WIP: Refactor agent package - not compiling

- Renamed AppMessage to AgentMessage throughout
- New agent-loop.ts with AgentLoopContext, AgentLoopConfig
- Removed transport abstraction, Agent now takes streamFn directly
- Extracted streamProxy to proxy.ts utility
- Removed agent-loop from pi-ai (now in agent package)
- Updated consumers (coding-agent, mom) for AgentMessage rename
- Tests updated but some consumers still need migration

Known issues:
- AgentTool, AgentToolResult not exported from pi-ai
- Attachment not exported from pi-agent-core
- ProviderTransport removed but still referenced
- messageTransformer -> convertToLlm migration incomplete
- CustomMessages declaration merging not working properly

packages/agent/test/agent-loop.test.ts

@@ -0,0 +1,535 @@
+import {
+	type AssistantMessage,
+	type AssistantMessageEvent,
+	EventStream,
+	type Message,
+	type Model,
+	type UserMessage,
+} from "@mariozechner/pi-ai";
+import { Type } from "@sinclair/typebox";
+import { describe, expect, it } from "vitest";
+import { agentLoop, agentLoopContinue } from "../src/agent-loop.js";
+import type { AgentContext, AgentEvent, AgentLoopConfig, AgentMessage, AgentTool } from "../src/types.js";
+
+// Mock stream for testing - mimics MockAssistantStream
+class MockAssistantStream extends EventStream<AssistantMessageEvent, AssistantMessage> {
+	constructor() {
+		super(
+			(event) => event.type === "done" || event.type === "error",
+			(event) => {
+				if (event.type === "done") return event.message;
+				if (event.type === "error") return event.error;
+				throw new Error("Unexpected event type");
+			},
+		);
+	}
+}
+
+function createUsage() {
+	return {
+		input: 0,
+		output: 0,
+		cacheRead: 0,
+		cacheWrite: 0,
+		totalTokens: 0,
+		cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
+	};
+}
+
+function createModel(): Model<"openai-responses"> {
+	return {
+		id: "mock",
+		name: "mock",
+		api: "openai-responses",
+		provider: "openai",
+		baseUrl: "https://example.invalid",
+		reasoning: false,
+		input: ["text"],
+		cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+		contextWindow: 8192,
+		maxTokens: 2048,
+	};
+}
+
+function createAssistantMessage(
+	content: AssistantMessage["content"],
+	stopReason: AssistantMessage["stopReason"] = "stop",
+): AssistantMessage {
+	return {
+		role: "assistant",
+		content,
+		api: "openai-responses",
+		provider: "openai",
+		model: "mock",
+		usage: createUsage(),
+		stopReason,
+		timestamp: Date.now(),
+	};
+}
+
+function createUserMessage(text: string): UserMessage {
+	return {
+		role: "user",
+		content: text,
+		timestamp: Date.now(),
+	};
+}
+
+// Simple identity converter for tests - just passes through standard messages
+function identityConverter(messages: AgentMessage[]): Message[] {
+	return messages.filter((m) => m.role === "user" || m.role === "assistant" || m.role === "toolResult") as Message[];
+}
+
+describe("agentLoop with AgentMessage", () => {
+	it("should emit events with AgentMessage types", async () => {
+		const context: AgentContext = {
+			systemPrompt: "You are helpful.",
+			messages: [],
+			tools: [],
+		};
+
+		const userPrompt: AgentMessage = createUserMessage("Hello");
+
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			convertToLlm: identityConverter,
+		};
+
+		const streamFn = () => {
+			const stream = new MockAssistantStream();
+			queueMicrotask(() => {
+				const message = createAssistantMessage([{ type: "text", text: "Hi there!" }]);
+				stream.push({ type: "done", reason: "stop", message });
+			});
+			return stream;
+		};
+
+		const events: AgentEvent[] = [];
+		const stream = agentLoop(userPrompt, context, config, undefined, streamFn);
+
+		for await (const event of stream) {
+			events.push(event);
+		}
+
+		const messages = await stream.result();
+
+		// Should have user message and assistant message
+		expect(messages.length).toBe(2);
+		expect(messages[0].role).toBe("user");
+		expect(messages[1].role).toBe("assistant");
+
+		// Verify event sequence
+		const eventTypes = events.map((e) => e.type);
+		expect(eventTypes).toContain("agent_start");
+		expect(eventTypes).toContain("turn_start");
+		expect(eventTypes).toContain("message_start");
