Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications. Use when deploying an application, setting up CI/CD, writing GitHub Actions workflows, configuring health checks, or asking about rollback strategies.
Create Mermaid diagrams (activity, deployment, sequence, architecture) from text descriptions or source code. Use when asked to "create a diagram", "generate mermaid", "document architecture", "code to diagram", "create design doc", or "convert code to diagram". Supports hierarchical on-demand guide loading, Unicode semantic symbols, and Python utilities for diagram extraction and image conversion.
Docker and Docker Compose patterns for local development, container security, networking, volume strategies, and multi-service orchestration. Use when writing a Dockerfile, setting up docker-compose, containerizing an app, or asking about container security and networking.
Deep search via Perplexity API. Three modes: search (quick facts), reason (complex analysis), research (in-depth reports). Returns AI-grounded answers with citations.
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Use when designing a database schema, writing SQL queries, optimizing slow queries, adding indexes, or asking about database security and migrations.
Reviews a GitHub pull request diff and produces a structured report covering correctness, security, Python best practices, and test coverage. Use when asked to review a PR, check a pull request, analyze a diff, or validate code before merging.
Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Use when starting a Python project, choosing a framework, structuring code, adding type hints, or asking about Python best practices.
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements. Use when writing Python tests, setting up pytest, creating fixtures, mocking dependencies, or improving test coverage.