finished">\n${escapeXmlContent(summaryText)}\n</dyad-compaction>`;
    const backupPathNote = backupPath
      ? `\nIf you need to retrieve earlier parts of the conversation history, you can read the backup file at: ${backupPath}\nNote: This file may be large. Read only the sections you need or use grep to search for specific content rather than reading the entire file.`
      : "";
    const separator =
      fullResponse.length > 0 && !fullResponse.endsWith("\n") ? "\n" : "";
    fullResponse = `${fullResponse}${separator}${inlineCompaction}${backupPathNote}\n`;
    await updateResponseInDb(placeholderMessageId, fullResponse);
  };

  // Check Pro status or Basic Agent mode
  // Basic Agent mode allows non-Pro users with quota (quota check is done in chat_stream_handlers)
  // Read-only mode (ask mode) is allowed for all users without Pro
  if (
    !readOnly &&
    !planModeOnly &&
    !isDyadProEnabled(settings) &&
    !isBasicAgentMode(settings)
  ) {
    safeSend(event.sender, "chat:response:error", {
      chatId: req.chatId,
      error:
        "Agent v2 requires Dyad Pro. Please enable Dyad Pro in Settings → Pro.",
    });
    return false;
  }

  const loadChat = async () =>
    db.query.chats.findFirst({
      where: eq(chats.id, req.chatId),
      with: {
        messages: {
          orderBy: (messages, { asc }) => [asc(messages.createdAt)],
        },
        app: true,
      },
    });

  // Get the chat and app — may be re-queried after compaction
  const initialChat = await loadChat();

  if (!initialChat || !initialChat.app) {
    throw new DyadError(
      `Chat not found: ${req.chatId}`,
      DyadErrorKind.NotFound,
    );
  }

  let chat = initialChat;

  for (const id of getMidTurnCompactionSummaryIds(chat.messages)) {
    hiddenMessageIdsForStreaming.add(id);
  }

  const appPath = getDyadAppPath(chat.app.path);

  const maybePerformPendingCompaction = async (options?: {
    showOnTopOfCurrentResponse?: boolean;
    force?: boolean;
  }) => {
    if (
      settings.enableContextCompaction === false ||
      (!options?.force && !(await isChatPendingCompaction(req.chatId)))
    ) {
      return false;
    }

    logger.info(`Performing pending compaction for chat ${req.chatId}`);
    const existingCompactionSummaryIds = new Set(
      chat.messages
        .filter((message) => message.isCompactionSummary)
        .map((message) => message.id),
    );
    const compactionResult = await performCompaction(
      event,
      req.chatId,
      appPath,
      dyadRequestId,
      (accumulatedSummary: string) => {
        // Stream compaction summary to the frontend in real-time.
        // During mid-turn compaction, keep already streamed content visible.
        const compactionPreview = `<dyad-compaction title="Compacting conversation">\n${escapeXmlContent(accumulatedSummary)}\n</dyad-compaction>`;
        const previewContent = options?.showOnTopOfCurrentResponse
          ? `${fullResponse}${streamingPreview ? streamingPreview : ""}\n${compactionPreview}`
          : compactionPreview;
        sendResponseChunk(
          event,
          req.chatId,
          chat,
          previewContent,
          placeholderMessageId,
          hiddenMessageIdsForStreaming,
          true, // Full messages: compaction changes message list
        );
      },
      {
        // Mid-turn compaction should not render as a separate message above the
        // current turn on subsequent streams, so keep its DB timestamp in turn order.
        createdAtStrategy: options?.showOnTopOfCurrentResponse
          ? "now"
          : "before-latest-user",
      },
    );
    if (!compactionResult.success) {
      logger.warn(
        `Compaction failed for chat ${req.chatId}: ${compactionResult.error}`,
      );
      // Continue anyway - compaction failure shouldn't block the conversation
    }

    // Re-query to pick up the newly inserted compaction summary message.
    // Only update if compaction succeeded — a failed compaction may have left
    // partial state that would corrupt subsequent message history.
    if (compactionResult.success) {
      const refreshedChat = await loadChat();
      if (refreshedChat?.app) {
        chat = refreshedChat;
      }

      if (options?.showOnTopOfCurrentResponse) {
        for (const message of chat.messages) {
          if (
            message.isCompactionSummary &&
            !existingCompactionSummaryIds.has(message.id)
          ) {
            hiddenMessageIdsForStreaming.add(message.id);
          }
        }
        await appendInlineCompactionToTurn(
          compactionResult.summary,
          compactionResult.backupPath,
        );
      }
    }

    if (options?.showOnTopOfCurrentResponse) {
      sendResponseChunk(
        event,
        req.chatId,
        chat,
        fullResponse + streamingPreview,
        placeholderMessageId,
        hiddenMessageIdsForStreaming,
        true, // Full messages: post-compaction refresh
      );
    }

    return compactionResult.success;
  };

  // Check if compaction is pending and enabled before processing the message
  await maybePerformPendingCompaction();

  // Send initial message update
  safeSend(event.sender, "chat:response:chunk", {
    chatId: req.chatId,
    messages: chat.messages.filter(
      (message) => !hiddenMessageIdsForStreaming.has(message.id),
    ),
  });

  // Track pending user messages to inject after tool results
  const pendingUserMessages: UserMessageContentPart[][] = [];
  // Store injected messages with their insertion index to re-inject at the same spot each step
  const allInjectedMessages: InjectedMessage[] = [];
  const warningMessages: string[] = [];

  try {
    // Get model client
    const { modelClient } = await getModelClient(
      settings.selectedModel,
      settings,
    );

    // Load persisted todos from a previous turn (if any)
    const persistedTodos = await loadTodos(appPath, chat.id);
    // Ensure .dyad/ is gitignored (idempotent; also done by compaction/plans)
    // Skip in read-only/plan-only mode to avoid modifying the workspace
    if (!readOnly && !planModeOnly) {
      await ensureDyadGitignored(appPath).catch((err: unknown) =>
        logger.warn("Failed to ensure .dyad gitignored:", err),
      );
    }
    if (persistedTodos.length > 0) {
      // Emit loaded todos to the renderer so the UI shows them immediately
      safeSend(event.sender, "agent-tool:todos-update", {
        chatId: chat.id,
        todos: persistedTodos,
      });
    }

    // Build tool execute context
    const fileEditTracker: FileEditTracker = Object.create(null);
    const ctx: AgentContext = {
      event,
      appId: chat.app.id,
      appPath,
      chatId: chat.id,
      supabaseProjectId: chat.app.supabaseProjectId,
      supabaseOrganizationSlug: chat.app.supabaseOrganizationSlug,
      neonProjectId: chat.app.neonProjectId,
      neonActiveBranchId:
        chat.app.neonActiveBranchId ?? chat.app.neonDevelopmentBranchId,
      frameworkType: detectFrameworkType(appPath),
      messageId: placeholderMessageId,
      isSharedModulesChanged: false,
      todos: persistedTodos,
      dyadRequestId,
      fileEditTracker,
      isDyadPro: isDyadProEnabled(settings),
      onXmlStream: (accumulatedXml: string) => {
        // Stream accumulated XML to UI without persisting
        streamingPreview = accumulatedXml;
        sendResponseChunk(
          event,
          req.chatId,
          chat,
          fullResponse + streamingPreview,
          placeholderMessageId,
          hiddenMessageIdsForStreaming,
        );
      },
      onXmlComplete: (finalXml: string) => {
        // Write final XML to DB and UI
        const xmlChunk = `${finalXml}\n`;
        fullResponse += xmlChunk;
        streamingPreview = ""; // Clear preview
        updateResponseInDb(placeholderMessageId, fullResponse);
        sendResponseChunk(
          event,
          req.chatId,
          chat,
          fullResponse,
          placeholderMessageId,
          hiddenMessageIdsForStreaming,
        );
      },
      requireConsent: async (params: {
        toolName: string;
        toolDescription?: string | null;
        inputPreview?: string | null;
      }) => {
        return requireAgentToolConsent(event, {
          chatId: chat.id,
          toolName: params.toolName as AgentToolName,
          toolDescription: params.toolDescription,
          inputPreview: params.inputPreview,
        });
      },
      appendUserMessage: (content: UserMessageContentPart[]) => {
        pendingUserMessages.push(content);
      },
      onUpdateTodos: (todos) => {
        safeSend(event.sender, "agent-tool:todos-update", {
          chatId: chat.id,
          todos,
        });
      },
      onWarningMessage: (message) => {
        warningMessages.push(message);
      },
    };

    // Build tool set (agent tools + MCP tools)
    // In read-only mode, only include read-only tools and skip MCP tools
    // (since we can't determine if MCP tools modify state)
    // In plan mode, only include planning tools (read + questionnaire/plan tools)
    const agentTools = buildAgentToolSet(ctx, {
      readOnly,
      planModeOnly,
      basicAgentMode: !readOnly && !planModeOnly && isBasicAgentMode(settings),
    });
    const mcpTools =
      readOnly || planModeOnly ? {} : await getMcpTools(event, ctx);
    const allTools: ToolSet = { ...agentTools, ...mcpTools };

    // Prepare message history with graceful fallback
    // Use messageOverride if provided (e.g., for summarization)
    // If a compaction summary exists, only include messages from that point onward
    // (pre-compaction messages are preserved in DB for the user but not sent to LLM)
    const messageHistory: ModelMessage[] = messageOverride
      ? messageOverride
      : buildChatMessageHistory(chat.messages);

    // Used to swap out pre-compaction history while preserving in-flight turn steps.
    let baseMessageHistoryCount = messageHistory.length;
    let compactBeforeNextStep = false;
    let compactedMidTurn = false;
    let compactionFailedMidTurn = false;
    // Tracks the difference between the compacted base message count and the
    // SDK's initialMessages count. Used to adjust injection indices after
    // compaction so that subsequent steps (which use the SDK's shorter base)
    // inject user messages at the correct position.
    let compactionIndexDelta = 0;

    const maxOutputTokens = await getMaxTokens(settings.selectedModel);
    const temperature = await getTemperature(settings.selectedModel);

    // Run one or more generation passes. If the model emits a chat message while
    // there are still incomplete todos, we append a reminder and do another pass.
    const maxTodoFollowUpLoops = 1;
    let todoFollowUpLoops = 0;
    let hasInjectedPlanningQuestionnaireReflection = false;
    let currentMessageHistory = messageHistory;
    const accumulatedAiMessages: ModelMessage[] = [];
    // Track total steps across all passes to detect step limit
    let totalStepsExecuted = 0;

    // If there are persisted todos from a previous turn, inject a synthetic
    // user message so the LLM is aware of them. Inserted BEFORE the user's
    // current message so the user's actual request is the last thing the LLM
    // reads, giving it natural priority over stale todos.
    if (
      !messageOverride &&
      !readOnly &&
      !planModeOnly &&
      persistedTodos.length > 0 &&
      hasIncompleteTodos(persistedTodos)
    ) {
      const incompleteTodos = persistedTodos.filter(
        (t) => t.status === "pending" || t.status === "in_progress",
      );
      const todoSummary = formatTodoSummary(incompleteTodos);
      const syntheticMessage: ModelMessage = {
        role: "user",
        content: [
          {
            type: "text",
            text: `[System] You have unfinished todos from your previous turn:\n${todoSummary}\n\nThe user's next message is their current request. If their request relates to these todos, continue working on them. If their request is about something different, discard these old todos by calling update_todos with merge=false and an empty list, then focus entirely on the user's new request.`,
          },
        ],
      };
      // Insert before the last message (the user's current message) so the
      // user's intent is the final thing the LLM sees.
      const insertIndex = Math.max(0, currentMessageHistory.length - 1);
      currentMessageHistory = [
        ...currentMessageHistory.slice(0, insertIndex),
        syntheticMessage,
        ...currentMessageHistory.slice(insertIndex),
      ];
    }

    while (!abortController.signal.aborted) {
      // Reset mid-turn compaction state at the start of each pass.
      // These flags track compaction within a single pass and must not persist
      // across passes (e.g., todo follow-up passes).
      compactedMidTurn = false;
      compactionFailedMidTurn = false;
      compactBeforeNextStep = false;
      compactionIndexDelta = 0;
      postMidTurnCompactionStartStep = null;
      baseMessageHistoryCount = currentMessageHistory.length;

      let passProducedChatText = false;
      let responseMessages: ModelMessage[] = [];
      let steps: Array<{
        toolCalls: Array<unknown>;
        response?: { messages?: ModelMessage[] };
      }> = [];
      let terminatedRetryCount = 0;
      let needsContinuationInstruction = false;

      // Retry loop: if the stream terminates with a transient error, captured text/tool events are replayed into message history, a continuation instruction is appended, and the stream is re-opened.
      while (!abortController.signal.aborted) {
        let streamErrorFromCallback: unknown;
        const retryReplayEvents: RetryReplayEvent[] = [];
        activeRetryReplayEvents = retryReplayEvents;
        const attemptMessages = needsContinuationInstruction
          ? [
              ...currentMessageHistory,
              buildTerminatedRetryContinuationInstruction(),
            ]
          : currentMessageHistory;
        const attemptToolInputIds = new Set<string>();
        const cleanupAttemptToolStreamingEntries = () => {
          for (const toolCallId of attemptToolInputIds) {
            cleanupStreamingEntry(toolCallId);
          }
          attemptToolInputIds.clear();
        };

        try {
          const streamResult = streamText({
            model: modelClient.model,
            headers: {
              ...getAiHeaders({
                builtinProviderId: modelClient.builtinProviderId,
              }),
              [DYAD_INTERNAL_REQUEST_ID_HEADER]: dyadRequestId,
            },
            providerOptions: getProviderOptions({
              dyadAppId: chat.app.id,
              dyadRequestId,
              dyadDisableFiles: true, // Local agent uses tools, not file injection
              files: [],
              mentionedAppsCodebases: [],
              builtinProviderId: modelClient.builtinProviderId,
              settings,
            }),
            maxOutputTokens,
            temperature,
            maxRetries: 2,
            system: systemPrompt,
            messages: attemptMessages,
            tools: allTools,
            stopWhen: [
              stepCountIs(maxToolCallSteps),
              // We instruct AI to only emit set chat summary tool call at the end of the turn.
              hasToolCall(setChatSummaryTool.name),
              // User needs to explicitly set up integration before AI can continue.
              hasToolCall(addIntegrationTool.name),
              // In plan mode, also stop after writing a plan or exiting plan mode.
              ...(planModeOnly
                ? [
                    hasToolCall(writePlanTool.name),
                    hasToolCall(exitPlanTool.name),
                  ]
                : []),
            ],
            abortSignal: abortController.signal,
            // Inject pending user messages (e.g., images from web_crawl) between steps
            // We must re-inject all accumulated messages each step because the AI SDK
            // doesn't persist dynamically injected messages in its internal state.
            // We track the insertion index so messages appear at the same position each step.
            prepareStep: async (options) => {
              let stepOptions = options;

              if (
                !messageOverride &&
                compactBeforeNextStep &&
                !compactedMidTurn &&
                settings.enableContextCompaction !== false
              ) {
                compactBeforeNextStep = false;
                const inFlightTailMessages = options.messages.slice(
                  baseMessageHistoryCount,
                );
                const compacted = await maybePerformPendingCompaction({
                  showOnTopOfCurrentResponse: true,
                  force: true,
                });

                if (compacted) {
                  compactedMidTurn = true;
                  // Preserve only messages generated after this compaction boundary.
                  postMidTurnCompactionStartStep = options.stepNumber;
                  // Clear stale injected messages — their insertAtIndex values are
                  // based on the pre-compaction message array which has been rebuilt
                  // with a different (typically smaller) count. Keeping them would
                  // cause injectMessagesAtPositions to splice at wrong positions.
                  allInjectedMessages.length = 0;
                  const preCompactionBaseCount = baseMessageHistoryCount;
                  const compactedMessageHistory = buildChatMessageHistory(
                    chat.messages,
                    {
                      // Keep the structured in-flight assistant/tool messages from
                      // the current stream instead of the placeholder DB content.
                      excludeMessageIds: new Set([placeholderMessageId]),
                    },
                  );
                  baseMessageHistoryCount = compactedMessageHistory.length;
                  // The compacted history includes the compaction summary, but the
                  // AI SDK's initialMessages does not. Track the delta so we can
                  // adjust injection indices after prepareStepMessages runs.
                  compactionIndexDelta =
                    baseMessageHistoryCount - preCompactionBaseCount;
                  stepOptions = {
                    ...options,
                    // Preserve in-flight turn messages so same-turn tool loops can
                    // continue, while later turns are compacted via persisted history.
                    messages: [
                      ...compactedMessageHistory,
                      ...inFlightTailMessages,
                    ],
                  };
                } else {
                  // Prevent repeated compaction attempts if the first one fails.
                  compactionFailedMidTurn = true;
                }
              }

              const preparedStep = prepareStepMessages(
                stepOptions,
                pendingUserMessages,
                allInjectedMessages,
              );

              // After mid-turn compaction, injection indices are based on the
              // compacted message array (which includes the compaction summary).
              // The AI SDK's internal messages don't include this summary, so
              // subsequent steps have a shorter base. Adjust indices now so
              // future re-injections land at the correct position.
              if (compactionIndexDelta !== 0) {
                for (const injection of allInjectedMessages) {
                  injection.insertAtIndex = Math.max(
                    0,
                    injection.insertAtIndex - compactionIndexDelta,
                  );
                }
                // Always reset, even when no injections exist yet — a tool may
                // add pending messages in a later step and their indices should
                // not be shifted by a stale delta.
                compactionIndexDelta = 0;
              }

              // prepareStepMessages returns undefined when it has no additional
              // injections/cleanups to apply. If we already replaced the base
              // message history (e.g., after mid-turn compaction), we still need
              // to return the updated options.
              let result =
                preparedStep ??
                (stepOptions === options ? undefined : stepOptions);

              // Defensive: ensure injected user messages don't break
              // tool_use/tool_result pairing. Catches edge cases where
              // injection indices become stale after compaction.
              if (result?.messages) {
                const fixed = ensureToolResultOrdering(result.messages);
                if (fixed) {
                  logger.warn(
                    `ensureToolResultOrdering fixed misplaced user messages in chat ${req.chatId}`,
                  );
                  result = { ...result, messages: fixed };
                }
              }

              return result;
            },
            onStepFinish: async (step) => {
              if (!hasInjectedPlanningQuestionnaireReflection) {
                const questionnaireError =
                  getPlanningQuestionnaireErrorFromStep(step);
                if (questionnaireError) {
                  pendingUserMessages.push([
                    {
                      type: "text",
                      text: buildPlanningQuestionnaireReflectionMessage(
                        questionnaireError,
                        planModeOnly,
                      ),
                    },
                  ]);
                  hasInjectedPlanningQuestionnaireReflection = true;
                  logger.info(
                    `Injected synthetic planning_questionnaire reflection message for chat ${req.chatId}`,
                  );
                }
              }

              if (
                settings.enableContextCompaction === false ||
                compactedMidTurn ||
                typeof step.usage.totalTokens !== "number"
              ) {
                return;
              }

              const shouldCompact = await checkAndMarkForCompaction(
                req.chatId,
                step.usage.totalTokens,
              );

              // If this step triggered tool calls, compact before the next step
              // in this same user turn instead of waiting for the next message.
              // Only attempt mid-turn compaction once per turn.
              if (
                shouldCompact &&
                step.toolCalls.length > 0 &&
                !compactionFailedMidTurn
              ) {
                compactBeforeNextStep = true;
              }
            },
            onFinish: async (response) => {
              const totalTokens = response.usage?.totalTokens;
              const inputTokens = response.usage?.inputTokens;
              const cachedInputTokens = response.usage?.cachedInputTokens;
              logger.log(
                "Total tokens used:",
                totalTokens,
                "Input tokens:",
                inputTokens,
                "Cached input tokens:",
                cachedInputTokens,
                "Cache hit ratio:",
                cachedInputTokens
                  ? (cachedInputTokens ?? 0) / (inputTokens ?? 0)
                  : 0,
              );
              if (typeof totalTokens === "number") {
                await db
                  .update(messages)
                  .set({ maxTokensUsed: totalTokens })
                  .where(eq(messages.id, placeholderMessageId))
                  .catch((err) =>
                    logger.error("Failed to save token count", err),
                  );
              }
            },
            onError: (error: any) => {
              const normalizedError = unwrapStreamError(error);
              streamErrorFromCallback = normalizedError;
              logger.error(
                "Local agent stream error:",
                getErrorMessage(normalizedError),
              );
            },
          });

          let inThinkingBlock = false;
          let streamErrorFromIteration: unknown;

          try {
            for await (const part of streamResult.fullStream) {
              if (abortController.signal.aborted) {
                logger.log(`Stream aborted for chat ${req.chatId}`);
                // Clean up pending consent/questionnaire requests to prevent stale UI banners
                clearPendingConsentsForChat(req.chatId);
                clearPendingQuestionnairesForChat(req.chatId);
                break;
              }

              let chunk = "";

