Skill UI

This comprehensive pipeline guides users from a vague research concept to a fully structured, testable academic proposal. It first refines the core methodology (research-refine) to establish a stable thesis, and then generates a detailed, claim-driven experiment roadmap (experiment-plan). This end-to-end workflow ensures that the final academic output is both elegant and empirically validated.

Grype is an open-source vulnerability scanner from Anchore. It inspects container images, filesystems, and SBOMs for known CVEs. It leverages Syft-generated SBOMs to match packages against multiple vulnerability databases (NVD, GitHub Advisories). Use it for security assessments, auditing, and integrating into CI/CD pipelines to enforce vulnerability standards and manage supply chain risks.

Use Trivy to automate comprehensive vulnerability detection (CVEs, misconfigurations) in Docker container images within CI/CD pipelines. This skill guides users on establishing robust quality gates—such as integrating into GitHub Actions or GitLab CI—to ensure that only secure images are pushed to production registries, covering OS packages, dependencies, and Dockerfile best practices.

Kubesec is a powerful open-source tool designed to perform comprehensive security risk analysis on Kubernetes resource manifests (YAML/JSON). It automatically detects critical misconfigurations, potential privilege escalation vectors, and deviations from industry security best practices. It provides actionable scoring and hardening recommendations, making it essential for CI/CD pipelines, security auditing, and automated compliance checks.

This skill provides comprehensive guidance on hardening GitHub Actions CI/CD pipelines against modern supply chain attacks, credential theft, and privilege escalation. It teaches best practices such as pinning actions to immutable SHA digests, minimizing GITHUB_TOKEN permissions, preventing script injection from untrusted inputs, and implementing required approval gates for critical deployments.

Orchestrates WCAG 2.2 Level A/AA scans, fixes, and verifications across React, Next.js, Vue, Angular, Svelte, and plain HTML codebases, producing before/after diffs, contrast checks, compliance reports, and CI/CD-ready hooks.

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.

Master the use of the `gh` CLI to interact with core GitHub features. This guide covers managing issues, checking Pull Request statuses, listing and debugging CI workflow runs, and executing advanced data queries via the GitHub API. Essential for automating DevOps workflows and debugging CI/CD pipelines directly from the terminal.

This skill provides a systematic pipeline for safely executing large-scale code refactors across multiple files or subsystems. It first performs parallel, dependency-aware analysis to map the entire scope, synthesizing a single, actionable plan. The process then breaks the work into independent 'work packets,' which are executed sequentially or in parallel by specialized worker agents, ensuring strict dependency management and behavior parity throughout the entire process.

A comprehensive guide to designing scalable, cost-effective, and compliant architectures on Microsoft Azure. This skill covers the entire lifecycle, from gathering detailed business requirements (SLA, RPO/RTO) and selecting appropriate service patterns (AKS, Serverless, Data Factory), to generating Infrastructure as Code (IaC) using Bicep. It also includes steps for cost optimization, reserved instance planning, and setting up robust CI/CD pipelines via Azure DevOps or GitHub Actions.

Provides Playwright-driven browser automation for scraping structured data, driving multi-step workflows, managing sessions and anti-detection tactics, and capturing screenshots/PDFs in production pipelines.

This comprehensive workflow guides the design, optimization, and deployment of scalable, cost-effective Google Cloud Platform (GCP) architectures for both startups and large enterprises. It covers the full lifecycle, from gathering detailed requirements (compliance, SLA) and recommending optimal patterns (Serverless, GKE, Data Pipelines) to estimating costs, generating Infrastructure as Code (IaC) using Terraform, setting up CI/CD pipelines, and completing a thorough security review.