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Found 18 Skills
Design and build agent-first CLIs with HATEOAS JSON responses, context-protecting output, and self-documenting command trees. Use when creating new CLI tools, adding commands to existing CLIs (joelclaw, slog, igs), or reviewing CLI design for agent-friendliness. Triggers on 'build a CLI', 'add a command', 'CLI design', 'agent-friendly output', or any task involving command-line tool creation.
Use when designing a new CLI, reviewing an existing CLI, or resolving uncertainty about a CLI's role, user type, interaction form, statefulness, risk profile, or human-vs-machine surfaces.
Unix-composable CLI design patterns. Use when building CLI tools, designing command trees, implementing output layers, or testing CLI behavior. Covers stream separation (stdout/stderr), format flags (--json/--plain), exit codes, TTY detection, composability, and error design. Language-agnostic principles; TypeScript implementation patterns in resources/. For API design (REST, HTTP), see api-design.
Use this skill when building command-line interfaces, designing CLI argument parsers, writing help text, adding interactive prompts, managing config files, or distributing CLI tools. Triggers on argument parsing, subcommands, flags, positional arguments, stdin/stdout piping, shell completions, interactive menus, dotfile configuration, and packaging CLIs as npm/pip/cargo/go binaries.
Design command-line interface parameters and UX: arguments, flags, subcommands, help text, output formats, error messages, exit codes, prompts, config/env precedence, and safe/dry-run behavior. Use when you're designing a CLI spec (before implementation) or refactoring an existing CLI's surface area for consistency, composability, and discoverability.
Design command-line interface parameters and UX: arguments, flags, subcommands, help text, output formats, error messages, exit codes, prompts, config/env precedence, and safe/dry-run behavior. Use when you’re designing a CLI spec (before implementation) or refactoring an existing CLI’s surface area for consistency, composability, and discoverability.
A scoring scale for evaluating how well a CLI is designed for AI agents, based on the "Rewrite Your CLI for AI Agents" principles.
Build command-line interfaces for AI agents. Covers arguments, flags, subcommands, help text, output formats, error messages, exit codes, config/env precedence, and safe/dry-run behavior. Use when building a new CLI or refactoring an existing one for agent use.
Expert guide for building command-line interfaces with Node.js (Commander, Inquirer, Ora) or Python (Click, Typer, Rich). Use when creating CLI tools, terminal UX, argument parsing, or interactive prompts.
Python design patterns for CLI scripts and utilities — type-first development, deep modules, complexity management, and red flags. Use when reading, writing, reviewing, or refactoring Python files, especially in .trellis/scripts/ or any CLI/scripting context. Also activate when planning module structure, deciding where to put new code, or doing code review.
Design CLI tools with consistent UX patterns.
Use this skill whenever designing, building, or reviewing a command-line tool that AI agents or automation will invoke — covers non-interactive flags, layered --help with examples, stdin/pipeline composition, actionable errors, idempotency, dry-run, destructive-action safety, and predictable command structure. Trigger even if the user doesn't explicitly say "agent-friendly" — apply whenever they are writing `--help` text, adding a new subcommand, designing error messages, or reviewing a CLI's UX.