2024년 12월 4일 (수) 07:44 기준 최신판

본 문서는 Claude AI의 활용에 대한 내용이다.

chatGPT와는 다른 Claude AI관련 사항을 확인한다.

Claude professional 버전의 활용을 중심으로 설명한다.

Clause AI

클로드는 Anthropic이라는 회사가 개발한 AI 어시스턴트입니다. 클로드의 주요 발전 과정을 살펴보면:

2022년 말: 클로드 1.0이 처음 출시되었습니다.

2023년:

클로드 2가 출시되어 더 발전된 기능을 선보였습니다. 클로드 2.1이 출시되어 성능이 한층 개선되었습니다.

2024년:

클로드 3 제품군이 출시되었습니다. 여기에는:

Claude 3 Haiku: 빠른 속도에 최적화된 모델 Claude 3 Sonnet: 균형잡힌 성능을 제공하는 모델 Claude 3 Opus: 복잡한 작업과 글쓰기에 특화된 모델 이 포함됩니다.

Claude Projects

Pro version의 가장 큰 차이점은 Project의 사용이다.

Projects의 사용

Claude Project, team 요약 설명 - Good

Claude Projects의 주요 특징

클로드 프로젝트의 주요 특징

맞춤형 Custom Instructions 설정
맞춤형 지식 기반 구축
200K 컨텍스트 창 지원
팀 공유 기능
아티팩트(Artifacts) 생성 기능

Custom Instructions의 설정

맞춤형 행동방식 설정을 통해서, AI의 행동 방식, 지식 적용 방법, 응답 스타일을 세밀하게 조정할 수 있다.

Projects 만들기

Claude Credit 구성방법

Claude 구성 및 설정 기초 (링크)

기능설명

[클로드 유투브3:30초]

기능

4가지 추가 기능

컴퓨터 USE 기능

직접 컴퓨터 사용(베타), 1:40초

데이터 분석 기능 (한글 지원)

분석도구, Latex 렌더링, 시각적 PDF 분석

그림파일을 분석해서 답변을 해줌 - 이전에는 따로 해야 함

Cladue computer use

[computer use 예]

[발표 자료]

가상 컴퓨터를 사용하여, 클로드가 컴퓨터를 동작하여, 직접 작업을 실시할 수 있게 함. 가상OS, 에이전트 역할

주의사항 - API키가 있어야 함

Computer use

Claude Compute Use 주요기능

컴퓨터 핸들링

* 화면 인식 및 제어 - Claude API를 통해 화면 인식, 카우스 키보드 제어
* 명령어의 컴퓨터 명령어로 변환
* 다양한 도구 및 소프퉤어 활용 - 스프레드 시트, 텍스트 편집기, 브라우저 등 컴퓨터에 있는 유틸리티 AI 직접 사용

작동 순서

1. 사용자 프롬프트에 동작 설명해 주기

2. Claude의 도구 사용 결정 컴퓨터에 있는 사용 도구 정의를 로드하고, 사용자 쿼리에 맞춰 도구 사용 요청을 사용자에게 함

3. 도구 입력 추출 - Claude 요청에서 도구 이름과 입력을 추출, 컨테이너 또는 가상머신에서 도구를 사용

4. Claude 동작 - 사용자가 원하는 결과 도출까지 반복

Computer use 설치

1. 다음의 링크에서 Docker 데스크탑 설치

데스크 탑 설치

2. 터미널로 Claude API키 입력 도커 실행:

docker run -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY -v $HOME/.anthropic:/home/computeruse/.anthropic -p 5900:5900 -p 8501:8501 -p 6080:6080 -p 8080:8080 -it ghcr.io/anthropics/anthropic-quickstarts:computer-use-demo-latest

3. http://localhost:8080 으로 실행 API 키 발급 및 사용 - https://console.anthropic.com/settings/keys

4. 한글로 답변하게 설정: system prompt Custom System Prompt Suffix "Answer in Korean"

Claude API key 발급 및 사용

[AI 초보자 가이드, Claude AI Hub]

Anthropic API 콘솔 이동

API 키생성

Curl을 이용한 API Key 사용

curl https://api.anthropic.com/v1/messages \
 -H "Content-Type: application/json" \
 -H "x-api-key: YOUR_API_KEY" \
 -H "anthropic-version: 2024-10-01" \
 -d '{
   "model": "claude-3-5-sonnet-20241022",
   "max_tokens": 1024,
   "messages": [
     {
       "role": "user",
       "content": "Can you summarize the key findings of the latest research paper on AI ethics?"
     }
   ]
 }'

