17.4 基本技能示例
示例概述
本节将通过几个完整的示例来展示如何开发不同类型的 Skills。这些示例涵盖了常见的使用场景，可以作为开发自己 Skills 的参考。
示例 1：文本处理 Skill
1.1 Skill 定义
src/skills/text_processor.py
from typing import Dict, Any
from claude_code_sdk import Skill, SkillContext, SkillResult
class TextProcessorSkill(Skill):
"""文本处理 Skill"""
def __init__(self):
super().__init__(
name="text-processor",
version="1.0.0",
description="Process and transform text"
)
def get_parameters_schema(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "Text to process"
},
"operations": {
"type": "array",
"description": "List of operations to apply",
"items": {
"type": "object",
"properties": {
"type": {
"type": "string",
"enum": ["uppercase", "lowercase", "title", "reverse", "remove_spaces", "count_words"]
},
"params": {
"type": "object"
}
}
}
}
},
"required": ["text"]
}
def execute(self, parameters: Dict[str, Any], context: SkillContext) -> SkillResult:
try:
text = parameters["text"]
operations = parameters.get("operations", [])
应用操作
result = text
for operation in operations:
op_type = operation.get("type")
op_params = operation.get("params", {})
result = self.apply_operation(result, op_type, op_params)
return SkillResult(
success=True,
data={
"original": text,
"processed": result,
"operations_applied": len(operations)
}
)
except Exception as e:
return SkillResult(
success=False,
error=str(e)
)
def apply_operation(self, text: str, op_type: str, params: Dict[str, Any]) -> str:"""应用单个操作"""
if op_type == "uppercase":
return text.upper()
elif op_type == "lowercase":
return text.lower()
elif op_type == "title":
return text.title()
elif op_type == "reverse":
return text[::-1]
elif op_type == "remove_spaces":
return text.replace(" ", "")
elif op_type == "count_words":
return str(len(text.split()))
else:
raise ValueError(f"Unknown operation: {op_type}")
1.2 使用示例
examples/text_processor_example.py
from skills.text_processor import TextProcessorSkill
from claude_code_sdk import SkillContext
创建 Skill 实例
skill = TextProcessorSkill() context = SkillContext()
示例 1：基本使用
result = skill.execute( { "text": "Hello World", "operations": [ {"type": "uppercase"} ] }, context )
print(result.data["processed"]) # "HELLO WORLD"
示例 2：多个操作
result = skill.execute( { "text": "Hello World", "operations": [ {"type": "lowercase"}, {"type": "remove_spaces"} ] }, context )
print(result.data["processed"]) # "helloworld"
示例 3：反转文本
result = skill.execute( { "text": "Hello World", "operations": [ {"type": "reverse"} ] }, context )
print(result.data["processed"]) # "dlroW olleH"
示例 2：代码生成 Skill
2.1 Skill 定义
src/skills/code_generator.py
from typing import Dict, Any
from claude_code_sdk import Skill, SkillContext, SkillResult
class CodeGeneratorSkill(Skill):
"""代码生成 Skill"""
def __init__(self):
super().__init__(
name="code-generator",
version="1.0.0",
description="Generate code from specifications"
)
def get_parameters_schema(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"language": {
"type": "string",
"enum": ["python", "javascript", "java", "go"],
"description": "Programming language"
},
"type": {
"type": "string",
"enum": ["function", "class", "interface", "enum"],
"description": "Code type to generate"
},
"name": {
"type": "string",
"description": "Name of the function/class"
},
"description": {
"type": "string",
"description": "Description of what the code should do"
},
"parameters": {
"type": "array",
"description": "List of parameters",
"items": {
"type": "object",
"properties": {
"name": {"type": "string"},
"type": {"type": "string"},
"default": {"type": "string"}
}
}
},
"return_type": {
"type": "string",
"description": "Return type"
}
},
"required": ["language", "type", "name", "description"]
}
def execute(self, parameters: Dict[str, Any], context: SkillContext) -> SkillResult:
