Loading...
Loading...
Found 104 Skills
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.
Creates pytest fixtures following project patterns including factory fixtures, async fixtures, and multi-layer organization. Use when setting up test fixtures, creating test data, organizing test utilities, or structuring conftest.py files. Works with Python test files, pytest configuration, and .py test utilities.
Modern Python tooling best practices using uv, ruff, ty, and pytest. Mandates the Trail of Bits Python coding standards for project setup, dependency management, linting, type checking, and testing. Based on patterns from trailofbits/cookiecutter-python.
Comprehensive pytest testing skill for Python projects. Write efficient, maintainable tests with fixtures, parametrization, markers, mocking, and assertions. Use when: (1) Writing new tests for Python code, (2) Setting up pytest in a project, (3) Creating fixtures for test dependencies, (4) Parametrizing tests for multiple inputs, (5) Mocking/patching with monkeypatch, (6) Debugging test failures, (7) Organizing test suites with markers, (8) Any Python testing task.
Develop Python applications using modern patterns, uv, functional-first design, and production-first practices. Use this whenever working with .py files, pyproject.toml, uv commands, pip/pip3, poetry, virtualenv/venv, inline script metadata, or Python tooling like pytest, mypy, ruff, asyncio, itertools, functools, or dataclasses. If the task involves running Python, managing Python dependencies, creating environments, or building Python packages, load this skill and prefer uv-oriented workflows.
Write comprehensive backend tests including unit tests, integration tests, and API tests. Use when testing REST APIs, database operations, authentication flows, or business logic. Handles Jest, Pytest, Mocha, testing strategies, mocking, and test coverage.
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.
Integrate Open-Meteo Weather Forecast, Air Quality, and Geocoding APIs: query design, variable selection, timezone/timeformat/units, multi-location batching, and robust error handling. Keywords: Open-Meteo, /v1/forecast, /v1/air-quality, geocoding-api, hourly, daily, current, timezone=auto, timeformat=unixtime, models, WMO weather_code, CAMS, GeoNames, httpx, FastAPI, pytest.
HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.
Evidence-based test debugging enforcing systematic root cause analysis. Use when tests are failing, pytest errors occur, test suite not passing, debugging test failures, or fixing broken tests. Prevents assumption-based fixes by enforcing proper diagnostic sequence. Works with Python (.py), JavaScript/TypeScript (.js/.ts), Go, Rust test files. Supports pytest, jest, vitest, mocha, go test, cargo test, and other frameworks.
Modern Python development with uv, the fast Python package and project manager. Covers project management (uv init, uv add, uv sync, uv lock), virtual environments, Python version management (uv python install/pin), script runners (uv run), tool management (uvx), workspace support for monorepos, and publishing to PyPI. Includes Python patterns for FastAPI, Pydantic, async/await, type checking, pytest, structlog, and CLI tools. Use when initializing Python projects, managing dependencies with uv, configuring pyproject.toml, setting up virtual environments, running scripts, managing Python versions, building monorepos with workspaces, containerizing Python apps, or writing modern Python with type hints.
HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Covers REST APIs, GraphQL, request/response validation, authentication, and error handling. Use when user mentions API testing, Supertest, httpx, REST testing, endpoint testing, HTTP response validation, or testing API routes.