Standardizes the creation of production-grade CLI tools optimized for AI agents and automated workflows.
This skill provides a comprehensive framework for building command-line interfaces that are predictable, composable, and machine-parseable. It enforces best practices such as strict separation of stdout for data and stderr for logs, consistent JSON output for programmatic consumption, and semantic exit codes for robust script branching. Designed specifically for 'agentic workflows,' it helps developers create tools that AI assistants like Claude can effectively navigate, chain, and automate without parsing errors or unpredictable behavior.
Key Features
017 GitHub stars
02Strict stdout/stderr stream separation for clean data piping and logging
03Best practices for secure credential storage using OS keyrings and environment variables
04Standardized resource-action command architecture for intuitive navigation
05Mandatory JSON output flags for machine-readable results across all commands
06Semantic exit code mapping for reliable error handling in automated scripts
Use Cases
01Building internal DevOps tools that need to be chained with Unix pipes and scripts
02Creating CLI wrappers for complex APIs that AI agents can use to perform autonomous tasks
03Refactoring legacy command-line tools to improve developer experience and automation compatibility
