Translate vague feedback into structured prompts for coding agents.
npx skills add https://github.com/kennykankush/skillpack --skill max-prompt
Please help me install this Agent Skill. Skill: max-prompt Source: https://github.com/kennykankush/skillpack/tree/main/plugins/workbench/skills/max-prompt Command: npx skills add https://github.com/kennykankush/skillpack --skill max-prompt
This skill converts vague feedback, taste, or half-formed instincts about a product into a precise, implementation-ready prompt for a coding agent. It helps bridge the gap between intuition and concrete engineering tasks, reducing ambiguity in design-to-code handoffs.
Provide your vague feedback or design intuition to generate an implementation-ready prompt for a coding agent.
High-intent search queries and answers about installing and using this skill.
To convert vague UI UX feedback into an implementation prompt, you input your design critique and the tool outputs a structured prompt specifying mechanism, ownership, constraints, implementation, and verification for coding agents.
The best way to structure design critique for frontend tasks is to define the mechanism, ownership, constraints, implementation, and verification, ensuring your design intuition becomes a consistent and testable engineering prompt.
Yes, you can generate prompts for component architecture and interaction refinements by translating half-formed instincts into actionable directives tailored specifically for coding agents to implement.
Yes, this tool works for design to code handoffs by bridging the gap between intuition and concrete engineering tasks, reducing ambiguity without requiring deep technical prerequisite knowledge from the reviewer.
Frontend polish prompts fail to produce testable outputs because vague feedback lacks structure. Defining required rules like mechanism, constraints, and verification ensures the generated prompt drives consistent, testable engineering tasks.
You do not need any specific components to translate design intuition. You simply provide your vague feedback, and the tool applies its internal structure to generate an implementation-ready prompt for your coding agent.
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