diff --git a/apps/open-swe/src/graphs/programmer/nodes/generate-message/index.ts b/apps/open-swe/src/graphs/programmer/nodes/generate-message/index.ts
index a1c63e2c..2ee2f35a 100644
--- a/apps/open-swe/src/graphs/programmer/nodes/generate-message/index.ts
+++ b/apps/open-swe/src/graphs/programmer/nodes/generate-message/index.ts
@@ -3,10 +3,12 @@ import {
   GraphState,
   GraphConfig,
   GraphUpdate,
+  TaskPlan,
 } from "@open-swe/shared/open-swe/types";
 import {
   getModelManager,
   loadModel,
+  Provider,
   supportsParallelToolCallsParam,
   Task,
 } from "../../../../utils/llms/index.js";
@@ -50,7 +52,12 @@ import {
   trackCachePerformance,
 } from "../../../../utils/caching.js";
 import { createMarkTaskCompletedToolFields } from "@open-swe/shared/open-swe/tools";
-import { HumanMessage } from "@langchain/core/messages";
+import {
+  BaseMessage,
+  BaseMessageLike,
+  HumanMessage,
+} from "@langchain/core/messages";
+import { BindToolsInput } from "@langchain/core/language_models/chat_models";
 
 const logger = createLogger(LogLevel.INFO, "GenerateMessageNode");
 
@@ -91,7 +98,10 @@ const formatStaticInstructionsPrompt = (
 
 const formatCacheablePrompt = (
   state: GraphState,
-  isAnthropicModel: boolean,
+  args?: {
+    isAnthropicModel?: boolean;
+    excludeCacheControl?: boolean;
+  },
 ): CacheablePromptSegment[] => {
   const codeReview = getCodeReviewFields(state.internalMessages);
 
@@ -99,15 +109,19 @@ const formatCacheablePrompt = (
     // Cache Breakpoint 2: Static Instructions
     {
       type: "text",
-      text: formatStaticInstructionsPrompt(state, isAnthropicModel),
-      cache_control: { type: "ephemeral" },
+      text: formatStaticInstructionsPrompt(state, !!args?.isAnthropicModel),
+      ...(!args?.excludeCacheControl
+        ? { cache_control: { type: "ephemeral" } }
+        : {}),
     },
 
     // Cache Breakpoint 3: Dynamic Context
     {
       type: "text",
       text: formatDynamicContextPrompt(state),
-      cache_control: { type: "ephemeral" },
+      ...(!args?.excludeCacheControl
+        ? { cache_control: { type: "ephemeral" } }
+        : {}),
     },
   ];
 
@@ -119,7 +133,9 @@ const formatCacheablePrompt = (
         review: codeReview.review,
         newActions: codeReview.newActions,
       }),
-      cache_control: { type: "ephemeral" },
+      ...(!args?.excludeCacheControl
+        ? { cache_control: { type: "ephemeral" } }
+        : {}),
     });
   }
 
@@ -147,20 +163,18 @@ const formatSpecificPlanPrompt = (state: GraphState): HumanMessage => {
   });
 };
 
-export async function generateAction(
+async function createToolsAndPrompt(
   state: GraphState,
   config: GraphConfig,
-): Promise<GraphUpdate> {
-  const model = await loadModel(config, Task.PROGRAMMER);
-  const modelManager = getModelManager();
-  const modelName = modelManager.getModelNameForTask(config, Task.PROGRAMMER);
-  const modelSupportsParallelToolCallsParam = supportsParallelToolCallsParam(
-    config,
-    Task.PROGRAMMER,
-  );
+  options: {
+    latestTaskPlan: TaskPlan | null;
+    missingMessages: BaseMessage[];
+  },
+): Promise<{
+  providerTools: Record<Provider, BindToolsInput[]>;
+  providerMessages: Record<Provider, BaseMessageLike[]>;
+}> {
   const mcpTools = await getMcpTools(config);
-  const markTaskCompletedTool = createMarkTaskCompletedToolFields();
-  const isAnthropicModel = modelName.includes("claude-");
   const sharedTools = [
     createGrepTool(state),
     createShellTool(state),
@@ -168,69 +182,132 @@ export async function generateAction(
     createUpdatePlanToolFields(),
     createGetURLContentTool(state),
     createInstallDependenciesTool(state),
-    markTaskCompletedTool,
+    createMarkTaskCompletedToolFields(),
     createSearchDocumentForTool(state, config),
     ...mcpTools,
   ];
-  const anthropicModelTools = [
-    {
-      type: "text_editor_20250429",
-      name: "str_replace_based_edit_tool",
-    },
-  ];
-  const nonAnthropicModelTools = [createApplyPatchTool(state)];
 
