What phrases trigger the prompt optimization behavior?

You can activate it using trigger terms like 'optimize prompt', 'reduce LLM cost', 'improve prompt performance', or 'rewrite prompt'.

Which Claude Code plugins does this skill work with?

It integrates directly with the prompt-architect for advanced engineering and the llm-integration-expert for API-specific optimizations.

Will optimizing my prompt affect the quality of the AI's answer?

The skill is designed to maintain or improve quality. By providing clearer and more direct instructions, it often helps the LLM focus better on the core task.

How does the Prompt Optimizer skill reduce LLM costs?

It analyzes your prompts to remove unnecessary words and structural redundancies, resulting in a lower token count per request without losing the original meaning.

Prompt Optimizer Adapter

Name: Prompt Optimizer Adapter
Author: BbgnsurfTech

byBbgnsurfTech

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データサイエンスとML

Refines and condenses AI prompts to minimize token consumption while maximizing output quality and performance.

概要

The Prompt Optimizer skill (skill-adapter) is a specialized tool designed to streamline interactions with Large Language Models by identifying redundancies and verbosity in user instructions. By rewriting prompts into concise, high-impact language, it significantly reduces token usage and associated costs while improving the speed and clarity of LLM responses. This skill is essential for developers and AI engineers looking to scale their applications efficiently, providing a systematic way to maintain high-quality outputs while optimizing the underlying computational resources.

主な機能

3 GitHub stars
Performance-driven optimization for faster model response times
Seamless integration with prompt architect and LLM integration tools
Context-aware simplification that preserves original prompt intent
Token-conscious prompt rewriting for significant cost reduction
Redundancy and verbosity analysis for cleaner AI instructions

ユースケース

Decreasing latency in time-sensitive AI-driven applications
Reducing operational costs for high-volume LLM API implementations
Standardizing complex instructions into efficient, high-performance templates

概要

主な機能

3 GitHub stars
Performance-driven optimization for faster model response times
Seamless integration with prompt architect and LLM integration tools
Context-aware simplification that preserves original prompt intent
Token-conscious prompt rewriting for significant cost reduction
Redundancy and verbosity analysis for cleaner AI instructions

ユースケース

Decreasing latency in time-sensitive AI-driven applications
Reducing operational costs for high-volume LLM API implementations
Standardizing complex instructions into efficient, high-performance templates