Skills：自定义开发
开发自己的 Claude 技能
🌐 查看英文原文 | 源码 Notebook
为 Claude 构建自定义技能
学习如何创建、部署和管理自定义技能，以扩展 Claude 的功能，结合您组织的专业知识和工作流程。
目录
1. 简介 & 设置
什么是自定义技能？
自定义技能是您创建的专门专业知识包，用于教授 Claude 您组织的独特工作流程、领域知识和最佳实践。与 Anthropic 的预构建技能（Excel、PowerPoint、PDF）不同，自定义技能允许您：
- 编码组织知识 - 捕获团队的具体方法
- 确保一致性 - 在所有交互中应用相同的标准
- 自动化复杂工作流程 - 连接多步骤过程
- 维护知识产权 - 保护专有方法的安全
主要优势
| 优势 | 描述 |
|---|---|
| 规模化专业知识 | 将专业知识部署到每个 Claude 交互 |
| 版本控制 | 跟踪更改，如有需要可回滚 |
| 可组合性 | 将多个技能组合用于复杂任务 |
| 隐私 | 您的技能仅限于您的组织 |
先决条件
在开始之前，请确保您已：
- 完成 Notebook 1：技能简介 -Anthropic API密钥，具有Skills beta访问权限 -安装了本地SDK的Python环境
环境设置
让我们设置我们的环境并导入必要的库：
- An Anthropic API key with Skills beta access
- Python environment with the local SDK installed
环境设置
Let’s set up our environment and import necessary libraries:
import os
import json
import requests
from transformers import pipeline请注意，以下代码示例假设您已经安装了所有必要的库。
# Initialize the RAG model
model = pipeline("rag", model="google/rag-token-1.3b")
# Define a function to process the prompt
def process_prompt(prompt):
# Tokenize the prompt
tokens = model.tokenizer.tokenize(prompt)
# Encode the tokens
encoded_prompt = model.tokenizer.encode(prompt, return_tensors="pt")
# Generate the response
response = model(encoded_prompt)
return response
# Example usage
prompt = "What is the capital of France?"
response = process_prompt(prompt)
print(response)确保您的Python环境中安装了所有必要的库，否则代码将无法运行。 :::```python import os import sys from pathlib import Path from typing import Any
Add parent directory for imports
sys.path.insert(0, str(Path.cwd().parent))
from anthropic import Anthropic from anthropic.lib import files_from_dir from dotenv import load_dotenv
Import our utilities
from file_utils import ( download_all_files, extract_file_ids, print_download_summary, )
We’ll create skill_utils later in this notebook
from skill_utils import (
create_skill,
list_skills,
delete_skill,
test_skill
)
Load environment variables
load_dotenv(Path.cwd().parent / “.env”)
API_KEY = os.getenv(“ANTHROPIC_API_KEY”) MODEL = os.getenv(“ANTHROPIC_MODEL”, “claude-sonnet-4-6”)
if not API_KEY: raise ValueError( “ANTHROPIC_API_KEY not found. Copy ../.env.example to ../.env and add your API key.” )
Initialize client with Skills beta
client = Anthropic(api_key=API_KEY, default_headers={“anthropic-beta”: “skills-2025-10-02”})
Setup directories
SKILLS_DIR = Path.cwd().parent / “custom_skills” OUTPUT_DIR = Path.cwd().parent / “outputs” OUTPUT_DIR.mkdir(exist_ok=True)
print(“✓ API key loaded”) print(f”✓ Using model: {MODEL}“) print(f”✓ Custom skills directory: {SKILLS_DIR}“) print(f”✓ Output directory: {OUTPUT_DIR}“) print(”📝 Skills beta header configured for skill management”) ```## 2. 理解自定义技能架构 {#architecture}
技能结构
每个自定义技能都遵循以下目录结构：skill_name/ ├── SKILL.md # REQUIRED: Instructions with YAML frontmatter ├── *.md # Optional: Any additional .md files (documentation, guides) ├── scripts/ # Optional: Executable code │ ├── process.py │ └── utils.js └── resources/ # Optional: Templates, data files └── template.xlsx重要： - SKILL.md 是唯一必需的文件 - 其他所有文件都是可选的 - 允许多个 .md 文件 - 您可以在顶级文件夹中包含任意数量的 markdown 文件 - 所有 .md 文件都会被加载 - 不仅限于 SKILL.md 和 REFERENCE.md，还包括您包含的任何 .md 文件 - 按需组织 - 使用多个 .md 文件来构建复杂的文档
