Skill UI

Analyzes module coupling using the three-dimensional model from Balancing Coupling in Software Design to evaluate dependency strength, distance, and volatility, pinpoint architectural smells, and guide decoupling or integration decisions.

Analyzes code coverage during fuzzing campaigns to assess harness quality, spot blockers like magic values, and guide instrumentation or corpus updates.

Assists with coverage report analyzer tasks within test automation, offering best-practice guidance, code/config templates, step-by-step workflows, and validation to keep reports reliable.

A comprehensive guide derived from C++ Core Guidelines, enforcing modern, safe, and idiomatic practices for C++17, C++20, and C++23. It emphasizes crucial principles like RAII, type safety, immutability, and proper resource ownership using smart pointers. Use this when writing new features, reviewing existing code, or making architectural decisions to ensure code quality and consistency.

A specialist guide for designing, implementing, and optimizing high-performance C++ applications using modern standards (C++20/23). Expertise covers advanced topics like concepts, coroutines, template metaprogramming, and zero-overhead abstractions. Use this when tackling complex memory management, concurrency bottlenecks, or integrating build systems via CMake, ensuring code meets industrial quality standards through rigorous sanitization and profiling.

Guides an agent through C++17/20 testing with CMake, CTest, and GoogleTest/Mock, covering new or flaky tests, CI gates, coverage builds, and sanitizer diagnostics to keep regression safety in place.

Automates cpu profiler configuration guidance for performance testing, covering load, stress, benchmarking, and monitoring scenarios to ensure best practices.

This skill provides a comprehensive guide to implementing the Command Query Responsibility Segregation (CQRS) pattern. It is crucial for separating read and write concerns, allowing independent scaling of read models, optimizing complex query performance, and building robust, event-sourced architectures when read and write data models differ.

Automates intelligent alert rule creation for SREs and DevOps, guiding through thresholds, routing, escalation, and runbooks to monitor latency, error rates, throughput, resource use, availability, and SLO violations.

Transforms detailed user requirements into secure, production-ready Ansible playbooks that automate server configuration, software deployments, and infrastructure workflows across multiple platforms for repeatable DevOps operations.

Automates crafting APM dashboards by identifying required metrics, selecting golden signals, and generating configurations for Grafana, Datadog, or other monitoring platforms, so you can quickly visualize application health and performance.

Builds robust and secure webhook receiver endpoints capable of handling events from external services (e.g., Stripe, GitHub). Key features include HMAC signature verification, idempotency checking, and asynchronous queue processing to prevent timeouts and ensure reliable event ingestion.