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Found 130 Skills
Use when Java XML-RPC API work requires contract decisions for fault signaling and interoperability, including defining XmlRpcException-based failures, replacing void returns with explicit operation results, reviewing handlers for return-code anti-patterns, and migrating DTOs from Serializable to JAXB.
Automates architecture validation for Clean Architecture, Hexagonal, Layered, and MVC patterns. Detects layer boundary violations, dependency rule breaches, and architectural anti-patterns. Use when asked to "validate architecture", "check layer boundaries", "architectural review", before major refactoring, or as pre-commit quality gate. Adapts to project's architectural style by reading ARCHITECTURE.md.
Code review and PR review skill for Python PySide6/Qt 6.8+ applications. Focuses on modern best practices, performance, thread safety, signal/slot patterns, Model/View architecture, QML integration, and async patterns. Use when reviewing Python Qt code, PySide6 PRs, GUI application code, or when asked to review code that uses QtWidgets, QtQuick, QtCore, QtGui, or any Qt module. Catches common anti-patterns, memory issues, thread violations, and suggests modern Qt 6.8+ idioms.
Create and optimize CLAUDE.md memory files or .claude/rules/ modular rules for Claude Code projects. Comprehensive guidance on file hierarchy, content structure, path-scoped rules, best practices, and anti-patterns. Use when working with CLAUDE.md files, .claude/rules directories, setting up new projects, or improving Claude Code's context awareness.
Checks session scope mismatch, streaming resource holding, missing cleanup, pool config, error path leaks, factory vs injection anti-patterns.
Expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. Use when selecting architecture patterns, choosing Azure services, or implementing production-ready solutions.
Deep code simplification, refactoring, and quality refinement. Analyzes structural complexity, anti-patterns, and readability debt, then applies targeted refactoring preserving exact behavior. Language-agnostic: Python, Go, TypeScript/JavaScript, Rust. Use this skill when the goal is simplification and clarity rather than bug-finding. Triggers on: "simplify this code", "clean up my code", "refactor for clarity", "reduce complexity", "make this more readable", "code quality pass", "tech debt cleanup", "run the code refiner", "simplify recent changes", "this code is messy", "too much nesting", "this function is too long", "clean this up before I PR it", "tidy up my code", cyclomatic complexity, cognitive complexity, code smells.
Scans .NET code for ~50 performance anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O with tiered severity classification. Use when analyzing .NET code for optimization opportunities, reviewing hot paths, or auditing allocation-heavy patterns.
XAF Memory Leak Prevention - event handler symmetry (OnActivated/OnDeactivated/Dispose), ObjectSpace scoped disposal with using statement, batch processing large datasets, IDisposable pattern for controllers with List<IDisposable> tracker, WeakEventSubscription, static reference anti-patterns, CollectionSource disposal, Session/HttpContext/Application anti-patterns (WebForms), ObjectSpacePool, controller lifecycle tracking, NavigationMonitor, warning signs, diagnostic tools (dotMemory, PerfView, XAF Tracing). Use when diagnosing memory leaks, auditing controller disposal, reviewing ObjectSpace lifetime, or reviewing Session usage in DevExpress XAF applications.
Best practices for writing MSTest 3.x/4.x unit tests. Use when the user needs to write, improve, or review MSTest tests, including modern assertions, data-driven tests, test lifecycle, and common anti-patterns. Covers MSTest.Sdk, sealed classes, Assert.Throws, DynamicData with ValueTuples, TestContext, and conditional execution.
Extract learnings about skill creation/improvement from a session and propagate them to the central skill learnings file, then sync to appropriate skills. Use when a session revealed patterns, anti-patterns, or insights about structuring skills. Invoke via /update-skill-learnings or after skill creation/improvement sessions.
Learns from DAG execution history to improve future performance. Identifies successful patterns, detects anti-patterns, and provides recommendations. Activate on 'learn patterns', 'execution patterns', 'what worked', 'optimize based on history', 'pattern analysis'. NOT for failure analysis (use dag-failure-analyzer) or performance profiling (use dag-performance-profiler).