소스 정보
- 저장소
- microwind/ai-skills
- 최근 소스 활동
- 2026년 3월 26일 14:58
- 감지된 SKILL.md 언어
- 중국어
- 스타
- 68
- 포크
- 17
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
SOC 직업 분류 기준
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/microwind/ai-skills --skill flask-django명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
| name | Flask/Django分析器 |
| description | 当审查Flask/Django代码、规划项目结构、调试框架问题或优化框架性能时，分析Flask/Django Web框架的最佳实践和架构模式。 |
| license | MIT |
Web框架实现快速开发，但不良模式会创建维护噩梦。
核心原则: Web框架实现快速开发，但不良模式会创建维护噩梦。
始终:
触发短语:
问题:
项目结构混乱，违反框架设计原则
错误示例:
- 所有代码放在一个文件
- 模型与视图耦合
- 缺少模块化设计
- 业务逻辑分散
解决方案:
1. 遵循MVC/MVT架构
2. 使用蓝图/应用分离
3. 创建清晰的模块结构
4. 实现关注点分离
问题:
数据库设计不当，查询效率低下
错误示例:
- 缺少索引优化
- N+1查询问题
- 事务管理不当
- 数据模型设计不合理
解决方案:
1. 优化数据库索引
2. 使用select_related/prefetch_related
3. 合理管理事务
4. 规范数据模型设计
问题:
Web应用存在安全漏洞
错误示例:
- 缺少CSRF保护
- SQL注入风险
- XSS攻击漏洞
- 认证机制不完善
解决方案:
1. 启用CSRF保护
2. 使用ORM防止SQL注入
3. 模板自动转义
4. 实现完善的认证系统
import ast
import os
import re
from typing import List, Dict, Any, Optional, Tuple
from dataclasses import dataclass
from collections import defaultdict
@dataclass
class FlaskIssue:
"""Flask代码问题"""
file_path: str
line_number: int
column: int
severity: str # error, warning, info
message: str
rule_id: str
suggestion: Optional[str] = None
@dataclass
class RouteMetrics:
"""路由指标"""
endpoint: str
methods: List[str]
line_number: int
has_auth: bool
has_validation: bool
complexity: int
docstring: bool
@dataclass
class ModelMetrics:
"""模型指标"""
name: str
fields_count: int
relationships_count: int
has_indexes: bool
has_validators: bool
docstring: bool
:
():
.project_root = project_root
.issues: [FlaskIssue] = []
.route_metrics: [RouteMetrics] = []
.model_metrics: [ModelMetrics] = []
.config_files: [] = []
.template_files: [] = []
() -> [, ]:
results = {
: .analyze_project_structure(),
: .analyze_routes(),
: .analyze_models(),
: .analyze_templates(),
: .analyze_config(),
: .analyze_security(),
: .analyze_performance(),
: .issues,
: .generate_summary()
}
results
() -> [, ]:
structure = {
: ,
: ,
: ,
: ,
: ,
: {},
: []
}
root, dirs, files os.walk(.project_root):
rel_path = os.path.relpath(root, .project_root)
structure[][rel_path] = {
: dirs,
: files
}
files files:
(os.path.join(root, files ), ) f:
content = f.read()
content:
structure[] =
dirs ( f.lower() f files):
structure[] =
files files:
structure[] =
dirs dirs:
structure[] =
dirs dirs:
structure[] =
structure[]:
structure[].append({
: ,
: ,
:
})
structure[]:
structure[].append({
: ,
: ,
:
})
structure
() -> [, ]:
route_files = .find_files([, , , ])
file_path route_files:
.analyze_route_file(file_path)
{
: (.route_metrics),
: .route_metrics,
: [issue issue .issues issue.rule_id.startswith()]
}
() -> :
:
(file_path, , encoding=) f:
content = f.read()
tree = ast.parse(content, filename=file_path)
node ast.walk(tree):
(node, ast.FunctionDef):
decorators = [d d node.decorator_list
(d, ast.Call)
(d.func, ast.Name)
d.func. [, ]]
decorators:
.analyze_route_function(node, file_path, decorators)
Exception e:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=,
column=,
severity=,
message=,
rule_id=
))
() -> :
route_info = .extract_route_info(decorators[])
has_auth = .check_route_auth(node)
has_validation = .check_route_validation(node)
complexity = .calculate_complexity(node)
has_docstring = ast.get_docstring(node)
metrics = RouteMetrics(
endpoint=route_info.get(, ),
methods=route_info.get(, []),
line_number=node.lineno,
has_auth=has_auth,
has_validation=has_validation,
complexity=complexity,
docstring=has_docstring
)
.route_metrics.append(metrics)
has_auth (method [, , ] method metrics.methods):
.issues.append(FlaskIssue(
file_path=file_path,
line_number=node.lineno,
column=,
severity=,
message=,
rule_id=,
suggestion=
))
has_validation (method [, , ] method metrics.methods):
.issues.append(FlaskIssue(
file_path=file_path,
line_number=node.lineno,
column=,
severity=,