try:
language = parameters["language"]
code_type = parameters["type"]
name = parameters["name"]
description = parameters["description"]
params = parameters.get("parameters", [])
return_type = parameters.get("return_type", "void")
生成代码
code = self.generate_code( language, code_type, name, description, params, return_type )
return SkillResult(
success=True,
data={
"language": language,
"type": code_type,
"name": name,
"code": code,
"description": description
}
)
except Exception as e:
return SkillResult(
success=False,
error=str(e)
)
def generate_code(self, language: str, code_type: str, name: str, description: str, params: list, return_type: str) -> str:"""生成代码""" generators = { "python": self.generate_python, "javascript": self.generate_javascript, "java": self.generate_java, "go": self.generate_go } generator = generators.get(language)
if not generator:
raise ValueError(f"Unsupported language: {language}")
return generator(code_type, name, description, params, return_type)
def generate_python(self, code_type: str, name: str, description: str, params: list, return_type: str) -> str:
"""生成 Python 代码"""
param_str = ", ".join([f"{p['name']}: {p['type']}" for p in params])
if code_type == "function":
code = f'''def {name}({param_str}) -> {return_type}:
"""
{description}
"""
pass
'''
elif code_type == "class":
code = f'''class {name}:
"""
{description}
"""
def __init__(self{self._init_params(params)}):
pass
'''
else:
raise ValueError(f"Unsupported code type: {code_type}")
return code
def generate_javascript(self, code_type: str, name: str, description: str, params: list, return_type: str) -> str:
"""生成 JavaScript 代码"""
param_str = ", ".join([f"{p['name']}" for p in params])
if code_type == "function":
code = f'''/**
* {description}
* @param {param_str}
* @returns {{{return_type}}}
*/
function {name}({param_str}) {{
// TODO: implement
}}
'''
elif code_type == "class":
code = f'''/**
* {description}
*/
class {name} {{
constructor({param_str}) {{
// TODO: implement
}}
}}
'''
else:
raise ValueError(f"Unsupported code type: {code_type}")
return code
def generate_java(self, code_type: str, name: str, description: str, params: list, return_type: str) -> str:
"""生成 Java 代码"""
param_str = ", ".join([f"{p['type']} {p['name']}" for p in params])
if code_type == "function":
code = f'''/**
* {description}
*/
public {return_type} {name}({param_str}) {{
// TODO: implement
return null;
}}
'''
elif code_type == "class":
code = f'''/**
* {description}
*/
public class {name} {{
public {name}({param_str}) {{
// TODO: implement
}}
}}
'''
else:
raise ValueError(f"Unsupported code type: {code_type}")
return code
def generate_go(self, code_type: str, name: str, description: str, params: list, return_type: str) -> str:
"""生成 Go 代码"""
param_str = ", ".join([f"{p['name']} {p['type']}" for p in params])
if code_type == "function":
code = f'''// {description}
func {name}({param_str}) {return_type} {{
// TODO: implement
return
}}
'''
elif code_type == "class":
code = f'''// {description}
type {name} struct {{
// TODO: add fields
}}
// New{name} creates a new {name}
func New{name}({param_str}) *{name} {{
return &{name}{{
// TODO: initialize fields
}}
}}
'''
else:
raise ValueError(f"Unsupported code type: {code_type}")
return code
def _init_params(self, params: list) -> str:"""生成初始化参数"""
if not params:
return ""
return ", " + ", ".join([p["name"] for p in params])
2.2 使用示例
examples/code_generator_example.py
from skills.code_generator import CodeGeneratorSkill
from claude_code_sdk import SkillContext
创建 Skill 实例
skill = CodeGeneratorSkill() context = SkillContext()
示例 1：生成 Python 函数