파이썬 API사용 예

 
<source lang="Python">
import requests
import json

API_KEY = 'YOUR_API_KEY'
url = 'https://api.anthropic.com/v1/messages'

headers = {
    'Content-Type': 'application/json',
    'x-api-key': API_KEY,
    'anthropic-version': '2024-10-01'
}

data = {
    "model": "claude-3-5-sonnet-20241022",
    "max_tokens": 1024,
    "messages": [
        {
            "role": "user",
            "content": "Explain the concept of reinforcement learning in simple terms."
        }
    ]
}

response = requests.post(url, headers=headers, data=json.dumps(data))

if response.status_code == 200:
    print("Claude's response:", response.json()['content'])
else:
    print("Error:", response.status_code, response.text)
</source>

Automate process with claude

[Automate 방법에 대한 유튜브]

1단계

프로세스 문서화

2단계

프롬프트 시퀀스

대화형 프롬프트 시퀀스로 작성할 것 (step by step)

3단계

만들어진 프롬프트 시퀀스를 Claude에 업로드 할 수 있는 instruction 세트로 바꾸기

쳌므인 또는 피드백 루프에 추가해야함

특정 단계 이후에 의견을 요청하는지 확인

Claude Projects

클로드의 프로젝트 기능

의미1

GPTs가 custom GPT라고 불리는 것처럼, 동작 기능에 대한 정의를 사용

의미2

여러 GPTs를 사용하는 것처럼, Projects에서 각각의 역할을 부여하고, 그 결과를 리턴 받아 재귀적 응답 사용

- 찾고 있음... 이게 안나오네...

프로젝트 프로세스

Claude의 프로젝트를 구성하고 결과를 얻는 과정을 단계별로 설명해드리겠습니다:

1. 프로젝트 생성

- claude.ai 웹사이트에서 'Projects' 섹션으로 이동
- 우측 상단의 'Create New Project' 클릭
- 프로젝트 이름과 목적 입력
- 프로젝트 생성 버튼 클릭

2. 커스텀 지시사항 설정

 - 프로젝트의 'Custom Instructions' 섹션으로 이동
 - 다음 요소들을 포함하여 지시사항 작성:
 - 프로젝트의 주요 목적
 - 수행할 작업의 단계별 프로세스
 - 필요한 피드백 루프
 - 결과물의 형식과 스타일
 - 지시사항 저장

3. 프롬프트 시퀀스 구현

 1단계: 초기 입력 받기
 - 사용자로부터 필요한 기본 정보 요청
 - 입력 내용 확인 및 요약

 2단계: 작업 진행
 - 단계별 작업 수행
 - 각 단계마다 피드백 요청
 - 필요시 수정 및 조정

 3단계: 결과물 생성
 - 최종 결과물 제시
 - 품질 확인 및 피드백
 - 필요시 수정 사항 반영

4. 테스트 및 최적화

- 샘플 데이터로 프로세스 테스트
- 피드백 루프 작동 확인
- 결과물 품질 평가
- 필요한 경우 지시사항 수정

5. 실제 사용

- 프로젝트에 실제 데이터/요청 입력
- 프로세스에 따라 단계별 진행
- 피드백 제공하며 결과물 조정
- 최종 결과물 확인 및 저장

6. 결과물 관리

- 생성된 결과물 저장
- 필요시 추가 수정 요청
- 프로젝트 재사용 또는 개선

프로젝트 사용 시 주의사항:

- 명확한 목표와 요구사항 설정
- 구체적인 피드백 제공
- 단계별 결과물 확인
- 일관된 품질 유지를 위한 기준 설정

이러한 구조적 접근을 통해 일관되고 품질 높은 결과물을 얻을 수 있습니다.

개략적 claude 사용법

Claude 사용법 기준설명

이거 직접 해보기 프로젝트 만들기, 순서 instruction 부분

Custom instructions about Claude projects

Custom instructions are specific guidelines for AI language models like Claude to tailor their behaviour, output, and capabilities for particular tasks or projects. These instructions serve as a way to “program” the AI, ensuring it responds in a manner that aligns with the user’s goals and project requirements.

Best practices for Format and Syntax

When crafting custom instructions for Claude projects, consider the following best practices:

1. Use Clear and Concise Language Write instructions that are easy to understand and leave no room for ambiguity.

2. Organize with Headers Use markdown headers to structure your instructions logically.

3. Utilize Lists Emply numbered or bulleted lists for step-by-step processes logically.

4. Specify Desired Output Format Clearly state how you want the information presented. (e.g. as a table, list or paragraph)

5. Include Examples Provide sample inputs and outputs to illustrate your expecatations

6. Use Code Blocks Use markdown code blocks for any code-related instructions for clarity.

7. Define Scope and limitations Clearly state what the AI should and should not do.

8. Encourage Flexibility Allow the AI to use its judgement when apporpriate.

요약

명확하고 간결한 언어 사용
목차 (마크다운으로 header 생성) - 흐름
세부 목차 - 세부 내용
결과 예상
예시 포함
코드도 포함
범주, 제한 제시
직접 판단 여유 주기

Example: Custom Instructions for a Project Management Web App.

