Railway Tools

HCP Packer registry integration for tracking and managing image metadata.

Generates service-specific configuration files for GitLab stack projects using .env as primary config source. Creates nginx, PostgreSQL, Redis configs, meta files (CLAUDE.md, .gitignore, .dockerignore), with strict validation for secrets and paths

Terraform module generation and refactoring skills including module design and Terraform Stacks.

Validates GitLab stack projects before deployment, ensuring proper architecture patterns, directory structure, secrets management, .env configuration, and Docker best practices. Detects issues and provides actionable guidance

Manages Docker secrets for GitLab stack projects, ensuring secrets are never in .env or docker-compose.yml. Handles migration from environment variables, validation, auditing, and secure secret generation

Comprehensive Python 3.13+ expertise system covering modern Python development, async programming, type hints, performance optimization, and cloud deployment. PROACTIVELY activate for: (1) ANY Python task, (2) Python 3.13+ features (free-threading, JIT), (3) asyncio and concurrent programming, (4) Type hints and mypy/pyright, (5) Package management (uv, pip, poetry), (6) Project structure (src layout, pyproject.toml), (7) FastAPI and web development, (8) Pydantic data validation, (9) Testing (pytest, coverage), (10) Cloudflare Workers/Containers Python, (11) GitHub Actions Python workflows, (12) Performance optimization and profiling, (13) Security best practices (OWASP), (14) Ruff linting and formatting. Provides: Python 3.13 free-threading and JIT, asyncio patterns, comprehensive type hints, uv package management, FastAPI production patterns, Pydantic vs dataclass guidance, pytest testing, Cloudflare Python optimization, GitHub Actions caching, memory profiling, security hardening.