+		expect(eventTypes).toContain("message_end");
+		expect(eventTypes).toContain("turn_end");
+		expect(eventTypes).toContain("agent_end");
+	});
+
+	it("should handle custom message types via convertToLlm", async () => {
+		// Create a custom message type
+		interface CustomNotification {
+			role: "notification";
+			text: string;
+			timestamp: number;
+		}
+
+		const notification: CustomNotification = {
+			role: "notification",
+			text: "This is a notification",
+			timestamp: Date.now(),
+		};
+
+		const context: AgentContext = {
+			systemPrompt: "You are helpful.",
+			messages: [notification as unknown as AgentMessage], // Custom message in context
+			tools: [],
+		};
+
+		const userPrompt: AgentMessage = createUserMessage("Hello");
+
+		let convertedMessages: Message[] = [];
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			convertToLlm: (messages) => {
+				// Filter out notifications, convert rest
+				convertedMessages = messages
+					.filter((m) => (m as { role: string }).role !== "notification")
+					.filter((m) => m.role === "user" || m.role === "assistant" || m.role === "toolResult") as Message[];
+				return convertedMessages;
+			},
+		};
+
+		const streamFn = () => {
+			const stream = new MockAssistantStream();
+			queueMicrotask(() => {
+				const message = createAssistantMessage([{ type: "text", text: "Response" }]);
+				stream.push({ type: "done", reason: "stop", message });
+			});
+			return stream;
+		};
+
+		const events: AgentEvent[] = [];
+		const stream = agentLoop(userPrompt, context, config, undefined, streamFn);
+
+		for await (const event of stream) {
+			events.push(event);
+		}
+
+		// The notification should have been filtered out in convertToLlm
+		expect(convertedMessages.length).toBe(1); // Only user message
+		expect(convertedMessages[0].role).toBe("user");
+	});
+
+	it("should apply transformContext before convertToLlm", async () => {
+		const context: AgentContext = {
+			systemPrompt: "You are helpful.",
+			messages: [
+				createUserMessage("old message 1"),
+				createAssistantMessage([{ type: "text", text: "old response 1" }]),
+				createUserMessage("old message 2"),
+				createAssistantMessage([{ type: "text", text: "old response 2" }]),
+			],
+			tools: [],
+		};
+
+		const userPrompt: AgentMessage = createUserMessage("new message");
+
+		let transformedMessages: AgentMessage[] = [];
+		let convertedMessages: Message[] = [];
+
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			transformContext: async (messages) => {
+				// Keep only last 2 messages (prune old ones)
+				transformedMessages = messages.slice(-2);
+				return transformedMessages;
+			},
+			convertToLlm: (messages) => {
+				convertedMessages = messages.filter(
+					(m) => m.role === "user" || m.role === "assistant" || m.role === "toolResult",
+				) as Message[];
+				return convertedMessages;
+			},
+		};
+
+		const streamFn = () => {
+			const stream = new MockAssistantStream();
+			queueMicrotask(() => {
+				const message = createAssistantMessage([{ type: "text", text: "Response" }]);
+				stream.push({ type: "done", reason: "stop", message });
+			});
+			return stream;
+		};
+
+		const stream = agentLoop(userPrompt, context, config, undefined, streamFn);
+
+		for await (const _ of stream) {
+			// consume
+		}
+
+		// transformContext should have been called first, keeping only last 2
+		expect(transformedMessages.length).toBe(2);
+		// Then convertToLlm receives the pruned messages
+		expect(convertedMessages.length).toBe(2);
+	});
+
+	it("should handle tool calls and results", async () => {
+		const toolSchema = Type.Object({ value: Type.String() });
+		const executed: string[] = [];
+		const tool: AgentTool<typeof toolSchema, { value: string }> = {
+			name: "echo",
+			label: "Echo",
+			description: "Echo tool",
+			parameters: toolSchema,
+			async execute(_toolCallId, params) {
+				executed.push(params.value);
+				return {
+					content: [{ type: "text", text: `echoed: ${params.value}` }],
+					details: { value: params.value },
+				};
+			},
+		};
+
+		const context: AgentContext = {
+			systemPrompt: "",
+			messages: [],
+			tools: [tool],
+		};
+
+		const userPrompt: AgentMessage = createUserMessage("echo something");
+
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			convertToLlm: identityConverter,
+		};
+
+		let callIndex = 0;
+		const streamFn = () => {
+			const stream = new MockAssistantStream();
+			queueMicrotask(() => {
+				if (callIndex === 0) {
+					// First call: return tool call
+					const message = createAssistantMessage(
+						[{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }],
+						"toolUse",
+					);
+					stream.push({ type: "done", reason: "toolUse", message });
+				} else {
+					// Second call: return final response
+					const message = createAssistantMessage([{ type: "text", text: "done" }]);
+					stream.push({ type: "done", reason: "stop", message });
+				}
+				callIndex++;
+			});
+			return stream;
+		};
+
+		const events: AgentEvent[] = [];
+		const stream = agentLoop(userPrompt, context, config, undefined, streamFn);
+
+		for await (const event of stream) {
+			events.push(event);
+		}
+
+		// Tool should have been executed
+		expect(executed).toEqual(["hello"]);
+
+		// Should have tool execution events
+		const toolStart = events.find((e) => e.type === "tool_execution_start");
+		const toolEnd = events.find((e) => e.type === "tool_execution_end");
+		expect(toolStart).toBeDefined();
+		expect(toolEnd).toBeDefined();
+		if (toolEnd?.type === "tool_execution_end") {
+			expect(toolEnd.isError).toBe(false);
+		}
+	});
+
+	it("should inject queued messages and skip remaining tool calls", async () => {
+		const toolSchema = Type.Object({ value: Type.String() });
+		const executed: string[] = [];
+		const tool: AgentTool<typeof toolSchema, { value: string }> = {
+			name: "echo",
+			label: "Echo",
+			description: "Echo tool",
+			parameters: toolSchema,
+			async execute(_toolCallId, params) {
+				executed.push(params.value);
+				return {
+					content: [{ type: "text", text: `ok:${params.value}` }],
+					details: { value: params.value },
+				};
+			},
+		};
+
+		const context: AgentContext = {
+			systemPrompt: "",
+			messages: [],
+			tools: [tool],
+		};
+
+		const userPrompt: AgentMessage = createUserMessage("start");
+		const queuedUserMessage: AgentMessage = createUserMessage("interrupt");
+
+		let queuedDelivered = false;
+		let callIndex = 0;
+		let sawInterruptInContext = false;
+
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			convertToLlm: identityConverter,
+			getQueuedMessages: async () => {
+				// Return queued message after first tool executes
+				if (executed.length === 1 && !queuedDelivered) {
+					queuedDelivered = true;
+					return [queuedUserMessage];
+				}
+				return [];
+			},
+		};
+
+		const events: AgentEvent[] = [];
+		const stream = agentLoop(userPrompt, context, config, undefined, (_model, ctx, _options) => {
+			// Check if interrupt message is in context on second call
+			if (callIndex === 1) {
+				sawInterruptInContext = ctx.messages.some(
+					(m) => m.role === "user" && typeof m.content === "string" && m.content === "interrupt",
+				);
+			}
+
+			const mockStream = new MockAssistantStream();
+			queueMicrotask(() => {
+				if (callIndex === 0) {
+					// First call: return two tool calls
+					const message = createAssistantMessage(
+						[
+							{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "first" } },
+							{ type: "toolCall", id: "tool-2", name: "echo", arguments: { value: "second" } },
+						],
+						"toolUse",
+					);
+					mockStream.push({ type: "done", reason: "toolUse", message });
+				} else {
+					// Second call: return final response
+					const message = createAssistantMessage([{ type: "text", text: "done" }]);
+					mockStream.push({ type: "done", reason: "stop", message });
+				}
+				callIndex++;
+			});
+			return mockStream;
+		});
+
+		for await (const event of stream) {
+			events.push(event);
+		}
+
+		// Only first tool should have executed
+		expect(executed).toEqual(["first"]);
+
+		// Second tool should be skipped
+		const toolEnds = events.filter(
+			(e): e is Extract<AgentEvent, { type: "tool_execution_end" }> => e.type === "tool_execution_end",
+		);
+		expect(toolEnds.length).toBe(2);
+		expect(toolEnds[0].isError).toBe(false);
+		expect(toolEnds[1].isError).toBe(true);
+		if (toolEnds[1].result.content[0]?.type === "text") {
+			expect(toolEnds[1].result.content[0].text).toContain("Skipped due to queued user message");
+		}
+
+		// Queued message should appear in events
+		const queuedMessageEvent = events.find(
+			(e) =>
+				e.type === "message_start" &&
+				e.message.role === "user" &&
+				typeof e.message.content === "string" &&
+				e.message.content === "interrupt",
+		);
+		expect(queuedMessageEvent).toBeDefined();
+
+		// Interrupt message should be in context when second LLM call is made
+		expect(sawInterruptInContext).toBe(true);
+	});
+});
+
+describe("agentLoopContinue with AgentMessage", () => {
+	it("should throw when context has no messages", () => {
+		const context: AgentContext = {
+			systemPrompt: "You are helpful.",
+			messages: [],
+			tools: [],
+		};
+
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			convertToLlm: identityConverter,
+		};
+
+		expect(() => agentLoopContinue(context, config)).toThrow("Cannot continue: no messages in context");
+	});
+
+	it("should continue from existing context without emitting user message events", async () => {
+		const userMessage: AgentMessage = createUserMessage("Hello");
+
+		const context: AgentContext = {
+			systemPrompt: "You are helpful.",
+			messages: [userMessage],
+			tools: [],
+		};
+
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			convertToLlm: identityConverter,
+		};
+
+		const streamFn = () => {
+			const stream = new MockAssistantStream();
+			queueMicrotask(() => {
+				const message = createAssistantMessage([{ type: "text", text: "Response" }]);
+				stream.push({ type: "done", reason: "stop", message });
+			});
+			return stream;
+		};
+
+		const events: AgentEvent[] = [];
+		const stream = agentLoopContinue(context, config, undefined, streamFn);
+
+		for await (const event of stream) {
+			events.push(event);
+		}
+
+		const messages = await stream.result();
+
+		// Should only return the new assistant message (not the existing user message)
+		expect(messages.length).toBe(1);
+		expect(messages[0].role).toBe("assistant");
+
+		// Should NOT have user message events (that's the key difference from agentLoop)
+		const messageEndEvents = events.filter((e) => e.type === "message_end");
+		expect(messageEndEvents.length).toBe(1);
+		expect((messageEndEvents[0] as any).message.role).toBe("assistant");
+	});
+
+	it("should allow custom message types as last message (caller responsibility)", async () => {
+		// Custom message that will be converted to user message by convertToLlm
+		interface HookMessage {
+			role: "hookMessage";
+			text: string;
+			timestamp: number;
+		}
+
+		const hookMessage: HookMessage = {
+			role: "hookMessage",
+			text: "Hook content",
+			timestamp: Date.now(),
+		};
+
+		const context: AgentContext = {
+			systemPrompt: "You are helpful.",
+			messages: [hookMessage as unknown as AgentMessage],
+			tools: [],
+		};
+
+		const config: AgentLoopConfig = {
+			model: createModel(),
+			convertToLlm: (messages) => {
+				// Convert hookMessage to user message
+				return messages
+					.map((m) => {
+						if ((m as any).role === "hookMessage") {
+							return {
+								role: "user" as const,
+								content: (m as any).text,
+								timestamp: m.timestamp,
+							};
+						}
+						return m;
+					})
+					.filter((m) => m.role === "user" || m.role === "assistant" || m.role === "toolResult") as Message[];
+			},
+		};
+
+		const streamFn = () => {
+			const stream = new MockAssistantStream();
+			queueMicrotask(() => {
+				const message = createAssistantMessage([{ type: "text", text: "Response to hook" }]);
+				stream.push({ type: "done", reason: "stop", message });
+			});
+			return stream;
+		};
+
+		// Should not throw - the hookMessage will be converted to user message
+		const stream = agentLoopContinue(context, config, undefined, streamFn);
+
+		const events: AgentEvent[] = [];
+		for await (const event of stream) {
+			events.push(event);
+		}
+
+		const messages = await stream.result();
+		expect(messages.length).toBe(1);
+		expect(messages[0].role).toBe("assistant");
+	});
+});

