uv-python-workflow
Use UV package manager for all Python operations instead of pip/python
Use UV package manager for all Python operations instead of pip/python
JavaScript project structure, package.json configuration, dependency management, and Maven integration standards for consistent project setup and builds
Python development. Use when writing Python code, CLI tools, scripts, or services. Emphasizes stdlib, type hints, pytest toolchain, and minimal dependencies.
Use when starting infrastructure, testing, deployment, or framework-specific tasks - automatically searches PRPM registry for relevant expertise packages and suggests installation to enhance capabilities for the current task
Use for PlatformIO build/upload/monitor tasks in this repo. Must match repo README conventions.
Use when upgrading dependencies. Produces safe upgrade plan, changelog links, and validation steps.
Python package reorganization with pyproject.toml inside package directory
Auto-detects project language from package.json, pyproject.toml, go.mod, Cargo.toml, etc.
Initialize Python projects with uv. Use when running uv init, checking generated files, setting uv add-bounds in pyproject.toml, verifying uv installation (including Windows), or preparing initial dependency setup.
Migrate pyproject.toml from pre-PDM 2.0 syntax to modern PEP-compliant format. Focuses on dev-dependencies to dependency-groups conversion and PEP 621 project metadata. Integrates with Context7 for latest PDM documentation.
Guide for managing TypeScript monorepos with Turborepo and pnpm workspaces. Covers package creation, dependencies, pipeline configuration, and common patterns.
Diagnose and heal dependency issues in ANY package manager, ANY language. Use when facing version conflicts, security vulnerabilities, or dependency bloat.
Create, test, and maintain Homebrew formulas. Use when adding packages to a Homebrew tap, debugging formula issues, running brew audit/test, or automating version updates with livecheck.
Analyze and update Python dependencies in pyproject.toml, checking for compatibility and security vulnerabilities. Use when: updating dependencies, checking security issues, dependency analysis, version pinning, pip-audit, outdated packages.
Bootstrap a new Rust project with Nix flake, or add Nix flake to an existing Rust project. Triggers on "create a new Rust project", "bootstrap a Rust CLI/app/library", "add flake.nix to existing Rust project", "set up Rust with Nix", or similar requests for Rust project scaffolding with Nix/flake support.
Work on Python experiments in packages/python_viterbo. Use for layout conventions, stage entrypoints, lint/test commands, and asset/plot handling.
Auto-detects project language and framework from package.json, pyproject.toml, etc.
Install a default set of commonly used libraries when initializing a new TypeScript Node.js project (or retrofitting an existing one). Use when a user asks to "create a TypeScript project" and wants the standard dependencies installed (p-map, p-retry, luxon, lodash-es, winston, prisma + @prisma/client, ioredis, express, dotenv) plus common tooling (rimraf, tsc-alias) with optional @types packages and Prisma init.
Manage project dependencies across all apps. Use when installing, updating, or managing dependencies, or when user asks to install packages.
Expert in building and testing conda/bioconda recipes, including recipe creation, linting, dependency management, and debugging common build errors
Comprehensive guide for conda-forge recipe development. Handles legacy (meta.yaml) and modern (recipe.yaml) formats, linting, CI troubleshooting, and feedstock maintenance. Enhanced with patterns from real conda-forge feedstocks (2025). USE THIS SKILL WHEN: creating conda recipes, packaging Python/Rust/Go/C++ software, fixing conda-forge build failures, updating feedstocks, migrating to recipe.yaml format, setting up private channels, or troubleshooting conda-forge CI.
Best practices for structuring prpm.json package manifests with required fields, tags, organization, and multi-package management