Skill UI

This skill analyzes historical benchmark run data stored in JSON files. It surfaces key performance drift metrics over time, including win rate, average latency, p99 latency, and LLM-baseline cost. It is crucial for detecting subtle performance degradations or regressions that standard smoke tests might miss, ensuring stability across releases or corpus expansions.

This guide outlines a comprehensive, agent-focused testing workflow for modern C++ (C++17/20) using GoogleTest and CMake/CTest. It teaches key concepts like the TDD cycle (Red-Green-Refactor), utilizing mocking (gmock) and fixtures for isolation, setting up robust CI/CD integration, and debugging complex issues using sanitizers (ASAN, TSAN) and coverage analysis. Use this when writing, updating, or ensuring the functional robustness of C++ codebases.

This tool scaffolds a complete, canonical directory structure for creating new Claude Code plugins. It automatically generates necessary files like plugin.json, skill definitions (SKILL.md), command files, agent files, and comprehensive documentation (ADRs, README). Use it when you need to build a plugin that extends Claude Code's capabilities with custom skills, commands, and agents, ensuring adherence to the latest architectural standards.

Use CronCreate to schedule background workers that must persist even after session restarts. This utility provides various recommended schedules for critical, recurring tasks like security audits, performance optimization, memory consolidation, and documentation generation. It is essential for CI/CD pipelines, continuous monitoring, and maintaining system health.

This guide provides comprehensive testing patterns for C# and .NET applications. It covers best practices using xUnit, FluentAssertions, and advanced techniques like mocking (NSubstitute/Moq), parameterized testing, and full integration testing using Testcontainers and WebApplicationFactory. Ideal for improving test quality, coverage, and developing robust, maintainable codebases.

A comprehensive operational guide for support teams to manage complex customer billing workflows. It assists operators in diagnosing billing anomalies, processing refunds, triaging charges, and recovering customer portals. Use this when investigating billing discrepancies, assessing churn risk, or ensuring accurate subscription state and revenue management.

This utility facilitates the creation and management of Dynamic Agentic Architecture (DAA) agents. Unlike static systems, DAA agents are designed to continuously learn from interactions, adapt their behavior based on performance metrics, and propagate knowledge across multiple agents. It provides comprehensive tools for agent creation, monitoring learning progress, checking performance, manual adaptation, and knowledge sharing, ensuring robust and evolving AI workflows.

This tool guides the creation of actionable monitoring dashboards for observability platforms like Grafana and SigNoz. Instead of merely displaying raw metrics, it focuses on structuring data to answer critical operational questions: Is the system healthy? Where are the bottlenecks? What changes occurred? And what action should be taken? It transforms raw metrics into decision-making tools.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

A comprehensive methodology for accelerating large-scale data ingestion, ETL processes, backfilling, and data warehouse loading. It guides users in identifying and optimizing bottlenecks—such as source extraction, network transfer, and loading speed—while strictly ensuring data correctness and maintaining clear accounting checkpoints throughout the pipeline.

Automates the scaffolding of a complete Aggregate Root structure following Domain-Driven Design (DDD) principles. It generates necessary boilerplate files including the core entity, immutable value objects, repository interface, domain events, and unit test stubs within a specified bounded context. This tool is essential for modeling new business concepts or extending existing domain models while maintaining strong architectural integrity.

This tool scaffolds a complete directory structure for a new Domain-Driven Design (DDD) Bounded Context. It automatically generates the standard layout, including `domain`, `application`, and `infrastructure` layers, and populates index files for clean module exports. Ideal for starting new microservices, splitting monoliths, or structuring fresh modules.