create-agent

name	create-agent
description	Bootstrap a modular AI agent with OpenRouter SDK, extensible hooks, and optional Ink TUI
metadata	{"version":"0.0.0","homepage":"https://openrouter.ai"}

Build a Modular AI Agent with OpenRouter

This skill helps you create a modular AI agent with:

• Standalone Agent Core - Runs independently, extensible via hooks
• OpenRouter SDK - Unified access to 300+ language models
• Optional Ink TUI - Beautiful terminal UI (separate from agent logic)

Architecture

┌─────────────────────────────────────────────────────┐
│                    Your Application                 │
├─────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  │
│  │   Ink TUI   │  │  HTTP API   │  │   Discord   │  │
│  └──────┬──────┘  └──────┬──────┘  └──────┬──────┘  │
│         │                │                │         │
│         └────────────────┼────────────────┘         │
│                          ▼                          │
│              ┌───────────────────────┐              │
│              │      Agent Core       │              │
│              │  (hooks & lifecycle)  │              │
│              └───────────┬───────────┘              │
│                          ▼                          │
│              ┌───────────────────────┐              │
│              │    OpenRouter SDK     │              │
│              └───────────────────────┘              │
└─────────────────────────────────────────────────────┘

Prerequisites

Get an OpenRouter API key at: https://openrouter.ai/settings/keys

⚠️ Security: Never commit API keys. Use environment variables.

Project Setup

Step 1: Initialize Project

mkdir my-agent && cd my-agent
npm init -y
npm pkg set type="module"

Step 2: Install Dependencies

npm install @openrouter/sdk zod eventemitter3
npm install ink react  # Optional: only for TUI
npm install -D typescript @types/react tsx

Step 3: Create tsconfig.json

{
  "compilerOptions": {
    "target": "ES2022",
    "module": "NodeNext",
    "moduleResolution": "NodeNext",
    "jsx": "react-jsx",
    "strict": true,
    "esModuleInterop": true,
    "skipLibCheck": true,
    "outDir": "dist"
  },
  "include": ["src"]
}

Step 4: Add Scripts to package.json

{
  "scripts": {
    "start": "tsx src/cli.tsx",
    "start:headless": "tsx src/headless.ts",
    "dev": "tsx watch src/cli.tsx"
  }
}

File Structure

src/
├── agent.ts        # Standalone agent core with hooks
├── tools.ts        # Tool definitions
├── cli.tsx         # Ink TUI (optional interface)
└── headless.ts     # Headless usage example

Step 1: Agent Core with Hooks

Create src/agent.ts - the standalone agent that can run anywhere:

import { OpenRouter, tool, stepCountIs } from '@openrouter/sdk';
import type { Tool, StopCondition, StreamableOutputItem } from '@openrouter/sdk';
import { EventEmitter } from 'eventemitter3';
import { z } from 'zod';

// Message types
export interface Message {
  role: 'user' | 'assistant' | 'system';
  content: string;
}

// Agent events for hooks (items-based streaming model)
export interface AgentEvents {
  'message:user': (message: Message) => void;
  'message:assistant': (message: Message) => void;
  'item:update': (item: StreamableOutputItem) => void;  // Items emitted with same ID, replace by ID
  'stream:start': () => void;
  'stream:delta': (delta: string, accumulated: string) => void;
  'stream:end': (fullText: string) => void;
  'tool:call': (name: string, args: unknown) => void;
  'tool:result': (name: string, result: unknown) => void;
  'reasoning:update': (text: string) => void;  // Extended thinking content
  'error': (error: Error) => void;
  'thinking:start': () => void;
  'thinking:end': () => void;
}


// Agent configuration
export interface AgentConfig {
  apiKey: string;
  model?: string;
  instructions?: string;
  tools?: Tool<z.ZodTypeAny, z.ZodTypeAny>[];
  maxSteps?: number;
}

// The Agent class - runs independently of any UI
export class Agent extends EventEmitter<AgentEvents> {
  private client: OpenRouter;
  private messages: Message[] = [];
  private config: Required<Omit<AgentConfig, 'apiKey'>> & { apiKey: string };

  constructor(config: AgentConfig) {
    super();
    this.client = new OpenRouter({ apiKey: config.apiKey });
    this.config = {
      apiKey: config.apiKey,
      model: config.model ?? 'openrouter/auto',
      instructions: config.instructions ?? 'You are a helpful assistant.',
      tools: config.tools ?? [],
      maxSteps: config.maxSteps ?? 5,
    };
  }

  // Get conversation history
  getMessages(): Message[] {
    return [...this.messages];
  }

  // Clear conversation
  clearHistory(): void {
    this.messages = [];
  }

  // Add a system message
  setInstructions(instructions: string): void {
    this.config.instructions = instructions;
  }

  // Register additional tools at runtime
  addTool(newTool: Tool<z.ZodTypeAny, z.ZodTypeAny>): void {
    this.config.tools.push(newTool);
  }

  // Send a message and get streaming response using items-based model
  // Items are emitted multiple times with the same ID but progressively updated content
  // Replace items by their ID rather than accumulating chunks
  async send(content: string): Promise<string> {
    const userMessage: Message = { role: 'user', content };
    this.messages.push(userMessage);
    this.emit('message:user', userMessage);
    this.emit('thinking:start');

    try {
      const result = this.client.callModel({
        model: this.config.model,
        instructions: this.config.instructions,
        input: this.messages.map((m) => ({ role: m.role, content: m.content })),
        tools: this.config.tools.length > 0 ? this.config.tools : undefined,
        stopWhen: [stepCountIs(this.config.maxSteps)],
      });

      this.emit('stream:start');
      let fullText = '';

      // Use getItemsStream() for items-based streaming (recommended)
      // Each item emission is complete - replace by ID, don't accumulate
      for await (const item of result.getItemsStream()) {
        // Emit the item for UI state management (use Map keyed by item.id)
        this.emit('item:update', item);

        switch (item.type) {
          case 'message':
            // Message items contain progressively updated content
            const textContent = item.content?.find((c: { type: string }) => c.type === 'output_text');
            if (textContent && 'text' in textContent) {
              const newText = textContent.text;
              if (newText !== fullText) {
                const delta = newText.slice(fullText.length);
                fullText = newText;
                this.emit('stream:delta', delta, fullText);
              }
            }
            break;
          case 'function_call':
            // Function call arguments stream progressively
            if (item.status === 'completed') {
              this.emit('tool:call', item.name, JSON.parse(item.arguments || '{}'));
            }
            break;
          case 'function_call_output':
            this.emit('tool:result', item.callId, item.output);
            break;
          case 'reasoning':
            // Extended thinking/reasoning content
            const reasoningText = item.content?.find((c: { type: string }) => c.type === 'reasoning_text');
            if (reasoningText && 'text' in reasoningText) {
              this.emit('reasoning:update', reasoningText.text);
            }
            break;
          // Additional item types: web_search_call, file_search_call, image_generation_call
        }
      }

      // Get final text if streaming didn't capture it
      if (!fullText) {
        fullText = await result.getText();
      }

      this.emit('stream:end', fullText);

      const assistantMessage: Message = { role: 'assistant', content: fullText };
      this.messages.push(assistantMessage);
      this.emit('message:assistant', assistantMessage);

      return fullText;
    } catch (err) {
      const error = err instanceof Error ? err : new Error(String(err));
      this.emit('error', error);
      throw error;
    } finally {
      this.emit('thinking:end');
    }
  }

  // Send without streaming (simpler for programmatic use)
  async sendSync(content: string): Promise<string> {
    const userMessage: Message = { role: 'user', content };
    this.messages.push(userMessage);
    this.emit('message:user', userMessage);

    try {
      const result = this.client.callModel({
        model: this.config.model,
        instructions: this.config.instructions,
        input: this.messages.map((m) => ({ role: m.role, content: m.content })),
        tools: this.config.tools.length > 0 ? this.config.tools : undefined,
        stopWhen: [stepCountIs(this.config.maxSteps)],
      });

      const fullText = await result.getText();
      const assistantMessage: Message = { role: 'assistant', content: fullText };
      this.messages.push(assistantMessage);
      this.emit('message:assistant', assistantMessage);

      return fullText;
    } catch (err) {
      const error = err instanceof Error ? err : new Error(String(err));
      this.emit('error', error);
      throw error;
    }
  }
}

