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squidllee
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cli-for-agents

Designs and reviews command-line interfaces for reliable non-interactive execution by coding agents.

Updated Aug 22, 2026
Search Tags:#automation#cli#idempotency#command-line#non-interactive#agent-friendly#help documentation
One-click install
npx skills add https://github.com/squidllee/skills --skill cli-for-agents-squidllee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cli-for-agents
Source: https://github.com/squidllee/skills/tree/main/cli-for-agent/skills/cli-for-agents
Command: npx skills add https://github.com/squidllee/skills --skill cli-for-agents-squidllee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Human-oriented CLIs often block automation: interactive prompts, arrow-key menus, missing examples in help text, and non-idempotent commands cause coding agents to hang or fail. This Skill provides design guidelines for building CLIs that agents can run headlessly and compose in pipelines. ## Core Features & Use Cases - Non-interactive design patterns: Ensures every input is expressible as a flag, with interactive mode only as a fallback. - Layered help and examples: Structures --help per subcommand with copy-pasteable example invocations instead of dumping full manuals. - Agent-safe behaviors: Covers stdin/pipeline support, fast actionable errors, idempotency, --dry-run, --force flags, and machine-useful success output. - Use Case: When building a new deploy CLI, apply these patterns so an agent can run mycli deploy --env staging --tag v1.2.3 --force without prompts, preview changes with --dry-run, and parse structured output like deploy IDs and URLs. ## Quick Start Ask the agent to review your CLI's command structure and help output against agent-friendly design patterns, or to design a new non-interactive CLI command with flags, examples, and dry-run support.

Frequently Asked Questions about cli-for-agents

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

FAQPage Schema
How do I make a CLI work with AI coding agents?▼

Make every input expressible as a flag so no interactive prompts are required, and provide layered --help with real example invocations per subcommand. Add idempotent behavior, --dry-run for destructive actions, and structured success output with IDs and URLs.

How to design CLI commands for automation and scripting?▼

Use a consistent resource-plus-verb structure like mycli service list, accept stdin where useful, and support chaining via flags such as --output. Avoid positional ordering quirks and never fall back to interactive prompts for missing values.

What should CLI --help output include for agents?▼

Each subcommand's --help should include an Examples section with real copy-pasteable invocations, since agents pattern-match on examples more than prose. Keep documentation layered so unused commands stay out of context.

Why do interactive CLI prompts break automation scripts?▼

Arrow-key menus, timed prompts, and confirmation dialogs block headless execution because agents cannot respond to them. The fix is flag-first design where interactive mode is only a fallback when flags are absent, plus --yes or --force to bypass confirmations.

How do I handle destructive CLI commands safely for agents?▼

Add a --dry-run flag so agents can preview planned changes before committing, and provide --yes or --force to skip confirmations while keeping safe defaults for humans. Make commands idempotent so retries do not duplicate side effects.

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