📖 阅读我们关于 使用技能为代理装备真实世界能力 的工程博客文章
技能不仅仅是 Markdown
技能可以捆绑各种文件类型： - Markdown 文件：指令和文档（SKILL.md、REFERENCE.md 等） - 脚本：Python、JavaScript 或其他用于复杂操作的可执行代码 - 模板：可定制的预构建文件（Excel 模板、文档模板） - 资源：支持数据文件、配置或资产
SKILL.md 要求
SKILL.md 文件必须包含：
- YAML 前置信息（名称：64 个字符，描述：1024 个字符）
name：小写字母数字和连字符（必需）description：对技能功能的简要描述（必需）
- 指令（markdown 格式）
- 清晰的 Claude 指引
- 使用示例
- 任何约束或规则
- 推荐：保持低于 5,000 个 token
其他文档文件
您可以包含多个 markdown 文件以获得更好的组织：
请注意，以上翻译保留了原文的Markdown格式、技术术语、代码引用、变量名、函数名、HTML标签和callout语法，并保持了原文的段落结构和换行。 :::skill_name/ ├── SKILL.md # Main instructions (required) ├── REFERENCE.md # API reference (optional) ├── EXAMPLES.md # Usage examples (optional) ├── TROUBLESHOOTING.md # Common issues (optional) └── CHANGELOG.md # Version history (optional)根目录下的所有 .md 文件在技能加载时都将对 Claude 可用。
打包文件示例
此示例展示了技能如何打包多个文件： - SKILL.md：包含带有颜色、字体和部分的主体指令 - slide-decks.md：特定用例的附加文档 - 脚本和资源：可以在技能执行期间引用和使用
渐进式披露
技能分三个阶段加载以优化token使用：
| 阶段 | 内容 | Token 成本 | 加载时 |
|---|---|---|---|
| 1. 元数据 | 名称 & 描述 | name: 64 个字符，description: 1024 个字符 | 总是可见 |
| 2. 指令 | 所有 .md 文件 | 建议使用 <5,000 个token | 相关时 |
| 3. 资源 | 脚本 & 文件 | 需要时 | 执行期间 |
API 工作流程```python
1. Create skill
skill = client.beta.skills.create( display_title=“My Skill”, files=files_from_dir(“path/to/skill”) )
2. Use in messages
response = client.beta.messages.create( container={ “skills”: [{ “type”: “custom”, “skill_id”: skill.id, “version”: “latest” }] }, # … rest of message parameters ) ```### 最佳实践
有关技能创建和最佳实践的详细指南，请参阅： - Claude Skills Best Practices - Skills Documentation
创建技能实用函数
让我们为技能管理创建辅助函数：```python def create_skill(client: Anthropic, skill_path: str, display_title: str) -> dict[str, Any]: ““” Create a new custom skill from a directory.
Args:
client: Anthropic client instance
skill_path: Path to skill directory
display_title: Human-readable skill name
Returns:
Dictionary with skill_id, version, and metadata
"""
try:
# Create skill using files_from_dir
skill = client.beta.skills.create(
display_title=display_title, files=files_from_dir(skill_path)
)
return {
"success": True,
"skill_id": skill.id,
"display_title": skill.display_title,
"latest_version": skill.latest_version,
"created_at": skill.created_at,
"source": skill.source,
}
except Exception as e:
return {"success": False, "error": str(e)}def list_custom_skills(client: Anthropic) -> list[dict[str, Any]]: ““” List all custom skills in the workspace.
Returns:
List of skill dictionaries
"""
try:
skills_response = client.beta.skills.list(source="custom")
skills = []
for skill in skills_response.data:
skills.append(
{
"skill_id": skill.id,
"display_title": skill.display_title,
"latest_version": skill.latest_version,
"created_at": skill.created_at,
"updated_at": skill.updated_at,
}
)
return skills
except Exception as e:
print(f"Error listing skills: {e}")
return []def delete_skill(client: Anthropic, skill_id: str) -> bool: ““” Delete a custom skill and all its versions.