result = skill.execute( { "language": "python", "type": "function", "name": "calculate_sum", "description": "Calculate the sum of two numbers", "parameters": [ {"name": "a", "type": "int"}, {"name": "b", "type": "int"} ], "return_type": "int" }, context )
print(result.data["code"])
示例 2：生成 JavaScript 类
result = skill.execute( { "language": "javascript", "type": "class", "name": "User", "description": "User class with name and email", "parameters": [ {"name": "name", "type": "string"}, {"name": "email", "type": "string"} ] }, context )
print(result.data["code"])
示例 3：生成 Java 函数
result = skill.execute( { "language": "java", "type": "function", "name": "isValidEmail", "description": "Validate email address", "parameters": [ {"name": "email", "type": "String"} ], "return_type": "boolean" }, context )
print(result.data["code"])
示例 3：文件分析 Skill
3.1 Skill 定义
src/skills/file_analyzer.py
from typing import Dict, Any, List
from claude_code_sdk import Skill, SkillContext, SkillResult
import os
class FileAnalyzerSkill(Skill):
"""文件分析 Skill"""
def __init__(self):
super().__init__(
name="file-analyzer",
version="1.0.0",
description="Analyze files and directories"
)
def get_parameters_schema(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to file or directory"
},
"analysis_type": {
"type": "string",
"enum": ["structure", "size", "content", "all"],
"description": "Type of analysis to perform"
},
"recursive": {
"type": "boolean",
"description": "Analyze recursively for directories",
"default": False
},
"include_patterns": {
"type": "array",
"description": "File patterns to include",
"items": {"type": "string"}
},
"exclude_patterns": {
"type": "array",
"description": "File patterns to exclude",
"items": {"type": "string"}
}
},
"required": ["path"]
}
def execute(self, parameters: Dict[str, Any], context: SkillContext) -> SkillResult:
try:
path = parameters["path"]
analysis_type = parameters.get("analysis_type", "all")
recursive = parameters.get("recursive", False)
include_patterns = parameters.get("include_patterns", [])
exclude_patterns = parameters.get("exclude_patterns", [])
检查路径是否存在
if not os.path.exists(path):
return SkillResult(
success=False,
error=f"Path not found: {path}"
)
执行分析
if os.path.isfile(path):
result = self.analyze_file(
path, analysis_type, context
)
else:
result = self.analyze_directory(
path, analysis_type, recursive,
include_patterns, exclude_patterns, context
)
return SkillResult(
success=True,
data=result
)
except Exception as e:
return SkillResult(
success=False,
error=str(e)
)
def analyze_file(self, file_path: str, analysis_type: str,
context: SkillContext) -> Dict[str, Any]:"""分析单个文件""" result = { "type": "file", "path": file_path, "name": os.path.basename(file_path), "extension": os.path.splitext(file_path)[1] }
if analysis_type in ["size", "all"]:
result["size"] = os.path.getsize(file_path)
if analysis_type in ["content", "all"]:
try:
content = context.read_file(file_path)
result["content"] = {
"lines": len(content.split('\n')),
"characters": len(content),
"words": len(content.split())
}
except Exception as e:
result["content"] = {"error": str(e)}
return result
def analyze_directory(self, dir_path: str, analysis_type: str,
recursive: bool, include_patterns: List[str],
exclude_patterns: List[str], context: SkillContext) -> Dict[str, Any]:"""分析目录""" result = { "type": "directory", "path": dir_path, "name": os.path.basename(dir_path) }
收集文件
files = [] directories = []
for item in os.listdir(dir_path):
item_path = os.path.join(dir_path, item)
if os.path.isfile(item_path):
if self.should_include(item, include_patterns, exclude_patterns):
files.append(item_path)
elif os.path.isdir(item_path) and recursive:
directories.append(item_path)
分析文件
file_analyses = []
for file_path in files:
file_analysis = self.analyze_file(file_path, analysis_type, context)
file_analyses.append(file_analysis)