Custom Instruction - 한글이 잘 안된다고 하는데... 테스트 해볼 것

# Custom Instructions for Project Management Web App.

## Role and Purpose
You are assisting in the development of a project management web application. your primary function is to provide guidance, code snippets, and explanatiuons related to this project.

## General Behavior
- Prioritize clarity and efficiency in your responses.
- When providing code, use appropriate syntax highlighting.
- If unsure about a specific reqirement, ask for clarification before proceeding

## Technical Specifications
- Frontend: React.js with TypeScript
- Backend: Node.js with Express
- Database: MongoDB
- State Management: Redux
- UI Framework: Material-UI

## Key Features to Implement
1. User Authentication
2. Project Creation and Management
3. Task Assignment and Tracking
4. Team Collabortion Tools
5. Gantt Chart for Project Timeline
6. Dashboard with Project Analytics

## Code Style and Best Practices
- Follow React Hooks paradigm for functional components.
- Implement proper error handling and input validation.
- Write clean, modular, and well-commented code.
- Adhere to TypeScript best practices for type safety.

## Output Preferences
- When providing code snippets, include brief explanations of the code's functionality.
- For complex features, break down the implementation into step-by-step instructions.
- Suggest testing stratagies for critical components.

## Limitations
- Do not provide complete application code: focus on specific components or functions as requested.
- Avoid discussing deployment strategies or DevOps practices unless explicily asked.

## Additional Notes
- Be prepared to explain concepts related to state management, API integration, and database schema design.
- Offer suggestions for performance optimization and scalability when relevant.

This covers the project's technical stack, key features, coding standards, and output preferences, giving Claude a clear framework for providing relevant and helpful assistance.

클로드 사용자 지시

Using Clear and Concise Language in AI Instructions

Enhancing AI Communication Effectiveness

When workign with AImodels like Claude, the clarity of your instructions can significantly impact the success of your project. Clear and concise language ensures that the AI understands your reqrirement precisely, leading to more accurate and useful outpouts.

Why clear and concise language matters

- Reduces Misinterpretation: Ambiguous instructions can lead to unexpected or incorrect results.
- Save Time: Clear instructions mean fewer iterations and revisions.
- Improves Consistency: Well-defined instructions produce more consistent outputs across muliple runs.
- Enhances Efficiency: AI models can process and act on clear instructions more quickly.

Tips for writing clear and concise instructions

Use Simple Words: Avoid jargon or complex terminology unless necessary.
One Idea per Sentence: instead of vague requests, provide detailed instructions.
Acitive Voice: Use active voice for more direct and clear instruction.
Avoid Ambiguity: Clarify an terms that could have multiple interpretations.
Quantify When Possible: Use numbers and specific measurements where applicable.

Examples

Example 1: Data Analysis

Unclear: "Look at the sales data and tell me what's interesting."

Clear: "Analyze the monthly sale data from the past year. Identify the top 3 performing products, calculate the average sale value, and highlight any months where sales dropped by more than 10% compared to the previous month."

Example 2: Content Creation

Unclear: "Write somthing about healthy eating."

Clear: "Write 500-word bold post about the bernefits of a Mediterranean diet. Include at least 3 key health benefints, 4 staple foods of this diet, and 2 simple recipes. Use subheadings to organize the content."

Example 3: Image Editing

Unclear: "Make the picture look nicer."

Clear: "Adjust the imaage as follows: Increase brightness by 15%, enhance the contrast by 10%, apply a slight warm color filter(RGB values:255, 240, 220 at 20% opacity), and sharpen the overall image by 25%"

Example 4: Code Optimization

Unclear: "Make this code run faster."

Clear: "Optimize the given Python functions to reduce its execution time. Focus on minimizing nested loops, replacing inefficient data structures with more appropriate ones, and utilizing built-in functions where possible. Aim for a 30% reduction in processing time for an input size of 10,000 elements."

간결하고 정확한 표현

Organizing AI Instructions With Headers

Structuring for clarity and comprehension.

Organization is key when providing complex instructions to AI models. Effectively using headers can significantly improve the clarity and structure of your instructions, making them easier for both humans and AI to follow and understand.

Benefits of Using Headers

- Improved Readability: Headers break up large blocks of text, making insturctions more digestible.
- Clear Structure: They provide a logical flow to your insturctions guiding the AI through different sections.
- Easy Navigation: Headers allow quick document scanning to find specific information
- Enhanced Understanding: They help the AI model to categorize better and process differnet parts of the instructions.

Best Practices for Using Headers

. Use Hierarchy: Employ different levels of headers (H2, H3, H4) to show the relationship between sections.
. Be descriptive: Use clear, concise language in your headers that accurately describes the following content.
. Maintain Consistency: Use similar phrasing and grammatical structures across your headers.
. Keep It Short: Headers should be brief, ideally no more than 6~8 words.
. Use Keywords: Includie important keywords in your headers to improve searchability.

