Skill UI

This meta-skill coordinates the entire design lifecycle, ensuring that ideas are systematically refined through mandatory stages: brainstorming, risk assessment, and multi-agent review. It acts as a process gatekeeper, enforcing adherence to structured steps and mitigating risks before allowing implementation, thus preventing premature or flawed execution.

Guides implementing Kubernetes NetworkPolicy, RBAC, PodSecurityPolicy, Pod Security Standards, and OPA Gatekeeper constraints to enforce defense-in-depth across clusters, covering multi-tenant protection, admission control, and Istio service mesh policies.

This skill provides comprehensive methods for detecting and preventing privilege escalation within Kubernetes pods and containers. It details using runtime tools like Falco for monitoring syscalls and capabilities, and implementing admission controls via OPA Gatekeeper or Pod Security Admission to enforce security best practices, thereby hardening the cluster against unauthorized access and dangerous configurations.

OPA Gatekeeper is a powerful Kubernetes admission controller that enforces policies using Rego rules. It utilizes ConstraintTemplates and Constraints to validate, mutate, or deny API requests at the cluster admission stage. This tool is essential for implementing policy-as-code practices, ensuring that Kubernetes deployments adhere to organizational security standards, compliance requirements, and best practices, such as mandating labels or blocking privileged containers.

This skill covers implementing Open Policy Agent (OPA) and Gatekeeper for robust policy-as-code enforcement. Learn to write complex Rego policies, deploy OPA Gatekeeper as a Kubernetes admission controller, and integrate policy evaluation into CI/CD pipelines to enforce security and compliance across clusters.

AegisOps-AI is a professional-grade 'Living Pipeline' that integrates advanced AI reasoning directly into the SDLC. It acts as an intelligent gatekeeper, automating high-stakes audits across three domains: identifying memory vulnerabilities in Linux Kernel patches, detecting massive cost drifts in Terraform plans, and translating natural language security intent into hardened Kubernetes manifests.

A powerful pre-action hook designed to enforce rigorous checks before AI agents modify code, create files, or execute destructive commands. Instead of relying on superficial self-evaluation, GateGuard forces the LLM to gather concrete facts (like dependencies, data schemas, and impacted modules), significantly improving code reliability and architectural depth. It provides multiple gates for edits, writes, and destructive bash commands.

This skill implements advanced 'Gatekeeper' logic to optimize AI agent performance in long-running workflows. It prevents context window bloat by sharding metadata, allocating token budgets, and enforcing Atomic Precision to deliver purely functional, filler-free responses. Ideal for complex coding, multi-step reasoning, and large document analysis where conciseness is critical.

A comprehensive playbook detailing advanced techniques for bypassing core macOS security features, including TCC, Gatekeeper, SIP, and sandbox restrictions. This guide is essential for authorized red team operations and penetration testing targeting macOS endpoints, covering methods like direct database manipulation, extended attribute removal, and privilege escalation paths.

This skill enforces an algorithm-first discipline, requiring the user to state the time and space complexity (Big-O), the intended data structure, and the core algorithm family before writing any complex code (loops, queries, recursion). It serves as a critical gatekeeper to prevent common performance pitfalls like O(n²) complexity, N+1 database queries, and brute-force implementation errors, significantly improving code robustness and efficiency.