              // Handle thinking block transitions
              if (
                inThinkingBlock &&
                ![
                  "reasoning-delta",
                  "reasoning-end",
                  "reasoning-start",
                ].includes(part.type)
              ) {
                chunk = "</think>\n";
                inThinkingBlock = false;
              }

              switch (part.type) {
                case "text-delta":
                  passProducedChatText = true;
                  chunk += part.text;
                  maybeCaptureRetryReplayText(
                    activeRetryReplayEvents,
                    part.text,
                  );
                  break;

                case "reasoning-start":
                  if (!inThinkingBlock) {
                    chunk = "<think>";
                    inThinkingBlock = true;
                  }
                  break;

                case "reasoning-delta":
                  if (!inThinkingBlock) {
                    chunk = "<think>";
                    inThinkingBlock = true;
                  }
                  chunk += part.text;
                  break;

                case "reasoning-end":
                  if (inThinkingBlock) {
                    chunk = "</think>\n";
                    inThinkingBlock = false;
                  }
                  break;

                case "tool-input-start": {
                  // Initialize streaming state for this tool call
                  getOrCreateStreamingEntry(part.id, part.toolName);
                  attemptToolInputIds.add(part.id);
                  break;
                }

                case "tool-input-delta": {
                  // Accumulate args and stream XML preview
                  const entry = getOrCreateStreamingEntry(part.id);
                  if (entry) {
                    entry.argsAccumulated += part.delta;
                    const toolDef = findToolDefinition(entry.toolName);
                    if (toolDef?.buildXml) {
                      const argsPartial = parsePartialJson(
                        entry.argsAccumulated,
                      );
                      const xml = toolDef.buildXml(argsPartial, false);
                      if (xml) {
                        ctx.onXmlStream(xml);
                      }
                    }
                  }
                  break;
                }

                case "tool-input-end": {
                  // Build final XML and persist
                  const entry = getOrCreateStreamingEntry(part.id);
                  if (entry) {
                    const toolDef = findToolDefinition(entry.toolName);
                    if (toolDef?.buildXml) {
                      const argsPartial = parsePartialJson(
                        entry.argsAccumulated,
                      );
                      const xml = toolDef.buildXml(argsPartial, true);
                      if (xml) {
                        ctx.onXmlComplete(xml);
                      }
                    }
                  }
                  cleanupStreamingEntry(part.id);
                  attemptToolInputIds.delete(part.id);
                  break;
                }

                case "tool-call":
                  maybeCaptureRetryReplayEvent(retryReplayEvents, part);
                  // Tool execution happens via execute callbacks
                  break;

                case "tool-result":
                  maybeCaptureRetryReplayEvent(retryReplayEvents, part);
                  // Tool results are already handled by the execute callback
                  break;
              }

              if (chunk) {
                fullResponse += chunk;
                await updateResponseInDb(placeholderMessageId, fullResponse);
                sendResponseChunk(
                  event,
                  req.chatId,
                  chat,
                  fullResponse,
                  placeholderMessageId,
                  hiddenMessageIdsForStreaming,
                );
              }
            }
          } catch (error) {
            if (!abortController.signal.aborted) {
              streamErrorFromIteration = error;
            } else {
              logger.log(
                `Stream interrupted after abort for chat ${req.chatId}`,
              );
            }
          }

          // Close thinking block if still open
          if (inThinkingBlock) {
            const closingThinkBlock = "</think>\n";
            fullResponse += closingThinkBlock;
            await updateResponseInDb(placeholderMessageId, fullResponse);
          }
          activeRetryReplayEvents = null;

          if (abortController.signal.aborted) {
            break;
          }

          const streamError =
            streamErrorFromIteration ?? streamErrorFromCallback;
          if (streamError) {
            if (
              shouldRetryTransientStreamError({
                error: streamError,
                retryCount: terminatedRetryCount,
                aborted: abortController.signal.aborted,
              })
            ) {
              maybeAppendRetryReplayForRetry({
                retryReplayEvents,
                currentMessageHistoryRef: currentMessageHistory,
                accumulatedAiMessagesRef: accumulatedAiMessages,
                onCurrentMessageHistoryUpdate: (next) =>
                  (currentMessageHistory = next),
              });
              terminatedRetryCount += 1;
              needsContinuationInstruction = true;
              const retryDelayMs =
                STREAM_RETRY_BASE_DELAY_MS * terminatedRetryCount;
              sendTelemetryEvent("local_agent:terminated_stream_retry", {
                chatId: req.chatId,
                dyadRequestId,
                retryCount: terminatedRetryCount,
                error: String(streamError),
                phase: "stream_iteration",
              });
              logger.warn(
                `Transient stream termination for chat ${req.chatId}; retrying pass (${terminatedRetryCount}/${MAX_TERMINATED_STREAM_RETRIES}) after ${retryDelayMs}ms`,
              );
              await delay(retryDelayMs);
              continue;
            }
            sendTelemetryEvent(
              "local_agent:terminated_stream_retries_exhausted",
              {
                chatId: req.chatId,
                dyadRequestId,
                retryCount: terminatedRetryCount,
                error: String(streamError),
                phase: "stream_iteration",
              },
            );
            throw streamError;
          }

          try {
            const response = await streamResult.response;
            steps = (await streamResult.steps) ?? [];
            responseMessages = response.messages;
          } catch (err) {
            if (
              shouldRetryTransientStreamError({
                error: err,
                retryCount: terminatedRetryCount,
                aborted: abortController.signal.aborted,
              })
            ) {
              maybeAppendRetryReplayForRetry({
                retryReplayEvents,
                currentMessageHistoryRef: currentMessageHistory,
                accumulatedAiMessagesRef: accumulatedAiMessages,
                onCurrentMessageHistoryUpdate: (next) =>
                  (currentMessageHistory = next),
              });
              terminatedRetryCount += 1;
              needsContinuationInstruction = true;
              const retryDelayMs =
                STREAM_RETRY_BASE_DELAY_MS * terminatedRetryCount;
              sendTelemetryEvent("local_agent:terminated_stream_retry", {
                chatId: req.chatId,
                dyadRequestId,
                retryCount: terminatedRetryCount,
                error: String(err),
                phase: "response_finalization",
              });
              logger.warn(
                `Transient stream termination while finalizing response for chat ${req.chatId}; retrying pass (${terminatedRetryCount}/${MAX_TERMINATED_STREAM_RETRIES}) after ${retryDelayMs}ms`,
              );
              await delay(retryDelayMs);
              continue;
            }
            if (isTerminatedStreamError(err)) {
              sendTelemetryEvent(
                "local_agent:terminated_stream_retries_exhausted",
                {
                  chatId: req.chatId,
                  dyadRequestId,
                  retryCount: terminatedRetryCount,
                  error: String(err),
                  phase: "response_finalization",
                },
              );
            }
            logger.warn("Failed to retrieve stream response messages:", err);
            steps = [];
            responseMessages = [];
          }

