Skill UI

Guides senior data scientists through designing controlled experiments, engineering structured features, training ML models, and translating results into decisions using Python, R, SQL, and tools like Scikit-learn, XGBoost, and MLflow.

An expert architect specializing in designing and optimizing service mesh using industry leaders like Istio and Linkerd. This skill provides deep knowledge of cloud-native networking patterns, enabling secure, reliable microservices communication. It covers advanced topics including zero-trust networking, mTLS configuration, sophisticated traffic management (e.g., canary and blue-green deployments), observability integration, and multi-cluster federation.

This skill provides comprehensive guidelines for architecting and developing high-quality, maintainable software. It is deeply rooted in Clean Architecture and Domain-Driven Design (DDD) principles. It covers best practices for code decomposition, naming conventions, separation of concerns, and avoiding common anti-patterns. Use this skill when designing, analyzing, or developing complex, domain-specific software systems.

A comprehensive skill for optimizing complex SQL queries, designing robust database schemas, and troubleshooting performance bottlenecks across various dialects (PostgreSQL, MySQL, etc.). Use this when queries are slow, complex set-based logic is needed (CTEs, Window Functions), or when structuring/migrating a database schema. It provides detailed query plan analysis, advanced indexing strategies, and industry best practices.

This skill provides comprehensive performance optimization and best practices for PostgreSQL, maintained by Supabase. It guides users on optimizing database performance, covering critical areas such as writing efficient SQL queries, designing robust schemas, implementing proper indexing, managing connection pooling, and enforcing Row-Level Security (RLS).

This skill provides a comprehensive framework for designing optimal team structures for early-stage startups. It covers role-by-role hiring plans, compensation benchmarks (salary and total compensation), and equity allocation strategies, guiding founders from Pre-Seed through Series A to ensure scalable growth and proper talent investment.

This skill provides advanced expertise in Infrastructure as Code (IaC) using Terraform and OpenTofu. It covers designing robust, reusable modules, managing complex multi-cloud state backends, and implementing enterprise-grade CI/CD pipelines. It specializes in governance, Policy-as-Code, and achieving GitOps compliance for full infrastructure automation.

This comprehensive skill provides advanced architectural patterns for implementing robust API throttling and rate limiting policies. It covers critical concepts like concurrency limiting, priority queuing, circuit breakers, and adaptive throttling that adjust limits based on real-time backend health metrics (p95/p99 latency). Use this when designing resilient, scalable backend services that must protect themselves from overload and maintain stability under high load.

This skill provides advanced guidelines for designing robust and effective tools specifically for autonomous AI agents. It shifts the focus from traditional developer APIs to contracts optimized for Language Models (LLMs). Key topics covered include treating tool descriptions as prompt engineering, implementing namespacing, applying the Consolidation Principle, and utilizing Architectural Reduction patterns (like file system access) to maximize agent reliability and workflow complexity.

This skill focuses on implementing advanced TypeScript features to build robust, type-safe applications. It covers designing type-first APIs, utilizing generics, implementing custom type guards, branded types, and managing complex state with discriminated unions. It is essential for full-stack development, monorepo setups, and projects requiring maximum type integrity (e.g., integrating with tRPC).

This guide details the production-grade reference architecture for running complex GPU compute workflows on Vast.ai. It covers the foundational three-tier pattern—Orchestrator, GPU Workers, and Artifact Storage—providing blueprints for job queue management, fault-tolerant training pipelines, and robust checkpointing. Use this when designing scalable and reliable ML/AI training systems.

Expert capability for designing and implementing complex semantic search systems using vector databases. Proficient in embedding strategies, index optimization (HNSW, IVF), and advanced retrieval methods like RAG and hybrid search. Masters major platforms including Pinecone, Weaviate, Qdrant, Milvus, and pgvector for building sophisticated recommendation and similarity search applications.