fix: strip null values from tool call args to prevent Jinja template errors

src/api/transform/__tests__/openai-format.spec.ts

@@ -112,6 +112,39 @@ describe("convertToOpenAiMessages", () => {
 		})
 	})
 
+	it("should strip null values from tool call arguments to prevent Jinja template errors", () => {
+		const anthropicMessages: Anthropic.Messages.MessageParam[] = [
+			{
+				role: "assistant",
+				content: [
+					{
+						type: "tool_use",
+						id: "followup-123",
+						name: "ask_followup_question",
+						input: {
+							question: "Pick one",
+							follow_up: [
+								{ text: "Option A", mode: null },
+								{ text: "Option B", mode: "code" },
+							],
+						},
+					},
+				],
+			},
+		]
+
+		const openAiMessages = convertToOpenAiMessages(anthropicMessages)
+		const assistantMessage = openAiMessages[0] as OpenAI.Chat.ChatCompletionAssistantMessageParam
+		const toolCall = assistantMessage.tool_calls![0] as any
+		const args = JSON.parse(toolCall.function.arguments)
+
+		// null mode should be stripped (becomes undefined, omitted from JSON)
+		expect(args.follow_up[0]).toEqual({ text: "Option A" })
+		expect(args.follow_up[0].mode).toBeUndefined()
+		// non-null mode should be preserved
+		expect(args.follow_up[1]).toEqual({ text: "Option B", mode: "code" })
+	})
+
 	it("should handle user messages with tool results (no normalization without normalizeToolCallId)", () => {
 		const anthropicMessages: Anthropic.Messages.MessageParam[] = [
 			{

src/api/transform/openai-format.ts

@@ -467,8 +467,13 @@ export function convertToOpenAiMessages(
 					type: "function",
 					function: {
 						name: toolMessage.name,
-						// json string
-						arguments: JSON.stringify(toolMessage.input),
+						// Serialize as JSON, stripping null values to prevent Jinja template
+						// errors on local models (e.g. "Cannot convert value of type
+						// Optional<Any> to Jinja Value"). Null in tool args typically means
+						// "not provided" and should be omitted instead.
+						arguments: JSON.stringify(toolMessage.input, (_key, value) =>
+							value === null ? undefined : value,
+						),
 					},
 				}))
 

src/core/prompts/tools/native-tools/ask_followup_question.ts

@@ -7,7 +7,7 @@ Parameters:
 - follow_up: (required) A list of 2-4 suggested answers. Suggestions must be complete, actionable answers without placeholders. Optionally include mode to switch modes (code/architect/etc.)
 
 Example: Asking for file path
-{ "question": "What is the path to the frontend-config.json file?", "follow_up": [{ "text": "./src/frontend-config.json", "mode": null }, { "text": "./config/frontend-config.json", "mode": null }, { "text": "./frontend-config.json", "mode": null }] }
+{ "question": "What is the path to the frontend-config.json file?", "follow_up": [{ "text": "./src/frontend-config.json" }, { "text": "./config/frontend-config.json" }, { "text": "./frontend-config.json" }] }
 
 Example: Asking with mode switch
 { "question": "Would you like me to implement this feature?", "follow_up": [{ "text": "Yes, implement it now", "mode": "code" }, { "text": "No, just plan it out", "mode": "architect" }] }`
@@ -25,7 +25,12 @@ export default {
 	function: {
 		name: "ask_followup_question",
 		description: ASK_FOLLOWUP_QUESTION_DESCRIPTION,
-		strict: true,
+		// Note: strict mode is intentionally disabled for this tool.
+		// With strict: true, OpenAI requires ALL properties to be in the 'required' array,
+		// which forces the LLM to always provide explicit values (even null) for optional params.
+		// Local models using Jinja chat templates cannot handle null values in tool call arguments,
+		// causing "Cannot convert value of type Optional<Any> to Jinja Value" errors.
+		// By disabling strict mode, the LLM can omit the optional `mode` parameter entirely.
 		parameters: {
 			type: "object",
 			properties: {
@@ -44,11 +49,11 @@ export default {
 								description: FOLLOW_UP_TEXT_DESCRIPTION,
 							},
 							mode: {
-								type: ["string", "null"],
+								type: "string",
 								description: FOLLOW_UP_MODE_DESCRIPTION,
 							},
 						},
-						required: ["text", "mode"],
+						required: ["text"],
 						additionalProperties: false,
 					},
 					minItems: 1,

src/core/tools/AskFollowupQuestionTool.ts

@@ -39,10 +39,18 @@ export class AskFollowupQuestionTool extends BaseTool<"ask_followup_question"> {
 				return
 			}
 
-			// Transform follow_up suggestions to the format expected by task.ask
+			// Transform follow_up suggestions to the format expected by task.ask.
+			// Omit `mode` when it's null/undefined to avoid Jinja template errors
+			// on local models that can't handle null values in tool call arguments.
 			const follow_up_json = {
 				question,
-				suggest: follow_up.map((s) => ({ answer: s.text, mode: s.mode })),
+				suggest: follow_up.map((s) => {
+					const suggestion: { answer: string; mode?: string } = { answer: s.text }
+					if (s.mode != null) {
+						suggestion.mode = s.mode
+					}
+					return suggestion
+				}),
 			}
 
 			task.consecutiveMistakeCount = 0

src/core/tools/__tests__/askFollowupQuestionTool.spec.ts

@@ -82,6 +82,37 @@ describe("askFollowupQuestionTool", () => {
 		)
 	})
 
+	it("should strip null mode values from suggestions to prevent Jinja template errors", async () => {
+		const block: ToolUse = {
+			type: "tool_use",
+			name: "ask_followup_question",
+			params: {
+				question: "What would you like to do?",
+			},
+			nativeArgs: {
+				question: "What would you like to do?",
+				follow_up: [
+					{ text: "Option A", mode: null as any },
+					{ text: "Option B", mode: "code" },
+				],
+			},
+			partial: false,
+		}
+
+		await askFollowupQuestionTool.handle(mockCline, block as ToolUse<"ask_followup_question">, {
+			askApproval: vi.fn(),
+			handleError: vi.fn(),
+			pushToolResult: mockPushToolResult,
+		})
+
+		// mode: null should be stripped, mode: "code" should be preserved
+		expect(mockCline.ask).toHaveBeenCalledWith(
+			"followup",
+			expect.stringContaining('"suggest":[{"answer":"Option A"},{"answer":"Option B","mode":"code"}]'),
+			false,
+		)
+	})
+
 	it("should handle mixed suggestions with and without mode attributes", async () => {
 		const block: ToolUse = {
 			type: "tool_use",