engineering-devops-automator

Senior development guide skill covering pragmatic architecture decisions, technical planning from ambiguous requirements, production-safe rollout strategies, observability, and maintainability standards.

A frontend development guide covering React, Vue, Angular, and Svelte with decision rules for framework selection, performance optimization (Core Web Vitals, code splitting), accessibility (ARIA), and component architecture best practices.

Guides scalable backend system design including database schema architecture, API versioning, event-driven patterns, and cloud infrastructure. Covers microservice vs. monolith decisions, circuit breaker reliability, cursor-based pagination, caching strategies, and sub-20ms query performance optimization.

A comprehensive guide for designing distributed systems, covering the full process from requirements gathering and capacity estimation to component deep-dives, failure mode analysis, and monitoring setup. Helps create scalable and reliable architectures with decision frameworks for technology choices like SQL vs. NoSQL, caching strategies, and monolith-to-microservice migrations.

A collection of 9 engineering AI agent skills for Claude Code, each providing deep domain expertise with decision rules, production-grade code patterns, reference material, and runnable scripts for areas like frontend development, backend architecture, system design, and DevOps. Skills are self-contained directories with a SKILL.md, references, and CLI scripts that Claude reads automatically during relevant tasks.

A comprehensive security engineering guide covering application security, infrastructure hardening, threat modeling (STRIDE/DREAD), OWASP Top 10 remediation, vulnerability scanning, secrets management, and compliance frameworks like SOC 2, GDPR, and HIPAA.

Guides rapid prototyping and MVP development with stack selection, A/B testing scaffolding, and deployment strategies that prioritize speed-to-deploy over production hardening.

Provides ML engineering expertise covering PyTorch, HuggingFace Transformers, LoRA/QLoRA fine-tuning, RAG pipelines, and model deployment with GPU memory-aware training strategies.

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