Tycono AI Company Builder

Common errors

• Error: Tycono server not running or unreachable at http://localhost:PORT

  cause The 'tycono' client cannot connect to the 'tycono-server' instance.
  fix Start the `tycono-server` in a separate terminal (`npm install -g tycono-server && tycono-server start`) or ensure the `TYCONO_SERVER_URL` environment variable points to the correct address if it's not local.

• Error: Missing required environment variable ANTHROPIC_API_KEY

  cause The LLM (e.g., Claude) API key is not provided, preventing agents from functioning.
  fix Set the `ANTHROPIC_API_KEY` environment variable with your valid Anthropic API key before running Tycono. For other LLMs, consult the specific documentation.

• TypeError: Cannot read properties of undefined (reading 'name') in agent configuration.

  cause A YAML or Markdown agent/role definition file is malformed or missing a critical field like 'name'.
  fix Inspect your agent/role configuration files for syntax errors or missing mandatory properties. Ensure all required fields, such as `id`, `name`, `level`, `model`, etc., are present and correctly formatted.

• Error: The Tycono TUI requires a terminal that supports 256 colors.

  cause The terminal environment does not meet the minimum requirements for the rich TUI experience.
  fix Use a modern terminal emulator (e.g., iTerm2, Kitty, Alacritty, VS Code integrated terminal) that supports 256 colors. Ensure your `TERM` environment variable is correctly set (e.g., `xterm-256color`).

Warnings

• breaking Version 0.2.0 introduced significant changes to the core interaction model, making the TUI the default interface and adding 'Multi-Wave Resume' and 'Dual Mode' functionalities. Older CLI commands or programmatic integrations expecting pre-0.2.0 behavior may break.
  Fix: Review the latest documentation or `npx tycono` TUI for updated interaction patterns. Update any custom scripts or integrations to align with the new 'Multi-Wave' and 'Dual Mode' concepts.
• breaking The internal session management was refactored with a 'Session-Centric migration', explicitly removing 'Job' from the core. This indicates a potential breaking change for any programmatic interfaces or configurations that directly referenced 'Job' entities.
  Fix: Examine the changelog between v0.2.0 and v0.3.10 for specifics. Migrate any custom code from 'Job'-centric paradigms to the new 'Session'-centric approach.
• gotcha Tycono relies heavily on an LLM provider (e.g., Anthropic Claude) and the `tycono-server` backend for full functionality. Users might configure the `tycono` client without realizing the separate server component and API keys are critical for execution.
  Fix: Ensure `tycono-server` (available as a separate npm package) is installed and running, and that necessary LLM API keys (e.g., `ANTHROPIC_API_KEY`) are correctly set in your environment.
• gotcha The 'Company-as-Code' approach uses YAML and Markdown files for defining agents and organizational structure. Incorrect formatting, missing required fields, or logical errors in these declarative files can lead to unexpected agent behavior or runtime errors.
  Fix: Thoroughly validate your YAML/Markdown configuration files against the schema or examples provided in the official documentation. Use linters or schema validators if available.

Install

• npm install tycono npm
• yarn add tycono yarn
• pnpm add tycono pnpm

Imports

• runTyconoTUI

  import { runTyconoTUI } from 'tycono/cli';

  Primary entry point for the interactive Terminal User Interface (TUI). Often invoked via `npx tycono`.
• defineCompany
  wrong:

  const defineCompany = require('tycono').defineCompany;

  correct:

  import { defineCompany } from 'tycono/config';

  For programmatic definition of an AI company structure (roles, agents, hierarchy). Assumes an SDK exists for this, as 'Company-as-Code' is usually file-based (YAML/Markdown).
• executeTask
  wrong:

  const executeTask = require('tycono').executeTask;

  correct:

  import { executeTask } from 'tycono/api';

  To programmatically initiate a task for an AI company. This likely interacts with the 'tycono-server' API.

Quickstart

This quickstart demonstrates how to programmatically define an AI company with distinct roles and agents using assumed Tycono SDK APIs. It then initiates an autonomous task for the company, showcasing how to leverage LLMs (specifically Claude) for multi-agent collaboration. This example assumes 'tycono-server' is running to orchestrate the agents and requires an Anthropic API key.

import { defineCompany, executeTask } from 'tycono/api';
import { HumanAgent, ClaudeAgent, Role } from 'tycono/agents'; // Assuming agent types

const ANTHROPIC_API_KEY = process.env.ANTHROPIC_API_KEY ?? '';

if (!ANTHROPIC_API_KEY) {
  console.error('ANTHROPIC_API_KEY environment variable not set.');
  process.exit(1);
}

// Define roles within the company
const ceoRole = new Role('CEO', 'Oversees overall company strategy and delegates tasks.');
const engineerRole = new Role('Engineer', 'Implements technical solutions and writes code.');
const qaRole = new Role('QA', 'Tests and validates implemented solutions.');

// Define agents and assign them roles
const ceoAgent = new ClaudeAgent('Alice', 'claude-3-opus-20240229', ceoRole, ANTHROPIC_API_KEY);
const engineerAgent = new ClaudeAgent('Bob', 'claude-3-sonnet-20240229', engineerRole, ANTHROPIC_API_KEY);
const qaAgent = new ClaudeAgent('Charlie', 'claude-3-haiku-20240229', qaRole, ANTHROPIC_API_KEY);

// Define the company structure
const myAICorp = defineCompany({
  name: 'Innovation Inc.',
  description: 'An AI company focused on rapid prototyping and development.',
  roles: [ceoRole, engineerRole, qaRole],
  agents: [ceoAgent, engineerAgent, qaAgent],
  reportingStructure: [
    { from: engineerAgent, to: ceoAgent }, // Engineer reports to CEO
    { from: qaAgent, to: ceoAgent }      // QA reports to CEO
  ] // Simplified reporting for example
});

async function runAICompanyTask() {
  console.log(`Starting task for ${myAICorp.name}...`);
  try {
    const result = await executeTask(myAICorp, 'Develop a simple web-based calculator application.', {
      // Optional parameters for task execution, e.g., output directory, max steps
      outputDirectory: './projects/calculator-app',
      verbose: true
    });
    console.log('Task completed. Final output:', result.finalReport);
  } catch (error) {
    console.error('Error executing task:', error);
  }
}

runAICompanyTask();