Token导航 LogoToken导航TokenDH.com
研究检索敏感数据github未标认证来源可访问许可证需确认审计通过

create-agent创建 Agent

Agent Skill

create-agent 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

58,759

周安装

2,455

GitHub Stars

27

下载量

20,991
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:create-agent(创建 Agent)
来源仓库:https://github.com/openrouterteam/agent-skills
仓库路径:skills/create-agent
安装命令:
npx skills add https://github.com/openrouterteam/agent-skills --skill create-agent
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/openrouterteam/agent-skills --skill create-agent

简介

使用 OpenRouter SDK、可扩展挂钩和可选的终端 UI 引导模块化 AI 代理。

  • 独立代理核心独立于任何 UI 运行,具有用于流式响应、工具调用、推理和错误的基于事件的挂钩
  • 基于项目的流模型通过 ID 发出完整的、逐步更新的项目,而不是累积块,从而实现高效的 React 状态管理和并发输出处理
  • 通过 OpenRouter 支持 300 多种语言模型,具有动态模型发现功能;使用开放路由器/自动
  • 用于自动选择或按作者、上下文长度和定价查询模型 API
  • 可选配Ink TUI,提供美观的终端界面;代理还可以无头方式用于 HTTP API、Discord 机器人或编程使用
  • 内置Zod模式的工具系统;在运行时添加工具或定义用于计算器、时间、网络搜索、文件操作和图像生成的自定义工具

SKILL.md

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

OptionTypeDefaultDescription
apiKeystringrequiredOpenRouter API key
modelstring'openrouter/auto'Model to use
instructionsstring'You are a helpful assistant.'System prompt
toolsTool[][]Available tools
maxStepsnumber5Max agentic loop iterations

Methods

MethodReturnsDescription
send(content)PromiseSend message with streaming
sendSync(content)PromiseSend message without streaming
getMessages()Message[]Get conversation history
clearHistory()voidClear conversation
setInstructions(text)voidUpdate system prompt
addTool(tool)voidAdd tool at runtime

Events

EventPayloadDescription
message:userMessageUser message added
message:assistantMessageAssistant response complete
item:updateStreamableOutputItemItem emitted (replace by ID, don't accumulate)
stream:start-Streaming started
stream:delta(delta, accumulated)New text chunk
stream:endfullTextStreaming complete
tool:call(name, args)Tool being called
tool:result(name, result)Tool returned result
reasoning:updatetextExtended thinking content
thinking:start-Agent processing
thinking:end-Agent done processing
errorErrorError 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.

TypePurpose
messageAssistant text responses
function_callTool invocations with streaming arguments
function_call_outputResults from executed tools
reasoningExtended thinking content
web_search_callWeb search operations
file_search_callFile search operations
image_generation_callImage 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

Resources

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.51%
按下载量换算7,244

Claude

32.33%
按下载量换算6,786

Cursor

18.2%
按下载量换算3,820

Gemini CLI

9.63%
按下载量换算2,021

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills