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AXI Agent eXperience Interface CLI Design

source post: AXI: Agent eXperience Interface

otherweak
Original post

AXI: Agent eXperience Interface

Source: other · unknown Saved: 2026-07-06 Tags: other Display: AXI Agent eXperience Interface CLI Design — A set of 10 design principles for building CLI tools optimized for AI agent use rather than human interaction.

TL;DR

AXI (Agent eXperience Interface) is a set of 10 design principles for building CLI tools that are optimized for use by AI agents rather than human users. It aims to achieve 100% task success at the lowest token/cost overhead, validated across benchmarks. As AI agents increasingly interact with command-line tools, standard CLI conventions designed for humans create friction and errors. AXI provides a principled framework for designing agent-ergonomic CLIs that maximize task success rates while minimizing cost.

What the post showed

Caption: 10 design principles for agent-ergonomic CLI. 100% task success at the lowest cost — validated across two benchmarks and 915 runs.

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On-screen text / OCR: yell - {MEP} >| AX] , +. Ea . . ee i 0 - 7 y x ; Let’s build apps agents love.

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What it actually is

  • What: AXI (Agent eXperience Interface) is a set of 10 design principles for building CLI tools that are optimized for use by AI agents rather than human users. It aims to achieve 100% task success at the lowest token/cost overhead, validated across benchmarks.
  • Who built it / maintained by: unknown
  • Status: unknown
  • Why it matters: As AI agents increasingly interact with command-line tools, standard CLI conventions designed for humans create friction and errors. AXI provides a principled framework for designing agent-ergonomic CLIs that maximize task success rates while minimizing cost.
  • How it compares to alternatives:
  • Click
  • Typer
  • Commander.js
  • Cobra
  • oclif
  • GitHub stars: 0 · License: unknown · Archived: no

Links

Kickstarter guide

Visit axi.md to read the 10 design principles for agent-ergonomic CLI design. Apply these principles when building new CLI tools or refactoring existing ones to be consumed by AI agents. The framework is validation-backed across 915 benchmark runs, so prioritize principles shown to most impact task success rate.