          break;
        } finally {
          cleanupAttemptToolStreamingEntries();
        }
      }

      if (abortController.signal.aborted) {
        break;
      }

      // Track total steps for step limit detection
      totalStepsExecuted += steps.length;

      if (responseMessages.length > 0) {
        // For mid-turn compaction, slice off pre-compaction messages
        const messagesToAccumulate =
          compactedMidTurn && postMidTurnCompactionStartStep !== null
            ? (() => {
                // stepNumber is 0-indexed (from AI SDK: stepNumber = steps.length).
                // We want the step just before compaction to determine how many
                // response messages to skip (they belong to pre-compaction context).
                const prevStepMessages =
                  steps[postMidTurnCompactionStartStep - 1]?.response?.messages;
                if (!prevStepMessages) {
                  logger.warn(
                    `No step data found at index ${postMidTurnCompactionStartStep - 1} for mid-turn compaction slicing; persisting all messages`,
                  );
                }
                return responseMessages.slice(prevStepMessages?.length ?? 0);
              })()
            : responseMessages;
        accumulatedAiMessages.push(...messagesToAccumulate);
        currentMessageHistory = [
          ...currentMessageHistory,
          ...messagesToAccumulate,
        ];
      }

      // Check if the model ended with text only (no tool calls in the final step).
      // A final set_chat_summary call is end-of-turn metadata, so it should not
      // suppress the todo safety follow-up when the pass already produced text.
      // This is more reliable than passProducedChatText which is set on any text-delta
      // during the stream (including preambles before tool calls).
      const lastStep = steps.length > 0 ? steps[steps.length - 1] : null;
      const passEndedWithText =
        passProducedChatText &&
        (!lastStep ||
          lastStep.toolCalls.length === 0 ||
          stepOnlyCalledTool(lastStep, setChatSummaryTool.name));

      if (
        !shouldRunTodoFollowUpPass({
          readOnly,
          planModeOnly,
          passEndedWithText,
          todos: ctx.todos,
          todoFollowUpLoops,
          maxTodoFollowUpLoops,
        })
      ) {
        break;
      }

      todoFollowUpLoops += 1;
      const reminderText = buildTodoReminderMessage(ctx.todos);
      const reminderMessage: ModelMessage = {
        role: "user",
        content: [{ type: "text", text: reminderText }],
      };
      currentMessageHistory = [...currentMessageHistory, reminderMessage];
      // Note: Do NOT push reminderMessage to accumulatedAiMessages.
      // It is a synthetic message that should not be persisted to aiMessagesJson,
      // as it would pollute future conversation history with stale todo state.
      logger.info(
        `Starting todo follow-up pass ${todoFollowUpLoops}/${maxTodoFollowUpLoops} for chat ${req.chatId}`,
      );
    }

    // Handle cancellation paths where stream processing exits cleanly after abort.
    if (abortController.signal.aborted) {
      await db
        .update(messages)
        .set({
          content: appendCancelledResponseNotice(fullResponse ?? ""),
        })
        .where(eq(messages.id, placeholderMessageId));
      return false; // Cancelled - don't consume quota
    }

    // Check if we hit the step limit and append a notice to the response
    if (totalStepsExecuted >= maxToolCallSteps) {
      logger.info(
        `Chat ${req.chatId} hit step limit of ${maxToolCallSteps} steps`,
      );
      const stepLimitMessage = `\n\n<dyad-step-limit steps="${totalStepsExecuted}" limit="${maxToolCallSteps}">Automatically paused after ${totalStepsExecuted} tool calls.</dyad-step-limit>`;
      fullResponse += stepLimitMessage;
      await updateResponseInDb(placeholderMessageId, fullResponse);
      sendResponseChunk(
        event,
        req.chatId,
        chat,
        fullResponse,
        placeholderMessageId,
        hiddenMessageIdsForStreaming,
      );
    }

    // Save the AI SDK messages for multi-turn tool call preservation
    try {
      const aiMessagesJson = getAiMessagesJsonIfWithinLimit(
        accumulatedAiMessages,
      );
      if (aiMessagesJson) {
        await db
          .update(messages)
          .set({ aiMessagesJson })
          .where(eq(messages.id, placeholderMessageId));
      }
    } catch (err) {
      logger.warn("Failed to save AI messages JSON:", err);
    }

    // In read-only and plan mode, skip deploys and commits
    if (!readOnly && !planModeOnly) {
      // Deploy all Supabase functions if shared modules changed
      await deployAllFunctionsIfNeeded(ctx);

      // Commit all changes
      const commitResult = await commitAllChanges(ctx, ctx.chatSummary);

      if (commitResult.commitHash) {
        await db
          .update(messages)
          .set({ commitHash: commitResult.commitHash })
          .where(eq(messages.id, placeholderMessageId));
      }