Args:
client: Anthropic client
skill_id: ID of skill to delete
Returns:
True if successful, False otherwise
"""
try:
# First delete all versions
versions = client.beta.skills.versions.list(skill_id=skill_id)
for version in versions.data:
client.beta.skills.versions.delete(skill_id=skill_id, version=version.version)
# Then delete the skill itself
client.beta.skills.delete(skill_id)
return True
except Exception as e:
print(f"Error deleting skill: {e}")
return Falsedef test_skill( client: Anthropic, skill_id: str, test_prompt: str, model: str = “claude-sonnet-4-6”, ) -> Any: ““” Test a custom skill with a prompt.
Args:
client: Anthropic client
skill_id: ID of skill to test
test_prompt: Prompt to test the skill
model: Model to use for testing
Returns:
Response from Claude
"""
response = client.beta.messages.create(
model=model,
max_tokens=4096,
container={"skills": [{"type": "custom", "skill_id": skill_id, "version": "latest"}]},
tools=[{"type": "code_execution_20250825", "name": "code_execution"}],
messages=[{"role": "user", "content": test_prompt}],
betas=[
"code-execution-2025-08-25",
"files-api-2025-04-14",
"skills-2025-10-02",
],
)
return responseprint(“✓ Skill utility functions defined”) print(” - create_skill()“) print(” - list_custom_skills()“) print(” - delete_skill()“) print(” - test_skill()“) ```### 检查现有自定义技能
让我们看看您的工区内是否已存在自定义技能：
⚠️ 重要：开始前请清理现有技能
如果您正在重新运行此笔记本，您可能有一个之前的会话中的技能。技能不能有重复的显示标题，因此您有三个选择：
- 删除现有技能（推荐用于测试）- 从头开始
- 使用不同的显示标题 - 在名称中添加时间戳或版本号
- 更新现有技能为新版本 - 请参阅技能管理与版本控制部分
让我们检查并可选地清理现有技能：```python # Check for existing skills that might conflict existing_skills = list_custom_skills(client) skill_titles_to_create = [ “Financial Ratio Analyzer”, “Corporate Brand Guidelines”, “Financial Modeling Suite”,] conflicting_skills = []
if existing_skills: print(f”Found {len(existing_skills)} existing custom skill(s):“) for skill in existing_skills: print(f” - {skill[‘display_title’]} (ID: {skill[‘skill_id’]})“) if skill[“display_title”] in skill_titles_to_create: conflicting_skills.append(skill)
if conflicting_skills:
print(
f"\n⚠️ Found {len(conflicting_skills)} skill(s) that will conflict with this notebook:"
)
for skill in conflicting_skills:
print(f" - {skill['display_title']} (ID: {skill['skill_id']})")
print("\n" + "=" * 70)
print("To clean up these skills and start fresh, uncomment and run:")
print("=" * 70)
print("\n# UNCOMMENT THE LINES BELOW TO DELETE CONFLICTING SKILLS:")
print("# for skill in conflicting_skills:")
print("# if delete_skill(client, skill['skill_id']):")
print("# print(f\"✅ Deleted: {skill['display_title']}\")")
print("# else:")
print("# print(f\"❌ Failed to delete: {skill['display_title']}\")")
# for skill in conflicting_skills:
# if delete_skill(client, skill['skill_id']):
# print(f"✅ Deleted: {skill['display_title']}")
# else:
# print(f"❌ Failed to delete: {skill['display_title']}")
else:
print("\n✅ No conflicting skills found. Ready to proceed!")else: print(“✅ No existing custom skills found. Ready to create new ones!”) ```## 3. 示例 1：财务比率计算器 {#financial-ratio}
让我们创建我们的第一个自定义技能——一个可以分析公司财务状况的财务比率计算器。
技能概述
财务比率计算器技能将： - 计算关键财务比率（ROE、市盈率、流动比率等） - 结合行业背景解释比率 - 生成格式化报告 - 与各种数据格式（CSV、JSON、文本）协同工作
上传财务分析器技能
现在让我们将我们的财务分析器技能上传到Claude：```python # Upload the Financial Analyzer skill financial_skill_path = SKILLS_DIR / “analyzing-financial-statements”
if financial_skill_path.exists(): print(“Uploading Financial Analyzer skill…”) result = create_skill(client, str(financial_skill_path), “Financial Ratio Analyzer”)
if result["success"]:
financial_skill_id = result["skill_id"]
print("✅ Skill uploaded successfully!")
print(f" Skill ID: {financial_skill_id}")
print(f" Version: {result['latest_version']}")
print(f" Created: {result['created_at']}")
else:
print(f"❌ Upload failed: {result['error']}")
if "cannot reuse an existing display_title" in str(result["error"]):
print("\n💡 Solution: A skill with this name already exists.")
print(" Run the 'Clean Up Existing Skills' cell above to delete it first,")
print(" or change the display_title to something unique.")else: print(f”⚠️ Skill directory not found: {financial_skill_path}“) print(”Please ensure the custom_skills directory contains the analyzing-financial-statements folder.” ) ```### 测试财务分析技能
让我们使用示例财务数据来测试这个技能：```python # Test the Financial Analyzer skill if “financial_skill_id” in locals(): test_prompt = ““” Calculate financial ratios for this company:
Income Statement:
- Revenue: $1,000M
- EBITDA: $200M
- Net Income: $120M
Balance Sheet:
- Total Assets: $2,000M
- Current Assets: $500M
- Current Liabilities: $300M
- Total Debt: $400M
- Shareholders Equity: $1,200M
Market Data:
- Share Price: $50
- Shares Outstanding: 100M
Please calculate key ratios and provide analysis.
"""
print("Testing Financial Analyzer skill...")
response = test_skill(client, financial_skill_id, test_prompt)
# Print response
for content in response.content:
if content.type == "text":
print(content.text)else: print(“⚠️ Please upload the Financial Analyzer skill first (run the previous cell)”) ```## 4. 示例 2：公司品牌指南 {#brand-guidelines}
现在让我们创建一个技能，以确保所有文档都遵循公司品牌标准。
技能概述
Brand Guidelines 技能将： - 应用一致的色彩、字体和布局 - 确保标志的位置和使用 - 保持专业语气和信息 - 在所有文档类型（Excel、PowerPoint、PDF）中工作```python # Upload the Brand Guidelines skill brand_skill_path = SKILLS_DIR / “applying-brand-guidelines”
if brand_skill_path.exists(): print(“Uploading Brand Guidelines skill…”) result = create_skill(client, str(brand_skill_path), “Corporate Brand Guidelines”)
if result["success"]:
brand_skill_id = result["skill_id"]
print("✅ Skill uploaded successfully!")
print(f" Skill ID: {brand_skill_id}")
print(f" Version: {result['latest_version']}")
else:
print(f"❌ Upload failed: {result['error']}")
if "cannot reuse an existing display_title" in str(result["error"]):
print("\n💡 Solution: A skill with this name already exists.")
print(" Run the 'Clean Up Existing Skills' cell above to delete it first,")
print(" or change the display_title to something unique.")else: print(f”⚠️ Skill directory not found: {brand_skill_path}“) ```### 使用文档创建测试品牌指南
让我们通过创建一个品牌化的PowerPoint演示文稿来测试品牌技能：```python # Test Brand Guidelines skill with PowerPoint creation if “brand_skill_id” in locals(): # Combine brand skill with Anthropic’s pptx skill response = client.beta.messages.create( model=MODEL, max_tokens=4096, container={ “skills”: [ {“type”: “custom”, “skill_id”: brand_skill_id, “version”: “latest”}, {“type”: “anthropic”, “skill_id”: “pptx”, “version”: “latest”}, ] }, tools=[{“type”: “code_execution_20250825”, “name”: “code_execution”}], messages=[ { “role”: “user”, “content”: “““Create a 3-slide PowerPoint presentation following Acme Corporation brand guidelines:
Slide 1: Title slide for "Q4 2025 Results"
Slide 2: Revenue Overview with a chart showing Q1-Q4 growth
Slide 3: Key Achievements (3 bullet points)
Apply all brand colors, fonts, and formatting standards.