-  const tools = [
-    ...sharedTools,
-    ...(isAnthropicModel ? anthropicModelTools : nonAnthropicModelTools),
-  ];
   logger.info(
     `MCP tools added to Programmer: ${mcpTools.map((t) => t.name).join(", ")}`,
   );
-  // Cache Breakpoint 1: Add cache_control marker to the last tool for tools definition caching
-  tools[tools.length - 1] = {
-    ...tools[tools.length - 1],
-    cache_control: { type: "ephemeral" },
-  } as any;
 
-  const modelWithTools = model.bindTools(tools, {
-    tool_choice: "auto",
-    ...(modelSupportsParallelToolCallsParam
-      ? {
-          parallel_tool_calls: true,
-        }
-      : {}),
-  });
+  const anthropicModelTools = [
+    ...sharedTools,
+    {
+      type: "text_editor_20250429",
+      name: "str_replace_based_edit_tool",
+      cache_control: { type: "ephemeral" },
+    },
+  ];
+  const nonAnthropicModelTools = [
+    ...sharedTools,
+    { ...createApplyPatchTool(state), cache_control: { type: "ephemeral" } },
+  ];
+
+  const inputMessages = filterMessagesWithoutContent([
+    ...state.internalMessages,
+    ...options.missingMessages,
+  ]);
+  if (!inputMessages.length) {
+    throw new Error("No messages to process.");
+  }
+
+  const anthropicMessages = [
+    {
+      role: "system",
+      content: formatCacheablePrompt(
+        {
+          ...state,
+          taskPlan: options.latestTaskPlan ?? state.taskPlan,
+        },
+        {
+          isAnthropicModel: true,
+          excludeCacheControl: false,
+        },
+      ),
+    },
+    ...convertMessagesToCacheControlledMessages(inputMessages),
+    formatSpecificPlanPrompt(state),
+  ];
+
+  const nonAnthropicMessages = [
+    {
+      role: "system",
+      content: formatCacheablePrompt(
+        {
+          ...state,
+          taskPlan: options.latestTaskPlan ?? state.taskPlan,
+        },
+        {
+          isAnthropicModel: false,
+          excludeCacheControl: true,
+        },
+      ),
+    },
+    ...inputMessages,
+    formatSpecificPlanPrompt(state),
+  ];
+
+  return {
+    providerTools: {
+      anthropic: anthropicModelTools,
+      openai: nonAnthropicModelTools,
+      "google-genai": nonAnthropicModelTools,
+    },
+    providerMessages: {
+      anthropic: anthropicMessages,
+      openai: nonAnthropicMessages,
+      "google-genai": nonAnthropicMessages,
+    },
+  };
+}
+
+export async function generateAction(
+  state: GraphState,
+  config: GraphConfig,
+): Promise<GraphUpdate> {
+  const modelManager = getModelManager();
+  const modelName = modelManager.getModelNameForTask(config, Task.PROGRAMMER);
+  const modelSupportsParallelToolCallsParam = supportsParallelToolCallsParam(
+    config,
+    Task.PROGRAMMER,
+  );
+  const markTaskCompletedTool = createMarkTaskCompletedToolFields();
+  const isAnthropicModel = modelName.includes("claude-");
 
   const [missingMessages, { taskPlan: latestTaskPlan }] = await Promise.all([
     getMissingMessages(state, config),
     getPlansFromIssue(state, config),
   ]);
 
