ai-native-cli

# Agent-Friendly CLI Spec v0.1 When building or modifying CLI tools, follow these rules to make them safe and reliable for AI agents to use. ## Overview A comprehensive design specification for building AI-native CLI tools. It defines 98 rules across three certification levels (Agent-Friendly, Agent-Ready, Agent-Native) with prioritized requirements (P0/P1/P2). The spec covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, self-description, and a feedback loop via a built-in issue system. ## When to Use This Skill - Use when building a new CLI tool that AI agents will invoke - Use when retrofitting an existing CLI to be agent-friendly - Use when designing command-line interfaces for automation pipelines - Use when auditing a CLI tool's compliance with agent-safety standards ## Core Philosophy 1. **Agent-first** -- default output is JSON; human-friendly is opt-in via `--human` 2. **Agent is untrusted** -- validate all input at the same level as a public API 3. **Fail-Closed** -- when validation logic itself errors, deny by default 4. **Verifiable** -- every rule is written so it can be automatically checked ## Layer Model This spec uses two orthogonal axes: - **Layer** answers rollout scope: `core`, `recommended`, `ecosystem` - **Priority** answers severity: `P0`, `P1`, `P2` Use layers for migration and certification: - **core** -- execution contract: JSON, errors, exit codes, stdout/stderr, safety - **recommended** -- bette...