result["files"] = file_analyses
result["file_count"] = len(files)
分析子目录
directory_analyses = []
for dir_path in directories:
dir_analysis = self.analyze_directory(
dir_path, analysis_type, recursive,
include_patterns, exclude_patterns, context
)
directory_analyses.append(dir_analysis)
result["directories"] = directory_analyses
result["directory_count"] = len(directories)
计算总大小
if analysis_type in ["size", "all"]:
total_size = sum(f.get("size", 0) for f in file_analyses)
for dir_analysis in directory_analyses:
total_size += dir_analysis.get("total_size", 0)
result["total_size"] = total_size
return result
def should_include(self, filename: str, include_patterns: List[str],
exclude_patterns: List[str]) -> bool:"""检查文件是否应该包含"""
检查排除模式
for pattern in exclude_patterns:
if self.match_pattern(filename, pattern):
return False
检查包含模式
if not include_patterns:
return True
for pattern in include_patterns:
if self.match_pattern(filename, pattern):
return True
return False
def match_pattern(self, filename: str, pattern: str) -> bool:"""匹配文件模式"""
import fnmatch
return fnmatch.fnmatch(filename, pattern)
3.2 使用示例
examples/file_analyzer_example.py
from skills.file_analyzer import FileAnalyzerSkill
from claude_code_sdk import SkillContext
创建 Skill 实例
skill = FileAnalyzerSkill() context = SkillContext()
示例 1：分析单个文件
result = skill.execute( { "path": "src/main.py", "analysis_type": "all" }, context )
print(result.data)
示例 2：分析目录
result = skill.execute( { "path": "src", "analysis_type": "size", "recursive": True }, context )
print(f"Total size: {result.data['total_size']} bytes")
示例 3：分析特定文件类型
result = skill.execute( { "path": "src", "analysis_type": "structure", "recursive": True, "include_patterns": [".py"], "exclude_patterns": ["pycache", ".pyc"] }, context )
print(f"Python files found: {result.data['file_count']}")
示例 4：测试生成 Skill
4.1 Skill 定义
src/skills/test_generator.py
from typing import Dict, Any
from claude_code_sdk import Skill, SkillContext, SkillResult
class TestGeneratorSkill(Skill):
"""测试生成 Skill"""
def __init__(self):
super().__init__(
name="test-generator",
version="1.0.0",
description="Generate unit tests from code"
)
def get_parameters_schema(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"file_path": {
"type": "string",
"description": "Path to the source file"
},
"test_framework": {
"type": "string",
"enum": ["pytest", "unittest", "jest"],
"description": "Test framework to use"
},
"include_edge_cases": {
"type": "boolean",
"description": "Include edge case tests",
"default": True
},
"include_mocks": {
"type": "boolean",
"description": "Include mock objects",
"default": False
}
},
"required": ["file_path"]
}
def execute(self, parameters: Dict[str, Any], context: SkillContext) -> SkillResult:
try:
file_path = parameters["file_path"]
test_framework = parameters.get("test_framework", "pytest")
include_edge_cases = parameters.get("include_edge_cases", True)
include_mocks = parameters.get("include_mocks", False)
读取源文件
source_code = context.read_file(file_path)
分析代码
functions = self.analyze_functions(source_code)
生成测试
test_code = self.generate_tests( file_path, functions, test_framework, include_edge_cases, include_mocks )
return SkillResult(
success=True,
data={
"source_file": file_path,
"test_framework": test_framework,
"functions_tested": len(functions),
"test_code": test_code
}
)
except Exception as e:
return SkillResult(
success=False,
error=str(e)
)
def analyze_functions(self, source_code: str) -> list:"""分析源代码中的函数"""
import re
functions = []
pattern = r'def\s+(\w+)\s*\(([^)]*)\):'
for match in re.finditer(pattern, source_code):
function_name = match.group(1)
params = match.group(2).strip()
functions.append({
"name": function_name,