-  const inputMessages = filterMessagesWithoutContent([
-    ...state.internalMessages,
-    ...missingMessages,
-  ]);
-  if (!inputMessages.length) {
-    throw new Error("No messages to process.");
-  }
-
-  const inputMessagesWithCache =
-    convertMessagesToCacheControlledMessages(inputMessages);
-  const response = await modelWithTools.invoke([
+  const { providerTools, providerMessages } = await createToolsAndPrompt(
+    state,
+    config,
     {
-      role: "system",
-      content: formatCacheablePrompt(
-        {
-          ...state,
-          taskPlan: latestTaskPlan ?? state.taskPlan,
-        },
-        isAnthropicModel,
-      ),
+      latestTaskPlan,
+      missingMessages,
     },
-    ...inputMessagesWithCache,
-    formatSpecificPlanPrompt(state),
-  ]);
+  );
+
+  const model = await loadModel(config, Task.PROGRAMMER, {
+    providerTools: providerTools,
+    providerMessages: providerMessages,
+  });
+
+  const modelWithTools = model.bindTools(
+    isAnthropicModel ? providerTools.anthropic : providerTools.openai,
+    {
+      tool_choice: "auto",
+      ...(modelSupportsParallelToolCallsParam
+        ? {
+            parallel_tool_calls: true,
+          }
+        : {}),
+    },
+  );
+  const response = await modelWithTools.invoke(
+    isAnthropicModel ? providerMessages.anthropic : providerMessages.openai,
+  );
 
   const hasToolCalls = !!response.tool_calls?.length;
   // No tool calls means the graph is going to end. Stop the sandbox.
diff --git a/apps/open-swe/src/graphs/reviewer/nodes/generate-review-actions/index.ts b/apps/open-swe/src/graphs/reviewer/nodes/generate-review-actions/index.ts
index e30d3801..3c1f5093 100644
--- a/apps/open-swe/src/graphs/reviewer/nodes/generate-review-actions/index.ts
+++ b/apps/open-swe/src/graphs/reviewer/nodes/generate-review-actions/index.ts
@@ -1,6 +1,7 @@
 import {
   getModelManager,
   loadModel,
+  Provider,
   supportsParallelToolCallsParam,
   Task,
 } from "../../../../utils/llms/index.js";
@@ -26,7 +27,7 @@ import {
   formatCodeReviewPrompt,
   getCodeReviewFields,
 } from "../../../../utils/review.js";
-import { BaseMessage } from "@langchain/core/messages";
+import { BaseMessage, BaseMessageLike } from "@langchain/core/messages";
 import { getMessageString } from "../../../../utils/message/content.js";
 import {
   CacheablePromptSegment,
@@ -35,6 +36,7 @@ import {
 } from "../../../../utils/caching.js";
 import { createScratchpadTool } from "../../../../tools/scratchpad.js";
 import { createViewTool } from "../../../../tools/builtin-tools/view.js";
+import { BindToolsInput } from "@langchain/core/language_models/chat_models";
 
 const logger = createLogger(LogLevel.INFO, "GenerateReviewActionsNode");
 
@@ -66,6 +68,9 @@ function formatSystemPrompt(state: ReviewerGraphState): string {
 
 const formatCacheablePrompt = (
   state: ReviewerGraphState,
+  args?: {
+    excludeCacheControl?: boolean;
+  },
 ): CacheablePromptSegment[] => {
   const codeReview = getCodeReviewFields(state.internalMessages);
 
@@ -73,7 +78,9 @@ const formatCacheablePrompt = (
     {
       type: "text",
       text: formatSystemPrompt(state),
-      cache_control: { type: "ephemeral" },
+      ...(!args?.excludeCacheControl
+        ? { cache_control: { type: "ephemeral" } }
+        : {}),
     },
   ];
 
@@ -85,7 +92,9 @@ const formatCacheablePrompt = (
         review: codeReview.review,
         newActions: codeReview.newActions,
       }),
-      cache_control: { type: "ephemeral" },
+      ...(!args?.excludeCacheControl
+        ? { cache_control: { type: "ephemeral" } }
+        : {}),
     });
   }
 
@@ -94,6 +103,9 @@ const formatCacheablePrompt = (
 
 function formatUserConversationHistoryMessage(
   messages: BaseMessage[],
+  args?: {
+    excludeCacheControl?: boolean;
+  },
 ): CacheablePromptSegment[] {
   return [
     {
@@ -104,22 +116,17 @@ If the history has been truncated, it is because the conversation was too long.
 <conversation_history>
 ${messages.map(getMessageString).join("\n")}
 </conversation_history>`,
-      cache_control: { type: "ephemeral" },
+      ...(!args?.excludeCacheControl
+        ? { cache_control: { type: "ephemeral" } }
+        : {}),
     },
   ];
 }
 
