Skill UI

This skill generates standardized, production-ready `mise.toml` configurations. It helps developers standardize runtime versions across mixed-language projects (e.g., Node.js, Python, Go, etc.) and CI/CD pipelines, eliminating the need for multiple legacy version managers like asdf or nvm. Ideal for ensuring reproducible, consistent development environments.

This guide provides a comprehensive, advanced methodology for red team operations. It covers critical topics such as Operational Security (OPSEC), designing robust C2 infrastructure using redirectors, employing living-off-the-land techniques, mastering lateral movement, establishing persistence, and planning data exfiltration while evading modern defensive systems. Use this to plan complex red team engagements or deeply understand Advanced Persistent Threat (APT) TTPs.

A comprehensive methodology and checklist for identifying and exploiting race conditions (TOCTOU) in web applications. It guides users to find timing windows, detect vulnerabilities like double-spend or rate limit bypass, and exploit concurrent request flaws in state-changing business logic. Essential for penetration testing and bug bounty hunting.

This skill provides a comprehensive checklist and detailed methodology for detecting HTTP Request Smuggling vulnerabilities. It covers various desynchronization types (CL.TE, TE.CL, TE.TE), including HTTP/2 and modern variants. Use this when penetration testing multi-server architectures, proxies, or load balancers to identify potential security bypasses, unauthorized access, or cache poisoning risks.

This advanced skill explores offensive reconnaissance techniques focused on defeating modern operating system security boundaries and mitigations. Topics include kernel/user boundary manipulation, sandbox escapes (AppContainer, LPAC), COM/RPC boundary exploitation, hypervisor interactions, and various integrity level bypassing methods. It is essential for planning advanced privilege escalation paths and understanding deep Windows security architecture, including AMSI, WDAC, and ETW manipulation.

This skill provides a deep dive into optimizing Oracle Cloud Infrastructure (OCI) resources. It guides users through selecting appropriate compute shapes (e.g., E5.Flex, A1.Flex) and understanding the performance tiers for block volumes (Balanced, Ultra High Performance). Users can programmatically query available shapes, create performance-tuned volumes, and monitor real-time IOPS and network bandwidth using the OCI SDK, ensuring optimal infrastructure decisions for any workload.

This guide provides comprehensive strategies for scaling datasets that exceed the capacity of a single node. It covers various architectural patterns, including multi-tenancy with payload partitioning and sliding time window management. We detail the full scaling progression, from optimizing a single node (Vertical Scaling) to distributing data across multiple nodes via sharding (Horizontal Scaling), ensuring reliable handling of massive, growing datasets.

A powerful, kubectl/docker-style CLI tool designed to manage and submit distributed computing jobs on the Qizhi (启智) platform. Use it for tasks like logging in, checking resource availability, discovering workspaces, and submitting complex GPU, CPU, or batch jobs efficiently.

This component is an essential extension for KubeSphere Observability Platform, designed for comprehensive collection, processing, and storage of Kubernetes and KubeSphere audit events. It supports various sinks, including OpenSearch and Doris, and provides an API for querying historical audit data, ensuring robust auditing capabilities for platform operations.

This extension component is integral to the KubeSphere Observability Platform. It provides robust mechanisms for collecting, processing, and storing Kubernetes events using the kube-events-exporter. Users can leverage the detailed event query API to gain deep insights into cluster activity, making it essential for comprehensive system monitoring and observability setup.

A comprehensive guide for simulating a full Software Development Life Cycle (SDLC) using specialized AI roles. It defines protocols for managing cross-functional teams (Dev, QA, DevOps, Product), covering sprint planning, codebase management, bug tracking, and deployment, ensuring context survival across multiple chat sessions.

KubeStellar Console is an open-source, multi-cluster Kubernetes dashboard (CNCF project) that provides advanced operational capabilities powered by an MCP server and built-in AI agent skills. It helps manage complex deployments across edge and cloud environments, offering AI-assisted troubleshooting, performance testing, and deep integration with major CNCF projects like Argo and Istio.