Skill UI

Grype is an open-source vulnerability scanner by Anchore that inspects container images, filesystems, and SBOMs for known CVEs. It leverages Syft-generated Software Bill of Materials (SBOMs) to match packages against multiple databases including NVD, GitHub Advisories, and OS-specific feeds. It is ideal for security assessments, CI/CD integration, and implementing severity-based build gates.

Vibers provides a human code review workflow for AI-generated GitHub projects; add the collaborator, GitHub Action, and commit guidance to receive spec- and security-focused feedback plus follow-up PR fixes.

AKF is the native metadata format specifically designed for tracking AI-generated or AI-modified content. It allows users to stamp files (including DOCX, PDF, images, and code) with detailed trust scores, source provenance, and compliance metadata. This tool is essential for professional workflows requiring strict auditing, compliance assurance, and verifiable data lineage, especially concerning regulations like the EU AI Act, HIPAA, and SOX.

This skill detects AI-generated deepfake audio used in voice phishing (vishing) attacks. It functions by extracting critical spectral features (including MFCCs, spectral centroid, and zero-crossing rate) and passing them through advanced machine learning models (like Random Forest and Gradient Boosting). The system supports batch forensic analysis, provides confidence scores, and generates detailed reports to verify the authenticity of recorded voice calls, making it essential for cybersecurity incident response and fraud investigation.

This skill is designed to detect and rewrite text that exhibits common characteristics of AI-generated Chinese writing, such as rigid structures, mechanical connectors, and over-polished phrasing. It helps users 'de-AI' their content by restoring natural human rhythm. Key use cases include reducing AIGC signals in academic papers (for CNKI/VIP checks), and converting the writing tone to specific styles like Zhihu, Xiaohongshu, or literary prose.

Build production-quality, accessible, responsive user interfaces. Use for creating or modifying components, layouts, state management, and ensuring WCAG compliance. Focuses on design system adherence, avoiding AI-generated aesthetics, and delivering polished, professional UI.

Provides the Google Model Armor CLI to filter user-generated content and run template-guided sanitization for prompts or responses, helping teams enforce safety policies during automation workflows and schema-driven inspections.

An advanced, AI-powered agent designed to generate comprehensive and workable unit tests for virtually any programming language (e.g., Python, C#, Java, Go, TypeScript). It operates via a sophisticated multi-agent pipeline (Research → Plan → Implement → Build → Test → Fix → Lint). This ensures generated tests are not only written following project conventions but also compile, pass all tests, and effectively improve code coverage.

This tool scaffolds a complete, production-ready Model Context Protocol (MCP) server project written in Rust. It utilizes the official `rmcp` SDK to ensure full compatibility. The generated structure includes modules for handling logic, defining tools, managing prompts, and providing resources. Users can configure different transports (stdio, SSE, HTTP) and immediately run the server for integration testing or production use.

A comprehensive tool for planning and auditing programmatic SEO pages generated at scale from structured data sources (CSV, JSON, APIs). It guides best practices for designing templates, defining scalable URL systems, establishing internal linking strategies (Hub/Spoke), and implementing robust quality gates. Use this when ensuring content uniqueness, preventing thin content penalties, and mitigating risks associated with large-scale, data-driven content generation.

Utilize advanced media intelligence to analyze audio, image, video, and text for synthetic manipulation and AI-generated content. This skill detects deepfakes, traces the original AI synthesis source, applies and detects watermarks, verifies speaker identity, and provides comprehensive media provenance analysis, ensuring media authenticity claims are rigorously supported.

This skill is designed for scenarios requiring complex, multi-step task decomposition. Instead of asking an Agent to perform the task directly, it guides the process of requesting a clear, actionable, sequential execution plan from a stronger Agent. The core function emphasizes that the user must execute the generated plan themselves, ensuring the output is a roadmap, not a final answer.