Skill UI

Implement a comprehensive observability stack for Webflow Data API v2 integrations. This skill provides structured code using Prometheus metrics, OpenTelemetry distributed tracing, and structured logging (pino) to monitor API call frequency, latency, error rates, and rate limit usage. Ideal for developers building robust, production-grade Webflow-connected SaaS applications that require deep performance insights and reliable alerting.

This comprehensive guide details the process for upgrading the `webflow-api` SDK, specifically migrating from Webflow Data API v1 to v2. It covers critical breaking changes, including authentication method updates, endpoint structure changes (e.g., v1 to v2 base URL), and method call changes (e.g., PUT to PATCH). It provides detailed maps and code examples to ensure developers can maintain robust and up-to-date Webflow integrations.

This module provides a centralized catalog of configuration abstractions for administrative panels. By defining standardized interfaces (like AdminConfig), it ensures type safety and consistency when accessing application settings across different parts of the web application. Developers should import the specific abstraction needed to maintain robust code structure.

This comprehensive guide outlines best practices for designing and organizing robust backend APIs within the Webiny framework. It details core architectural patterns, including singleton Services (for external APIs or cohesive domain logic), transient UseCases (single-method business orchestrators), and Repository patterns for persistence. Use this skill to structure features, manage dependencies, and ensure scalable, maintainable backend code.

This guide details how to programmatically define, configure, and extend Headless CMS content models using the ModelFactory pattern. It covers defining various field types (text, richText, asset, ref, object, etc.), applying advanced validation rules, setting up layouts, and managing API access control. It is essential for developers building custom content structures in a robust, code-driven manner.

This guide details how to extend the Webiny CLI by adding custom commands using the `CliCommandFactory` pattern. Developers can define command structures, handle typed parameters, and implement custom logic for various tasks, including data migration, code generation, deployment scripting, or system health checks. It covers command definition, parameter handling, and formatted terminal output using the `Ui` service.

This guide details the standard project layout for Webiny applications. It explains the critical role of `webiny.config.tsx` as the single, central configuration point for registering all custom extensions. It covers various extension types, including API endpoints, Admin UI components, Infrastructure configuration (AWS), and CLI commands, helping developers understand where and how to integrate custom code.

XcodeBuildMCP is a unified skill set designed to streamline the entire mobile and desktop development lifecycle. It replaces raw command-line tools like xcodebuild, xcrun, and simctl, providing structured workflows for iOS, macOS, watchOS, tvOS, and visionOS. Capabilities include project discovery, managing simulator and physical device workflows, advanced UI automation (gestures, view inspection), robust logging, and deep debugging using LLDB. It simplifies complex build, test, and run operations across multiple platforms.

This powerful compiler ingests heterogeneous research inputs, including PDF papers, code repositories, experiment logs, and raw notes. It transforms this diverse data into a comprehensive, structured Agent-Native Research Artifact (ARA). The system extracts core knowledge atoms, builds cognitive maps (claims, concepts, heuristics), and generates a verifiable, executable knowledge package for advanced AI consumption and research iteration.

This tool assists engineers in transforming vague work logs into structured, evidence-backed impact statements for professional documentation. It uniquely mines Copilot CLI session logs, git commits, and GitHub PRs to reconstruct forgotten work. It enforces a mandatory 'Action → Result → Evidence' impact contract, making it indispensable for preparing performance reviews, promotion packets, and self-assessments.

Cavecrew provides three subagent presets—investigator, builder, and reviewer—that compress tool results into minimal structured output, reducing main-context usage. Ideal for code search, small edits, and diff reviews in long sessions.

Analyzes git diffs to generate narrative commit messages explaining the why behind changes, following Conventional Commits format. Helps developers write clear, meaningful commit logs for version control and pull requests by transforming raw code changes into structured stories.