Skill UI

A comprehensive, end-to-end methodology designed for software engineers and AI agents to safely and systematically integrate machine learning models into existing non-ML codebases. It guides users through critical phases, including problem framing, data readiness, architectural decoupling (via APIs/services), baseline model implementation, and final MLOps pipeline setup.

Master professional Python testing practices using the pytest framework. This guide covers Test-Driven Development (TDD) methodology, advanced features like fixtures (with different scopes), parametrization, assertion techniques, and achieving high code coverage, ensuring robust and maintainable software.

This guide provides comprehensive patterns for writing reliable and maintainable tests in Rust, adhering to the TDD methodology. It covers unit testing, integration testing, asynchronous programming with Tokio, property-based testing, mocking, and robust error/panic handling. Ideal for developers looking to elevate their Rust code quality and coverage.

An advanced tool for network intelligence that calculates weighted graph scores to map the optimal path to a target. It identifies potential introducers, measures 'bridge value' across connections, and helps determine whether a connection requires a warm introduction or direct outreach on platforms like X and LinkedIn. Ideal for users needing the raw ranking methodology.

This skill guides users through Phases 2 (Pseudocode Design) and 3 (Architecture Design) of the SPARC methodology. It translates high-level specifications into detailed technical blueprints, covering algorithm pseudocode, module boundaries, API contracts (using DDD patterns), and infrastructure planning, ensuring a robust plan before writing production code.

This skill executes the final two phases of the SPARC methodology: Refinement and Completion. It systematically reviews the implemented feature through rigorous code reviews, expands test coverage (unit, integration, edge cases), validates performance, generates a traceability matrix, creates comprehensive documentation, and confirms deployment readiness. It ensures the feature is robust, tested, and production-ready.

This example demonstrates the structure of a blocked fixture within a testing framework. It serves as a placeholder to illustrate required missing elements, such as a detailed description, and is useful for understanding fixture setup requirements and testing methodology.

This skill transforms unstructured task lists into a disciplined, protected daily schedule. It implements the Deep Work methodology by classifying tasks into deep and shallow categories, budgeting shallow work time, and creating an energy-first time-blocked plan. It enforces strict limits, such as a 4-hour deep work ceiling, ensuring focus remains the protected resource throughout the day. Includes logging and end-of-day shutdown rituals.