Examples of Effective Header Use

Example 1: Writing a Research Paper

## Introduction
### Background Information
### Thesis Satement

## Literature Review
### Current State of Research
### Gaps in Existing Studies

## Methodology
### Data Collections
### Analysis Techniques

## Results
### Key Findings
### Statistical Analysis

## Discussion
### Interpretation of Results
### Implications for the Field

## Conclusion
### Summary of Findings
### Future Research Directions

Example 2: Developing a Mobile App

 
## Project Overview
### App Purpose and Target audience
### key Features

## Design Phase
### User Interfface Mockups
### User Experience Flow

## Development
### Frontend Development
#### UI Implementation
#### State Management
### Backend Development
#### API Design
#### Database Structure

## Testing
### Unit Testing
### Integration Testing
### User Acceptance Testing

## Deployment
### App Store Submission
### Marketing Strategy

By organizing your AI instructions with clear, descriptive headers, you create a roadmap that guides the AI through complex tasks.

'잘 정의된 목차'

Utilizing Lists in AI Instructions

The Power of Structured Information

When crafting instructions for AI models, incorporating lists can significantly enhance clarity and organization.Lists are powerful tools for presenting information in a structured, easy-to-digest format, making your instructions more effective and easier for the AI to process.

Why Use Lists in AI Instructions?
- Clarity: Lists break down complex information into manageable chunks.
- Organization: They provide a clear structure for step-by-step processes or related points.
- Readability: Lists are easier to scan and understand quickly than long paragraphs.
- Prioritization: Numbered lists can indicate order of importance or sequence of steps.
- Completeness: Lists help ensure all necessary points are covered without omission.

Types of Lists and When to Use Them

1. Bulleted Lists: Use for unordered items or points of equal importance.

Ideal for features, characteristics, or options
Good for presenting multiple examples

2. Numbered Lists: Use for sequential steps or prioritized items.

Perfect for step-by-step instructions
Useful for ranking items by importance

3. Checklist: Use for tasks that need to be completed or verified.

Excellent for quality assurance processes
Helpful for project requirements or criteria

Best Practices for Using Lists

- Keep items parallel: Start each item with the same part of speech (e.g., all verbs or all nouns).
- Be concise: Keep list items brief and to the point.
- Use appropriate punctuation: End each item with a period if it’s a complete sentence; otherwise, no punctuation is needed.
- Limit list length: Aim for 5-9 items per list for optimal readability.
- Use sub-lists when necessary: For complex points, consider using nested lists.

Examples of Effective List Usage in AI Instructions

Example 1: Data Analysis Task

Analyze the provided sales data and create a report with the following elements:

1. Executive Summary

Overall sales trend
Top-performing product category
Key findings

2. Sales Breakdown

Monthly sales figures
Year-over-year comparison
Sales by region

3. Product Analysis

Top 5 products by revenue
Bottom 5 products by revenue
Product category performance

4. Customer Insights

Customer demographics
Purchase frequency analysis
Customer lifetime value calculation

5. Recommendations

Areas for improvement
Potential growth opportunities
Suggested action items

Example 2: Content Creation Guidelines

When creating blog posts, adhere to the following guidelines:

Structure:

Engaging introduction
Clear thesis statement
3-5 main points with supporting evidence
Compelling conclusion
Call-to-action

Style:

Use active voice
Keep sentences concise (15-20 words on average)
Vary paragraph length (2-4 sentences)
Incorporate relevant examples and analogies

Formatting:

Use headers and subheaders (H2, H3, H4)
Include bulleted or numbered lists where appropriate
Add relevant images or infographics
Use block quotes for important statements

SEO Considerations:

Include the target keyword in the title, first paragraph, and at least one header
Optimize meta description
Use internal and external links
Aim for a minimum of 1,200 words

By effectively utilizing lists in your AI instructions, you can create clear, structured guidelines that are easy for the AI to follow.

리스트 사용 이점

Specifying Desired Output Format in AI Instructions

Tailoring AI Responses for Maximum Utility

When working with AI models, clearly specifying the desired output format is crucial for obtaining results that meet your needs. By providing explicit instructions about how you want the information presented, you can ensure that the AI’s response is accurate, immediately useful, and easy to integrate into your workflow.

Common Output Formats

Paragraphs: For narrative explanations or detailed descriptions.
Bullet Points: For concise lists of items or key points.
Numbered Lists: For step-by-step instructions or prioritized information.
Tables: For organized presentation of data or comparisons.
JSON: For structured data that needs to be parsed by software.
CSV: This is for tabular data that can be easily imported into spreadsheets.
Markdown: This is for formatted text that can be easily converted to other formats.

Best Practices for Specifying Output Format

- Be Explicit: Clearly state the format you want, e.g., “Present the information in a table with three  -  Date, Event, and Outcome.”
- Provide Examples: If possible, give a sample of the desired format to guide the AI.
- Specify Details: Include information about headers, column names, or specific formatting requirements.
- Consider the End Use: Consider how the output will be used and specify a format that aligns with that purpose.
- Be Consistent: Use similar format specifications across related tasks for uniformity.