message=,
rule_id=,
suggestion=
))
complexity > :
.issues.append(FlaskIssue(
file_path=file_path,
line_number=node.lineno,
column=,
severity=,
message=,
rule_id=,
suggestion=
))
() -> [, ]:
info = {: , : []}
decorator.args:
(decorator.args[], ast.Str):
info[] = decorator.args[].s
(decorator.args[], ast.Constant):
info[] = decorator.args[].value
keyword decorator.keywords:
keyword.arg == :
(keyword.value, ast.):
methods = []
elt keyword.value.elts:
(elt, ast.Str):
methods.append(elt.s)
(elt, ast.Constant):
methods.append(elt.value)
info[] = methods
info
() -> :
auth_decorators = []
decorator node.decorator_list:
(decorator, ast.Name):
decorator. [, , ]:
auth_decorators.append(decorator.)
(decorator, ast.Call):
(decorator.func, ast.Name):
decorator.func. [, , ]:
auth_decorators.append(decorator.func.)
(auth_decorators) >
() -> :
validation_patterns = [
,
,
,
,
,
,
]
child ast.walk(node):
(child, ast.Call):
(child.func, ast.Attribute):
(pattern child.func.attr pattern validation_patterns):
(child.func, ast.Name):
child.func. validation_patterns:
() -> [, ]:
model_files = .find_files([, ])
file_path model_files:
.analyze_model_file(file_path)
{
: (.model_metrics),
: .model_metrics,
: [issue issue .issues issue.rule_id.startswith()]
}
() -> :
:
(file_path, , encoding=) f:
content = f.read()
tree = ast.parse(content, filename=file_path)
node ast.walk(tree):
(node, ast.ClassDef):
.is_model_class(node):
.analyze_model_class(node, file_path)
Exception e:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=,
column=,
severity=,
message=,
rule_id=
))
() -> :
base node.bases:
(base, ast.Name):
base. [, , ]:
(base, ast.Attribute):
base.attr == :
decorator node.decorator_list:
(decorator, ast.Name):
decorator. == :
() -> :
fields_count =
relationships_count =
has_indexes =
has_validators =
item node.body:
(item, ast.Assign):
target item.targets:
(target, ast.Name):
(item.value, ast.Call):
(item.value.func, ast.Name):
item.value.func. [, , , ]:
fields_count +=
keyword item.value.keywords:
keyword.arg == keyword.value.value :
has_indexes =
(item.value.func, ast.Attribute):
item.value.func.attr [, , ]:
item.value.func.attr == :
relationships_count +=
:
fields_count +=
has_docstring = ast.get_docstring(node)
metrics = ModelMetrics(
name=node.name,
fields_count=fields_count,
relationships_count=relationships_count,
has_indexes=has_indexes,
has_validators=has_validators,
docstring=has_docstring
)
.model_metrics.append(metrics)
fields_count > :
.issues.append(FlaskIssue(
file_path=file_path,
line_number=node.lineno,
column=,
severity=,
message=,
rule_id=,
suggestion=
))
has_docstring:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=node.lineno,
column=,
severity=,
message=,
rule_id=,
suggestion=
))
() -> [, ]:
template_dirs = [, ]
template_dir template_dirs:
template_path = os.path.join(.project_root, template_dir)
os.path.exists(template_path):
.analyze_template_directory(template_path)
{
: (.template_files),
: [issue issue .issues issue.rule_id.startswith()]
}
() -> :
root, dirs, files os.walk(template_dir):
file files:
file.endswith((, , , )):
file_path = os.path.join(root, file)
.analyze_template_file(file_path)
() -> :
:
(file_path, , encoding=) f:
content = f.read()
.template_files.append(file_path)
.check_template_security(file_path, content)
.check_template_structure(file_path, content)
Exception e:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=,
column=,
severity=,
message=,
rule_id=
))
() -> :
lines = content.split()
line_num, line (lines, ):
line line:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=line_num,
column=line.find(),
severity=,
message=,
rule_id=,
suggestion=
))
line line line line:
() -> :
lines = content.split()
has_extends = ( line line lines)
has_extends file_path.endswith():
is_base_template = ( line line lines)
is_base_template:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=,
