3209 skills
Use when the /systems-design-review mode is active. 7-step design review methodology -- understand the design, classify the system, evaluate against codebase, adversarial analysis, tradeoff validation, synthesis, and action items. Governs conversation flow, delegation patterns, and user validation checkpoints.
Use when the /systems-design mode is active. 9-phase structured design methodology -- problem framing, system classification, constraints, candidate architectures, tradeoff analysis, risk review, refinement, migration planning, and documentation. Governs conversation flow, delegation patterns, and user validation checkpoints.
Domain patterns for workflow orchestration systems — long-running processes, state machines, saga coordination, human-in-the-loop gates, retry and timeout hierarchies, and failure modes. Use when designing or evaluating workflow engines, job orchestrators, or multi-step business process systems.
Domain patterns for web service architecture — API design (REST/GraphQL/gRPC), scaling, data layer, observability, failure modes, and anti-patterns. Use when designing or evaluating a web service, API, or request/response system.
Domain patterns for single-page application architecture — client-side routing, state management, rendering strategies, authentication, performance, and offline support. Use when designing or evaluating a browser-based SPA, progressive web app, or rich client-side application.
Domain patterns for real-time and collaborative systems — persistent connections, state synchronization, conflict resolution, presence, fan-out, and failure modes. Use when designing or evaluating chat systems, collaborative editors, live dashboards, gaming backends, or any system with bidirectional real-time communication.
Domain patterns for peer-to-peer system architecture — network topologies, NAT traversal, peer discovery, data distribution, consistency without central authority, identity and trust, and incentive mechanisms. Use when designing or evaluating a decentralized, peer-to-peer, or mesh-networked system.
Domain patterns for multi-tenant SaaS platforms — tenant isolation models, data partitioning, noisy neighbor mitigation, per-tenant configuration, billing metering, and failure modes. Use when designing or evaluating SaaS products that serve multiple customers from shared infrastructure.
Domain patterns for ML/AI serving and training systems — model serving, feature stores, training pipelines, experiment tracking, A/B testing, GPU scheduling, and failure modes. Use when designing or evaluating machine learning infrastructure, model serving platforms, or AI-powered product features.
Domain patterns for event-driven and message-based systems — pub/sub, event sourcing, CQRS, sagas, delivery guarantees, schema evolution, and failure modes. Use when designing or evaluating systems built around events, messages, or asynchronous workflows.
Domain patterns for enterprise integration — legacy modernization, strangler fig, anti-corruption layers, API gateways, canonical data models, event-carried state transfer, and failure modes. Use when designing or evaluating integration between existing enterprise systems, legacy modernization, or multi-system orchestration.
Domain patterns for edge computing and offline-first systems — sync protocols, conflict resolution under partition, local-first architecture, constrained resources, intermittent connectivity, and failure modes. Use when designing or evaluating mobile apps, IoT systems, field-deployed software, or any system that must work without reliable network access.
Foundational patterns for distributed systems — consensus, consistency models, replication, partitioning, clock synchronization, distributed transactions, and failure modes. Use when designing or evaluating any system that spans multiple nodes, processes, or failure domains.
Domain patterns for data pipeline architecture — batch processing, stream processing, ETL/ELT, DAG scheduling, data quality, schema evolution, backfill strategies, and failure modes. Use when designing or evaluating data pipelines, ETL systems, or streaming data infrastructure.
Domain patterns for CLI tools and developer SDKs — command structure, configuration layering, plugin architecture, distribution, backward compatibility, shell integration, and failure modes. Use when designing or evaluating command-line tools, developer platforms, or SDK libraries.
Domain patterns for Azure cloud architecture — compute selection, managed services, identity (Entra ID), networking, data platform, messaging, deployment, cost management, and operational patterns. Use when designing or evaluating a system deployed on Microsoft Azure.
Object-oriented design principles as a lens for system architecture — SOLID, composition over inheritance, the actor model, design patterns (and when they're wrong), encapsulation, polymorphism, and responsibility-driven design. Use when evaluating code organization, module boundaries, or object/component relationships.
The Unix/Linux design philosophy as a lens for system design — mechanism vs policy, composability, small tools, text streams, convention over configuration, and the principle of least surprise. Use when evaluating designs for composability, simplicity, or separation of concerns.
Domain-Driven Design as a lens for system architecture — bounded contexts, aggregates, ubiquitous language, context mapping, domain events, and strategic vs tactical patterns. Use when modeling complex business domains, defining service boundaries, or evaluating whether a system's structure reflects its domain.
Catalog of reusable architectural primitives — boundaries, contracts, state machines, queues, caches, consistency models, and more. For each: what it is, when it's right, when it's WRONG. Use when selecting patterns for a design or evaluating whether a pattern fits.
Adversarial review of a system design from 6 critical perspectives -- SRE, security, staff engineer, finance, operator, and developer advocate. Produces a unified risk assessment. Use for INTERACTIVE on-demand reviews during a design conversation (/adversarial-review). For RECIPE-DRIVEN reviews (where prior step context is needed), use the systems-design-critic agent instead.
Use when verifying that completed work actually works. Auto-surface during /verify mode, post-implementation review, or before claiming a task is done. Teaches testing outcomes vs implementation, the unit/integration/smoke gradient, and what "done" actually means.
User-need reviewer that speaks for the person who isn't in the room — the one who will actually live with what gets built. Hunts the gap between "we can build this" and "they actually want this," in the patient, impatient voice of the absent user. Use at any checkpoint — brainstorm, design, plan, implement, debug, review — when a feature is being built because it's buildable rather than wanted, the recovery path is missing, or nobody can name the person this serves: "do they actually want this, and can they live with it?"
Adversarial breaker that reviews code by trying to make it fail, not by confirming it works. Hunts the unhappy paths — malformed input, the empty string, the reversed range, the race condition — as a gleeful adversary who assumes everything is broken until a concrete attempt to break it comes up empty. Use at any checkpoint — brainstorm, design, plan, implement, debug, review — when the happy path is celebrated while the edges sit unexamined, "looks fine" stands in for "I tried to break it and couldn't," or nobody has named the input that makes this fall over: "how does this fail, and where ar
