Create and evaluate AI skills with SKILL.md metadata and test cases.
npx skills add https://github.com/a0972199950/lazy-cv --skill skill-creator-a0972199950
Please help me install this Agent Skill. Skill: skill-creator Source: https://github.com/a0972199950/lazy-cv/tree/main/.agents/skills/skill-creator Command: npx skills add https://github.com/a0972199950/lazy-cv --skill skill-creator-a0972199950
This Skill streamlines the entire process of creating and improving AI skills, from initial concept to robust performance testing, making AI development accessible and efficient.
SKILL.md, and structuring skill resources.Use the skill-creator to help me build a new skill that can summarize meeting transcripts.
High-intent search queries and answers about installing and using this skill.
To build and test AI skills, you define the skill intent, write the `SKILL.md` metadata, and develop test cases to run evaluations against baseline models. This process structures your resources and validates performance before deployment.
Optimizing AI skill descriptions involves iteratively tuning the metadata text based on performance metrics and evaluation results. This automated refinement ensures the skill triggers accurately when users submit relevant prompts.
Automated evaluation for prompt engineering works by running your developed test cases against baseline AI models to analyze results. This identifies performance gaps and guides the iterative refinement of your skill logic.
You do not need specific external frameworks to start AI skill development, as the process relies on structuring `SKILL.md` metadata and defining test cases. It integrates directly with your existing AI model execution environments for testing.
An AI skill may fail to trigger correctly if the intent definition is unclear or the `SKILL.md` description lacks optimization. Running performance evaluations and analyzing baseline model results helps pinpoint and resolve these triggering inaccuracies.
Marcu-LoretoGuide users through defining intents, designing prompts, and implementing logic for AI skills.
vnmoorthyMonitor live apps for console errors and performance regressions post-deploy.
selcukyucelGenerate structured evaluation datasets with binary rubric scoring for AI outputs.
PatrickjoshanedezCreate, refine, and benchmark AI skills with SKILL.md files and test suites.