Convert vague prompts into testable EARS-based specifications.
npx skills add https://github.com/aleister1102/skills --skill prompt-optimizer-aleister1102
Please help me install this Agent Skill. Skill: prompt-optimizer Source: https://github.com/aleister1102/skills/tree/main/prompt-optimizer Command: npx skills add https://github.com/aleister1102/skills --skill prompt-optimizer-aleister1102
Converts vague prompts into precise, testable EARS-based specifications to create clearer, verifiable requirements and prompts.
Provide a vague prompt, and I will generate a complete EARS-based specification with domain grounding and a structured prompt ready for implementation.
High-intent search queries and answers about installing and using this skill.
EARS transformation works by converting descriptive requirements into precise EARS-formatted statements that are verifiable. It grounds requirements in established domain theories to improve credibility and rigor, outputting a structured Role/Skills/Workflows/Examples/Formats prompt for implementation.
To refine a prompt for development workflows, you provide the vague prompt to generate a complete EARS-based specification. This end-to-end specification includes domain grounding, examples, and a structured prompt format ready for immediate implementation in design, development, and evaluation tasks.
EARS transformation for prompt optimization is a method that converts descriptive requirements into precise, testable EARS-formatted statements. It maps requirements to established domain theories to improve credibility, delivering verifiable specifications and structured prompts for implementation.
You need EARS-based specifications when vague prompts require conversion into clearer, verifiable requirements. This approach applies across design, development, and evaluation workflows to ensure your prompts are precise, testable, and grounded in established domain theories.
Yes, you can use domain-theory grounding to improve requirement credibility by mapping your specifications to established theories. This technique enhances rigor during EARS transformation, ensuring the generated structured prompts are verifiable and grounded in recognized domain frameworks.
The best way to structure prompts for implementation is to generate a Role/Skills/Workflows/Examples/Formats output. This structured format is produced after completing EARS transformation and domain-theory grounding, delivering a complete specification ready for development workflows.
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