Examples of Format Specifications

Example 1: Data Analysis Report

Generate a sales analysis report with the following sections:

1. Executive Summary (2-3 paragraphs)
2. Monthly Sales Breakdown (table format with columns: Month, Revenue, % Change)
3. Top 5 Products (bullet point list with product name and total sales)
4. Regional Performance (bar chart description in markdown format)
5. Recommendations (numbered list with 3-5 actionable items)

Ensure each section has a clear heading and subheadings where appropriate.

Example 2: Technical Documentation

Create API documentation in the following format:
# API Endpoint Name

## Description
[1-2 sentences describing the endpoint's purpose]

## Request Format
- Method: [GET/POST/PUT/DELETE]
- URL: `[endpoint URL]`

## Parameters
| Name | Type | Required | Description |
|------|------|----------|-------------|
| [param1] | [string/int/etc] | [Yes/No] | [Brief description] |
| [param2] | [string/int/etc] | [Yes/No] | [Brief description] |

## Response Formatjson
{
  "key1": "value1",
  "key2": "value2"
}## Error Codes
- 400: Bad Request
- 401: Unauthorized
- 404: Not Found
- 500: Internal Server Error

## Example Usage
[Provide a code snippet demonstrating how to use the API]

Repeat this structure for each API endpoint in the documentation.

결과물 형태 제시

Including Examples in AI Instructions

Illuminating Expectations through Concrete Illustrations

Examples serve as concrete illustrations of your expectations, helping the AI better understand and execute your instructions.

The Value of Examples in AI Instructions

# Clarity: Examples provide tangible representations of abstract concepts.
# Context: They offer additional context that text instructions alone might not convey.
# Precision: Examples help refine the AI’s understanding of specific requirements.
# Inspiration: They can guide the AI towards creative solutions within the desired framework.
# Error Reduction: Clear examples minimize misinterpretations and errors in AI outputs.

Best Practices for Including Examples

# Relevance: Ensure examples are directly related to the task at hand.
# Diversity: Provide a range of examples to cover different aspects or variations of the task.
# Simplicity: Start with simple examples before introducing more complex ones.
# Contrast: When appropriate, include both positive and negative examples to clarify boundaries.
# Format Consistency: Present examples in a format that matches your desired output.
# Explanation: When necessary, briefly explain why an example is good or relevant.
# Real-world Application: Use examples that reflect real-world scenarios when possible.

Types of Examples

# Input-Output Pairs: Show both the input given and the expected output.
# Before-After Scenarios: Demonstrate transformations or changes.
# Sample Excerpts: Provide text, code, or data snippets that illustrate the desired style or format.
# Visual Examples: Use diagrams, charts, or descriptions of visual elements for design-related tasks.
# Analogies: Draw parallels to familiar concepts to explain new or complex ideas.

Example Scenarios

Scenario 1: Writing a Product Description

Task: Write a compelling product description for a new smartphone.

Example:
"Experience the future of mobile technology with the XYZ UltraPhone. This sleek device boasts a stunning 6.5-inch OLED display that brings your content to life with vibrant colors and deep blacks. Capture life's moments in extraordinary detail with our advanced triple-lens camera system, featuring a 108MP main sensor. Powered by the latest A15 chip, the UltraPhone delivers lightning-fast performance whether you're multitasking, gaming, or streaming. With an all-day battery life and fast charging capability, you'll never be left stranded. The UltraPhone isn't just a smartphone; it's your gateway to a world of possibilities."

Key Elements to Note:
- Engaging opening line
- Specific features (screen size, display type, camera specs, processor)
- Benefits of each feature
- Emotional appeal in the closing statement

Scenario 2: Data Analysis Task

Task: Analyze a dataset and provide insights.

Example Input:Date,Product,Sales
2023-01-01,Widget A,150
2023-01-01,Widget B,200
2023-01-02,Widget A,175
2023-01-02,Widget B,180
2023-01-03,Widget A,160
2023-01-03,Widget B,220

Example Output:
1. Sales Summary:
   - Total sales for the period: 1,085 units
   - Average daily sales: 361.67 units

2. Product Performance:
   - Widget A total sales: 485 units
   - Widget B total sales: 600 units
   - Widget B outperformed Widget A by 23.71%

3. Trend Analysis:
   - Widget A shows a slight upward trend (150 -> 175 -> 160)
   - Widget B shows consistent growth (200 -> 180 -> 220)

4. Recommendations:
   - Investigate the factors contributing to Widget B's superior performance
   - Develop strategies to boost Widget A sales, possibly learning from Widget B's success
   - Continue monitoring daily sales to identify any emerging patterns

Key Elements to Note:
- Clear sections for different types of analysis
- Use of both exact figures and percentages
- Identification of trends
- Actionable recommendations based on the data

By including well-crafted examples in your AI instructions, you provide the AI with clear guidelines and expectations.