column=,
severity=,
message=,
rule_id=,
suggestion=
))
() -> [, ]:
config_files = .find_files([, , , ])
file_path config_files:
.analyze_config_file(file_path)
{
: (.config_files),
: [issue issue .issues issue.rule_id.startswith()]
}
() -> :
:
(file_path, , encoding=) f:
content = f.read()
.check_config_security(file_path, content)
.check_config_structure(file_path, content)
Exception e:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=,
column=,
severity=,
message=,
rule_id=
))
() -> :
lines = content.split()
line_num, line (lines, ):
line line:
value = line.split()[].strip()
value.startswith() value.startswith():
.issues.append(FlaskIssue(
file_path=file_path,
line_number=line_num,
column=line.find(),
severity=,
message=,
rule_id=,
suggestion=
))
line line:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=line_num,
column=line.find(),
severity=,
message=,
rule_id=,
suggestion=
))
() -> :
has_env_vars = content content
has_env_vars:
.issues.append(FlaskIssue(
file_path=file_path,
line_number=,
column=,
severity=,
message=,
rule_id=,
suggestion=
))
() -> [, ]:
security_issues = []
.has_csrf_protection():
security_issues.append({
: ,
: ,
: ,
:
})
.has_security_headers():
security_issues.append({
: ,
: ,
: ,
:
})
{
: security_issues,
: .calculate_security_score(security_issues)
}
() -> :
root, dirs, files os.walk(.project_root):
file files:
file.endswith():
file_path = os.path.join(root, file)
:
(file_path, , encoding=) f:
content = f.read()
content.lower() content:
:
() -> :
() -> [, ]:
performance_issues = []
.has_cache_config():
performance_issues.append({
: ,
: ,
: ,
:
})
.has_connection_pool():
performance_issues.append({
: ,
: ,
: ,
:
})
{
: performance_issues,
: .calculate_performance_score(performance_issues)
}
() -> :
() -> :
() -> :
complexity =
child ast.walk(node):
(child, (ast.If, ast.While, ast.For, ast.ExceptHandler)):
complexity +=
(child, ast.BoolOp):
complexity += (child.values) -
complexity
() -> []:
found_files = []
root, dirs, files os.walk(.project_root):
file files:
file filenames:
found_files.append(os.path.join(root, file))
found_files
() -> :
score =
issue issues:
issue[] == :
score -=
issue[] == :
score -=
issue[] == :
score -=
(, score)
() -> :
score =
issue issues:
issue[] == :
score -=
issue[] == :
score -=
issue[] == :
score -=
(, score)
() -> [, ]:
total_issues = (.issues)
error_count = ([i i .issues i.severity == ])
warning_count = ([i i .issues i.severity == ])
info_count = ([i i .issues i.severity == ])
{
: total_issues,
: error_count,
: warning_count,
: info_count,
: (, - error_count * - warning_count * - info_count),
: .generate_recommendations()
}
() -> [[, ]]:
recommendations = []
issue_counts = defaultdict()
issue .issues:
issue_counts[issue.rule_id] +=
issue_counts[] > :
recommendations.append({
: ,
: ,
:
})
issue_counts[] > :
recommendations.append({
: ,
: ,
:
})
issue_counts[] > :
recommendations.append({
: ,
: ,
:
})
recommendations
:
():
.project_root = project_root
.issues: [FlaskIssue] = []
() -> [, ]:
{
: .analyze_settings(),
: .analyze_urls(),
: .analyze_views(),
: .analyze_models(),
: .analyze_admin(),
: .issues
}
() -> [, ]:
settings_files = [, , ]
issues = []
settings_file settings_files:
settings_path = os.path.join(.project_root, settings_file)
os.path.exists(settings_path):
{: issues}
() -> [, ]:
url_files = []
issues = []
root, dirs, files os.walk(.project_root):
file files:
file == :
{: issues}
() -> [, ]:
view_files = []
issues = []
root, dirs, files os.walk(.project_root):
file files:
file == :
{: issues}
() -> [, ]:
model_files = []
issues = []
root, dirs, files os.walk(.project_root):
file files:
file == :
{: issues}
() -> [, ]:
admin_files = []
issues = []
root, dirs, files os.walk(.project_root):
file files:
file == :
{: issues}
():
project_path =
flask_analyzer = FlaskAnalyzer(project_path)
flask_result = flask_analyzer.analyze_project()
()
()
()
django_analyzer = DjangoAnalyzer(project_path)
django_result = django_analyzer.analyze_project()
()
()
__name__ == :
main()
import time
import psutil
import threading
from typing import Dict, List, Any, Callable
from dataclasses import dataclass
from functools import wraps
@dataclass
class PerformanceMetric:
"""性能指标"""
name: str
value: float
unit: str
timestamp: float
metadata: Dict[str, Any]
class FlaskDjangoPerformanceAnalyzer:
def __init__(self):
self.metrics: List[PerformanceMetric] = []
self.is_monitoring = False
self.monitor_thread = None
def start_monitoring(self, interval: int = 5) -> None:
"""开始性能监控"""
self.is_monitoring = True
self.monitor_thread = threading.Thread(
target=self._monitor_loop,
args=(interval,),
daemon=True
)
self.monitor_thread.start()
() -> :
.is_monitoring =
.monitor_thread:
.monitor_thread.join()
() -> :
.is_monitoring:
._collect_system_metrics()
time.sleep(interval)
() -> :
cpu_percent = psutil.cpu_percent()
.record_metric(, cpu_percent, )
memory = psutil.virtual_memory()
.record_metric(, memory.percent, )
.record_metric(, memory.available, )
disk = psutil.disk_usage()
.record_metric(, disk.percent, )
.record_metric(, disk.free, )
() -> :
metric = PerformanceMetric(
name=name,
value=value,
unit=unit,
timestamp=time.time(),
metadata=metadata {}
)
.metrics.append(metric)
(.metrics) > :
.metrics = .metrics[-:]
() -> :
() -> :
():
start_time = time.time()
start_memory = psutil.Process().memory_info().rss
:
result = func(*args, **kwargs)
success =
error =
Exception e:
success =
error = (e)
:
end_time = time.time()
end_memory = psutil.Process().memory_info().rss
.record_metric(,
end_time - start_time, ,
{: success, : error})
.record_metric(,
end_memory - start_memory, ,
{: success, : error})
result
wrapper
decorator
() -> :
() -> :
():
start_time = time.time()
:
result = func(*args, **kwargs)
query_count = (result, , )
success =
Exception e:
query_count =
success =
:
end_time = time.time()
.record_metric(,
end_time - start_time, ,
{: query_count, : success})
.record_metric(,
query_count, ,
{: success})
result
wrapper
decorator
() -> :
request_data:
.record_metric(,
request_data[], ,
{: request_data.get(, )})
request_data:
.record_metric(,
request_data[], ,
{: request_data.get(, )})
() -> [, ]:
report = {
: time.time(),
: ._generate_summary(),
: ._group_metrics_by_type(),
: ._analyze_trends(),
: ._generate_performance_recommendations()
}
report
() -> [, ]:
.metrics:
{: }
metrics_by_type = defaultdict()
metric .metrics:
metrics_by_type[metric.name].append(metric)
summary = {}
metric_type, metrics metrics_by_type.items():
metrics:
values = [m.value m metrics]
summary[metric_type] = {
: (values) / (values),
: (values),
: (values),
: (values),
: metrics[].unit
}
summary
() -> [, [PerformanceMetric]]:
grouped = defaultdict()
metric .metrics:
grouped[metric.name].append(metric)
(grouped)
() -> [, ]:
trends = {}
grouped = ._group_metrics_by_type()
metric_type, metrics grouped.items():
(metrics) >= :
recent = metrics[-].value
earliest = metrics[].value
recent > earliest * :
trends[metric_type] =
recent < earliest * :
trends[metric_type] =
:
trends[metric_type] =
trends
() -> [[, ]]:
recommendations = []
summary = ._generate_summary()
summary summary[][] > :
recommendations.append({
: ,
: ,
: ,
:
})
summary summary[][] > :
recommendations.append({
: ,
: ,
: ,
:
})
request_metrics = [m m .metrics m.name]
request_metrics:
avg_response_time = (m.value m request_metrics) / (request_metrics)
avg_response_time > :
recommendations.append({
: ,
: ,
: ,
:
})
recommendations
():
analyzer = FlaskDjangoPerformanceAnalyzer()
analyzer.start_monitoring()
():
time.sleep()
():
time.sleep()
[]
home_view()
get_users()
analyzer.analyze_request_performance({
: ,
: ,
:
})
time.sleep()
analyzer.stop_monitoring()
report = analyzer.generate_performance_report()
(, report)
__name__ == :
main()