Explorar skills

Manage security policies, firewall zones, access control rules (ACLs), and guest network access. Perform comprehensive security audits and compliance reviews.

生成面向敏捷开发团队的精炼设计文档。MVP导向，避免过度设计。使用场景：(1) 需要为新功能或系统模块生成设计文档 (2) 需要明确功能边界和交互流程 (3) 需要提供实现思路和关键方法 (4) 需要阐述技术难点和解决方案。该skill会先分析项目技术栈和现有组件，然后生成精炼、重点突出的设计文档。

Automate application deployment to cloud platforms and servers. Use when setting up CI/CD pipelines, deploying to Docker/Kubernetes, or configuring cloud infrastructure. Handles GitHub Actions, Docker, Kubernetes, AWS, Vercel, and deployment best practices.

Write Python code following FiftyOne's official conventions. Use when contributing to FiftyOne, developing plugins, or writing code that integrates with FiftyOne's codebase.

Quick-reference card for all caveman modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /caveman-help, "caveman help", "what caveman commands", "how do I use caveman".

Generate comprehensive network infrastructure reports including health status, performance analysis, security audits, and capacity planning recommendations.

Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.

Comprehensive AWS cost analysis and optimization recommendations using AWS CLI and Cost Explorer

Test-Driven Development workflow - write tests first, then implementation

Maintain a clear and informative changelog for software releases. Use when documenting version changes, tracking features, or communicating updates to users. Handles semantic versioning, changelog formats, and release notes.

World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, or implementing data governance.

Search logs and codebases for error patterns, stack traces, and