Skill UI

This skill provides comprehensive code reviews, helping users assess code quality, identify various potential issues (syntax, logic, security, performance), and receive actionable suggestions for improvement. It generates a detailed, structured report covering a summary, found issues, and quality metrics.

This skill generates structured and standardized Git commit messages following the Conventional Commits specification. By analyzing code changes (via diff or status), it helps developers automatically create clear, actionable, and searchable commit history messages, ensuring consistency across the project.

This skill automatically generates comprehensive unit tests based on provided source code. It supports multiple programming languages (Python, JavaScript, Java, Go, Rust) and popular testing frameworks (pytest, Jest, JUnit). Use it to improve code coverage, test boundary conditions, and validate error handling efficiently, saving manual testing time.

This tool outlines the complete end-to-end migration process from an Oracle database environment to SQL Server. It automates schema conversion, data migration, and generates necessary assessment reports by simulating SSMA console operations. Ideal for database architects and developers planning heterogeneous database migrations.

Generates a highly polished, self-contained single-page HTML landing page optimized for maximum conversion. It incorporates advanced features like 3D CSS animations, GSAP scroll effects, and mouse parallax depth. To ensure accuracy, the skill uses a structured intake process (product pitch, target audience, brand colors, and tone) to build a conversion-ready page that reflects the actual product, not generic boilerplate. Outputs a single, deployable HTML file.

This skill provides an end-to-end solution to transform existing REST APIs, defined by OpenAPI or Swagger specifications, into functional MCP servers. It maps every API operation to a dedicated, callable LLM tool, automatically generating robust parameter schemas (Zod) and handling authentication wiring. Use this to expose internal or third-party APIs to LLMs, providing a complete workflow from spec ingestion to local testing and cloud deployment.

A comprehensive tool for the full lifecycle management of applications within the Lark ecosystem (Feishu/Miaoda). It supports three development paths: local full-stack development, HTML static hosting, and cloud-based AI session generation. Use this when creating, updating, deploying, or publishing any complex system, tool, or platform application.

This skill generates comprehensive Entity Relationship Diagrams (ERDs) and database schemas as D2 source code from an existing Entity Framework Core codebase. It analyzes DbContexts, DbSet declarations, Fluent API mappings, and migrations to accurately visualize tables, columns, primary/foreign keys, relationships (including many-to-many joins), owned types, and constraints. The output is a structured .d2 file, suitable for rendering into SVG or PNG, helping developers document the persistence model.

This skill guides the creation and maintenance of a `.geminiignore` file. By systematically filtering out machine-generated noise—such as build artifacts, dependency lock files, logs, and caches—it significantly optimizes the AI agent's context window. This process improves processing speed and, critically, reduces token consumption costs (FinOps).

This skill serves as a compatibility demonstration to verify that the Hermes Agent can successfully parse and load an SKILL.md file generated from an MDA source. It confirms that the compiled structure, including specific frontmatter and reserved metadata namespaces, survives the round-trip compilation process, ensuring structural integrity for the agent's skill registry.

This skill generates robust JSON-LD structured data markup for various web components, including blogs, FAQs, tools, and SaaS pages. By implementing standard Schema.org types (WebSite, Article, FAQPage, etc.), you can significantly improve your SEO, boost click-through rates (CTR), and provide clear context to both search engines and AI systems. Includes implementation guidance for modern frameworks like Next.js.

This guide provides a systematic, safe workflow for refactoring rapidly developed or AI-generated fullstack applications. It focuses on identifying and removing dead code, fixing broken imports, and consolidating repetitive logic while strictly maintaining existing API contracts, routes, and core functionality. Use this before launch to ensure a stable, maintainable production baseline, following a 'surgery, not demolition' philosophy.