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lev-ref

Codify agentic UX techniques for bi-directional human-agent communication in CLI interactions.

Updated Feb 13, 2026
Search Tags:#prompt engineering#design patterns#validation#cli#human-ai interaction#agentic ux
One-click install
npx skills add https://github.com/lev-os/lev-content --skill lev-ref
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lev-ref
Source: https://github.com/lev-os/lev-content/tree/main/sources/internal-docs/_inbox/lev-ref
Command: npx skills add https://github.com/lev-os/lev-content --skill lev-ref

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of designing effective and intuitive communication between humans and AI agents, transforming CLI interactions into teachable dialogues.

Core Features & Use Cases

  • CLI-as-Prompt Paradigm: Structures CLI outputs to serve as prompts for subsequent agents.
  • Enriched Response Protocol: Defines how to include meta-information (follow-ups, docs, confidence) alongside core output.
  • Teachable Moments: Implements patterns for error explanations, prompt scaffolding, and learning from corrections.
  • Validation Gates: Provides mechanisms for ensuring agent actions meet defined criteria.
  • Use Case: When developing a new CLI agent, use this Skill to ensure its outputs are not only informative but also guide the user and teach them how to interact more effectively in the future.

Quick Start

Apply the CLI-as-Prompt paradigm to structure agent outputs as prompts for the next agent in the chain.

Frequently Asked Questions about lev-ref

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

FAQPage Schema
What is the CLI-as-Prompt paradigm for human-agent interaction?▼

The CLI-as-Prompt paradigm structures command line interface outputs to serve as prompts for subsequent agents. It transforms standard CLI interactions into teachable dialogue moments for bi-directional human-agent communication.

How do I design validation gates for AI agents in a CLI?▼

Validation gates for AI agents are designed using established patterns that ensure agent actions meet defined criteria. This Skill provides specific mechanisms to implement these gates within CLI interactions for trust calibration.

How do I include meta-information in CLI agent responses?▼

You include meta-information in CLI agent responses using the Enriched Response Protocol. This defines how to add follow-ups, documentation links, and confidence levels alongside the core output.

Can I use this Skill for issue tracking and roadmap visibility?▼

Yes, you can use this Skill for issue tracking and roadmap visibility. It integrates with Leviathan concepts to provide these features while structuring agentic UX patterns for bi-directional communication.

What is the best way to create teachable moments in CLI outputs?▼

The best way to create teachable moments in CLI outputs is by implementing specific design patterns for error explanations, prompt scaffolding, and learning from corrections. This transforms interactions into continuous learning opportunities.

Do I need prior prompt engineering experience to structure agentic UX?▼

Prior prompt engineering experience is helpful but not strictly required. This Skill codifies advanced agentic UX techniques, establishing structured paradigms and protocols that guide effective bi-directional human-agent communication.

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