@554/better-skill-creator

To create AI skills that trigger accurately, use a structured development process defining clear use-cases, trigger phrases, and success criteria before writing. This ensures reliable integration and clean workflow completion across agent capabilities.

The best way to structure a SKILL.md file for workflow automation is to follow a guided framework covering frontmatter, body structure, and composability, ensuring the resulting skill is well-defined and functions as intended.

AI agent skills fail to trigger correctly when they lack clear use-case definitions and distinct trigger phrases. Prevent these common skill development pitfalls by establishing quantitative and qualitative success criteria before writing.

You validate AI tooling and new agent capabilities by running built-in validation tools that perform syntax and behavioral testing on the skill, ensuring robustness and confirming that the defined success criteria are met.

Yes, you need python3 installed in your environment to use this structured skill development process, as it provides the necessary runtime for executing the included validation tools and reference scripts.

Yes, you can define quantitative success criteria for AI tooling during skill development. Establishing these metrics early in the use-case canvas phase ensures the final skill functions as intended and maintains high quality.