Find the perfect capability for your agent.
Converts ORM calls to raw SQL and analyzes query performance. Detects N+1 queries, missing indexes, and other anti-patterns. Use when debugging slow queries, tracing ORM-generated SQL, or optimizing database performance for Sequelize, Prisma, TypeORM (Node.js), GORM, sqlc, sqlx, ent (Go), or SQLAlchemy, Django ORM, Peewee (Python).
Build FastAPI applications using Clean Architecture principles with proper layer separation (Domain, Infrastructure, API), dependency injection, repository pattern, and comprehensive testing. Use this skill when designing or implementing Python backend services that require maintainability, testability, and scalability.
MCP (Model Context Protocol) architecture patterns, security best practices, and memory management strategies. Use when designing, implementing, or debugging MCP servers in Python (FastMCP) or TypeScript.
エラーハンドリングのベストプラクティスを適用するスキル。回復可能性を基準にしたエラー設計、 Either/Result型の使用、ドメインエラーとシステムエラーの適切な分類を支援する。コードレビュー、 新規実装、リファクタリング時にエラー処理パターンの改善が必要な場合に使用。対象言語: Go, Rust, Scala, Java, TypeScript, JavaScript, Python。トリガー：「エラー処理を改善して」 「Result型を使いたい」「例外設計をレビューして」「回復可能なエラーの設計」といった エラーハンドリング関連リクエストで起動。
Use when building MCP servers or integrating external APIs/services via MCP (TypeScript or Python).
Generates FastAPI endpoints with proper Pydantic models, dependency injection, async handlers, and OpenAPI documentation. Use when building Python REST APIs.
Setup Sentry Tracing (Performance Monitoring) in any project. Use this when asked to add performance monitoring, enable tracing, track transactions/spans, or instrument application performance. Supports JavaScript, TypeScript, Python, Ruby, React, Next.js, and Node.js.
Setup Sentry Logging in any project. Use this when asked to add Sentry logs, enable structured logging, setup console log capture, or integrate logging with Sentry. Supports JavaScript, TypeScript, Python, Ruby, React, Next.js, and other frameworks.
Setup Sentry Metrics in any project. Use this when asked to add Sentry metrics, track custom metrics, setup counters/gauges/distributions, or instrument application performance metrics. Supports JavaScript, TypeScript, Python, React, Next.js, and Node.js.
Setup Sentry Logging in any project. Use when asked to add Sentry logs, enable structured logging, capture console logs, or integrate logging libraries (Pino, Winston, Loguru) with Sentry. Supports JavaScript, Python, and Ruby.
Setup Sentry Metrics in any project. Use when asked to add custom metrics, track counters/gauges/distributions, or instrument application performance. Supports JavaScript and Python.
Django API development for 2025. Covers Django Ninja (modern, async-first, type-safe) and Django REST Framework (mature, ecosystem-rich). Use when building REST APIs, choosing between frameworks, implementing authentication, permissions, filtering, pagination, or async endpoints.
Python environment setup on your computer for Badger 2350 development. Use when installing Python, setting up virtual environments, installing development tools like mpremote or ampy, or configuring the computer-side development environment for Badger 2350 projects.
Create MicroPython applications for Universe 2025 (Tufty) Badge including display graphics, button handling, and MonaOS app structure. Use when building badge apps, creating interactive displays, or developing MicroPython programs.
Python language expertise for writing idiomatic, production-quality Python code. Use for Python development, type hints, async patterns, testing with pytest, packaging, and following PEP 8 standards. Triggers: python, py, pytest, pep8, typing, asyncio, poetry, uv, pyproject.
Detects changes between python-socketio versions by comparing git diffs, analyzes API changes (new/modified/removed functions, classes, parameters), and updates corresponding .pyi stub files. Use when python-socketio releases a new version and stubs need to be synchronized, or when the user mentions "update stubs", "socketio upgrade", "sync stubs with socketio", or "check socketio changes".
UV for fast Python package management, virtual environments, and project workflows
Configure Python projects with pyproject.toml for modern packaging, tools, and dependency management
