Skill UI

This tool guides the creation of actionable monitoring dashboards for observability platforms like Grafana and SigNoz. Instead of merely displaying raw metrics, it focuses on structuring data to answer critical operational questions: Is the system healthy? Where are the bottlenecks? What changes occurred? And what action should be taken? It transforms raw metrics into decision-making tools.

Use this skill for optimizing large-scale data ingestion, ETL, and data warehouse loading. It helps diagnose bottlenecks (such as extraction speed, network transfer, or loading time) and implements best practices like idempotent writes, native cloud scans, and checkpointing to achieve maximum processing speed while strictly guaranteeing data integrity and traceability.

A comprehensive guide to safe and reversible database migration patterns. Covers zero-downtime schema changes, data backfilling, and rollbacks for major databases like PostgreSQL and MySQL, and popular ORMs (Prisma, Drizzle, Django). Learn techniques like concurrent indexing and the expand-contract pattern to ensure production stability.

Automates the scaffolding of a complete Aggregate Root structure within a specified Bounded Context, adhering strictly to Domain-Driven Design (DDD) principles. It generates necessary files including the entity, supporting value objects, repository interface, domain event definitions, and comprehensive unit test stubs, significantly accelerating the modeling of new business concepts and enforcing domain invariants.

This tool automates the creation of a standard directory structure for a Domain-Driven Design (DDD) Bounded Context. It is essential when starting a new subdomain, separating a large monolithic application, or setting up a fresh, well-organized module structure, adhering to best practices for domain, application, and infrastructure layers.

A deterministic 'Stop hook' designed to enforce session hygiene for AI agents. It checks machine-verifiable facts such as file modification timestamps of learning logs, disk space, and predefined rationalization patterns. This gate ensures that complex tasks lead to captured knowledge, acting as a mechanical safeguard complementing AI self-auditing.

A comprehensive guide covering modern application deployment strategies, including Blue-Green, Canary, and Rolling deployments, ensuring zero downtime. It also provides deep dives into Docker multi-stage builds, container best practices, and setting up robust CI/CD pipelines using tools like GitHub Actions.

This comprehensive tool guides developers through the entire plugin ecosystem, helping them find and recommend the optimal plugins for any given workflow or task. It covers core coordination, multi-agent collaboration, advanced memory management (Vector DB, RAG), architectural design (ADR/DDD), security auditing, and modern development methodologies. Use it when starting a new project or optimizing existing development pipelines.

This guide outlines best practices for building scalable and maintainable Django applications and APIs. It covers recommended project layouts, implementing separated configuration files (dev/prod), advanced ORM techniques, and integrating middlewares, caching, and signals for enterprise-level robustness. Ideal for professional backend development.

A comprehensive guide covering essential security best practices for Django applications. It details how to implement robust authentication, granular authorization (RBAC), and crucial security settings like CSRF/XSS protection, HSTS, and secure environment configuration to prevent common vulnerabilities in production deployments.

A comprehensive guide to implementing Test-Driven Development (TDD) for Django projects. This skill covers the full Red-Green-Refactor cycle, utilizing pytest, pytest-django, and factory_boy to write robust unit and integration tests for Django models, views, and DRF APIs. Essential for developers aiming to build large-scale, high-quality Python applications.

A comprehensive, multi-phase checklist for ensuring the quality, security, and deployment readiness of Django applications. It covers linting (ruff, mypy), unit testing (pytest), database migrations, security audits (bandit, pip-audit), and performance checks, making it an essential quality gate for CI/CD pipelines before merging or deploying to production.