Does this skill support platforms other than Claude Code?

Yes, Skill Creator Pro includes logic to adapt frontmatter and instruction sets for various platforms including Codex, Gemini CLI, Antigravity, and GitHub Copilot.

How does Benchmark mode improve skill reliability?

Benchmark mode runs evaluations multiple times (N runs) to compute variance. This identifies flaky assertions where the AI might pass or fail inconsistently, allowing developers to tighten instructions.

Why are instructions written in a 'WHAT + WHY' format?

Providing the reasoning (the 'Why') alongside the action (the 'What') helps the AI model understand the context and intent, leading to better adaptation when it encounters edge cases not explicitly covered.

What is the Pro Skill Standard enforced by this tool?

The Pro Skill Standard is a mandatory structural framework requiring valid YAML frontmatter, specific trigger conditions, 12-18 'WHAT + WHY' formatted instructions, and a minimum of two evaluation prompts with five assertions each.

Skill Creator Pro

Name: Skill Creator Pro
Author: CUBETIQ

byCUBETIQ

•

Developer Tools

Automates the end-to-end development lifecycle for AI skills, from initial drafting and editing to rigorous evaluation and benchmarking.

Skill Creator Pro is a sophisticated meta-skill designed for developers and AI engineers to build, refine, and maintain production-grade capabilities within the Cubis Foundry ecosystem. By enforcing the 'Pro Skill Standard,' it ensures that every created skill includes precise trigger conditions, structured 'WHAT + WHY' instructions, and comprehensive evaluation suites. Whether you are bootstrapping a new domain-specific capability or auditing existing instructions for platforms like Claude Code, Codex, or Gemini, this tool provides the necessary framework for iterative improvement and high-accuracy routing.

Key Features

01Variance analysis to identify and resolve flaky AI instructions

02Full lifecycle support with dedicated Create, Edit, Eval, and Benchmark modes

031 GitHub stars

04Assertion-based evaluation design to test behavioral output consistency

05Multi-platform adaptation logic for Claude Code, Gemini, and Antigravity

06Automated Pro Skill Standard checklist for quality assurance

Use Cases

01Architecting new domain-specific skills for custom AI agent environments

02Benchmarking skill reliability across multiple runs to ensure production readiness

03Refining existing skill instructions based on performance eval failures

Key Features

01Variance analysis to identify and resolve flaky AI instructions

02Full lifecycle support with dedicated Create, Edit, Eval, and Benchmark modes

031 GitHub stars

04Assertion-based evaluation design to test behavioral output consistency

05Multi-platform adaptation logic for Claude Code, Gemini, and Antigravity

06Automated Pro Skill Standard checklist for quality assurance

Use Cases

01Architecting new domain-specific skills for custom AI agent environments

02Benchmarking skill reliability across multiple runs to ensure production readiness

03Refining existing skill instructions based on performance eval failures