Skill UI

This guide details how to use Shopify Metafields and Metaobjects via the GraphQL Admin API. Metafields allow attaching key-value custom data to existing resources (like products or orders), while Metaobjects enable defining entirely new, structured content types. Together, they provide a powerful way for developers to model complex custom data, often eliminating the need for external databases to extend e-commerce functionality.

This catalog provides comprehensive abstractions, hooks, and types for developing complex administrative web forms. It covers data binding, field rendering, state management, and robust data validation. By utilizing components like FieldBuilder, FormView, and useForm, developers can create structured, reusable, and highly maintainable form interfaces.

This guide details how to implement a highly customized CMS field type within the Webiny framework. It covers extending DataFieldBuilder, defining complex validation logic, creating a FieldType.Factory, and proper registration using Dependency Injection (DI). Furthermore, it demonstrates module augmentation for enhancing TypeScript autocomplete in the fields registry, ensuring a complete, robust development workflow and exposing a fluent builder API.

This skill allows developers to deeply customize the website builder's page settings. You can add entirely new settings tabs (e.g., Publishing, Analytics) or modify existing groups by injecting custom fields. It leverages PageSettingsGroup and PageSettingsGroupModifier interfaces, ensuring all custom data is safely managed and stored within the doc.extensions object, preventing conflicts with built-in system properties.

This minimal example demonstrates the structure of an MDA source file, including advanced frontmatter fields (metadata) and how to properly implement relationship-graph footnotes. It serves as a crucial reference fixture for users learning the MDA source format.

This CLI alias serves as a system maintenance tool for PUA agent state. It scans for stale PUA agent data, identifying and safely removing only confirmed orphan records to maintain system integrity. It also manages configuration files, ensuring unknown fields are preserved when updating the primary config JSON.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

Direct access to Google's SEO APIs including Search Console, PageSpeed Insights, CrUX field data, Indexing API, and GA4 organic traffic. Provides real-time field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use for SEO analysis, website performance monitoring, and search optimization.

Combines a curated Japanese NLP resource dataset with live web research to produce an up-to-date trend report on models, tooling, benchmarks, embeddings, speech, and related subfields.

This skill demonstrates OpenCode's compatibility with MDA-compiled SKILL.md files. It verifies that the loader correctly parses crucial frontmatter fields (like name, description, and metadata) after the source has gone through the MDA compilation process, ensuring robust skill integration and data integrity.

This utility reads structured JSON outputs from multi-search-engine APIs (e.g., Google Scholar, arXiv) provided via standard input. It converts these normalized records into a clean, minimal BibTeX format, suitable for academic papers. It intelligently preserves crucial metadata like DOI, authors, and years while automatically handling data sanitization, deduplication of DOIs, and protecting complex fields like corporate names.

A robust toolkit for deterministic, structural PDF manipulation. This skill allows users to perform programmatic tasks such as extracting text and tables from reports, merging multiple PDF files, splitting documents by page ranges, filling out form fields, or generating entirely new PDFs from structured data (e.g., JSON). It is designed for explicit, byte-level operations, distinguishing it from LLM-based natural language rewriting tools.