Skill UI

Implements schema.org JSON-LD across webpages so search engines grasp content intent and serve rich results like FAQs, breadcrumbs, and products, with validation checklists and contextual guidance.

This skill validates API responses against predefined schemas, including OpenAPI and JSON Schema, to ensure strict contract compliance and data integrity. Use it for implementing robust contract tests in middleware or CI/CD pipelines, detecting schema drift, and guaranteeing backward compatibility across API versions.

This tool rigorously validates API schemas against industry standards, including OpenAPI 3.0/3.1, JSON Schema, and GraphQL SDL. It performs structural analysis to detect incomplete schemas, inconsistent naming, undocumented endpoints, and critical breaking changes. Use it within your CI/CD pipeline to ensure API contracts are robust, compliant, and maintainable before release.

Helps implement, audit, and validate JSON-LD schema markup so websites earn rich results, clarify content for AI search, and track structured data issues reported in Search Console before launching updates.

An expert guide for developing production-grade AI applications, chatbots, and generative UIs using the Vercel AI SDK, Next.js, and React. Covers core concepts including streaming text (`streamText`), managing chat state (`useChat`), implementing complex tool/function calling, and ensuring robust structured data generation (JSON schemas) across multiple LLM providers.

Detect, validate, or generate Schema.org JSON-LD structured data for web pages. Supports rich result types, checks deprecated schemas, and provides ready-to-use templates. Ideal for SEO specialists and developers.

Audit, validate, and enhance GEO structured data by detecting existing JSON-LD/microdata/RDFa, checking schema.org compliance, and generating ready-to-use JSON-LD to boost AI discoverability.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

This solution enforces strict data contract validation for all APIs using OpenAPI Specification (OAS) and JSON Schema. It ensures that all incoming requests and outgoing responses conform to predefined structures. By implementing validation at both the API Gateway (runtime) and during development (shift-left), it effectively prevents critical security vulnerabilities such as SQL injection, XSS, unauthorized data leakage, and mass assignment.

Generates implementation-ready JSON-LD schema markup for 10 types (e.g., FAQPage, Product, Article). It validates all fields against Google rich result eligibility rules, flags missing data with fix instructions, and provides clean, ready-to-paste script blocks to optimize search engine visibility and achieve rich results.

Analyzes Excel and CSV uploads with DuckDB, inspecting schemas, running SQL, summarizing statistics, and exporting results so users can explore structured data efficiently.

Command-line wrapper around the Google Workspace Admin SDK that fetches audit logs, activity streams, and usage reports (customer, entity, user) for administrators, with schema inspection helpers to craft --params and --json flags.