max-prompt

Translate vague feedback into structured prompts for coding agents.

Updated Apr 26, 2026

Search Tags:#frontend #ui-ux #prompt-engineering #design-critique #implementation-prompt #vague-feedback

Ready to run

npx skills add https://github.com/kennykankush/skillpack --skill max-prompt

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

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.

Core Features & Use Cases

Translates instincts into a structured prompt that captures mechanism, ownership, constraints, and verification.
Supports UI/UX critique, frontend polish, component architecture, and interaction/animation refinements.
Provides clear, actionable prompts tailored for coding agents to implement changes quickly and consistently.

Quick Start

Provide your vague feedback or design intuition to generate an implementation-ready prompt for a coding agent.

Frequently Asked Questions about max-prompt

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I turn vague UI UX feedback into an implementation prompt for coding agents?▼

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.

What is the best way to structure design critique for frontend engineering tasks?▼

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.

Can I use this to generate prompts for component architecture and interaction refinements?▼

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.

Does this tool work for design to code handoffs without prerequisite technical knowledge?▼

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.

Why do my frontend polish prompts fail to produce testable coding agent outputs?▼

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.

What components do I need to translate design intuition into an actionable frontend prompt?▼

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.