Create and refine AI skills with SKILL.md files and performance evaluations.
npx skills add https://github.com/Jaydpatel01/.github --skill skill-creator-jaydpatel01
Please help me install this Agent Skill. Skill: skill-creator Source: https://github.com/Jaydpatel01/.github/tree/main/skills/skill-creator Command: npx skills add https://github.com/Jaydpatel01/.github --skill skill-creator-jaydpatel01
This Skill streamlines the entire lifecycle of creating and improving AI-powered skills, from initial concept to performance optimization and deployment.
SKILL.md files.SKILL.md, write test cases, run evaluations against a baseline, analyze the results, and iterate on the skill's logic and description until it performs optimally.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 an AI agent skill, you define the intent, write the SKILL.md file, and run iterative testing with quantitative and qualitative evaluations to benchmark performance and refine the logic.
Improving AI skill invocation accuracy requires targeted description tuning and prompt engineering to enhance discoverability, ensuring the skill triggers reliably based on user intent during evaluations.
Yes, you can evaluate prompt engineering changes by running iterative tests against a performance baseline, analyzing quantitative and qualitative metrics to measure improvements in the AI skill.
Skill development starts by interviewing for requirements and drafting the initial SKILL.md file, which establishes the core logic and intent before moving into iterative testing and refinement.
Yes, the skill development lifecycle supports quantitative performance benchmarking by facilitating structured evaluations that measure how well the AI skill performs against defined test cases and baselines.
You should iterate on an AI skill's description and logic after analyzing evaluation results and user feedback, refining both the prompt engineering and processing logic until performance metrics meet optimal standards.
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