packages/agent/test/agent.test.ts

@@ -1,12 +1,10 @@
 import { getModel } from "@mariozechner/pi-ai";
 import { describe, expect, it } from "vitest";
-import { Agent, ProviderTransport } from "../src/index.js";
+import { Agent } from "../src/index.js";
 
 describe("Agent", () => {
 	it("should create an agent instance with default state", () => {
-		const agent = new Agent({
-			transport: new ProviderTransport(),
-		});
+		const agent = new Agent();
 
 		expect(agent.state).toBeDefined();
 		expect(agent.state.systemPrompt).toBe("");
@@ -23,7 +21,6 @@ describe("Agent", () => {
 	it("should create an agent instance with custom initial state", () => {
 		const customModel = getModel("openai", "gpt-4o-mini");
 		const agent = new Agent({
-			transport: new ProviderTransport(),
 			initialState: {
 				systemPrompt: "You are a helpful assistant.",
 				model: customModel,
@@ -37,9 +34,7 @@ describe("Agent", () => {
 	});
 
 	it("should subscribe to events", () => {
-		const agent = new Agent({
-			transport: new ProviderTransport(),
-		});
+		const agent = new Agent();
 
 		let eventCount = 0;
 		const unsubscribe = agent.subscribe((_event) => {
@@ -61,9 +56,7 @@ describe("Agent", () => {
 	});
 
 	it("should update state with mutators", () => {
-		const agent = new Agent({
-			transport: new ProviderTransport(),
-		});
+		const agent = new Agent();
 
 		// Test setSystemPrompt
 		agent.setSystemPrompt("Custom prompt");
@@ -101,38 +94,19 @@ describe("Agent", () => {
 	});
 
 	it("should support message queueing", async () => {
-		const agent = new Agent({
-			transport: new ProviderTransport(),
-		});
+		const agent = new Agent();
 
 		const message = { role: "user" as const, content: "Queued message", timestamp: Date.now() };
-		await agent.queueMessage(message);
+		agent.queueMessage(message);
 
 		// The message is queued but not yet in state.messages
 		expect(agent.state.messages).not.toContainEqual(message);
 	});
 
 	it("should handle abort controller", () => {
-		const agent = new Agent({
-			transport: new ProviderTransport(),
-		});
+		const agent = new Agent();
 
 		// Should not throw even if nothing is running
 		expect(() => agent.abort()).not.toThrow();
 	});
 });
-
-describe("ProviderTransport", () => {
-	it("should create a provider transport instance", () => {
-		const transport = new ProviderTransport();
-		expect(transport).toBeDefined();
-	});
-
-	it("should create a provider transport with options", () => {
-		const transport = new ProviderTransport({
-			getApiKey: async (provider) => `test-key-${provider}`,
-			corsProxyUrl: "https://proxy.example.com",
-		});
-		expect(transport).toBeDefined();
-	});
-});

packages/agent/test/e2e.test.ts

@@ -1,25 +1,8 @@
 import type { AssistantMessage, Model, ToolResultMessage, UserMessage } from "@mariozechner/pi-ai";
-import { calculateTool, getModel } from "@mariozechner/pi-ai";
+import { getModel } from "@mariozechner/pi-ai";
 import { describe, expect, it } from "vitest";
-import { Agent, ProviderTransport } from "../src/index.js";
-
-function createTransport() {
-	return new ProviderTransport({
-		getApiKey: async (provider) => {
-			const envVarMap: Record<string, string> = {
-				google: "GEMINI_API_KEY",
-				openai: "OPENAI_API_KEY",
-				anthropic: "ANTHROPIC_API_KEY",
-				xai: "XAI_API_KEY",
-				groq: "GROQ_API_KEY",
-				cerebras: "CEREBRAS_API_KEY",
-				zai: "ZAI_API_KEY",
-			};
-			const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
-			return process.env[envVar];
-		},
-	});
-}
+import { Agent } from "../src/index.js";
+import { calculateTool } from "./utils/calculate.js";
 
 async function basicPrompt(model: Model<any>) {
 	const agent = new Agent({
@@ -29,7 +12,6 @@ async function basicPrompt(model: Model<any>) {
 			thinkingLevel: "off",
 			tools: [],
 		},
-		transport: createTransport(),
 	});
 
 	await agent.prompt("What is 2+2? Answer with just the number.");
@@ -57,7 +39,6 @@ async function toolExecution(model: Model<any>) {
 			thinkingLevel: "off",
 			tools: [calculateTool],
 		},
-		transport: createTransport(),
 	});
 
 	await agent.prompt("Calculate 123 * 456 using the calculator tool.");
@@ -99,7 +80,6 @@ async function abortExecution(model: Model<any>) {
 			thinkingLevel: "off",
 			tools: [calculateTool],
 		},
-		transport: createTransport(),
 	});
 
 	const promptPromise = agent.prompt("Calculate 100 * 200, then 300 * 400, then sum the results.");
@@ -129,7 +109,6 @@ async function stateUpdates(model: Model<any>) {
 			thinkingLevel: "off",
 			tools: [],
 		},
-		transport: createTransport(),
 	});
 