// Factory function for easy creation
export function createAgent(config: AgentConfig): Agent {
  return new Agent(config);
}

Step 2: Define Tools

Create src/tools.ts:

import { tool } from '@openrouter/sdk';
import { z } from 'zod';

export const timeTool = tool({
  name: 'get_current_time',
  description: 'Get the current date and time',
  inputSchema: z.object({
    timezone: z.string().optional().describe('Timezone (e.g., "UTC", "America/New_York")'),
  }),
  execute: async ({ timezone }) => {
    return {
      time: new Date().toLocaleString('en-US', { timeZone: timezone || 'UTC' }),
      timezone: timezone || 'UTC',
    };
  },
});

export const calculatorTool = tool({
  name: 'calculate',
  description: 'Perform mathematical calculations',
  inputSchema: z.object({
    expression: z.string().describe('Math expression (e.g., "2 + 2", "sqrt(16)")'),
  }),
  execute: async ({ expression }) => {
    // Simple safe eval for basic math
    const sanitized = expression.replace(/[^0-9+\-*/().\s]/g, '');
    const result = Function(`"use strict"; return (${sanitized})`)();
    return { expression, result };
  },
});

export const defaultTools = [timeTool, calculatorTool];

Step 3: Headless Usage (No UI)

Create src/headless.ts - use the agent programmatically:

import { createAgent } from './agent.js';
import { defaultTools } from './tools.js';

async function main() {
  const agent = createAgent({
    apiKey: process.env.OPENROUTER_API_KEY!,
    model: 'openrouter/auto',
    instructions: 'You are a helpful assistant with access to tools.',
    tools: defaultTools,
  });

  // Hook into events
  agent.on('thinking:start', () => console.log('\n🤔 Thinking...'));
  agent.on('tool:call', (name, args) => console.log(`🔧 Using ${name}:`, args));
  agent.on('stream:delta', (delta) => process.stdout.write(delta));
  agent.on('stream:end', () => console.log('\n'));
  agent.on('error', (err) => console.error('❌ Error:', err.message));

  // Interactive loop
  const readline = await import('readline');
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
  });

  console.log('Agent ready. Type your message (Ctrl+C to exit):\n');

  const prompt = () => {
    rl.question('You: ', async (input) => {
      if (!input.trim()) {
        prompt();
        return;
      }
      await agent.send(input);
      prompt();
    });
  };

  prompt();
}

main().catch(console.error);

Run headless: OPENROUTER_API_KEY=sk-or-... npm run start:headless

Step 4: Ink TUI (Optional Interface)

Create src/cli.tsx - a beautiful terminal UI that uses the agent with items-based streaming:

import React, { useState, useEffect, useCallback } from 'react';
import { render, Box, Text, useInput, useApp } from 'ink';
import type { StreamableOutputItem } from '@openrouter/sdk';
import { createAgent, type Agent, type Message } from './agent.js';
import { defaultTools } from './tools.js';

// Initialize agent (runs independently of UI)
const agent = createAgent({
  apiKey: process.env.OPENROUTER_API_KEY!,
  model: 'openrouter/auto',
  instructions: 'You are a helpful assistant. Be concise.',
  tools: defaultTools,
});

function ChatMessage({ message }: { message: Message }) {
  const isUser = message.role === 'user';
  return (
    <Box flexDirection="column" marginBottom={1}>
      <Text bold color={isUser ? 'cyan' : 'green'}>
        {isUser ? '▶ You' : '◀ Assistant'}
      </Text>
      <Text wrap="wrap">{message.content}</Text>
    </Box>
  );
}

