Unit Testing

Measure relationships between variables using correlation coefficients, correlation matrices, and association tests for correlation measurement, relationship analysis, and multicollinearity detection

Apply this repository's coding conventions and patterns. Use when writing or reviewing code in this codebase to ensure consistency with established patterns for DI, logging, error handling, testing, and documentation. Auto-trigger when implementing features, fixing bugs, or reviewing code changes.

Browser automation with Playwright for modern web scraping. Use this skill for scraping JavaScript-rendered pages, handling complex interactions, managing multiple browser contexts, or testing web applications. NOT needed for static HTML parsing or processing already-fetched content.

Unit testing framework for Python using pytest. Use when writing test cases, validating code behavior, checking test coverage, or debugging test failures.

Advanced scientific computing for portfolio optimization, statistical testing, and numerical methods. Use when minimizing portfolio variance, fitting distributions to returns data, performing correlation analysis, running hypothesis tests, or solving constrained optimization problems. Provides optimization algorithms (BFGS, SLSQP) and statistical distributions essential for risk modeling.

Graph algorithms for network analysis including shortest paths, cycle detection, and connectivity analysis. Create directed/undirected graphs with weighted edges. Use when modeling currency exchange networks, detecting arbitrage opportunities via negative cycles, finding optimal trading routes, calculating path lengths, analyzing network topology, or working with any connected data structures. Supports Bellman-Ford, Dijkstra, and other graph algorithms.

Comprehensive testing guidelines for Vitest and React Testing Library. Covers quality standards, AAA pattern, naming conventions, branch coverage, and best practices. Reference this skill when creating or updating test code during Phase 2 (Testing & Stories).

Algorithmic trading strategies and execution systems. Use for building trading bots, backtesting strategies, and implementing automated trading rules.

Implement Traveling Salesman Problem algorithms for route optimization. Use this skill when finding shortest routes through multiple points, solving pick path problems, implementing nearest neighbor or 2-opt algorithms, or optimizing travel sequences.

Rust testing patterns and best practices. Use this skill when writing, reviewing, or modifying Rust tests. Covers test organization, assertions with pretty_assertions, parameterized tests, and testing multiple input formats.

Comprehensive Storybook story creation guidelines. Covers story structure, naming conventions, and visual testing patterns. Reference this skill when creating Storybook stories for components with conditional rendering or complex UI states during Phase 2 (Testing & Stories).

WebAssembly runtime execution and instantiation. Use when running compiled WebAssembly modules, testing WASM execution, or interfacing with WASM instances from Python.

QEMU ARM emulation for running ARM binaries and system images on x86 hosts. Use when emulating ARM architecture, running ARM Linux kernels, testing ARM binaries, or creating ARM development environments.

Comprehensive React component coding guidelines, refactoring principles, and architectural patterns. **CRITICAL**: Focuses on patterns AI commonly fails to implement correctly, especially testability, props control, and component responsibility separation. Reference this skill when implementing or refactoring React components during Phase 2.

Browser testing, web scraping, and UI validation using Playwright MCP. Use this skill when you need to test Streamlit apps, validate web interfaces, test responsive design, check accessibility, or automate browser interactions through MCP tools.

Internationalization (i18n) and localization (l10n) testing for global products including translations, locale formats, RTL languages, and cultural appropriateness. Use when launching in new markets or building multi-language products.

Testing in production with feature flags, canary deployments, synthetic monitoring, and chaos engineering. Use when implementing production observability or progressive delivery.

Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.

Migrate Python projects from setup.py/setup.cfg to pyproject.toml for use with uv. Use when upgrading legacy Python packaging, converting setup.py to modern pyproject.toml format, setting up dependency groups for development/testing, and ensuring `uv run pytest` works correctly.

Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions.