prompt-optimizer

Name: prompt-optimizer
Availability: InStock
Author: webmanufaktur

Analyze prompts to reduce token usage while preserving logical intent.

1|Updated Jan 15, 2026

Search Tags:#prompt engineering #optimization #prompt analysis #ai efficiency #token reduction

Ready to run

npx skills add https://github.com/webmanufaktur/pwaiworkflow --skill prompt-optimizer-webmanufaktur

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-optimizer
Source: https://github.com/webmanufaktur/pwaiworkflow/tree/main/.agents/skills/general/prompt-optimizer
Command: npx skills add https://github.com/webmanufaktur/pwaiworkflow --skill prompt-optimizer-webmanufaktur

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the issue of overly verbose or inefficient prompts that consume unnecessary tokens and computational resources.

Core Features & Use Cases

Prompt Analysis: Identifies redundancy, verbosity, and fragmentation in user-provided prompts.
Token Optimization: Generates a revised, more concise version of the prompt.
Use Case: You have a lengthy prompt for an AI agent that is not performing as expected. Use this Skill to analyze and shorten the prompt, potentially improving its focus and reducing processing costs.

Quick Start

Optimize the attached prompt file 'complex_analysis_prompt.md' to reduce token usage.

Frequently Asked Questions about prompt-optimizer

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

FAQPage Schema

How do I reduce token usage in lengthy AI prompts?▼

To reduce token usage in AI prompts, you can optimize them by analyzing and eliminating verbosity, redundancy, and fragmentation. This process generates a condensed, structured revision that preserves logical intent while improving processing efficiency.

What is prompt optimization and how does it work?▼

Prompt optimization is the process of analyzing natural language instructions to identify and eliminate verbosity, redundancy, and fragmentation. It works by generating a condensed, structured prompt revision that maintains logical intent while lowering token consumption.

Can I optimize a prompt file to improve AI agent performance?▼

Yes, you can optimize an attached prompt file to improve AI agent performance. By shortening lengthy instructions and reducing fragmentation, the agent receives a more focused prompt, which can resolve unexpected behavior and lower processing costs.

What is the best way to condense verbose natural language instructions for AI?▼

The best way to condense verbose natural language instructions is through structural analysis that targets redundancy and fragmentation. This approach produces a structured revision of the prompt, ensuring the logical intent is preserved without unnecessary token consumption.

Does prompt optimization preserve the original logical intent of the instructions?▼

Yes, prompt optimization preserves the original logical intent of the instructions. It specifically targets and removes verbosity, redundancy, and fragmentation, ensuring the condensed prompt revision maintains the exact meaning while improving AI processing efficiency.