"params": [p.strip() for p in params.split(',') if p.strip()]
})
return functions
def generate_tests(self, file_path: str, functions: list, test_framework: str, include_edge_cases: bool, include_mocks: bool) -> str:"""生成测试代码""" generators = { "pytest": self.generate_pytest, "unittest": self.generate_unittest, "jest": self.generate_jest } generator = generators.get(test_framework)
if not generator:
raise ValueError(f"Unsupported test framework: {test_framework}")
return generator(file_path, functions, include_edge_cases, include_mocks)
def generate_pytest(self, file_path: str, functions: list, include_edge_cases: bool, include_mocks: bool) -> str:
"""生成 pytest 测试"""
import os
module_name = os.path.splitext(os.path.basename(file_path))[0]
test_code = f'''import pytest
from {module_name} import {', '.join([f['name'] for f in functions])}
'''
for func in functions:
test_code += f'''class Test{func['name'].capitalize()}:
"""Test cases for {func['name']}"""
def test_{func['name']}_basic(self):
"""Basic test for {func['name']}"""TODO: implement test
pass
'''
if include_edge_cases:
test_code += f''' def test_{func['name']}_edge_cases(self):
"""Edge case tests for {func['name']}"""TODO: implement edge case tests
pass
'''
if include_mocks:
test_code += f''' def test_{func['name']}_with_mocks(self):
"""Test {func['name']} with mocks"""TODO: implement tests with mocks
pass
'''
return test_code
def generate_unittest(self, file_path: str, functions: list, include_edge_cases: bool, include_mocks: bool) -> str:
"""生成 unittest 测试"""
import os
module_name = os.path.splitext(os.path.basename(file_path))[0]
test_code = f'''import unittest
from {module_name} import {', '.join([f['name'] for f in functions])}
class Test{module_name.capitalize()}(unittest.TestCase):
"""Test cases for {module_name}"""
'''
for func in functions:
test_code += f''' def test_{func['name']}(self):
"""Test {func['name']}"""TODO: implement test
pass
'''
if include_edge_cases:
test_code += f''' def test_{func['name']}_edge_cases(self):
"""Test {func['name']} edge cases"""TODO: implement edge case tests
pass
''' test_code += '''if name == 'main':
unittest.main()
'''
return test_code
def generate_jest(self, file_path: str, functions: list, include_edge_cases: bool, include_mocks: bool) -> str:
"""生成 Jest 测试"""
import os
module_name = os.path.splitext(os.path.basename(file_path))[0]
test_code = f'''const {{ {', '.join([f['name'] for f in functions])} }} = require('./{module_name}');
'''
for func in functions:
test_code += f'''describe('{func['name']}', () => {{
test('basic test', () => {{
// TODO: implement test
}});
'''
if include_edge_cases:
test_code += f''' test('edge cases', () => {{
// TODO: implement edge case tests
}});
'''
if include_mocks:
test_code += f''' test('with mocks', () => {{
// TODO: implement tests with mocks
}});
'''
test_code += '});\n'
return test_code
4.2 使用示例
examples/test_generator_example.py
from skills.test_generator import TestGeneratorSkill
from claude_code_sdk import SkillContext
创建 Skill 实例
skill = TestGeneratorSkill() context = SkillContext()
示例 1：生成 pytest 测试
result = skill.execute( { "file_path": "src/utils.py", "test_framework": "pytest", "include_edge_cases": True, "include_mocks": False }, context )
print(result.data["test_code"])
示例 2：生成 unittest 测试
result = skill.execute( { "file_path": "src/utils.py", "test_framework": "unittest" }, context )
print(result.data["test_code"])
示例 3：生成 Jest 测试
result = skill.execute( { "file_path": "src/utils.js", "test_framework": "jest" }, context )
print(result.data["test_code"])
总结
通过这些示例，我们可以看到如何开发不同类型的 Skills：
- 文本处理 Skill：展示基本的文本转换操作
- 代码生成 Skill：展示如何根据规范生成代码
- 文件分析 Skill：展示如何分析文件和目录结构
- 测试生成 Skill：展示如何自动生成测试代码
这些示例可以作为开发自己 Skills 的起点和参考。
在下一节中，我们将探讨 Skills 的测试与调试方法。