      // Store Neon DB timestamp for version tracking / time-travel
      if (ctx.neonProjectId && ctx.neonActiveBranchId) {
        try {
          await storeDbTimestampAtCurrentVersion({ appId: ctx.appId });
        } catch (error) {
          logger.error(
            "Error storing Neon timestamp at current version:",
            error,
          );
        }
      }
    }

    // Mark as approved (auto-approve for local-agent)
    await db
      .update(messages)
      .set({ approvalState: "approved" })
      .where(eq(messages.id, placeholderMessageId));

    // Send telemetry for files with multiple edit tool types
    for (const [filePath, counts] of Object.entries(fileEditTracker)) {
      const toolsUsed = Object.entries(counts).filter(([, count]) => count > 0);
      if (toolsUsed.length >= 2) {
        sendTelemetryEvent("local_agent:file_edit_retry", {
          filePath,
          ...counts,
        });
      }
    }

    // Send completion
    safeSend(event.sender, "chat:response:end", {
      chatId: req.chatId,
      updatedFiles: !readOnly,
      chatSummary: ctx.chatSummary,
      warningMessages:
        warningMessages.length > 0 ? [...new Set(warningMessages)] : undefined,
    } satisfies ChatResponseEnd);

    return true; // Success
  } catch (error) {
    // Clean up any pending consent/questionnaire requests for this chat to prevent
    // stale UI banners and orphaned promises
    clearPendingConsentsForChat(req.chatId);
    clearPendingQuestionnairesForChat(req.chatId);

    if (abortController.signal.aborted) {
      // Handle cancellation
      await db
        .update(messages)
        .set({
          content: appendCancelledResponseNotice(fullResponse ?? ""),
        })
        .where(eq(messages.id, placeholderMessageId));
      return false; // Cancelled - don't consume quota
    }

    logger.error("Local agent error:", error);
    safeSend(event.sender, "chat:response:error", {
      chatId: req.chatId,
      error: `Error: ${getErrorMessage(error)}`,
      warningMessages:
        warningMessages.length > 0 ? [...new Set(warningMessages)] : undefined,
    });
    return false; // Error - don't consume quota
  }
}

function buildTerminatedRetryContinuationInstruction(): ModelMessage {
  return {
    role: "user",
    content: [{ type: "text", text: STREAM_CONTINUE_MESSAGE }],
  };
}

function unwrapStreamError(error: unknown): unknown {
  if (isRecord(error) && "error" in error) {
    return error.error;
  }
  return error;
}

function getErrorMessage(error: unknown): string {
  if (error instanceof Error) {
    return `${error.name}: ${error.message}`;
  }
  if (typeof error === "string") {
    return error;
  }
  if (isRecord(error)) {
    if (typeof error.message === "string" && error.message.length > 0) {
      return error.message;
    }
    if ("error" in error) {
      return getErrorMessage(error.error);
    }
    if ("cause" in error) {
      return getErrorMessage(error.cause);
    }
  }
  try {
    return JSON.stringify(error);
  } catch {
    return String(error);
  }
}

function isTerminatedStreamError(error: unknown): boolean {
  const normalized = unwrapStreamError(error);
  const message = getErrorMessage(normalized).toLowerCase();
  if (message.includes("typeerror: terminated") || message === "terminated") {
    return true;
  }
  const cause =
    isRecord(normalized) && "cause" in normalized
      ? normalized.cause
      : undefined;
  if (cause) {
    return isTerminatedStreamError(cause);
  }
  return false;
}

function isRetryableProviderStreamError(error: unknown): boolean {
  const normalized = unwrapStreamError(error);
  if (!isRecord(normalized)) {
    return false;
  }

  const statusCode =
    (typeof normalized.statusCode === "number" && normalized.statusCode) ||
    (typeof normalized.status === "number" && normalized.status) ||
    (isRecord(normalized.response) &&
    typeof normalized.response.status === "number"
      ? normalized.response.status
      : undefined);

  if (
    typeof statusCode === "number" &&
    (statusCode >= 500 || RETRYABLE_STREAM_ERROR_STATUS_CODES.has(statusCode))
  ) {
    return true;
  }

  const errorString =
    [
      typeof normalized.message === "string" ? normalized.message : undefined,
      typeof normalized.code === "string" ? normalized.code : undefined,
      typeof normalized.type === "string" ? normalized.type : undefined,
    ]
      .filter(Boolean)
      .join(" ")
      .toLowerCase() || getErrorMessage(normalized).toLowerCase();

  return RETRYABLE_STREAM_ERROR_PATTERNS.some((pattern) =>
    errorString.includes(pattern),
  );
}

function shouldRetryTransientStreamError(params: {
  error: unknown;
  retryCount: number;
  aborted: boolean;
}): boolean {
  const { error, retryCount, aborted } = params;
  return (
    !aborted &&
    retryCount < MAX_TERMINATED_STREAM_RETRIES &&
    (isTerminatedStreamError(error) || isRetryableProviderStreamError(error))
  );
}

async function delay(ms: number): Promise<void> {
  await new Promise<void>((resolve) => setTimeout(resolve, ms));
}

async function updateResponseInDb(messageId: number, content: string) {
  await db
    .update(messages)
    .set({ content })
    .where(eq(messages.id, messageId))
    .catch((err) => logger.error("Failed to update message", err));
}

