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bashli

Orchestrate shell commands from JSON or YAML specs with variable scope.

2|Updated Feb 22, 2026
Search Tags:#automation#workflow#structured data#cli#shell#interpolation
One-click install
npx skills add https://github.com/weisberg/agent_tools --skill bashli
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bashli
Source: https://github.com/weisberg/agent_tools/tree/main/tools/bashli
Command: npx skills add https://github.com/weisberg/agent_tools --skill bashli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Facilitates safe, reliable execution of complex shell commands for AI workflows, replacing fragile scripts with structured definitions.

Core Features & Use Cases

  • Structured Command Execution: Use JSON or YAML specs to run, transform, and capture shell commands with safety and precision.
  • Variable Interpolation: Inject dynamic data into commands and manage scope reliably.
  • Use Case: Automate codebase setup by running multiple dependent commands, capturing outputs, and asserting system states, all in an error-resilient manner.

Quick Start

Use bashli to list files in current directory and save output to a variable.

Frequently Asked Questions about bashli

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

FAQPage Schema
How do I execute structured shell commands for AI workflows without fragile scripts?▼

Structured shell command execution for AI workflows uses JSON or YAML specs to safely run, transform, and capture outputs. This replaces fragile scripts with predictable definitions, reducing errors and enabling complex orchestration with variable scope and output limits.

How do I automate codebase setup by running multiple dependent shell commands?▼

Automating codebase setup involves running multiple dependent shell commands using structured definitions. You can capture outputs, inject dynamic data via variable interpolation, and assert system states in an error-resilient manner, ensuring reliable environment management for AI agents.

What is variable interpolation in shell command orchestration and how does it work?▼

Variable interpolation in shell command orchestration injects dynamic data into commands and manages scope reliably. It allows structured JSON or YAML specs to define variables, ensuring safe and predictable execution of complex workflows for AI agents.

Can I use JSON or YAML specs to manage environment setup and data collection with AI agents?▼

Yes, JSON and YAML specs can manage environment setup and data collection with AI agents. They define structured command execution, enabling safe orchestration of shell tasks, variable interpolation, output limits, and structured results for predictable automation.

Why does my AI agent's shell workflow fail unpredictably during complex command orchestration?▼

Complex shell workflows fail unpredictably when using fragile scripts without structured definitions. By adopting JSON or YAML specs with variable scope management, output limits, and structured results, you reduce errors and ensure safe, reliable execution for AI agents.

What are the limitations of using structured shell workflows for AI agents?▼

Structured shell workflows for AI agents require JSON or YAML spec definitions and rely on variable interpolation for dynamic data. While they reduce errors in complex orchestration, users must manage variable scope and output limits carefully to maintain predictable execution.

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