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lyra-prompt-optimizer

Optimize prompts through a bilingual 4-phase methodology across multiple platforms.

Updated Aug 27, 2026
Search Tags:#prompt-optimization#CoT#ToT#AoT#GoT#Lyra
One-click install
npx skills add https://github.com/PhamMinhHaiAu-12035071/cursor-pro-max --skill lyra-prompt-optimizer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lyra-prompt-optimizer
Source: https://github.com/PhamMinhHaiAu-12035071/cursor-pro-max/tree/main/.claude/skills/lyra-prompt-optimizer
Command: npx skills add https://github.com/PhamMinhHaiAu-12035071/cursor-pro-max --skill lyra-prompt-optimizer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Lyra v2 transforms vague prompts into precise, structured prompts, reducing ambiguity and token waste while increasing output quality across Claude, ChatGPT, and Gemini. It provides a bilingual, multi-platform workflow for consistent prompt engineering at scale.

Core Features & Use Cases

  • 4-phase methodology (Dialogue, Blueprint, Synthesis, Refinement)
  • 3 optimization levels (Quick Boost, Deep Dive, Revolutionary)
  • 4 reasoning frameworks (CoT, ToT, GoT, AoT)
  • Bilingual English/Vietnamese support
  • References, examples, and a library of best practices for cross-platform prompt engineering
  • Seamless integration with the Cursor-pro-max ecosystem for commands and skills
  • Use cases include crafting robust prompts for software engineering tasks, cross-platform prompt optimization, and rapid iteration pipelines.

Quick Start

Use Lyra to initialize an optimization session by supplying an original prompt and selecting an optimization level. The system will guide you through a focused dialogue, blueprinting, synthesis, and refinement steps to produce a ready-to-use, platform-optimized prompt.

Frequently Asked Questions about lyra-prompt-optimizer

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

FAQPage Schema
How do I optimize prompts for different AI platforms like Claude and ChatGPT?▼

To optimize prompts for Claude and ChatGPT, provide your original prompt and select an optimization level. A 4-phase methodology refines it into a structured, platform-optimized prompt, reducing ambiguity and token waste.

When should I use Chain of Thought or Tree of Thoughts for prompt engineering?▼

Use reasoning frameworks like Chain of Thought (CoT), Tree of Thoughts (ToT), Graph of Thoughts (GoT), or Algorithm of Thoughts (AoT) when you need to structure complex reasoning in prompts to improve output quality and token efficiency.

What is the best way to reduce token waste in vague prompts?▼

The best way to reduce token waste in vague prompts is to apply a structured optimization workflow that transforms them into precise prompts through blueprinting, synthesis, and refinement steps.

Does this prompt optimization workflow support bilingual inputs?▼

Yes, the prompt optimization workflow supports bilingual English and Vietnamese inputs, transforming them into clear, actionable prompts across multiple platforms.

How do I start a prompt optimization session step by step?▼

To start a prompt optimization session, supply an original prompt and select an optimization level. The system guides you through Dialogue, Blueprint, Synthesis, and Refinement steps to produce a ready-to-use prompt.

What are the different optimization levels available for prompt engineering?▼

The available optimization levels for prompt engineering are Quick Boost, Deep Dive, and Revolutionary, which scale the depth of the 4-phase methodology applied to your original prompt.

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