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create-agent

Bootstrap modular AI agents with OpenRouter SDK and optional Ink TUI.

2|Updated Mar 11, 2026
Search Tags:#typescript#cli#llm#sdk#ai agent#openrouter
One-click install
npx skills add https://github.com/HokageZ/JOB-HUNTER --skill create-agent-hokagez
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: create-agent
Source: https://github.com/HokageZ/JOB-HUNTER/tree/main/.agents/skills/create-agent
Command: npx skills add https://github.com/HokageZ/JOB-HUNTER --skill create-agent-hokagez

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @openrouter/sdk, zod, eventemitter3, ink, react, typescript, tsx, and includes scripts (resource) components.

What problem does it solve?

This Skill streamlines the creation of modular AI agents, abstracting away complex SDK integrations and providing a flexible architecture for building custom AI applications.

Core Features & Use Cases

  • Modular Agent Core: Build agents with extensible hooks and lifecycle management.
  • OpenRouter SDK Integration: Seamlessly access a wide range of LLMs.
  • Optional Ink TUI: Develop interactive terminal UIs for agents.
  • Use Case: Quickly prototype an AI assistant that can answer questions, perform calculations, and access real-time information, all managed through a clean, extensible codebase.

Quick Start

Use the create-agent skill to bootstrap a new agent project with OpenRouter SDK and an optional Ink TUI.

Frequently Asked Questions about create-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I bootstrap a modular AI agent using the OpenRouter SDK?▼

You can bootstrap a modular AI agent using TypeScript by leveraging this Skill's structured architecture, which abstracts OpenRouter SDK integration and provides extensible hooks for lifecycle management.

Can I build an interactive terminal UI for an AI agent with Ink and React?▼

Yes, you can build an interactive terminal UI for an AI agent using the optional Ink TUI, which integrates React components to render interactive interfaces within your TypeScript CLI environment.

What is the best way to structure a TypeScript CLI application for LLM integration?▼

The best way to structure a TypeScript CLI for LLM integration is using a modular agent core with extensible hooks and lifecycle management, enabling seamless OpenRouter SDK access alongside optional Ink TUI rendering.

Does this approach support headless usage for automated AI agent workflows?▼

Yes, the modular agent architecture supports programmatic headless usage, allowing developers to deploy automated AI workflows without requiring the interactive Ink TUI interface.

How do extensible hooks manage the lifecycle of an AI agent?▼

Extensible hooks manage the AI agent lifecycle by providing structured interception points within the modular core, allowing developers to inject custom logic and control state transitions during LLM interactions.

Do I need Zod and EventEmitter3 to prototype custom AI applications?▼

You need Zod for schema validation and EventEmitter3 for event-driven lifecycle management to effectively prototype custom AI applications with structured extensible hooks and OpenRouter SDK integration.

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