Menu
专业级容器化部署和自动化运维技能，基于FootballPrediction项目实战经验，提供Docker容器管理、权限修复、健康监控、故障诊断、一键部署等10个核心能力。
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Comprehensive API testing including unit tests, integration tests, performance testing, and automated test pipelines. Use when testing REST endpoints, validating API responses, load testing, or setting up test automation.
Manage code quality for Football Prediction project using Make commands. Use when running quality checks, formatting code, running tests, or preparing for commits. Supports black, flake8, mypy, bandit, pytest, and coverage tools.
Collect football data from external APIs including FotMob L2 data, odds information, and real-time match statistics. Use when gathering match data, collecting historical statistics, or updating prediction datasets.
Design and optimize data pipelines for football prediction system. Use when building ETL processes, data transformations, or optimizing data flow between PostgreSQL, Redis, and external APIs.
Manage PostgreSQL database operations including migrations, query optimization, connection pooling, and data backup/restore. Use when handling database tasks, optimizing queries, or managing database connections.
Manage application deployment including Docker containers, production environments, and service orchestration. Use when deploying to production, managing Docker services, or handling deployment rollbacks.
| name | deployment-operations |
| description | 专业级容器化部署和自动化运维技能，基于FootballPrediction项目实战经验，提供Docker容器管理、权限修复、健康监控、故障诊断、一键部署等10个核心能力。 |
基于实战经验的专业级容器化部署和自动化运维技能，专注于Docker容器化部署、生产环境管理和系统运维自动化。
from skills.deployment_operations import DeploymentOperationsSkill, get_skill_info
# 获取技能信息
skill_info = get_skill_info()
print(f"技能: {skill_info['name']}, 版本: {skill_info['version']}")
# 创建技能实例
skill = DeploymentOperationsSkill()
# 生成生产环境配置
production_template = skill.generate_docker_compose_template('production')
# 生成影子测试环境配置
shadow_template = skill.generate_docker_compose_template('shadow')
# 修复项目目录权限
result = skill.fix_container_permissions('/path/to/project')
if result['success']:
print("权限修复成功!")
# 检查容器健康状态
health = skill.check_container_health('footballprediction-app-shadow')
print(f"容器状态: {health['status']}, 健康: {health.get('health_status', 'unknown')}")
# 生成部署脚本
deploy_script = skill.generate_deployment_script('production')
with open('deploy.sh', 'w') as f:
f.write(deploy_script)
# 诊断容器问题
diagnosis = skill.troubleshoot_container_issues('container-name')
for issue in diagnosis['issues']:
print(f"问题: {issue}")
for rec in diagnosis['recommendations']:
print(f"建议: {rec}")
# 生成监控仪表板
dashboard = skill.generate_monitoring_dashboard()
print(f"系统健康评分: {dashboard['summary']['health_score']}%")
该技能已在FootballPrediction v2.3.0-production项目中完成实战验证：
from skills.deployment_operations import DeploymentOperationsSkill
skill = DeploymentOperationsSkill()
def health_check_command():
dashboard = skill.generate_monitoring_dashboard()
return dashboard['summary']['health_score']
def troubleshoot_command(container_name):
return skill.troubleshoot_container_issues(container_name)
# 部署前权限修复
skill.fix_container_permissions(project_root)
# 生成部署配置
config = skill.generate_docker_compose_template(environment)
# 部署后验证
dashboard = skill.generate_monitoring_dashboard()
assert dashboard['summary']['health_score'] >= 80
docs/deployment_operations_skill_guide.mdDEPLOYMENT_SKILL_TEST_REPORT.md.claude/skills/deployment-operations/deployment_operations.py该技能专注于解决容器化部署和运维中的实际问题，提供自动化、智能化的解决方案，显著提高部署效率和运维质量。
deployment-management: Deployment management (Docker, production)docker-devops: Docker and DevOps best practicesperformance-monitoring: System performance monitoringcode-quality: Code quality management