com um clique
prompt-engineer
设计、优化和测试AI模型提示词,使用系统化的提示工程技术,包括少样本学习、思维链和结构化输出。
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
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设计、优化和测试AI模型提示词,使用系统化的提示工程技术,包括少样本学习、思维链和结构化输出。
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
自动分析B站视频内容,下载视频并拆解成帧图片,使用AI分析并生成详细的专题文档或实操教程。
设计RESTful API并生成OpenAPI/Swagger规范文档,遵循行业最佳实践。包括端点命名、请求/响应模式和错误处理模式。
为GitHub Actions、GitLab CI、Azure DevOps和Jenkins生成CI/CD流水线,包含构建、测试、部署阶段、缓存和密钥管理。
全面的代码审查技能,分析代码质量、识别问题、安全漏洞,并提供带严重性评级的改进建议。
设计和优化数据库模式,支持PostgreSQL、MySQL、SQLite和MongoDB。包括ER建模、规范化、索引优化和迁移脚本生成。
创建和管理多容器应用的Docker Compose配置,包含生产级设置、健康检查和网络配置。
| name | prompt-engineer |
| description | 设计、优化和测试AI模型提示词,使用系统化的提示工程技术,包括少样本学习、思维链和结构化输出。 |
| metadata | {"short-description":"设计高效的AI提示词"} |
Design and optimize prompts for AI models using proven techniques.
/prompt commandYou are a prompt engineering expert that creates effective AI prompts.
You are a [ROLE] that [PRIMARY_FUNCTION].
## Core Responsibilities
1. [Responsibility 1]
2. [Responsibility 2]
3. [Responsibility 3]
## Guidelines
- Always [guideline 1]
- Never [guideline 2]
- When uncertain, [fallback behavior]
## Output Format
[Specify exact format expected]
## Examples
[Provide 2-3 examples of ideal responses]
Classify the sentiment of customer reviews.
Examples:
Review: "This product exceeded my expectations! Fast shipping too."
Sentiment: positive
Review: "Broke after one week. Complete waste of money."
Sentiment: negative
Review: "It works as described. Nothing special."
Sentiment: neutral
Now classify:
Review: "{user_input}"
Sentiment:
Solve this step by step:
Problem: A store has 150 apples. They sell 40% on Monday and 30 more on Tuesday. How many remain?
Let me think through this:
1. Starting amount: 150 apples
2. Monday sales: 150 × 0.40 = 60 apples sold
3. After Monday: 150 - 60 = 90 apples
4. Tuesday sales: 30 apples sold
5. After Tuesday: 90 - 30 = 60 apples
Answer: 60 apples remain
Extract information from the text and return as JSON.
Text: "John Smith, age 32, works as a software engineer at Google in Mountain View. He can be reached at john.smith@email.com."
Output format:
{
"name": "string",
"age": number,
"occupation": "string",
"company": "string",
"location": "string",
"email": "string"
}
Response:
{
"name": "John Smith",
"age": 32,
"occupation": "software engineer",
"company": "Google",
"location": "Mountain View",
"email": "john.smith@email.com"
}
You are an expert code reviewer with 15 years of experience in TypeScript and React. You have a keen eye for:
- Performance bottlenecks
- Security vulnerabilities
- Code maintainability
- Best practices violations
When reviewing code:
1. First identify critical issues that could cause bugs or security problems
2. Then note performance concerns
3. Finally suggest style improvements
Always explain WHY something is an issue, not just WHAT is wrong.
prompts, ai, llm, optimization, templates