paseo

Automate CLI-based orchestration and management of AI agents.

Updated Apr 25, 2026
One-click install
npx skills add https://github.com/KQDtianxiaK/AtHand --skill paseo-kqdtianxiak
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paseo
Source: https://github.com/KQDtianxiaK/AtHand/tree/main/paseo-main/skills/paseo
Command: npx skills add https://github.com/KQDtianxiaK/AtHand --skill paseo-kqdtianxiak

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Efficiently manage and orchestrate AI agents from a single, consistent CLI, eliminating manual coordination and scattered tools.

Core Features & Use Cases

  • List, create, run, wait, and inspect agents across local projects or globally.
  • Attach to running agents, view logs, and manage output through structured prompts and interactions.
  • Support loops and schedules to automate iterative tasks and long-running workflows.

Quick Start

Load this skill to quickly list, create, and manage AI agents from the command line using Paseo.

Frequently Asked Questions about paseo

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

FAQPage Schema
How do I orchestrate AI agents from the command line?

To orchestrate AI agents from the command line, use a CLI skill that provides a structured command surface to list, run, wait, and inspect agents across local projects. It eliminates manual coordination by managing everything from a single consistent interface.

Can I monitor running AI agents and view their logs locally?

Yes, you can monitor running AI agents and view their logs locally by attaching to active processes. The CLI allows you to attach to running agents, view logs, and manage output through structured prompts and interactions.

How do I automate iterative tasks and long-running workflows for AI agents?

You can automate iterative tasks and long-running workflows for AI agents by utilizing loop and schedule commands. This support allows you to automate iterative tasks and long-running workflows directly from your local environment.

What is the best way to manage multiple AI agents across different local projects?

The best way to manage multiple AI agents across different local projects is using a consistent CLI. It provides a structured command surface for listing, creating, running, and inspecting agents globally or locally.

Does CLI-based AI agent orchestration require any external dependencies?

No, CLI-based AI agent orchestration using this approach requires no external dependencies. It operates within your local environment and includes safety checks to manage initialization and interaction.