// Render streaming items by type using the items-based pattern
function ItemRenderer({ item }: { item: StreamableOutputItem }) {
  switch (item.type) {
    case 'message': {
      const textContent = item.content?.find((c: { type: string }) => c.type === 'output_text');
      const text = textContent && 'text' in textContent ? textContent.text : '';
      return (
        <Box flexDirection="column" marginBottom={1}>
          <Text bold color="green">◀ Assistant</Text>
          <Text wrap="wrap">{text}</Text>
          {item.status !== 'completed' && <Text color="gray">▌</Text>}
        </Box>
      );
    }
    case 'function_call':
      return (
        <Text color="yellow">
          {item.status === 'completed' ? '  ✓' : '  🔧'} {item.name}
          {item.status === 'in_progress' && '...'}
        </Text>
      );
    case 'reasoning': {
      const reasoningText = item.content?.find((c: { type: string }) => c.type === 'reasoning_text');
      const text = reasoningText && 'text' in reasoningText ? reasoningText.text : '';
      return (
        <Box flexDirection="column" marginBottom={1}>
          <Text bold color="magenta">💭 Thinking</Text>
          <Text wrap="wrap" color="gray">{text}</Text>
        </Box>
      );
    }
    default:
      return null;
  }
}

function InputField({
  value,
  onChange,
  onSubmit,
  disabled,
}: {
  value: string;
  onChange: (v: string) => void;
  onSubmit: () => void;
  disabled: boolean;
}) {
  useInput((input, key) => {
    if (disabled) return;
    if (key.return) onSubmit();
    else if (key.backspace || key.delete) onChange(value.slice(0, -1));
    else if (input && !key.ctrl && !key.meta) onChange(value + input);
  });

  return (
    <Box>
      <Text color="yellow">{'> '}</Text>
      <Text>{value}</Text>
      <Text color="gray">{disabled ? ' ···' : '█'}</Text>
    </Box>
  );
}

function App() {
  const { exit } = useApp();
  const [messages, setMessages] = useState<Message[]>([]);
  const [input, setInput] = useState('');
  const [isLoading, setIsLoading] = useState(false);
  // Use Map keyed by item ID for efficient React state updates (items-based pattern)
  const [items, setItems] = useState<Map<string, StreamableOutputItem>>(new Map());

  useInput((_, key) => {
    if (key.escape) exit();
  });

  // Subscribe to agent events using items-based streaming
  useEffect(() => {
    const onThinkingStart = () => {
      setIsLoading(true);
      setItems(new Map()); // Clear items for new response
    };

    // Items-based streaming: replace items by ID, don't accumulate
    const onItemUpdate = (item: StreamableOutputItem) => {
      setItems((prev) => new Map(prev).set(item.id, item));
    };

    const onMessageAssistant = () => {
      setMessages(agent.getMessages());
      setItems(new Map()); // Clear streaming items
      setIsLoading(false);
    };

    const onError = (err: Error) => {
      setIsLoading(false);
    };

    agent.on('thinking:start', onThinkingStart);
    agent.on('item:update', onItemUpdate);
    agent.on('message:assistant', onMessageAssistant);
    agent.on('error', onError);

    return () => {
      agent.off('thinking:start', onThinkingStart);
      agent.off('item:update', onItemUpdate);
      agent.off('message:assistant', onMessageAssistant);
      agent.off('error', onError);
    };
  }, []);

  const sendMessage = useCallback(async () => {
    if (!input.trim() || isLoading) return;
    const text = input.trim();
    setInput('');
    setMessages((prev) => [...prev, { role: 'user', content: text }]);
    await agent.send(text);
  }, [input, isLoading]);

  return (
    <Box flexDirection="column" padding={1}>
      <Box marginBottom={1}>
        <Text bold color="magenta">🤖 OpenRouter Agent</Text>
        <Text color="gray"> (Esc to exit)</Text>
      </Box>

      <Box flexDirection="column" marginBottom={1}>
        {/* Render completed messages */}
        {messages.map((msg, i) => (
          <ChatMessage key={i} message={msg} />
        ))}