-export async function generateReviewActions(
-  state: ReviewerGraphState,
-  config: GraphConfig,
-): Promise<ReviewerGraphUpdate> {
-  const model = await loadModel(config, Task.REVIEWER);
-  const modelManager = getModelManager();
-  const modelName = modelManager.getModelNameForTask(config, Task.REVIEWER);
-  const modelSupportsParallelToolCallsParam = supportsParallelToolCallsParam(
-    config,
-    Task.REVIEWER,
-  );
+function createToolsAndPrompt(state: ReviewerGraphState): {
+  providerTools: Record<Provider, BindToolsInput[]>;
+  providerMessages: Record<Provider, BaseMessageLike[]>;
+} {
   const tools = [
     createGrepTool(state),
     createShellTool(state),
@@ -129,34 +136,87 @@ export async function generateReviewActions(
       "when generating a final review, after all context gathering and reviewing is complete",
     ),
   ];
-  tools[tools.length - 1] = {
-    ...tools[tools.length - 1],
+  const anthropicTools = tools;
+  anthropicTools[anthropicTools.length - 1] = {
+    ...anthropicTools[anthropicTools.length - 1],
     cache_control: { type: "ephemeral" },
   } as any;
+  const nonAnthropicTools = tools;
 
-  const modelWithTools = model.bindTools(tools, {
-    tool_choice: "auto",
-    ...(modelSupportsParallelToolCallsParam
-      ? {
-          parallel_tool_calls: true,
-        }
-      : {}),
-  });
-
-  const reviewerMessagesWithCache = convertMessagesToCacheControlledMessages(
-    state.reviewerMessages,
-  );
-  const response = await modelWithTools.invoke([
+  const anthropicMessages = [
     {
       role: "system",
-      content: formatCacheablePrompt(state),
+      content: formatCacheablePrompt(state, { excludeCacheControl: false }),
     },
     {
       role: "user",
-      content: formatUserConversationHistoryMessage(state.internalMessages),
+      content: formatUserConversationHistoryMessage(state.internalMessages, {
+        excludeCacheControl: false,
+      }),
     },
-    ...reviewerMessagesWithCache,
-  ]);
+    ...convertMessagesToCacheControlledMessages(state.reviewerMessages),
+  ];
+  const nonAnthropicMessages = [
+    {
+      role: "system",
+      content: formatCacheablePrompt(state, { excludeCacheControl: true }),
+    },
+    {
+      role: "user",
+      content: formatUserConversationHistoryMessage(state.internalMessages, {
+        excludeCacheControl: true,
+      }),
+    },
+    ...state.reviewerMessages,
+  ];
+
+  return {
+    providerTools: {
+      anthropic: anthropicTools,
+      openai: nonAnthropicTools,
+      "google-genai": nonAnthropicTools,
+    },
+    providerMessages: {
+      anthropic: anthropicMessages,
+      openai: nonAnthropicMessages,
+      "google-genai": nonAnthropicMessages,
+    },
+  };
+}
+
+export async function generateReviewActions(
+  state: ReviewerGraphState,
+  config: GraphConfig,
+): Promise<ReviewerGraphUpdate> {
+  const modelManager = getModelManager();
+  const modelName = modelManager.getModelNameForTask(config, Task.REVIEWER);
+  const modelSupportsParallelToolCallsParam = supportsParallelToolCallsParam(
+    config,
+    Task.REVIEWER,
+  );
+  const isAnthropicModel = modelName.includes("claude-");
+
+  const { providerTools, providerMessages } = createToolsAndPrompt(state);
+
+  const model = await loadModel(config, Task.REVIEWER, {
+    providerTools,
+    providerMessages,
+  });
+  const modelWithTools = model.bindTools(
+    isAnthropicModel ? providerTools.anthropic : providerTools.openai,
+    {
+      tool_choice: "auto",
+      ...(modelSupportsParallelToolCallsParam
+        ? {
+            parallel_tool_calls: true,
+          }
+        : {}),
+    },
+  );
+
+  const response = await modelWithTools.invoke(
+    isAnthropicModel ? providerMessages.anthropic : providerMessages.openai,
+  );
 
   logger.info("Generated review actions", {
     ...(getMessageContentString(response.content) && {
diff --git a/apps/open-swe/src/tools/builtin-tools/view.ts b/apps/open-swe/src/tools/builtin-tools/view.ts
index 1485af63..1ca6f57a 100644
--- a/apps/open-swe/src/tools/builtin-tools/view.ts
+++ b/apps/open-swe/src/tools/builtin-tools/view.ts
@@ -26,7 +26,7 @@ export function createViewTool(
           sandbox,
           path,
           workDir,
-          view_range,
+          view_range as [number, number] | undefined,
         );
 
