Skill UI

This guide sets up a robust local development workflow for integrating with the Gamma REST API. It includes a reusable client wrapper, a polling helper for handling asynchronous tasks, and a local mock server. Use this setup when building automation scripts, testing API calls offline, or simulating API responses without needing external service credentials or network connectivity.

A comprehensive guide for configuring API access across distinct environments (Development, Staging, Production) for SaaS services. It details architectural patterns for separating workspaces, managing environment-specific secrets (e.g., using AWS Secrets Manager), and implementing environment guards to ensure code behaves correctly and securely in different stages of deployment. Ideal for CI/CD pipeline setup and robust client-side configuration.

This skill generates robust, type-safe client Software Development Kits (SDKs) for multiple languages (including Python, TypeScript, Go, and Java) directly from OpenAPI 3.0+ specifications. It automatically handles complex API patterns such as authentication (Bearer, OAuth2), automatic retries with exponential backoff, and sophisticated pagination helpers. Use this when you need to create standardized, idiomatic client libraries to consume a defined API contract across diverse development stacks.

Generates conventional commit messages using AI by analyzing staged Git changes and recommending standardized text for features or fixes, helping teams keep commit history consistent during development.

Generates realistic database seed data and scripts for development or testing, leveraging Faker libraries to respect schema constraints, maintain relationships, and allow configurable volumes for quick population of demo or test environments.

Generates ORM models and database schemas for frameworks like TypeORM, Prisma, Sequelize, SQLAlchemy, Django ORM, Entity Framework, and Hibernate, translating user requests into ready-to-use model code or schema definitions to accelerate backend development.

This skill orchestrates a comprehensive, multi-stage Git development workflow, simulating the process from code commit to PR preparation. It leverages specialized AI agents (code reviewers, test automators, prompt engineers) to systematically enforce best practices. Key functions include code quality assessment, breaking change analysis, running unit/integration/E2E tests, and generating Conventional Commit messages, ensuring code readiness and high quality before merging.

This skill automates the complete software development workflow: staging all changes, creating a structured conventional commit message, and pushing the results to the remote repository. It is ideal for developers who have completed a feature or batch of changes and need to reliably share their work while adhering to standard Git best practices.

A collection of production-ready GitHub Actions workflow patterns designed for automating the entire software development lifecycle (SDLC). Use these templates to streamline continuous integration (CI), build Docker images, deploy to Kubernetes clusters, perform security scans, and execute matrix testing across various tech stacks.

This skill guide helps developers master best practices and architectural patterns for Godot 4 game development using GDScript. It thoroughly covers implementing game systems, managing complex state machines, utilizing signals, and optimizing performance. Use this when building robust, scalable, or advanced Godot games.

Collection of Go idioms and best practices for building robust, maintainable services, covering simplicity, zero values, interface returns, error handling, and concurrency when writing, reviewing, or refactoring Go code.

This skill simulates a senior Go developer, specializing in writing high-performance, production-grade Go applications. It covers advanced topics like concurrent programming using goroutines and channels, designing robust microservices with gRPC/REST, and optimizing code using pprof and benchmarks. It enforces idiomatic Go patterns, context propagation, and strict testing practices (table-driven, fuzzing, race detection).