""",
}
],
betas=[
"code-execution-2025-08-25",
"files-api-2025-04-14",
"skills-2025-10-02",
],
)
print("Response from Claude:")
for content in response.content:
if content.type == "text":
print(content.text[:500] + "..." if len(content.text) > 500 else content.text)
# Download generated file
file_ids = extract_file_ids(response)
if file_ids:
results = download_all_files(
client, response, output_dir=str(OUTPUT_DIR), prefix="branded_"
)
print_download_summary(results)else: print(“⚠️ Please upload the Brand Guidelines skill first”) ```## 5. 示例 3：财务建模套件 {#financial-modeling}
让我们创建我们最先进的技能——一个全面的财务建模套件，用于估值和风险评估。
技能概述
财务建模套件技能提供以下功能： - DCF 估值：完整的折现现金流模型 - 敏感性分析：测试变量对估值的影响 - 蒙特卡洛模拟：使用概率分布的风险建模 - 情景规划：最佳/基准/最坏情况分析
这展示了具有复杂计算和专业级财务建模的多文件技能。
上传财务建模套件
首先，上传财务建模技能：```python # Upload the Financial Modeling Suite skill modeling_skill_path = SKILLS_DIR / “creating-financial-models”
if modeling_skill_path.exists(): print(“Uploading Financial Modeling Suite skill…”) result = create_skill(client, str(modeling_skill_path), “Financial Modeling Suite”)
if result["success"]:
modeling_skill_id = result["skill_id"]
print("✅ Skill uploaded successfully!")
print(f" Skill ID: {modeling_skill_id}")
print(f" Version: {result['latest_version']}")
print("\nThis skill includes:")
print(" - DCF valuation model (dcf_model.py)")
print(" - Sensitivity analysis framework (sensitivity_analysis.py)")
print(" - Monte Carlo simulation capabilities")
print(" - Scenario planning tools")
else:
print(f"❌ Upload failed: {result['error']}")else: print(f”⚠️ Skill directory not found: {modeling_skill_path}“) print(”Please ensure the custom_skills directory contains the creating-financial-models folder.” ) ```### 测试财务建模套件
让我们通过一个DCF估值请求来测试高级建模功能：```python # Test the Financial Modeling Suite with a DCF valuation if “modeling_skill_id” in locals(): dcf_test_prompt = ““” Perform a DCF valuation for TechCorp with the following data:
Historical Financials (Last 3 Years):
- Revenue: $500M, $600M, $750M
- EBITDA Margin: 25%, 27%, 30%
- CapEx: $50M, $55M, $60M
- Working Capital: 15% of revenue
Projections:
- Revenue growth: 20% for years 1-3, then declining to 5% by year 5
- EBITDA margin expanding to 35% by year 5
- Terminal growth rate: 3%
Market Assumptions:
- WACC: 10%
- Tax rate: 25%
- Current net debt: $200M
- Shares outstanding: 100M
Please create a complete DCF model with sensitivity analysis on WACC and terminal growth.
Generate an Excel file with the full model including:
1. Revenue projections
2. Free cash flow calculations
3. Terminal value
4. Enterprise value to equity value bridge
5. Sensitivity table
"""
print("Testing Financial Modeling Suite with DCF valuation...")
print("=" * 70)
print("\n⏱️ Note: Complex financial model generation may take 1-2 minutes.\n")
response = client.beta.messages.create(
model=MODEL,
max_tokens=4096,
container={
"skills": [
{"type": "custom", "skill_id": modeling_skill_id, "version": "latest"},
{"type": "anthropic", "skill_id": "xlsx", "version": "latest"},
]
},
tools=[{"type": "code_execution_20250825", "name": "code_execution"}],
messages=[{"role": "user", "content": dcf_test_prompt}],
betas=[
"code-execution-2025-08-25",
"files-api-2025-04-14",
"skills-2025-10-02",
],
)
# Print Claude's response
for content in response.content:
if content.type == "text":
# Print first 800 characters to keep output manageable
text = content.text
if len(text) > 800:
print(text[:800] + "\n\n[... Output truncated for brevity ...]")
else:
print(text)
# Download the DCF model if generated
file_ids = extract_file_ids(response)
if file_ids:
print("\n" + "=" * 70)
print("Downloading generated DCF model...")
