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optimize-prompts

Select the best prompt variation based on performance metrics on an evaluation set.

29|8|Updated Jul 5, 2026
Search Tags:#prompt optimization#LLM#LLM performance#prompt variation#eval set
One-click install
npx skills add https://github.com/ContextJet-ai/awesome-llm-observability --skill optimize-prompts
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: optimize-prompts
Source: https://github.com/ContextJet-ai/awesome-llm-observability/tree/main/skills/optimize-prompts
Command: npx skills add https://github.com/ContextJet-ai/awesome-llm-observability --skill optimize-prompts

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of manually tuning prompts for LLMs, offering an automated approach to optimize prompts systematically and improve their performance.

Core Features & Use Cases

  • Systematic Optimization: Automates the process of optimizing prompts against an evaluation set, selecting the best prompt based on performance metrics.
  • Evaluation Set Utilization: Utilizes pre-built evaluation sets or allows for custom sets to measure prompt quality.
  • Use Case: When you have a set of prompts that have plateaued in quality, this Skill can propose and evaluate new prompt variations to find the optimal one.

Quick Start

Trigger the optimize-prompts Skill with the command: "optimize my prompt".

Frequently Asked Questions about optimize-prompts

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

FAQPage Schema
How do I automate prompt optimization for better LLM performance?▼

You need a pre-built or custom evaluation set and an LLM scoring system to measure prompt quality. These prerequisites enable the Skill to systematically evaluate variations and select the highest-performing prompt.

What is the best way to evaluate prompt variations against an evaluation set?▼

It is designed for scenarios where manual prompt tuning has plateaued. By proposing and evaluating new prompt variations against an evaluation set, it systematically breaks through quality plateaus to find the optimal prompt.

Do I need a custom evaluation set to improve prompt quality?▼

Yes, an LLM scoring system is required to measure prompt quality on the evaluation set. The Skill relies on these scoring metrics to evaluate variations and select the optimal prompt for your LLM.

Can I use this for LLM performance improvement when prompt quality plateaus?▼

When prompt quality plateaus, this Skill proposes and evaluates new prompt variations against an evaluation set. It selects the best performing variation to systematically improve LLM results.

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