Provides file paths to language-specific reference files for the test ANALYSIS skills (assertion-quality, test-anti-patterns, test-gap-analysis, test-smell-detection, test-tagging). Read this catalog to discover available extension files (e.g., dotnet.md for .NET/MSTest/xUnit/NUnit/TUnit, python.md for pytest/unittest, typescript.md for Jest/Vitest/Mocha, java.md for JUnit/TestNG, etc.). Do not invoke this reference-only skill — its bundled files are read by the quality agent and analysis skills needing framework-specific lookup tables (test markers, assertion APIs, skip annotations, sleep patterns, mystery guest indicators, integration markers, setup/teardown, tag-support capability).
MANDATORY for static source-to-test pairing: find or list source files/modules without corresponding tests, or suggest test locations from repository structure. Invoke even for a tiny package; do not substitute manual globbing. Uses Roslyn for C#/.NET and tree-sitter for Python, TS/JS, Go, Java, Rust, Ruby, Kotlin, Swift, PowerShell, and C++. DO NOT USE FOR: real line/branch/Cobertura data, coverage-backed test priorities, CRAP risk, or grading existing tests.
Audits existing tests in any language using formal, research-backed test smell names and the testsmells.org 19-smell academic taxonomy. Use when the caller asks for an academic or citable test-smell review, named smell categories, or a formal severity-ranked smell assessment. Covers Assertion Roulette, Conditional Test Logic, Mystery Guest, Eager Test, Sleepy Test, Unknown Test, Sensitive Equality, and the rest of the catalog across .NET, Python, JavaScript/TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++. DO NOT USE FOR a quick pragmatic test review (use test-anti-patterns), writing or running tests, framework migration, coverage, or assertion-diversity metrics.
Run file-based C# apps with the .NET CLI when the user explicitly wants C#/.NET code without creating a project. Use for C# language/API experiments, one-file C# apps, small multi-file C# apps composed with `#:include`/`#:exclude`, or C# file-based apps linked with `#:ref`. Do not use for language-agnostic throwaway scripts, generic computations, Python/PowerShell-style automation, full projects, or existing app integration.
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
Optimize code performance through iterative improvements (max 2 rounds). Benchmark execution time and memory usage, compare against baseline implementations, and generate detailed optimization reports. Supports C++, Python, Java, Rust, and other languages.
Use when building, scaffolding, modifying, debugging, converting, or verifying Apache Flink Agents applications, including Flink Agents YAML, Workflow Agent, ReAct Agent, Actions, Resources, MCP servers, vector stores, runtime skills, Python, or Java. Do not use for ordinary Flink jobs that do not use Flink Agents.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Settle what domain terms mean per context, and which repository conventions or language standards (Go, Python) apply. Use when: names disagree or a rename is proposed.
Send and receive WhatsApp messages via the unofficial linked-device client pywhats (pip install pywhats) — pair with QR, send text/images, group chat, read receipts, presence/typing, and a long-running JSON event stream. Use when the user wants to script WhatsApp as a linked companion device (like WhatsApp Web), pair a device, send a WhatsApp from Python, or listen for inbound messages. Triggers: 'whatsapp', 'send whatsapp', 'pair whatsapp', 'pywhats', 'linked device', 'whatsapp web client'. NOT the official WhatsApp Business/Cloud API.
CCXT cryptocurrency trading library. Use for cryptocurrency exchange APIs, trading, market data, order management, and crypto trading automation across 150+ exchanges. Supports JavaScript/Python/PHP.
Cryptofeed - Real-time cryptocurrency market data feeds from 40+ exchanges. WebSocket streaming, normalized data, order books, trades, tickers. Python library for algorithmic trading and market data analysis.
This skill should be used when analyzing binaries, executables, or bytecode to understand what they do or how they work. Triggers on "binary", "executable", "ELF", "what does this do", "reverse engineer", "disassemble", "decompile", "pyc file", "python bytecode", "analyze binary", "figure out", "marshal". Routes to sub-skills for triage, static analysis, dynamic analysis, synthesis, or tool setup.
Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.