Llm Application Dev Prompt Optimize
Helps with LLMs, optimization as part of building AI and machine learning applications workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add rmyndharis-llm-application-dev-prompt-optimize npx -- -y @trustedskills/rmyndharis-llm-application-dev-prompt-optimize
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"rmyndharis-llm-application-dev-prompt-optimize": {
"command": "npx",
"args": [
"-y",
"@trustedskills/rmyndharis-llm-application-dev-prompt-optimize"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill optimizes prompts for Large Language Model (LLM) application development. It refines and improves existing prompts to enhance the quality, relevance, and accuracy of LLM outputs. The tool aims to boost efficiency in building AI applications by ensuring prompts elicit desired responses from LLMs.
When to use it
- You're experiencing inconsistent or unsatisfactory results from your current LLM prompts.
- You want to improve the performance of an existing LLM-powered application.
- You need to generate more targeted and relevant content using an LLM.
- You are looking for ways to reduce costs associated with LLM usage by improving prompt efficiency.
Key capabilities
- Prompt refinement
- Output quality enhancement
- Relevance improvement
- Accuracy optimization
Example prompts
- "Optimize this prompt: 'Write a short story about a cat.'"
- "Refine the following prompt to get more detailed responses: 'Summarize this article.'"
- "Improve this prompt for generating marketing copy: 'Create an ad for our new product.'"
Tips & gotchas
The skill works best with clear and concise prompts. Providing context or examples of desired output can further improve optimization results.
Tags
TrustedSkills Verification
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🌐 Community
Passed automated security scans.