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Found 76 Skills
Swift concurrency API reference — actors, Sendable, Task/TaskGroup, AsyncStream, continuations, isolation patterns, DispatchQueue-to-actor migration with gotcha tables
Apply systems thinking — causal loop diagrams, stock-and-flow models, system archetypes, and leverage-point analysis — to organizational, economic, or social problems where feedback loops, delays, or emergent behavior drive recurring failure across multiple interacting actors. Use this skill when the user describes a multi-actor situation that resists linear fixes: policy interventions that backfire, org-level fixes that break other teams, market symptoms that return after being solved, or time-lagged second-order consequences, even if they say 'why does fixing X make Y worse' or 'identify the leverage points in this system'. Do NOT use for single-cause software bugs, flaky tests, or regressions — those are debugging problems, not systems-thinking problems, even when phrased as 'this keeps coming back'.
Comprehensive guide for XState v5 ecosystem including state machines, actors, @xstate/store, and TanStack Query integration. Use when implementing state machines, event-driven stores, client state management, or integrating XState with React and TanStack Query for data fetching orchestration.
Apply systems thinking to leadership decisions and produce a Systems Thinking Pack (system boundary, actors & incentives map, feedback loops, second-order effects ledger, leverage points, intervention plan). Use for complex ecosystems, trade-offs, org/process redesign, and preventing unintended consequences.
Swift Concurrency patterns — async/await, actors, tasks, Sendable conformance. Use when writing async/await code, implementing actors, working with structured concurrency, or ensuring data race safety.
Motoko language pitfalls and modern syntax for the Internet Computer. Covers persistent actor requirements, stable types, mo:core standard library, type system rules, and common compilation errors. Use when writing Motoko canister code, fixing Motoko compiler errors, or generating Motoko actors. Do NOT use for deployment, icp.yaml config, or CLI commands — use icp-cli instead. Do NOT use for upgrade persistence patterns — use stable-memory instead.
Design and optimize systems for high concurrency, throughput, scalability, and elastic scale—concurrency models (threads, async/await, actors), lock-free patterns, connection pooling, caching stampede mitigation, horizontal scaling, load balancing, backpressure, queueing, rate limiting, bulkheads, read replicas, sharding, pool tuning, profiling, capacity planning, SLO-driven autoscaling, multi-region and CDN edge architecture. Use when the user asks about high concurrency, scalability, throughput, horizontal scaling, connection pooling, backpressure, rate limiting, caching stampede, read replica, sharding, autoscaling, capacity planning, lock contention, async scalability, or load balancing—not service decomposition (microservices-developer), event buses only (event-driven-architecture), generic CRUD (senior-software-engineer), SRE on-call only (site-reliability-engineer), load tests without architecture (performance-engineer), or cost-only FinOps (cloud-economist).
AI SDLC business analysis workflow. Use when an AI assistant needs to frame a feature or change before implementation, derive actors, workflows, business rules, assumptions, acceptance criteria, and richer spec context for requirements and design. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.
Optional AI SDLC user-experience workflow. Use when an AI assistant needs to define actors, goals, user journeys, interaction steps, loading/empty/error/success states, recovery behavior, content intent, accessibility requirements, or UX acceptance evidence and route them into traceable human and machine artifacts. Supports `--quick-flow` for a focused journey slice and `--full-flow` for strict state, accessibility, and acceptance coverage.
Use when writing async/await code, enabling strict concurrency, fixing Sendable errors, migrating from completion handlers, managing shared state with actors, or using Task/TaskGroup for concurrency.
Write unit and integration tests for Akka.NET actors using modern Akka.Hosting.TestKit patterns. Covers dependency injection, TestProbes, persistence testing, and actor interaction verification. Includes guidance on when to use traditional TestKit.
Calculate network centrality metrics to identify important nodes in graphs. Use this skill when the user needs to find key influencers, critical infrastructure nodes, or central actors in a network — even if they say 'who is most important in this network', 'key nodes', or 'network influence measurement'.