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Found 2,093 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
Idiomatic Python 3.14+ development. Use when writing Python code, CLI tools, scripts, or services. Emphasizes stdlib, type hints, uv/ruff toolchain, and minimal dependencies.
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.
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.
Set up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.
Perform a release-readiness review by locating the previous release tag from remote tags and auditing the diff (e.g., v1.2.3...<commit>) for breaking changes, regressions, improvement opportunities, and risks before releasing openai-agents-python.