results = download_all_files(
client, response, output_dir=str(OUTPUT_DIR), prefix="dcf_model_"
)
print_download_summary(results)
print("\n💡 Open the Excel file to explore the complete DCF valuation model!")else: print(“⚠️ Please upload the Financial Modeling Suite skill first (run the previous cell)”) ```## 6. 技能管理与版本控制 {#management}
对技能进行时间管理需要理解版本控制、更新和生命周期管理。
列出您的技能
了解您工作空间中所有自定义技能的概览：```python # List all your custom skills my_skills = list_custom_skills(client)
if my_skills: print(f”You have {len(my_skills)} custom skill(s):“) print(”=” * 70) for i, skill in enumerate(my_skills, 1): print(f”. {skill[‘display_title’]}“) print(f” Skill ID: {skill[‘skill_id’]}“) print(f” Current Version: {skill[‘latest_version’]}“) print(f” Created: {skill[‘created_at’]}“) if skill.get(”updated_at”): print(f” Last Updated: {skill[‘updated_at’]}“) print(”” + “=” * 70) else: print(“No custom skills found in your workspace.”) ```### 创建新版本
技能支持版本控制以维护历史记录并启用回滚。让我们增强我们的财务分析器技能并创建一个新版本。
第1步：增强财务分析器
我们将添加医疗行业基准，使我们的技能更加通用。这是一个现实场景，您会根据用户需求扩展技能的功能。
- healthcare industry：医疗行业
- versatile：通用的
- real-world scenario：现实场景
- expand a skill’s capabilities：扩展技能的功能```python # Add healthcare industry benchmarks to the Financial Analyzer # This demonstrates a realistic skill enhancement scenario
if “financial_skill_id” in locals(): # Read the current interpret_ratios.py file interpret_file_path = SKILLS_DIR / “analyzing-financial-statements” / “interpret_ratios.py”
with open(interpret_file_path) as f:
content = f.read()
# Add healthcare benchmarks after the 'manufacturing' section
healthcare_benchmarks = """ },
'healthcare': {
'current_ratio': {'excellent': 2.3, 'good': 1.8, 'acceptable': 1.4, 'poor': 1.0},
'debt_to_equity': {'excellent': 0.3, 'good': 0.6, 'acceptable': 1.0, 'poor': 1.8},
'roe': {'excellent': 0.22, 'good': 0.16, 'acceptable': 0.11, 'poor': 0.07},
'gross_margin': {'excellent': 0.65, 'good': 0.45, 'acceptable': 0.30, 'poor': 0.20},
'pe_ratio': {'undervalued': 18, 'fair': 28, 'growth': 40, 'expensive': 55}
"""
# Find the position after manufacturing section and before the closing brace
insert_pos = content.find(" }\n }") # Find the end of the BENCHMARKS dict
if insert_pos != -1:
# Insert the healthcare benchmarks
new_content = content[:insert_pos] + healthcare_benchmarks + content[insert_pos:]
# Save the enhanced file
with open(interpret_file_path, "w") as f:
f.write(new_content)
print("✅ Enhanced Financial Analyzer with healthcare industry benchmarks")
print("\nChanges made:")
print(" - Added healthcare industry to BENCHMARKS")
print(" - Includes specific thresholds for:")
print(" • Current ratio (liquidity)")
print(" • Debt-to-equity (leverage)")
print(" • ROE (profitability)")
print(" • Gross margin")
print(" • P/E ratio (valuation)")
print("\n📝 Now we can create a new version of the skill with this enhancement!")
else:
print("⚠️ Could not find the correct position to insert healthcare benchmarks")
print("The file structure may have changed.")else: print(“⚠️ Please upload the Financial Analyzer skill first (run cells in Section 3)”) ```#### 第2步：创建新版本
现在我们已经提升了我们的技能，让我们创建一个新版本来追踪这个变化：
```markdown Now that we’ve enhanced our skill, let’s create a new version to track this change: ``````python # Create a new version of the enhanced Financial Analyzer skill def create_skill_version(client: Anthropic, skill_id: str, skill_path: str): “““Create a new version of an existing skill.”“” try: version = client.beta.skills.versions.create( skill_id=skill_id, files=files_from_dir(skill_path) ) return { “success”: True, “version”: version.version, “created_at”: version.created_at, } except Exception as e: return {“success”: False, “error”: str(e)}
Create the new version with our healthcare enhancement
if “financial_skill_id” in locals(): print(“Creating new version of Financial Analyzer with healthcare benchmarks…”)
result = create_skill_version(
client, financial_skill_id, str(SKILLS_DIR / "analyzing-financial-statements")
)
if result["success"]:
print("✅ New version created successfully!")