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Using Code Blocks in AI Instructions

Enhancing Clarity and Precision in Technical Communication

When working with AI on programming tasks or technical instructions, using code blocks is essential for clear and unambiguous communication. Code blocks help separate code from regular text, preserve formatting, and ensure that the AI interprets your instructions correctly.

Benefits of Using Code Blocks

# Clarity: Clearly distinguishes code from surrounding text.
# Preservation of Structure: Maintains indentation and line breaks crucial for code readability.
# Syntax Highlighting: Many platforms provide language-specific highlighting, enhancing readability.
# Error Prevention: Reduces the risk of AI misinterpreting code as regular text or vice versa.
# Ease of Copy-Pasting: Facilitates easy transfer of code snippets for testing or implementation.

How to Use Code Blocks

# Markdown Format: Use triple backticks (“`) to enclose your code.
# Specify Language: After the opening backticks, specify the programming language for proper highlighting.
# Indentation: Maintain proper indentation within the code block for readability.
# Complete Snippets: Provide complete, runnable code snippets when possible.
# Comments: Use in-code comments to explain complex parts or provide context.

Best Practices for Using Code Blocks

# Context: Provide explanatory text before and/or after code blocks.
# Conciseness: Include only relevant code parts to maintain focus.
# Consistency: Use consistent styling and naming conventions across code blocks.
# Error Handling: Include error handling in your code examples when relevant.
# Multiple Examples: Provide multiple code blocks for complex concepts or different scenarios.

Examples of Effective Code Block Usage

Example 1: Python Function Definition

Here’s how you might define a simple function to calculate the factorial of a number:

def factorial(n):
    if n == 0 or n == 1:
        return 1
    else:
        return n * factorial(n - 1)

# Example usage
result = factorial(5)
print(f"The factorial of 5 is: {result}")

This code block clearly shows the function definition, includes a recursive implementation, and demonstrates how to use the function.

Example 2: HTML Structure with CSS

Here’s an example of how to structure a simple HTML page with embedded CSS:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>My Simple Page</title>
    <style>
        body {
            font-family: Arial, sans-serif;
            line-height: 1.6;
            margin: 0;
            padding: 20px;
        }
        .container {
            max-width: 800px;
            margin: 0 auto;
        }
        h1 {
            color: #333;
        }
    </style>
</head>
<body>
    <div class="container">
        <h1>Welcome to My Page</h1>
        <p>This is a simple HTML page with some basic styling.</p>
    </div>
</body>
</html>

This code block demonstrates a complete HTML structure with embedded CSS, showing how different elements work together.

Example 3: JavaScript API Request

Here’s an example of how to make an API request using JavaScript’s fetch function:

async function fetchUserData(userId) {
    try {
        const response = await fetch(`https://api.example.com/users/${userId}`);
        if (!response.ok) {
            throw new Error(`HTTP error! status: ${response.status}`);
        }
        const data = await response.json();
        console.log('User data:', data);
        return data;
    } catch (error) {
        console.error('There was a problem fetching the user data:', error);
    }
}

// Usage
fetchUserData(123)
    .then(userData => {
        // Do something with the user data
    })
    .catch(error => {
        // Handle any errors
    });

This code block shows how to structure an asynchronous function for API requests, including error handling and usage example.

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Defining Scope and Limitations in AI Instructions

Setting Clear Boundaries for Effective AI Interaction

When working with AI models, it’s crucial to clearly define the scope of the task and any applicable limitations. This practice helps ensure that the AI’s output aligns with your expectations and requirements while also preventing misunderstandings or overreach in the AI’s responses.

Importance of Defining Scope and Limitations

# Focus: Helps the AI concentrate on the specific task at hand.
# Accuracy: Improves the relevance and precision of the AI’s output.
# Efficiency: Reduces time spent on irrelevant or out-of-scope information.
# Expectations Management: Aligns the AI’s capabilities with user expectations.
# Ethical Considerations: Prevents the AI from venturing into potentially problematic areas.

Key Elements in Defining Scope and Limitations

# Task Description: Clearly state what the AI should do.
# Context: Provide relevant background information.
# Boundaries: Specify what should not be included or considered.
# Data Sources: Indicate what information the AI should use or ignore.
# Output Format: Define the desired format and structure of the response.
# Time or Resource Constraints: Mention any limitations on processing time or data usage.
# Ethical Guidelines: Outline any moral considerations or restrictions.

Best Practices for Defining Scope and Limitations

# Be Specific: Use clear, unambiguous language to describe the task and its boundaries.
# Prioritize: Indicate the most important aspects of the task.
# Use Examples: Provide examples of what’s in-scope and out-of-scope when possible.
# Consider Edge Cases: Anticipate and address potential grey areas or exceptions.
# Iterative Refinement: Be prepared to adjust scope and limitations based on initial results.

Examples of Defining Scope and Limitations

Example 1: Content Creation Task

Task: Write a blog post about the benefits of exercise.

