MCP HubMCP Hub
返回技能列表

providing-performance-optimization-advice

jeremylongshore
更新于 Today
6 次查看
409
51
409
在 GitHub 上查看
ai

关于

This skill provides comprehensive performance optimization advice for software projects when developers request improvements, reviews, or bottleneck analysis. It analyzes frontend, backend, and infrastructure layers to identify issues and anti-patterns, then delivers prioritized, actionable recommendations with estimated gains. Use it for performance tuning by triggering phrases like "optimize performance" or "improve speed."

技能文档

Overview

This skill empowers Claude to act as a performance optimization advisor, delivering a detailed report of potential improvements across various layers of a software application. It prioritizes recommendations based on impact and effort, allowing for a focused and efficient optimization strategy.

How It Works

  1. Analyze Project: Claude uses the plugin to analyze the project's codebase, infrastructure configuration, and architecture.
  2. Identify Optimization Areas: The plugin identifies potential optimization areas in the frontend, backend, and infrastructure.
  3. Prioritize Recommendations: The plugin prioritizes recommendations based on estimated performance gains and implementation effort.
  4. Generate Report: Claude presents a comprehensive report with actionable advice, performance gain estimates, and a phased implementation roadmap.

When to Use This Skill

This skill activates when you need to:

  • Identify performance bottlenecks in a software application.
  • Get recommendations for improving website loading speed.
  • Optimize database query performance.
  • Improve API response times.
  • Reduce infrastructure costs.

Examples

Example 1: Optimizing a Slow Website

User request: "My website is loading very slowly. Can you help me optimize its performance?"

The skill will:

  1. Analyze the website's frontend code, backend APIs, and infrastructure configuration.
  2. Identify issues such as unoptimized images, inefficient database queries, and lack of CDN usage.
  3. Generate a report with prioritized recommendations, including image optimization, database query optimization, and CDN implementation.

Example 2: Improving API Response Time

User request: "The API response time is too slow. What can I do to improve it?"

The skill will:

  1. Analyze the API code, database queries, and caching strategies.
  2. Identify issues such as inefficient database queries, lack of caching, and slow processing logic.
  3. Generate a report with prioritized recommendations, including database query optimization, caching implementation, and asynchronous processing.

Best Practices

  • Specificity: Provide specific details about the project and its performance issues to get more accurate and relevant recommendations.
  • Context: Explain the context of the performance problem, such as the expected user load or the specific use case.
  • Iteration: Review the recommendations and provide feedback to refine the optimization strategy.

Integration

This skill integrates well with other plugins that provide code analysis, infrastructure management, and deployment automation capabilities. For example, it can be used in conjunction with a code linting plugin to identify code-level performance issues or with an infrastructure-as-code plugin to automate infrastructure optimization tasks.

快速安装

/plugin add https://github.com/jeremylongshore/claude-code-plugins-plus/tree/main/performance-optimization-advisor

在 Claude Code 中复制并粘贴此命令以安装该技能

GitHub 仓库

jeremylongshore/claude-code-plugins-plus
路径: backups/skills-migration-20251108-070147/plugins/performance/performance-optimization-advisor/skills/performance-optimization-advisor
aiautomationclaude-codedevopsmarketplacemcp

相关推荐技能

llamaguard

其他

LlamaGuard是Meta推出的7-8B参数内容审核模型,专门用于过滤LLM的输入和输出内容。它能检测六大安全风险类别(暴力/仇恨、性内容、武器、违禁品、自残、犯罪计划),准确率达94-95%。开发者可通过HuggingFace、vLLM或Sagemaker快速部署,并能与NeMo Guardrails集成实现自动化安全防护。

查看技能

sglang

SGLang是一个专为LLM设计的高性能推理框架,特别适用于需要结构化输出的场景。它通过RadixAttention前缀缓存技术,在处理JSON、正则表达式、工具调用等具有重复前缀的复杂工作流时,能实现极速生成。如果你正在构建智能体或多轮对话系统,并追求远超vLLM的推理性能,SGLang是理想选择。

查看技能

evaluating-llms-harness

测试

该Skill通过60+个学术基准测试(如MMLU、GSM8K等)评估大语言模型质量,适用于模型对比、学术研究及训练进度追踪。它支持HuggingFace、vLLM和API接口,被EleutherAI等行业领先机构广泛采用。开发者可通过简单命令行快速对模型进行多任务批量评估。

查看技能

langchain

LangChain是一个用于构建LLM应用程序的框架,支持智能体、链和RAG应用开发。它提供多模型提供商支持、500+工具集成、记忆管理和向量检索等核心功能。开发者可用它快速构建聊天机器人、问答系统和自主代理,适用于从原型验证到生产部署的全流程。

查看技能