 	const events: Array<string> = [];
@@ -162,7 +141,6 @@ async function multiTurnConversation(model: Model<any>) {
 			thinkingLevel: "off",
 			tools: [],
 		},
-		transport: createTransport(),
 	});
 
 	await agent.prompt("My name is Alice.");
@@ -356,7 +334,6 @@ describe("Agent.continue()", () => {
 					systemPrompt: "Test",
 					model: getModel("anthropic", "claude-haiku-4-5"),
 				},
-				transport: createTransport(),
 			});
 
 			await expect(agent.continue()).rejects.toThrow("No messages to continue from");
@@ -368,7 +345,6 @@ describe("Agent.continue()", () => {
 					systemPrompt: "Test",
 					model: getModel("anthropic", "claude-haiku-4-5"),
 				},
-				transport: createTransport(),
 			});
 
 			const assistantMessage: AssistantMessage = {
@@ -405,7 +381,6 @@ describe("Agent.continue()", () => {
 					thinkingLevel: "off",
 					tools: [],
 				},
-				transport: createTransport(),
 			});
 
 			// Manually add a user message without calling prompt()
@@ -445,7 +420,6 @@ describe("Agent.continue()", () => {
 					thinkingLevel: "off",
 					tools: [calculateTool],
 				},
-				transport: createTransport(),
 			});
 
 			// Set up a conversation state as if tool was just executed

packages/agent/test/utils/calculate.ts

@@ -0,0 +1,32 @@
+import { type Static, Type } from "@sinclair/typebox";
+import type { AgentTool, AgentToolResult } from "../../src/types.js";
+
+export interface CalculateResult extends AgentToolResult<undefined> {
+	content: Array<{ type: "text"; text: string }>;
+	details: undefined;
+}
+
+export function calculate(expression: string): CalculateResult {
+	try {
+		const result = new Function(`return ${expression}`)();
+		return { content: [{ type: "text", text: `${expression} = ${result}` }], details: undefined };
+	} catch (e: any) {
+		throw new Error(e.message || String(e));
+	}
+}
+
+const calculateSchema = Type.Object({
+	expression: Type.String({ description: "The mathematical expression to evaluate" }),
+});
+
+type CalculateParams = Static<typeof calculateSchema>;
+
+export const calculateTool: AgentTool<typeof calculateSchema, undefined> = {
+	label: "Calculator",
+	name: "calculate",
+	description: "Evaluate mathematical expressions",
+	parameters: calculateSchema,
+	execute: async (_toolCallId: string, args: CalculateParams) => {
+		return calculate(args.expression);
+	},
+};

packages/agent/test/utils/get-current-time.ts

@@ -0,0 +1,46 @@
+import { type Static, Type } from "@sinclair/typebox";
+import type { AgentTool, AgentToolResult } from "../../src/types.js";
+
+export interface GetCurrentTimeResult extends AgentToolResult<{ utcTimestamp: number }> {}
+
+export async function getCurrentTime(timezone?: string): Promise<GetCurrentTimeResult> {
+	const date = new Date();
+	if (timezone) {
+		try {
+			const timeStr = date.toLocaleString("en-US", {
+				timeZone: timezone,
+				dateStyle: "full",
+				timeStyle: "long",
+			});
+			return {
+				content: [{ type: "text", text: timeStr }],
+				details: { utcTimestamp: date.getTime() },
+			};
+		} catch (_e) {
+			throw new Error(`Invalid timezone: ${timezone}. Current UTC time: ${date.toISOString()}`);
+		}
+	}
+	const timeStr = date.toLocaleString("en-US", { dateStyle: "full", timeStyle: "long" });
+	return {
+		content: [{ type: "text", text: timeStr }],
+		details: { utcTimestamp: date.getTime() },
+	};
+}
+
+const getCurrentTimeSchema = Type.Object({
+	timezone: Type.Optional(
+		Type.String({ description: "Optional timezone (e.g., 'America/New_York', 'Europe/London')" }),
+	),
+});
+
+type GetCurrentTimeParams = Static<typeof getCurrentTimeSchema>;
+
+export const getCurrentTimeTool: AgentTool<typeof getCurrentTimeSchema, { utcTimestamp: number }> = {
+	label: "Current Time",
+	name: "get_current_time",
+	description: "Get the current date and time",
+	parameters: getCurrentTimeSchema,
+	execute: async (_toolCallId: string, args: GetCurrentTimeParams) => {
+		return getCurrentTime(args.timezone);
+	},
+};