print(f" Version: {result['version']}")
print(f" Created: {result['created_at']}")
print("\n📊 Version History:")
print(" v1: Original skill with tech, retail, financial, manufacturing")
print(f" v{result['version']}: Enhanced with healthcare industry benchmarks")
else:
print(f"❌ Version creation failed: {result['error']}")else: print(“⚠️ Please run the previous cells to upload the skill and make enhancements first”) ```#### 第3步：测试新版本
让我们通过分析一家医疗保健公司来验证我们的增强功能是否有效：```python # Test the enhanced skill with healthcare industry data if “financial_skill_id” in locals(): healthcare_test_prompt = ““” Analyze this healthcare company using the healthcare industry benchmarks:
Company: MedTech Solutions (Healthcare Industry)
Income Statement:
- Revenue: $800M
- EBITDA: $320M
- Net Income: $160M
Balance Sheet:
- Total Assets: $1,200M
- Current Assets: $400M
- Current Liabilities: $200M
- Total Debt: $300M
- Shareholders Equity: $700M
Market Data:
- Share Price: $75
- Shares Outstanding: 50M
Please calculate key ratios and provide healthcare-specific analysis.
"""
print("Testing enhanced Financial Analyzer with healthcare company...")
print("=" * 70)
response = test_skill(client, financial_skill_id, healthcare_test_prompt, MODEL)
# Print Claude's analysis
for content in response.content:
if content.type == "text":
# Print first 1000 characters to keep output manageable
text = content.text
if len(text) > 1000:
print(text[:1000] + "\n\n[... Output truncated for brevity ...]")
else:
print(text)
print(
"\n✅ The skill now recognizes 'healthcare' as an industry and applies specific benchmarks!"
)else: print(“⚠️ Please run the previous cells to create the enhanced version first”) ```### 清理：管理您的技能
当您完成测试或需要清理工作区时，您可以有选择地删除技能。让我们回顾一下我们创建的内容，并提供清理选项：
When you’re done testing or need to clean up your workspace, you can selectively remove skills. Let’s review what we’ve created and provide options for cleanup:
-
Args: client: Anthropic client dry_run: If True, only show what would be deleted without actually deleting ““” # Get all current skills all_skills = list_custom_skills(client)
# Skills we created in this notebook notebook_skill_names = [ “Financial Ratio Analyzer”, “Corporate Brand Guidelines”, “Financial Modeling Suite”, ]
# Track skills created by this notebook notebook_skills = [] other_skills = []
for skill in all_skills: if skill[“display_title”] in notebook_skill_names: notebook_skills.append(skill) else: other_skills.append(skill)
print(“=” * 70) print(“SKILL INVENTORY REPORT”) print(“=” * 70)
print(f”custom skills in workspace: {len(all_skills)}“)
if notebook_skills: print(f”📚 Skills created by this notebook ({len(notebook_skills)}):“) for skill in notebook_skills: print(f” • {skill[‘display_title’]}“) print(f” ID: {skill[‘skill_id’]}“) print(f” Version: {skill[‘latest_version’]}“) print(f” Created: {skill[‘created_at’]}“) else: print(”✅ No skills from this notebook found”)
