Conception de CLI pour agents IA (98 règles)
/SKILLSpécification technique comprenant 98 règles pour la création d'outils en ligne de commande (CLI) que les agents IA peuvent utiliser en toute sécurité
name: ai-native-cli
description: "Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description."
risk: safe
source: https://github.com/ChaosRealmsAI/agent-cli-spec
date_added: "2026-03-15"
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
- Agent-first -- default output is JSON; human-friendly is opt-in via
--human - Agent is untrusted -- validate all input at the same level as a public API
- Fail-Closed -- when validation logic itself errors, deny by default
- 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 -- better machine UX: self-description, explicit modes, richer schemas
- ecosystem -- agent-native integration:
agent/,skills,issue, inline context
Certification maps to layers:
- Agent-Friendly -- all
corerules pass - Agent-Ready -- all
core+recommendedrules pass - Agent-Native -- all layers pass
How It Works
Step 1: Output Mode
Default is agent mode (JSON). Explicit flags to switch:
$ mycli list # default = JSON output (agent mode)
$ mycli list --human # human-friendly: colored, tables, formatted
$ mycli list --agent # explicit agent mode (override config if needed)- Default (no flag) -- JSON to stdout. Agent never needs to add a flag.
- --human -- human-friendly format (colors, tables, progress bars)
- --agent -- explicit JSON mode (useful when env/config overrides default)
Step 2: agent/ Directory Convention
Every CLI tool MUST have an agent/ directory at its project root. This is the
tool's identity and behavior contract for AI agents.
agent/
brief.md # One paragraph: who am I, what can I do
rules/ # Behavior constraints (auto-registered)
trigger.md # When should an agent use this tool
workflow.md # Step-by-step usage flow
writeback.md # How to write feedback back
skills/ # Extended capabilities (auto-registered)
getting-started.mdStep 3: Four Levels of Self-Description
- --brief (business card, injected into agent config)
- Every Command Response (always-on context: data + rules + skills + issue)
- --help (full self-description: brief + commands + rules + skills + issue)
- skills \<name\> (on-demand deep dive into a specific skill)
Certification Requirements
Each level includes all rules from the previous level.
Priority tag [P0]=agent breaks without it, [P1]=agent works but poorly, [P2]=nice to have.
Level 1: Agent-Friendly (core -- 20 rules)
Goal: CLI is a stable, callable API. Agent can invoke, parse, and handle errors.
Output -- default is JSON, stable schema
[P0]O1: Default output is JSON. No--jsonflag needed[P0]O2: JSON MUST passjq .validation[P0]O3: JSON schema MUST NOT change within same version
Error -- structured, to stderr, never interactive
[P0]E1: Errors ->{"error":true, "code":"...", "message":"...", "suggestion":"..."}to stderr[P0]E4: Error has machine-readablecode(e.g.MISSING_REQUIRED)[P0]E5: Error has human-readablemessage[P0]E7: On error, NEVER enter interactive mode -- exit immediately[P0]E8: Error codes are API contracts -- MUST NOT rename across versions
Exit Code -- predictable failure signals
[P0]X3: Parameter/usage errors MUST exit 2[P0]X9: Failures MUST exit non-zero -- never exit 0 then report error in stdout
Composability -- clean pipe semantics
[P0]C1: stdout is for data ONLY[P0]C2: logs, progress, warnings go to stderr ONLY
Input -- fail fast on bad input
[P1]I4: Missing required param -> structured error, never interactive prompt[P1]I5: