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Structured, end-to-end guidance for designing scalable, reliable systems: requirements, capacity estimation, architecture, and failure-mode planning.
Provides a step-by-step system-design playbook: clarify requirements, estimate capacity, define APIs and data models, produce high-level and low-level designs, and identify bottlenecks and reliability patterns. Includes capacity estimation templates, latency and storage references, architecture decision record conventions, and patterns for scaling, caching, and fault tolerance.
Use this skill when designing a new service or feature, writing a tech spec or ADR, selecting storage or communication patterns, planning capacity for anticipated load, or reviewing designs for scalability, reliability, or security gaps. It is also useful during architectural reviews and pre-production readiness checks.
Best used by agents integrated with developer tools and code review contexts (Claude-style and similar large-model agents that produce design docs and ADRs).
Purely instructional/reference skill for system design with no executable scripts. Covers the full design process from requirements through capacity estimation, HLD, LLD, ADRs, technology selection, scalability and reliability patterns. Exceptionally well-written with practical examples, decision matrices, ASCII diagrams, and Mermaid sequences. A comprehensive reference guide rather than an automation skill.
High-quality system design reference content. No security concerns whatsoever — no scripts, no network calls, no credentials. Well-structured with clear sections, practical examples, and useful decision frameworks. Lacks a scripts/ or references/ directory but this is appropriate for a purely instructional skill.
Docker Patterns
Production-ready Dockerfile and Compose patterns for Python (FastAPI/uv) and Node.js (Next.js), focused on multi-stage builds, caching, health checks, secrets,
Go — Advanced Patterns
Reference of idiomatic Go patterns: error handling, goroutines and channels, context usage, interfaces, generics, testing, and performance best practices.
Maestro Orchestrate
Orchestrates complex engineering workflows with enforced design and approval gates, child-agent delegation, and session state management.
FastAPI Project Templates
Creates production-ready FastAPI project scaffolds with async patterns, DI, middleware, and testing best practices for high-performance APIs.
OpenTestAI
Automated, high-confidence AI testing: bug detection, persona feedback, and prioritized test-case generation using many specialized tester profiles.
Canary — Post-Deploy Visual Monitor
Run a short post-deploy monitor that captures screenshots, checks console errors, and compares performance against baselines to detect regressions and page fail
BK-CI Design Patterns Guide
Practical guide to design patterns used in the BK-CI project (Kotlin/Spring). Covers factory, strategy, singleton, decorator, observer, template method, chain-o
Node.js Best Practices
Guidelines and decision-making for Node.js architecture, runtime, async patterns, security, validation, and testing to inform framework and system choices.
SSE Stream Resilience
Provide robust server-sent-events (SSE) stream management with Redis-backed registry, heartbeat monitoring, completion persistence, and background guardian clea
Payment Gateway Integration
Guides and code for integrating major payment providers (Stripe, PayPal, Square) with backend systems: payment intents, subscriptions, webhook handling, and PCI