Skill UI

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.

Designs comprehensive, production-ready observability strategies by integrating metrics, logs, and traces. This tool guides the setup of SLI/SLO frameworks, optimizes noisy alerting configurations, and generates detailed dashboards, ensuring deep visibility into service health and performance.

This skill specializes in implementing Service Level Objectives (SLOs) and Service Level Indicators (SLIs) to enforce reliability standards. It guides users in designing comprehensive SLO frameworks, calculating error budgets, and building robust monitoring systems. Use this when you need to establish data-driven reliability targets, balance feature velocity with technical health, and align service performance directly with core business objectives.

A comprehensive workflow for systematically reviewing medical evidence. It allows users to search databases for clinical studies, build curated citation collections, grade evidence using established frameworks like GRADE, and generate professionally formatted, structured reports in academic citation styles (e.g., AMA). Ideal for conducting literature reviews and supporting clinical research. This tool helps transform raw medical data into actionable, structured knowledge.

This skill coordinates the complex parallel execution of end-to-end, integration, and unit tests across multiple frameworks (e.g., Jest, Playwright, pytest) and CI/CD environments. It manages test splitting, worker allocation, tiered execution strategies, and aggregates results into unified reports. Ideal for optimizing the testing lifecycle and ensuring robust quality assurance in large-scale, multi-component applications. Key functions include intelligent retry logic for flaky tests and building CI pipelines (e.g., GitHub Actions matrix).

Automates PCI DSS validator work by guiding advanced security practitioners through best practices, generating production-ready code/configurations, and validating results against compliance frameworks.

Expert skill for building robust, enterprise-grade PHP applications using modern features (PHP 8.3+), major frameworks (Laravel, Symfony), and strict architectural patterns. Specializes in implementing typed DTOs, value objects, dependency injection, and ensuring high test coverage for secure REST/GraphQL APIs.

This skill specializes in designing, optimizing, and evaluating prompts for Large Language Models (LLMs). It allows users to generate optimized prompt templates, structured output schemas (e.g., JSON mode, function calling), and comprehensive test suites. Use this skill when building new LLM applications, implementing complex reasoning patterns like Chain-of-Thought, defining system guardrails, or building robust evaluation frameworks to measure and improve model performance.

This skill guides users through building a minimal yet comprehensive working application on the Replit platform. It demonstrates how to integrate and use core platform services such as the built-in Key-Value Database, Object Storage for file handling, user Authentication, and standard web frameworks (Express/Flask). Use this guide when starting a new Replit project or when learning the foundational infrastructure services provided by the platform.

This skill provides a comprehensive, expert guide to the entire reverse engineering lifecycle. It covers advanced techniques for binary analysis, including static analysis (disassembly, metadata extraction, control flow mapping) and dynamic analysis (API hooking, memory tracing). Mastery includes utilizing industry-leading tools such as IDA Pro, Ghidra, radare2, and specialized frameworks like pwntools and angr. The methodology is structured for secure research, CTF challenges, and vulnerability assessment, emphasizing best practices and ethical use.

This skill simulates an expert cybersecurity auditor specializing in DevSecOps methodologies and comprehensive security assurance. It guides users through running detailed security audits, performing threat modeling, and assessing vulnerabilities (e.g., IDOR). Capabilities cover SAST, DAST, cloud security posture, zero-trust architectures, and compliance adherence to major frameworks like GDPR, HIPAA, and PCI-DSS, ensuring security is integrated throughout the entire SDLC.