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Found 1,378 Skills
Build interactive data applications and dashboards with pure Python - no frontend experience required
Python code quality with ruff linter. Fast linting, rule selection, auto-fixing, and configuration. Use when checking Python code quality, enforcing standards, or finding bugs.
Set up GitHub Actions workflows for CI/CD with automated testing, linting, and deployment for Python/UV projects. Use when creating CI pipelines, automating tests, or setting up deployment workflows.
Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.
Review Python dependencies for known security advisories, stale version pins, and unsafe upgrade paths. Use when users ask for dependency security reviews, requirements or lockfile audits, upgrade planning, pre-release risk checks, or remediation prioritization for Python projects.
Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
Instruments Python and TypeScript code with MLflow Tracing for observability. Triggers on questions about adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, or tracing specific frameworks (LangGraph, LangChain, OpenAI, DSPy, CrewAI, AutoGen). Examples - "How do I add tracing?", "How to instrument my agent?", "How to trace my LangChain app?", "Getting started with MLflow tracing", "Trace my TypeScript app"
Manages Python CLI tools with uv. Learn when to use uvx for temporary execution, uv tool install for persistent tools, and how to differentiate between tool dependencies and project dependencies. Includes version management, listing, cleanup, and scenarios for running tools with specific Python versions.
Manages Python project dependencies with uv. Learn how to add, remove, and updates dependencies, organize them into groups (dev, test, lint, docs), pin versions, handle conflicts, and manages lock files for reproducible installations across environments. Use when adding or updating packages, organizing development dependencies, resolving version conflicts, or managing lock files in CI/CD pipelines.
Initialize and configure new Python projects with uv, including creating projects, setting up pyproject.toml, managing dependency groups, and pinning Python versions. Use when starting new projects, configuring development environments, or standardizing project structure with uv. Covers `uv init`, `uv add`, `uv python pin`, and initial project scaffolding with proper dependency organization.
Debugs and resolves common uv issues. Learn to diagnose dependency resolution failures, handle version conflicts, fix cache problems, troubleshoot Python environment issues, optimize performance, and solve platform-specific problems. Use when uv commands fail, dependencies won't resolve, cache is corrupted, Python installation issues occur, or performance is slow.
Migrate existing Python projects to uv from pip, Poetry, Pipenv, or Conda. Learn how to convert dependency files, preserve development environment setup, validate the migration, and plan team rollout. Use when converting legacy projects to modern uv tooling, consolidating different package managers, or standardizing Python development workflows across teams.