Installation

npm i @noetic-tools/core

Or with your preferred package manager:

bun add @noetic-tools/core
pnpm add @noetic-tools/core

@noetic-tools/core pulls in @openrouter/agent and zod automatically. It runs on Node.js 18+ and Bun.

Set Your API Key

Noetic calls LLMs through OpenRouter. Create a key at openrouter.ai/keys and export it — the runtime reads OPENROUTER_API_KEY by default:

export OPENROUTER_API_KEY=sk-or-...

Your First Agent

Build a ReAct agent that loops over a callModel step, calling tools until the model has its answer. Here is the whole program — save it as agent.mjs and run node agent.mjs:

import { AgentHarness, any, callModel, loop, until } from '@noetic-tools/core';
import type { ContextData } from '@noetic-tools/core';
import { z } from 'zod';

// A tool the agent can call. Inputs and outputs are validated with zod.
const searchTool = {
  name: 'search',
  description: 'Search the web for information',
  input: z.object({ query: z.string() }),
  output: z.object({ result: z.string() }),
  execute: async (args: { query: string }) => {
    return { result: `Results for: ${args.query}` };
  },
};

// A model call, looped until the model stops calling tools. The generics name
// the context shape and the step's input/output types the harness expects.
const assistant = callModel<ContextData, string, string>({
  id: 'assistant',
  model: 'openai/gpt-4o', // OpenRouter model id (provider/model)
  instructions: 'You are a helpful research assistant.',
  tools: [searchTool],
});

const agent = loop({
  id: 'agent-loop',
  steps: [assistant],
  until: any(until.noToolCalls(), until.maxSteps(5)),
});

// The harness runs the agent. `name` and `params` are required;
// `callModelDefaults` selects the provider and reads OPENROUTER_API_KEY from the env.
const harness = new AgentHarness({
  name: 'researcher',
  agentGraph: agent,
  params: {},
  callModelDefaults: { provider: 'openrouter' },
});

await harness.execute('What are the latest developments in AI?');
const response = await harness.getAgentResponse();
console.log(response.text);

Run it and the model's final answer prints to your terminal.

Using TypeScript? Save the file as agent.ts and run it with bunx tsx agent.ts (or bun run agent.ts) — both execute TypeScript directly, no build step. Plain node runs the .mjs version above.

What Happens When You Run It

The LLM receives the system prompt and your input.
If the model calls a tool, Noetic executes it and feeds the result back.
The loop repeats until the model responds without tool calls, or maxSteps is reached.
getAgentResponse() resolves with the final response.text.

Model ids use OpenRouter's provider/model format (e.g. openai/gpt-4o, anthropic/claude-sonnet-4). Browse them at openrouter.ai/models.

That is the whole ReAct shape expressed in three primitives: callModel, until.noToolCalls, and a loop. Everything else in Noetic composes the same way -- see Loop & Until.

Next Steps

Overview -- understand Noetic's philosophy and the 8 primitives.
Steps -- learn about runCode, callModel, and invokeTool.
AgentHarness -- the runtime that executes agents.
Control Flow -- conditional and inParallel for routing and parallel logic.
Loop & Until -- iteration with termination predicates.

Getting Started

Installation

Set Your API Key

Your First Agent

What Happens When You Run It

Next Steps

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