        {/* Render streaming items by type (items-based pattern) */}
        {Array.from(items.values()).map((item) => (
          <ItemRenderer key={item.id} item={item} />
        ))}
      </Box>

      <Box borderStyle="single" borderColor="gray" paddingX={1}>
        <InputField
          value={input}
          onChange={setInput}
          onSubmit={sendMessage}
          disabled={isLoading}
        />
      </Box>
    </Box>
  );
}

render(<App />);

Run TUI: OPENROUTER_API_KEY=sk-or-... npm start

Understanding Items-Based Streaming

The OpenRouter SDK uses an items-based streaming model - a key paradigm where items are emitted multiple times with the same ID but progressively updated content. Instead of accumulating chunks, you replace items by their ID.

How It Works

Each iteration of getItemsStream() yields a complete item with updated content:

// Iteration 1: Partial message
{ id: "msg_123", type: "message", content: [{ type: "output_text", text: "Hello" }] }

// Iteration 2: Updated message (replace, don't append)
{ id: "msg_123", type: "message", content: [{ type: "output_text", text: "Hello world" }] }

For function calls, arguments stream progressively:

// Iteration 1: Partial arguments
{ id: "call_456", type: "function_call", name: "get_weather", arguments: "{\"q" }

// Iteration 2: Complete arguments
{ id: "call_456", type: "function_call", name: "get_weather", arguments: "{\"query\": \"Paris\"}", status: "completed" }

Why Items Are Better

Traditional (accumulation required):

let text = '';
for await (const chunk of result.getTextStream()) {
  text += chunk;  // Manual accumulation
  updateUI(text);
}

Items (complete replacement):

const items = new Map<string, StreamableOutputItem>();
for await (const item of result.getItemsStream()) {
  items.set(item.id, item);  // Replace by ID
  updateUI(items);
}

Benefits:

• No manual chunk management - each item is complete
• Handles concurrent outputs - function calls and messages can stream in parallel
• Full TypeScript inference for all item types
• Natural Map-based state works perfectly with React/UI frameworks

Extending the Agent

Add Custom Hooks

const agent = createAgent({ apiKey: '...' });

// Log all events
agent.on('message:user', (msg) => {
  saveToDatabase('user', msg.content);
});

agent.on('message:assistant', (msg) => {
  saveToDatabase('assistant', msg.content);
  sendWebhook('new_message', msg);
});

agent.on('tool:call', (name, args) => {
  analytics.track('tool_used', { name, args });
});

agent.on('error', (err) => {
  errorReporting.capture(err);
});

Use with HTTP Server

import express from 'express';
import { createAgent } from './agent.js';

const app = express();
app.use(express.json());

// One agent per session (store in memory or Redis)
const sessions = new Map<string, Agent>();

app.post('/chat', async (req, res) => {
  const { sessionId, message } = req.body;

  let agent = sessions.get(sessionId);
  if (!agent) {
    agent = createAgent({ apiKey: process.env.OPENROUTER_API_KEY! });
    sessions.set(sessionId, agent);
  }

  const response = await agent.sendSync(message);
  res.json({ response, history: agent.getMessages() });
});

app.listen(3000);

Use with Discord

import { Client, GatewayIntentBits } from 'discord.js';
import { createAgent } from './agent.js';

const discord = new Client({
  intents: [GatewayIntentBits.Guilds, GatewayIntentBits.GuildMessages],
});

const agents = new Map<string, Agent>();

discord.on('messageCreate', async (msg) => {
  if (msg.author.bot) return;

  let agent = agents.get(msg.channelId);
  if (!agent) {
    agent = createAgent({ apiKey: process.env.OPENROUTER_API_KEY! });
    agents.set(msg.channelId, agent);
  }

  const response = await agent.sendSync(msg.content);
  await msg.reply(response);
});

discord.login(process.env.DISCORD_TOKEN);

Agent API Reference

Constructor Options

Option	Type	Default	Description
apiKey	string	required	OpenRouter API key
model	string	'openrouter/auto'	Model to use
instructions	string	'You are a helpful assistant.'	System prompt
tools	Tool[]	[]	Available tools
maxSteps	number	5	Max agentic loop iterations

Methods

Method	Returns	Description
send(content)	Promise	Send message with streaming
sendSync(content)	Promise	Send message without streaming
getMessages()	Message[]	Get conversation history
clearHistory()	void	Clear conversation
setInstructions(text)	void	Update system prompt
addTool(tool)	void	Add tool at runtime

Events

Event	Payload	Description
message:user	Message	User message added
message:assistant	Message	Assistant response complete
item:update	StreamableOutputItem	Item emitted (replace by ID, don't accumulate)
stream:start	-	Streaming started
stream:delta	(delta, accumulated)	New text chunk
stream:end	fullText	Streaming complete
tool:call	(name, args)	Tool being called
tool:result	(name, result)	Tool returned result
reasoning:update	text	Extended thinking content
thinking:start	-	Agent processing
thinking:end	-	Agent done processing
error	Error	Error occurred

Item Types (from getItemsStream)

The SDK uses an items-based streaming model where items are emitted multiple times with the same ID but progressively updated content. Replace items by their ID rather than accumulating chunks.

Type	Purpose
message	Assistant text responses
function_call	Tool invocations with streaming arguments
function_call_output	Results from executed tools
reasoning	Extended thinking content
web_search_call	Web search operations
file_search_call	File search operations
image_generation_call	Image generation operations

Discovering Models

Do not hardcode model IDs - they change frequently. Use the models API:

Fetch Available Models

interface OpenRouterModel {
  id: string;
  name: string;
  description?: string;
  context_length: number;
  pricing: { prompt: string; completion: string };
  top_provider?: { is_moderated: boolean };
}

async function fetchModels(): Promise<OpenRouterModel[]> {
  const res = await fetch('https://openrouter.ai/api/v1/models');
  const data = await res.json();
  return data.data;
}

// Find models by criteria
async function findModels(filter: {
  author?: string;      // e.g., 'anthropic', 'openai', 'google'
  minContext?: number;  // e.g., 100000 for 100k context
  maxPromptPrice?: number; // e.g., 0.001 for cheap models
}): Promise<OpenRouterModel[]> {
  const models = await fetchModels();

  return models.filter((m) => {
    if (filter.author && !m.id.startsWith(filter.author + '/')) return false;
    if (filter.minContext && m.context_length < filter.minContext) return false;
    if (filter.maxPromptPrice) {
      const price = parseFloat(m.pricing.prompt);
      if (price > filter.maxPromptPrice) return false;
    }
    return true;
  });
}

// Example: Get latest Claude models
const claudeModels = await findModels({ author: 'anthropic' });
console.log(claudeModels.map((m) => m.id));

// Example: Get models with 100k+ context
const longContextModels = await findModels({ minContext: 100000 });

// Example: Get cheap models
const cheapModels = await findModels({ maxPromptPrice: 0.0005 });

Dynamic Model Selection in Agent

// Create agent with dynamic model selection
const models = await fetchModels();
const bestModel = models.find((m) => m.id.includes('claude')) || models[0];

const agent = createAgent({
  apiKey: process.env.OPENROUTER_API_KEY!,
  model: bestModel.id,  // Use discovered model
  instructions: 'You are a helpful assistant.',
});

Using openrouter/auto

For simplicity, use openrouter/auto which automatically selects the best available model for your request:

const agent = createAgent({
  apiKey: process.env.OPENROUTER_API_KEY!,
  model: 'openrouter/auto',  // Auto-selects best model
});

Models API Reference

• Endpoint: GET https://openrouter.ai/api/v1/models
• Response: { data: OpenRouterModel[] }
• Browse models: https://openrouter.ai/models

Resources

• OpenRouter Docs: https://openrouter.ai/docs
• Models API: https://openrouter.ai/api/v1/models
• Ink Docs: https://github.com/vadimdemedes/ink
• Get API Key: https://openrouter.ai/settings/keys