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Found 2,120 Skills
Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
Backend services development with Python emphasizing security, performance, and maintainability for JARVIS AI Assistant
Use when designing data ownership, validation boundaries, consistency models, or configuration strategy in Python. Also use when encountering unclear ownership across modules, shared mutable state leaking between layers, validation gaps at ingress, cross-module transactional coupling, or config drift between environments.
Structure Python so LLMs can understand it in 50 lines.
Create and manipulate PowerPoint presentations programmatically. Build slide decks with layouts, shapes, charts, tables, and images. Generate data-driven presentations from templates.
Python software engineering guidelines from real PR review patterns. This skill should be used when writing, reviewing, or refactoring Python code — especially dataclasses, service interfaces, error handling, and type annotations. Triggers on tasks involving Python modules, API design, data modeling, type safety, exception handling, or refactoring for maintainability.
Python linting with Ruff - an extremely fast linter written in Rust. Use when: (1) Standardizing code quality, (2) Fixing style warnings, (3) Enforcing rules in CI, (4) Replacing flake8/isort/pyupgrade/autoflake, (5) Configuring lint rules and suppressions.
SQLAlchemy and database patterns for Python. Triggers on: sqlalchemy, database, orm, migration, alembic, async database, connection pool, repository pattern, unit of work.
Implements the Strategy pattern in Python backends. Run when the user mentions strategy pattern, or when you see or need a switch on type/method, multiple behaviors under the same contract, or interchangeable algorithms—apply this skill proactively without the user naming it.
Designs intuitive Python library APIs following principles of simplicity, consistency, and discoverability. Handles API evolution, deprecation, breaking changes, and error handling. Use when designing new library APIs, reviewing existing APIs for improvements, or managing API versioning and deprecations.
Python design patterns for CLI scripts and utilities — type-first development, deep modules, complexity management, and red flags. Use when reading, writing, reviewing, or refactoring Python files, especially in .trellis/scripts/ or any CLI/scripting context. Also activate when planning module structure, deciding where to put new code, or doing code review.
Comprehensive Python/FastAPI backend code review with optional parallel agents