Skill UI

This module provides multiple standardized abstractions for interacting with the OpenSearch API. It includes dedicated abstractions for clients, factories, and operational contexts, allowing developers to implement robust, scalable, and type-safe interactions with OpenSearch within the webiny ecosystem. Use these patterns to ensure consistent data access regardless of the specific usage pattern.

This abstraction provides the `CliCommandFactory` pattern, enabling developers to implement custom command-line interfaces (CLIs) for the Webiny ecosystem. It standardizes the process of defining, structuring, and interacting with various shell commands, ensuring robust and maintainable tooling within your application.

This skill provides a detailed guide on extending the Webiny Command Line Interface (CLI) by implementing custom commands. It utilizes the `CliCommandFactory` pattern to define structured commands, manage typed parameters, and execute complex logic. Use cases include automating data migrations, generating boilerplate code, executing custom deployment workflows, and performing CMS content exports.

This pattern provides a robust method for extending and customizing existing GraphQL APIs. Developers can implement `GraphQLSchemaFactory` to add custom root queries and mutations, injecting complex business logic and use cases directly into the API layer. It fully supports per-resolver dependency injection (DI), ensuring that every resolver has access to critical request-scoped context, such as identity and tenancy, making it ideal for building modular, enterprise-grade backend services.

This comprehensive guide provides structured troubleshooting and error handling advice for developers integrating with the Workhuman Social Recognition and Rewards APIs. It covers critical API concepts, including OAuth 2.0 authentication, managing point-based nominations, and synchronizing data with major HRIS systems like Workday and SAP SuccessFactors. Use this resource when building complex HR workflows or integrating Workhuman into platforms like Slack or Teams.

This guide provides comprehensive details for integrating with the Workhuman Social Recognition and rewards API. It covers key concepts such as OAuth 2.0 authentication, peer-to-peer recognition workflows, award configurations, and bidirectional synchronization with major HRIS systems like Workday and SAP SuccessFactors. Use this skill to build automated, engaging reward and recognition processes within enterprise applications.

This guide provides comprehensive security and integration details for the Workhuman Social Recognition and rewards API. Learn how to implement OAuth 2.0, manage peer-to-peer nominations, and sync data bidirectionally with major HRIS platforms like Workday and SAP SuccessFactors. Use cases include building custom recognition workflows and integrating with popular tools like Microsoft Teams and Slack.

This tool analyzes and refactors code to detect and correct anemic domain models. It enforces rich domain modeling patterns (Entities, Value Objects, Aggregates, Domain Events), improving encapsulation and business logic ownership. Use it when validating, reviewing, or refactoring core domain logic to ensure adherence to Domain-Driven Design (DDD) principles.

This advanced code reviewer analyzes your codebase through the principles of 12 classic software engineering books (e.g., Clean Code, DDIA, Mythical Man-Month). It detects conceptual flaws, design smells, tight coupling, missing abstractions, and architectural risks—issues that standard linters and basic AI tools often miss. Essential for major refactoring and pre-design validation.

Logic Lens is an advanced AI skill that performs deep, formal logic-driven code review. Unlike standard linters, it analyzes code for complex issues like race conditions, security vulnerabilities (SQL injection, XSS), type safety flaws, and algorithmic errors across 9 critical risk categories. It is ideal for pre-merge PR reviews, auditing sensitive code paths, and refactoring complex business logic.

Cavecrew provides a set of specialized subagents (investigator, builder, reviewer) designed for efficient code development delegation. Unlike vanilla agents, Cavecrew compresses output results, drastically reducing the token usage injected back into the main context. This allows users to maintain context over much longer, complex coding sessions, effectively preventing context exhaustion during large-scale refactoring, debugging, or multi-step feature development.