Skill UI

Generate complete, production-ready REST API implementations from existing OpenAPI specifications or database schemas. This skill scaffolds all necessary CRUD endpoints (GET, POST, PUT, DELETE) across multiple frameworks (Express, FastAPI, Spring Boot, etc.), automatically incorporating features like pagination, filtering, validation, and robust authentication middleware. Ideal for rapidly bootstrapping complex backend services from defined data models.

Automatically produce mocks, stubs, spies, or fakes for unit tests by analyzing dependencies and using frameworks like Jest or Sinon, so you can isolate modules quickly without hand-writing boilerplate doubles.

Aggregates test results from multiple frameworks, computes coverage/pass rate trends, and produces stakeholder-friendly HTML, PDF, or JSON reports for CI/CD test reports, coverage checks, failure analysis, or historical comparisons.

Automatically analyzes source files, detects or honors the requested testing framework, and produces comprehensive unit tests with mocks, edge cases, and assertions for Jest, pytest, JUnit, and other frameworks whenever users ask to generate tests.

A comprehensive guide for building professional, high-performance native iOS applications. Covers modern frameworks like SwiftUI and Swift 6, alongside deep expertise in UIKit, Core Data, networking (REST/GraphQL), performance profiling, and full App Store lifecycle management. Ideal for developers needing guidance on modern Apple ecosystem best practices.

Guides frontend developers through keyboard navigation testing, offering best-practice advice, code snippets, and automated validation for accessibility, frameworks, and performance.

A comprehensive guide to optimizing LLM API usage within LangChain frameworks. Techniques include implementing token usage tracking, model tiering to route tasks based on complexity, utilizing caching to eliminate duplicate calls, prompt compression for efficiency, and enforcing strict budget limits to manage operational costs effectively.

This comprehensive guide walks developers through migrating complex LLM codebases from raw SDK calls (OpenAI, Anthropic) or legacy frameworks (LlamaIndex) to the structured LangChain framework. It covers code assessment, pattern-by-pattern migration, advanced agent construction, robust tool calling, and transforming custom RAG pipelines into scalable, standardized chains.

A comprehensive guide for solo founders and indie hackers to launch profitable micro-SaaS products quickly. Covers the entire lifecycle: idea validation frameworks, building a Minimum Viable Product (MVP) using modern solo-founder stacks, implementing effective pricing psychology, and executing high-impact launch playbooks. Ship a real business in weeks, not months.

This skill outlines a comprehensive, low-downtime process for migrating APIs between different versions, frameworks, or platforms. It guides the implementation of advanced architectural patterns like the Strangler Fig pattern, traffic shadowing, and canary deployments. Use this when upgrading a monolithic API to microservices or transitioning between incompatible API versions.

A comprehensive skill set for building, deploying, and managing production-grade Machine Learning systems. Expertise spans modern frameworks (PyTorch, TensorFlow), model serving using Kubernetes, advanced feature engineering (Feast, Tecton), and robust MLOps practices (monitoring, A/B testing, CI/CD). Focuses on delivering scalable, reliable, and business-value-driven AI solutions.

This skill provides comprehensive guidance on training Mixture of Experts (MoE) models, including architectures like Mixtral and DeepSeek-V3. It details techniques for achieving large-scale model capacity with significantly reduced computational costs (e.g., 5x reduction vs. dense models). Topics covered include top-k routing, load balancing, expert parallelism, and integration with frameworks like DeepSpeed and HuggingFace for efficient, resource-constrained training.