         logger.info(`View command executed successfully on ${path}`);
diff --git a/apps/open-swe/src/utils/llms/load-model.ts b/apps/open-swe/src/utils/llms/load-model.ts
index 089af472..1d074210 100644
--- a/apps/open-swe/src/utils/llms/load-model.ts
+++ b/apps/open-swe/src/utils/llms/load-model.ts
@@ -1,16 +1,31 @@
 import { GraphConfig } from "@open-swe/shared/open-swe/types";
-import { getModelManager } from "./model-manager.js";
+import { getModelManager, Provider } from "./model-manager.js";
 import { FallbackRunnable } from "../runtime-fallback.js";
 import { Task, TASK_TO_CONFIG_DEFAULTS_MAP } from "./constants.js";
+import { BindToolsInput } from "@langchain/core/language_models/chat_models";
+import { BaseMessageLike } from "@langchain/core/messages";
 
-export async function loadModel(config: GraphConfig, task: Task) {
+export async function loadModel(
+  config: GraphConfig,
+  task: Task,
+  options?: {
+    providerTools?: Record<Provider, BindToolsInput[]>;
+    providerMessages?: Record<Provider, BaseMessageLike[]>;
+  },
+) {
   const modelManager = getModelManager();
 
   const model = await modelManager.loadModel(config, task);
   if (!model) {
     throw new Error(`Model loading returned undefined for task: ${task}`);
   }
-  const fallbackModel = new FallbackRunnable(model, config, task, modelManager);
+  const fallbackModel = new FallbackRunnable(
+    model,
+    config,
+    task,
+    modelManager,
+    options,
+  );
   return fallbackModel;
 }
 
diff --git a/apps/open-swe/src/utils/runtime-fallback.ts b/apps/open-swe/src/utils/runtime-fallback.ts
index bb14b2ba..5f5a6b21 100644
--- a/apps/open-swe/src/utils/runtime-fallback.ts
+++ b/apps/open-swe/src/utils/runtime-fallback.ts
@@ -1,6 +1,6 @@
 import { GraphConfig } from "@open-swe/shared/open-swe/types";
 import { Task } from "./llms/index.js";
-import { ModelManager } from "./llms/model-manager.js";
+import { ModelManager, Provider } from "./llms/model-manager.js";
 import { createLogger, LogLevel } from "./logger.js";
 import { Runnable, RunnableConfig } from "@langchain/core/runnables";
 import { StructuredToolInterface } from "@langchain/core/tools";
@@ -8,7 +8,11 @@ import {
   ConfigurableChatModelCallOptions,
   ConfigurableModel,
 } from "langchain/chat_models/universal";
-import { AIMessageChunk, BaseMessage } from "@langchain/core/messages";
+import {
+  AIMessageChunk,
+  BaseMessage,
+  BaseMessageLike,
+} from "@langchain/core/messages";
 import { ChatResult, ChatGeneration } from "@langchain/core/outputs";
 import { BaseLanguageModelInput } from "@langchain/core/language_models/base";
 import { BindToolsInput } from "@langchain/core/language_models/chat_models";
@@ -17,10 +21,21 @@ import { getMessageContentString } from "@open-swe/shared/messages";
 const logger = createLogger(LogLevel.DEBUG, "FallbackRunnable");
 
 interface ExtractedTools {
-  tools: StructuredToolInterface[];
+  tools: BindToolsInput[];
   kwargs: Record<string, any>;
 }
 
+function useProviderMessages(
+  initialInput: BaseLanguageModelInput,
+  providerMessages?: Record<Provider, BaseMessageLike[]>,
+  provider?: Provider,
+): BaseLanguageModelInput {
+  if (!provider || !providerMessages?.[provider]) {
+    return initialInput;
+  }
+  return providerMessages[provider];
+}
+
 export class FallbackRunnable<
   RunInput extends BaseLanguageModelInput = BaseLanguageModelInput,
   CallOptions extends
@@ -30,12 +45,18 @@ export class FallbackRunnable<
   private config: GraphConfig;
   private task: Task;
   private modelManager: ModelManager;
+  private providerTools?: Record<Provider, BindToolsInput[]>;
+  private providerMessages?: Record<Provider, BaseMessageLike[]>;
 