function sendResponseChunk(
  event: IpcMainInvokeEvent,
  chatId: number,
  chat: any,
  fullResponse: string,
  placeholderMessageId: number,
  hiddenMessageIds?: Set<number>,
  /** When true, sends the full messages array instead of an incremental update */
  sendFullMessages?: boolean,
) {
  if (sendFullMessages) {
    const currentMessages = [...chat.messages].filter(
      (message) => !hiddenMessageIds?.has(message.id),
    );
    const placeholderMsg = currentMessages.find(
      (m) => m.id === placeholderMessageId,
    );
    if (placeholderMsg) {
      placeholderMsg.content = fullResponse;
    }
    safeSend(event.sender, "chat:response:chunk", {
      chatId,
      messages: currentMessages,
    });
  } else {
    // Send incremental update with only the streaming message content
    // to reduce IPC overhead during high-frequency streaming
    safeSend(event.sender, "chat:response:chunk", {
      chatId,
      streamingMessageId: placeholderMessageId,
      streamingContent: fullResponse,
    });
  }
}

function getPlanningQuestionnaireErrorFromStep(step: {
  content?: unknown;
}): string | null {
  if (!Array.isArray(step.content)) {
    return null;
  }

  for (const part of step.content) {
    if (!isRecord(part) || part.toolName !== PLANNING_QUESTIONNAIRE_TOOL_NAME) {
      continue;
    }

    if (part.type === "tool-error") {
      return typeof part.error === "string" ? part.error : "Unknown tool error";
    }

    if (
      part.type === "tool-result" &&
      typeof part.output === "string" &&
      part.output.startsWith("Error:")
    ) {
      return part.output;
    }
  }

  return null;
}

function buildPlanningQuestionnaireReflectionMessage(
  errorDetail?: string,
  planModeOnly?: boolean,
): string {
  const base = "Your planning_questionnaire tool call had a format error.";
  const detail = errorDetail ? ` The error was: ${errorDetail}` : "";
  if (planModeOnly) {
    return `[System]${base}${detail} Review the tool's input schema, fix the issue, and re-call planning_questionnaire with correct arguments.`;
  }
  return `[System]${base}${detail} Skip the questionnaire step and proceed directly to the planning phase.`;
}

function isRecord(value: unknown): value is Record<string, unknown> {
  return typeof value === "object" && value !== null;
}

function stepOnlyCalledTool(
  step: { toolCalls: Array<unknown> },
  toolName: string,
): boolean {
  return (
    step.toolCalls.length > 0 &&
    step.toolCalls.every(
      (toolCall) => isRecord(toolCall) && toolCall.toolName === toolName,
    )
  );
}

function shouldRunTodoFollowUpPass(params: {
  readOnly: boolean;
  planModeOnly: boolean;
  passEndedWithText: boolean;
  todos: AgentContext["todos"];
  todoFollowUpLoops: number;
  maxTodoFollowUpLoops: number;
}): boolean {
  const {
    readOnly,
    planModeOnly,
    passEndedWithText,
    todos,
    todoFollowUpLoops,
    maxTodoFollowUpLoops,
  } = params;
  return (
    !readOnly &&
    !planModeOnly &&
    passEndedWithText &&
    hasIncompleteTodos(todos) &&
    todoFollowUpLoops < maxTodoFollowUpLoops
  );
}

async function getMcpTools(
  event: IpcMainInvokeEvent,
  ctx: AgentContext,
): Promise<ToolSet> {
  const mcpToolSet: ToolSet = {};

  try {
    const servers = await db
      .select()
      .from(mcpServers)
      .where(eq(mcpServers.enabled, true as any));

    for (const s of servers) {
      const client = await mcpManager.getClient(s.id);
      const toolSet = await client.tools();

      for (const [name, mcpTool] of Object.entries(toolSet)) {
        const key = `${sanitizeMcpName(s.name || "")}__${sanitizeMcpName(name)}`;

        mcpToolSet[key] = {
          description: mcpTool.description,
          inputSchema: mcpTool.inputSchema,
          execute: async (args: unknown, execCtx: ToolExecutionOptions) => {
            try {
              const inputPreview =
                typeof args === "string"
                  ? args
                  : Array.isArray(args)
                    ? args.join(" ")
                    : JSON.stringify(args).slice(0, 500);

              const ok = await requireMcpToolConsent(event, {
                serverId: s.id,
                serverName: s.name,
                toolName: name,
                toolDescription: mcpTool.description,
                inputPreview,
              });

              if (!ok) throw new Error(`User declined running tool ${key}`);

              // Emit XML for UI (MCP tools don't stream, so use onXmlComplete directly)
              const { serverName, toolName } = parseMcpToolKey(key);
              const content = JSON.stringify(args, null, 2);
              ctx.onXmlComplete(
                `<dyad-mcp-tool-call server="${serverName}" tool="${toolName}">\n${content}\n</dyad-mcp-tool-call>`,
              );

              const res = await mcpTool.execute(args, execCtx);
              const resultStr =
                typeof res === "string" ? res : JSON.stringify(res);

              ctx.onXmlComplete(
                `<dyad-mcp-tool-result server="${serverName}" tool="${toolName}">\n${resultStr}\n</dyad-mcp-tool-result>`,
              );

              return resultStr;
            } catch (error) {
              const errorMessage =
                error instanceof Error ? error.message : String(error);
              const errorStack =
                error instanceof Error && error.stack ? error.stack : "";
              ctx.onXmlComplete(
                `<dyad-output type="error" message="MCP tool '${key}' failed: ${escapeXmlAttr(errorMessage)}">${escapeXmlContent(errorStack || errorMessage)}</dyad-output>`,
              );
              throw error;
            }
          },
        };
      }
    }
  } catch (e) {
    logger.warn("Failed building MCP toolset for local-agent", e);
  }

  return mcpToolSet;
}
