sp-instructor-agent

To turn vague prompts into precise master prompts, you provide the initial input and the skill identifies flaws, proposes granular SP-atoms, and synthesizes a structured Master Prompt. It applies the SMART POLE framework to guide the refinement process.

The SMART POLE SP-atom framework is an instructional method for prompt engineering that breaks down vague instructions into granular components called SP-atoms. It identifies structural flaws and aligns the final Master Prompt with core categories.

To resolve conflicts in prompt engineering before execution, the skill applies readiness scoring and conflict resolution mechanisms. It evaluates the proposed SP-atoms to ensure the synthesized Master Prompt is structurally sound and ready for interactive use.

Yes, you can generate interactive learning exercises from a master prompt. The skill creates an active-exercise workflow alongside the structured Master Prompt, operating in guided-learning conversations to help users apply the refined instructions.

The best way to structure instructional prompts for AI agents is to use a framework that identifies flaws and proposes granular atoms. This skill synthesizes aligned Master Prompts and generates active-exercise workflows with readiness scoring before execution.