if other_skills: print(f”🔧 Other skills in workspace ({len(other_skills)}):“) for skill in other_skills: print(f” • {skill[‘display_title’]} (v{skill[‘latest_version’]})“)
# Cleanup options if notebook_skills: print(“” + “=” * 70) print(“CLEANUP OPTIONS”) print(“=” * 70)
if dry_run: print("\n🔍 DRY RUN MODE - No skills will be deleted") print("\nTo delete the notebook skills, uncomment and run:") print("-" * 40) print("# review_and_cleanup_skills(client, dry_run=False)") print("-" * 40) print("\nThis would delete:") for skill in notebook_skills: print(f" • {skill['display_title']}") else: print("\n⚠️ DELETION MODE - Skills will be permanently removed") print("\nDeleting notebook skills...") success_count = 0 for skill in notebook_skills: if delete_skill(client, skill["skill_id"]): print(f" ✅ Deleted: {skill['display_title']}") success_count += 1 else: print(f" ❌ Failed to delete: {skill['display_title']}") print(f"\n📊 Cleanup complete: {success_count}/{len(notebook_skills)} skills deleted")return { “total_skills”: len(all_skills), “notebook_skills”: len(notebook_skills), “other_skills”: len(other_skills), “notebook_skill_ids”: [s[“skill_id”] for s in notebook_skills], }
Run the review (in dry-run mode by default)
print(“Reviewing your custom skills workspace…”) cleanup_summary = review_and_cleanup_skills(client, dry_run=True)
Store skill IDs for potential cleanup
if cleanup_summary[“notebook_skill_ids”]: skills_to_cleanup = cleanup_summary[“notebook_skill_ids”] print(f”💡 Tip: {len(skills_to_cleanup)} skill(s) can be cleaned up when you’re done testing”)
UNCOMMENT THE LINE BELOW TO ACTUALLY DELETE THE NOTEBOOK SKILLS:
review_and_cleanup_skills(client, dry_run=False)
```## 7. 最佳实践与生产技巧 {#best-practices}
技能设计原则
- 单一职责：每个技能应专注于一个专业领域
- 清晰的文档：SKILL.md 应全面而简洁
- 错误处理：脚本应优雅地处理边缘情况
- 版本控制：使用 Git 跟踪技能变更
- 测试：在生产部署前始终测试技能
目录结构最佳实践custom_skills/ ├── financial_analyzer/ # Single purpose, clear naming │ ├── SKILL.md # Under 5,000 tokens │ ├── scripts/ # Modular Python/JS files │ └── tests/ # Unit tests for scripts ├── brand_guidelines/ # Organizational standards │ ├── SKILL.md │ ├── REFERENCE.md # Additional documentation │ └── assets/ # Logos, templates### 性能优化
| 策略 | 影响 | 实现 |
|---|---|---|
| 最小化前置信息 | 加快技能发现 | name: 64 个字符，description: 1024 个字符 |
| 懒加载 | 减少token使用 | 仅在需要时引用参考文件 |
| 技能组合 | 避免重复 | 组合技能与mega-skill |
| 缓存 | 加快响应 | 重复使用技能容器 |
安全考虑
- API密钥：技能中切勿硬编码凭证
- 数据隐私：不要在技能文件中包含敏感数据
- 访问控制：技能是特定于工作区的
- 验证：在脚本中清理输入
- 审计跟踪：记录技能使用情况以符合规定
下一步
🎉 恭喜！ 你已经学会了如何为Claude创建、部署和管理自定义技能。
你学到了什么
- ✅ 自定义技能架构和需求
- ✅ 使用SKILL.md和Python脚本创建技能
- ✅ 通过API上传技能
- ✅ 结合自定义和Anthropic技能
- ✅ 生产部署的最佳实践
- ✅ 解决常见问题的技巧
继续你的旅程
- 实验：根据你的用例修改示例技能
- 构建：为你的组织工作流程创建技能
- 优化：监控token使用和性能
- 分享：记录你的技能以供团队协作
资源
- Claude API 文档
- 技能文档
- 最佳实践
- 文件API文档
- 示例技能仓库（即将推出）
尝试的技能想法
- 📊 数据管道：带有验证的ETL工作流程
- 📝 文档模板：合同、提案、报告
- 🔍 代码审查：风格指南和最佳实践
- 📈 Analytics Dashboard: KPI tracking and visualization
- 🤖 Automation Suite: Repetitive task workflows
Happy skill building! 🚀
中文读者提示：本章节的代码和输出为英文原文。如需理解具体实现细节，可参考上方中文导读和代码注释。如有疑问，欢迎在 GitHub Issues 讨论。