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optimizing-prompts

Analyze and rewrite prompts to reduce token usage and preserve intent.

1|Updated Nov 21, 2025
Search Tags:#performance#LLM#conciseness#prompts#optimize#token#cost
One-click install
npx skills add https://github.com/pianzhu/my-claude-skills --skill optimizing-prompts
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: optimizing-prompts
Source: https://github.com/pianzhu/my-claude-skills/tree/main/skills/optimizing-prompts
Command: npx skills add https://github.com/pianzhu/my-claude-skills --skill optimizing-prompts

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users reduce token usage and monetary costs associated with prompts sent to large language models by analyzing prompts for verbosity and redundancies and rewriting them to be concise while preserving intent.

Core Features & Use Cases

  • Analyze prompts to identify redundancies, verbosity, and ambiguities.
  • Rewrite prompts to be concise while preserving meaning and required outputs.
  • Provide guidance and alternative phrasings to improve model performance and cost-efficiency.
  • Use Case: Teams can deploy a common, optimized prompting strategy across multiple tasks to reduce per-request costs.

Quick Start

Use the optimizing-prompts skill to rewrite a verbose prompt such as: "Please provide a detailed summary of this document, including all key points, definitions, and examples." The skill will return a concise version: "Summarize the document with key points and essential examples."

Frequently Asked Questions about optimizing-prompts

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

FAQPage Schema
How do I reduce token usage and cost for my LLM prompts?▼

To reduce LLM prompt token usage and cost, analyze and rewrite prompts to eliminate redundancies and verbosity while preserving the original meaning and required outputs.

What is prompt optimization for large language models?▼

Prompt optimization for large language models is the process of analyzing prompts for verbosity and ambiguities, then rewriting them to improve clarity, execution efficiency, and cost-efficiency.

How do I rewrite a verbose prompt to be concise without losing meaning?▼

You rewrite a verbose prompt to be concise by identifying redundancies and ambiguities, then rephrasing the text to retain key points and essential examples while stripping unnecessary filler.

Can I optimize prompts for code generation and documentation tasks?▼

Yes, you can optimize prompts for code generation and documentation tasks. The optimization process applies across domains to enable cost-efficient performance for chat prompts and code generation.

Does prompt optimization preserve the required model outputs?▼

Yes, prompt optimization preserves the required model outputs. It improves clarity and conciseness while maintaining the original intent and essential examples needed for accurate generation.

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