Scope:
- Focus on general physical and mental health benefits
- Include at least 3 types of exercise (e.g., cardio, strength training, flexibility)
- Target audience: adults aged 25-45 with sedentary jobs

Limitations:
- Do not discuss specific exercise routines or techniques
- Avoid mentioning branded fitness programs or equipment
- Do not make claims about treating or curing medical conditions
- Keep the post between 800-1000 words

Additional Guidelines:
- Use layman's terms, avoiding complex medical jargon
- Include 2-3 reliable sources for any statistical claims
- Conclude with a call-to-action encouraging readers to start exercising

Example 2: Data Analysis Task

Task: Analyze customer purchase data to identify trends and provide recommendations.

Scope:
- Use the provided CSV file containing 12 months of sales data
- Focus on identifying patterns in product categories, seasonal trends, and customer demographics
- Provide insights on top-selling products and underperforming areas

Limitations:
- Only use the data provided in the CSV file; do not incorporate external data sources
- Do not include any personally identifiable information about customers
- Limit the analysis to the past 12 months; do not extrapolate future trends

Output Requirements:
- Produce a summary report (max 2 pages) with key findings
- Include up to 3 data visualizations (charts or graphs)
- Provide a list of 3-5 actionable recommendations based on the analysis

Ethical Considerations:
- Ensure all insights and recommendations comply with data privacy regulations
- Avoid any analysis that could lead to discriminatory practices

Example 3: Code Review Task

Task: Review the provided Python script for a web scraping tool.

Scope:
- Check for code efficiency and adherence to PEP 8 style guidelines
- Identify any security vulnerabilities, particularly in handling user inputs
- Suggest improvements for error handling and logging

Limitations:
- Focus on the Python code only; do not review any associated HTML or JavaScript
- Limit suggestions to those that don't require changing the overall structure of the script
- Do not add new features; focus on improving existing functionality

Specific Areas to Address:
1. Input validation
2. Error handling and exception management
3. Use of appropriate libraries and functions
4. Code comments and documentation
5. Performance optimization for large datasets

Output Format:
- Provide a bullet-point list of issues found, categorized by severity (Critical, Major, Minor)
- For each issue, include:
  * The relevant line number(s)
  * A brief description of the problem
  * A suggested fix or improvement
- Conclude with a summary of the script's overall quality and main areas for improvement

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Encouraging Flexibility in AI Instructions

Balancing Structure with Adaptability for Optimal AI Performance

Incorporating a degree of flexibility can lead to more creative and comprehensive outputs. Encouraging flexibility allows the AI to leverage its full capabilities and potentially provide insights or solutions you might not have considered.

Benefits of Encouraging Flexibility

#Creative Solutions: Allows the AI to explore innovative approaches to problems.
#Comprehensive Responses: Enables the AI to cover aspects you might have overlooked.
#Adaptability: Helps the AI adjust to nuances or unexpected elements in the task.
#Learning Opportunity: Provides chances to discover new perspectives or methodologies.
#Improved Problem-Solving: Encourages the AI to think “outside the box” when appropriate.

Strategies for Encouraging Flexibility

#Open-Ended Questions: Use questions that invite exploration and multiple approaches.
#Suggest Alternatives: Explicitly state that the AI can suggest alternative methods if appropriate.
#Provide Guidelines, Not Rules: Frame instructions as guidelines that allow for interpretation.
#Encourage Explanations: Ask the AI to explain its reasoning or provide multiple options.
#Balance Structure and Freedom: Combine specific requirements with areas for creative input.

Best Practices for Balancing Flexibility and Structure

#Clear Core Objectives: Maintain clarity on the essential goals of the task.
#Define Boundaries: Specify areas where flexibility is encouraged and where it isn’t.
#Invite Creativity: Explicitly encourage the AI to be creative within defined parameters.
#Request Multiple Approaches: Ask for various ways to solve a problem or complete a task.
#Iterative Refinement: Use initial flexible outputs to refine and focus subsequent instructions.

Examples of Encouraging Flexibility in AI Instructions

Example 1: Creative Writing Task

Task: Write a short story about time travel.

Flexible Instructions:
1. Core Requirements:
   - The story should be between 500-1000 words.
   - It must involve time travel as a central element.
   - Include at least one character from the past and one from the future.

2. Creative Freedom:
   - You have flexibility in choosing the time periods, the method of time travel, and the plot.
   - Feel free to explore various genres (e.g., sci-fi, romance, mystery) as you see fit.
   - You're encouraged to incorporate unexpected twists or unique perspectives on time travel.

3. Additional Guidance:
   - Consider exploring themes such as causality, paradoxes, or the ethics of altering the past/future.
   - You may experiment with narrative structure if it enhances the time travel concept.

4. Output:
   - Provide the complete short story.
   - Additionally, briefly explain your creative choices and how they relate to the time travel theme.

Remember, while meeting the core requirements, you have the freedom to surprise me with your creative approach to this task.

