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Found 267 Skills
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.
When writing complex features or significant refactors or user ask explicitly, use an ExecPlan from design to implementation.
MUST be used whenever fixing test coverage for a Dune app to meet the 80% line coverage hard gate. This skill finds AND fixes coverage gaps — it configures tooling, writes missing tests, covers untested paths, and refactors code for testability. It does not just report. Triggers: test coverage, fix tests, write tests, add tests, coverage fix, 80% coverage, coverage gate, missing tests, testability, vitest coverage, jest coverage.
Find dead code and cleanup candidates such as unused exports, unreachable branches, orphaned files, stale feature flags, dead registrations, and compatibility layers with no live callers. Use when auditing refactors, bundle-size cleanup, architecture simplification, pre-release cleanup, reviewing requests to find unused code or decide what can be deleted, or when deciding whether code can be safely removed or auto-fixed.
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.
Domain-agnostic strategic decision analysis and wargaming. Auto-classifies scenario complexity: simple decisions get structured analysis (pre-mortem, ACH, decision trees); complex or adversarial scenarios get full multi-turn interactive wargames with AI-controlled actors, Monte Carlo outcome exploration, and structured adjudication. Generates visual dashboards and saves markdown decision journals. Use for business strategy, crisis management, competitive analysis, geopolitical scenarios, personal decisions, or any consequential choice under uncertainty. NOT for simple pros/cons lists, non-strategic decisions, or academic debate.
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, designing systems, or making architectural decisions. Enters plan mode, reads all available docs, explores the codebase deeply, then interviews the user relentlessly with ultrathink-level reasoning on every decision until a shared understanding is reached. Produces a validated design spec before any implementation begins. Triggers on feature requests, design discussions, refactors, new projects, component creation, system changes, and any task requiring design decisions.
Create multiple choice, true/false, fill-in-blank, matching quizzes. Auto-generate plausible distractors. Instant grading with explanations.
Reviews axum web framework code for routing patterns, extractor usage, middleware, state management, and error handling. Use when reviewing Rust code that uses axum, tower, or hyper for HTTP services. Covers axum 0.7+ patterns including State, Path, Query, Json extractors.