Prompt Optimizer
0Prompt Optimizer is designed to help users select appropriate prompt frameworks based on specific task scenarios and generate clearer, more actionable prompts. It assists prompt creators in optimizing their prompts for better performance.
64600Updated 1mo ago
Productivity
Quick InstallView Source
$ npx skills add https://github.com/chujianyun/skills --skill prompt-optimizerOverview
About This Skill
Prompt Optimizer is a reviewer and generator skill that diagnoses and improves AI prompts across different task scenarios. It helps prompt creators select the right framework for their use case—whether instructional, role-based, structured, or domain-specific—then generates clearer, more actionable prompt text. Rather than offering generic suggestions, it first assesses your prompt's current state and task requirements, then provides targeted improvements. Teams building AI agents, developing instruction sets, or refining Claude prompts benefit from this structured approach to prompt optimization.
How to Use
Add the skill to your project using the command provided.
Use Cases
Choosing the right prompt structure for a given task.
Improving the clarity and execution of prompts.
Refining and polishing existing prompts based on specific requirements.
Tags
Setup & Installation
Quick Install
Terminal
$ npx skills add https://github.com/chujianyun/skills --skill prompt-optimizerAlternative Install (Git Clone)
git clone https://github.com/chujianyun/skillsRequirements
- Claude Code or compatible AI agent
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Optimize this prompt for [TASK GOAL] in [COMPANY/INDUSTRY] context. Current prompt: "[PROMPT TO OPTIMIZE]". Focus on improving clarity, specificity, and actionability. Suggest a refined version and explain the optimizations made.
Example Output
### Optimized Prompt for Customer Feedback Analysis **Original Prompt:** "Analyze customer feedback for our e-commerce platform." **Optimized Prompt:** "As a data analyst for [Company Name], an e-commerce platform specializing in [INDUSTRY], analyze the last 3 months of customer feedback stored in [DATA SOURCE]. Focus on identifying: - Top 3 recurring complaints about product quality or shipping delays - Sentiment trends (positive/negative/neutral) in product reviews - Specific suggestions mentioned by customers for improving our checkout process Provide a summary report with: 1. A ranked list of pain points (1 being most critical) 2. 3 actionable recommendations to address the top issues 3. Sample responses to common complaints Prioritize feedback from VIP customers (top 10% by spending) and exclude spam or bot-generated comments." **Optimizations Applied:** - Added **context** (company, industry, data source) to ground the analysis - Defined **specific focus areas** (complaints, sentiment, suggestions) instead of vague "analyze" - Structured **output requirements** (ranked list, recommendations, sample responses) for actionability - Included **filtering criteria** (VIP customers, spam exclusion) to improve relevance - Set **time bounds** (last 3 months) for temporal context This version ensures the AI delivers a **targeted, structured, and business-relevant** analysis while minimizing ambiguity. Would you like me to refine this further for a specific use case (e.g., marketing, product development) or adjust the tone (e.g., technical, executive summary)?
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