Example 2: Data Visualization Task

Task: Create a data visualization plan for a company's annual sales report.

Flexible Instructions:
1. Essential Elements:
   - Visualize total annual sales, sales by product category, and sales trends over time.
   - Include at least one comparison to the previous year's performance.

2. Creative Aspects:
   - You have flexibility in choosing the types of charts or graphs for each data set.
   - Feel free to suggest interactive elements or novel visualization techniques.
   - Consider unconventional ways to represent the data while maintaining clarity.

3. Presentation:
   - Propose a color scheme and overall design theme.
   - You may suggest incorporating company branding elements, but this is optional.

4. Additional Considerations:
   - Think about how to effectively communicate the data to both technical and non-technical audiences.
   - You're encouraged to propose additional data points or comparisons that could provide valuable insights.

5. Output:
   - Describe your visualization plan, including the types of charts/graphs and your rationale.
   - Explain any unique or creative elements you've incorporated.
   - If possible, provide rough sketches or descriptions of any novel visualization ideas.

While addressing the core requirements, feel free to think creatively about how to make this sales report visually engaging and informative.

Example 3: Problem-Solving in Software Development

Task: Propose a solution for optimizing the performance of a slow-loading web application.

Flexible Instructions:
1. Context:
   - The web application is a content-heavy site with numerous images and dynamic elements.
   - Current load times exceed 10 seconds on average.

2. Core Objectives:
   - Reduce load time to under 3 seconds.
   - Maintain or improve user experience.
   - Ensure compatibility across major browsers and devices.

3. Areas for Flexible Thinking:
   - You have freedom in suggesting both front-end and back-end optimizations.
   - Consider various technologies or methodologies that could be applied.
   - Feel free to propose unconventional solutions if you believe they would be effective.

4. Considerations:
   - Think about both immediate fixes and long-term scalability.
   - Consider the trade-offs between performance, cost, and development time.
   - You may suggest changes to the current architecture if justified.

5. Output Required:
   - Provide a detailed outline of your proposed solution(s).
   - Explain the rationale behind your choices.
   - If applicable, offer multiple approaches with pros and cons for each.
   - Include any assumptions you've made and areas that might need further investigation.

While addressing the core performance issue, don't hesitate to think outside the box. Your unique perspective and creative problem-solving are encouraged.

By encouraging flexibility in your AI instructions, you open the door to innovative solutions and comprehensive analyses. This approach allows the AI to utilize its full range of capabilities while still working within the necessary task parameters. The key is to balance clear objectives with room for creativity and alternative approaches, potentially leading to outcomes that exceed your initial expectations.

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Advanced Tips

응답 태그를 추가하기

Projects에서 Custom instructions에 추가하는 것

When writing a response, first decide whether you want to write a short response or a long response. Note your decision inside <antThinking> </antThinking> tags.

래딧설명(회사링크 막힘)

Artifact 유지 방법 - 프롬프트

프로젝트에서 Claude Artifacts가 유일한 고유한 파일 배포를 사용하도록 유도하는 사용자 가이드 지침

- 프로젝트에 추가'를 클릭하면 XML 태그 title의 속성이 속성이 <AntArtifact>됩니다.file_name
- Claude는 사람이 읽을 수 있는 형식 title(예: "새로운 기능이 있는 수정된 웹 페이지")을 기본적으로 예약했기 때문에 파일 이름이 변경되는 경향이 있습니다.
- 이러한 방식으로 파일 이름이 사용되는 경우 문서에 단일 파일 처리("프로젝트 정보")를 보관하는 것이 더 적합합니다.

When creating a new Artifact, decide if you need to update an existing Artifact in the Project's documents or create a new one. **Updating an Artifact:** Always use its original identifier. For example, if the Artifact's identifier is "index" and its type is "html," keep using "index" and do not change it to something like "modified-index. Use the unsuffixed file stem (e.g., "index" not "index.html") as the identifier. Also, use this identifier as the title; don't change it to something like "Modified Index Page". This ensures the Artifact is properly overwritten in the project. **Creating a New Artifact:** Ensure you do not use an existing identifier or title. Check that the file stem and type do not clash with an existing one. Different file types can use the same stem (e.g., "index.css" and "index.html" are distinct). In both cases (updating/creating Artifacts), some rules should always be followed. The title and identifier must always be an exact match. Never combine multiple files into a single Artifact to avoid invalid Project files. When creating components for use in other files, make the component first and then reference its location in the Artifact it is to be transcluded into, rather than repeat the component content inline. Review the existing project structure and assets to understand their purposes and relationships. Assume new visual assets or files are distinct unless stated otherwise, and pay attention to the context provided in the request, including the intended use and placement of new assets.

Artifact 고정

참고 사항

Youtube Claude project사용법, 11분20초~

Claude에서 Assigning role, 페르소나 부여

Custom Instructions for Claude Projects: A Comprehensive Guide

Flow 디자인, 구독 $20