   constructor(
     primaryRunnable: any,
     config: GraphConfig,
     task: Task,
     modelManager: ModelManager,
+    options?: {
+      providerTools?: Record<Provider, BindToolsInput[]>;
+      providerMessages?: Record<Provider, BaseMessageLike[]>;
+    },
   ) {
     super({
       configurableFields: "any",
@@ -47,6 +68,8 @@ export class FallbackRunnable<
     this.config = config;
     this.task = task;
     this.modelManager = modelManager;
+    this.providerTools = options?.providerTools;
+    this.providerMessages = options?.providerMessages;
   }
 
   async _generate(
@@ -90,11 +113,31 @@ export class FallbackRunnable<
         let runnableToUse: Runnable<BaseLanguageModelInput, AIMessageChunk> =
           model;
 
-        const tools = this.extractBoundTools();
-        if (tools && "bindTools" in runnableToUse && runnableToUse.bindTools) {
+        // Check if provider-specific tools exist for this provider
+        const providerSpecificTools =
+          this.providerTools?.[modelConfig.provider];
+        let toolsToUse: ExtractedTools | null = null;
+
+        if (providerSpecificTools) {
+          // Use provider-specific tools if available
+          const extractedTools = this.extractBoundTools();
+          toolsToUse = {
+            tools: providerSpecificTools,
+            kwargs: extractedTools?.kwargs || {},
+          };
+        } else {
+          // Fall back to extracted bound tools from primary model
+          toolsToUse = this.extractBoundTools();
+        }
+
+        if (
+          toolsToUse &&
+          "bindTools" in runnableToUse &&
+          runnableToUse.bindTools
+        ) {
           runnableToUse = (runnableToUse as ConfigurableModel).bindTools(
-            tools.tools,
-            tools.kwargs,
+            toolsToUse.tools,
+            toolsToUse.kwargs,
           );
         }
 
@@ -103,7 +146,14 @@ export class FallbackRunnable<
           runnableToUse = runnableToUse.withConfig(config);
         }
 
-        const result = await runnableToUse.invoke(input, options);
+        const result = await runnableToUse.invoke(
+          useProviderMessages(
+            input,
+            this.providerMessages,
+            modelConfig.provider,
+          ),
+          options,
+        );
         this.modelManager.recordSuccess(modelKey);
         return result;
       } catch (error) {
@@ -131,6 +181,10 @@ export class FallbackRunnable<
       this.config,
       this.task,
       this.modelManager,
+      {
+        providerTools: this.providerTools,
+        providerMessages: this.providerMessages,
+      },
     ) as unknown as ConfigurableModel<RunInput, CallOptions>;
   }
 
@@ -145,6 +199,10 @@ export class FallbackRunnable<
       this.config,
       this.task,
       this.modelManager,
+      {
+        providerTools: this.providerTools,
+        providerMessages: this.providerMessages,
+      },
     ) as unknown as ConfigurableModel<RunInput, CallOptions>;
   }
 
diff --git a/apps/web/src/components/thread/messages/ai.tsx b/apps/web/src/components/thread/messages/ai.tsx
index 0b650de8..bea37ea7 100644
--- a/apps/web/src/components/thread/messages/ai.tsx
+++ b/apps/web/src/components/thread/messages/ai.tsx
@@ -315,7 +315,7 @@ export function mapToolMessageToActionStepProps(
       success,
       command: args.command || "view",
       path: args.path || "",
-      view_range: args.view_range,
+      view_range: args.view_range as [number, number] | undefined,
       output,
       reasoningText,
     };
diff --git a/packages/shared/src/open-swe/tools.ts b/packages/shared/src/open-swe/tools.ts
index 866479ca..e027c14f 100644
--- a/packages/shared/src/open-swe/tools.ts
+++ b/packages/shared/src/open-swe/tools.ts
@@ -554,10 +554,10 @@ export function createViewToolFields(targetRepository: TargetRepository) {
       .string()
       .describe("The path to the file or directory to operate on"),
     view_range: z
-      .tuple([z.number(), z.number()])
+      .array(z.number())
       .optional()
       .describe(
-        "Optional array of two integers [start, end] specifying line numbers to view. Line numbers are 1-indexed. Use -1 for end to read to end of file. Only applies to view command.",
+        "Optional array of two integers [start, end] specifying line numbers to view. Line numbers are 1-indexed. Use -1 for end to read to end of file. Only applies to view command. If this is passed, ensure it is a valid array, containing only two positive integers.",
       ),
   });