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Found 470 Skills
Monitor Catchtable for open reservation slots and attempt booking using a logged-in Chrome session.
MSW 아바타 코스튬 관리. 코스튬 조회/적용, CostumeManagerComponent 17슬롯, 아바타 유틸리티. DefaultPlayer뿐 아니라 모든 엔티티(NPC, 몬스터 등)에 적용 가능. Use for avatar costume get/set, CostumeManagerComponent 17 equip slots, avatar utilities. Keywords: costume, avatar, equip, slot, 코스튬, 아바타, 장비, 꾸미기, 모자, 상의, 하의, 무기.
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).
Use for anything related to EAS Observe — adding `expo-observe` to an Expo project (AppMetricsRoot/ObserveRoot HOC, markInteractive, the useObserve hook, and the Expo Router / React Navigation integrations for per-route metrics), querying via the EAS CLI (`eas observe:metrics-summary`, `observe:metrics`, `observe:routes`, `observe:events`, `observe:versions`), or interpreting the resulting metrics (cold/warm launch, TTR, TTI, navigation cold/warm TTR, update download, and the TTI frameRate params for triaging slow startups).
Top-level workflow skill for USD performance diagnosis and optimization. Use for slow loading, high memory, low FPS, or 'optimize my scene' requests; delegates auth/runtime setup to Phase 0 owners.
Use whenever researching a technical question — a library, tool, API, error, version, or "what's the best way to X" — or whenever you're about to answer from memory. Forces multiple real searches over primary sources (official docs, source code, high-vote Stack Overflow, maintainer blogs) instead of one search plus training-data filler, and rejects SEO content-farm slop. Trigger on "research X", "look into", "what's the best library for", "how does X work", "is this still true", "find out".
De-slop pass for any text: detects and erases the statistical fingerprints of AI writing (negative parallelism / "not X but Y", em-dash abuse, rule-of-three, false ranges, puffery vocabulary, uniform cadence, hedged both-sidesing) and rewrites the text into its target register — academic article, tweet, reddit post, email, blog, anything between. Use when the user says "fuck slop", "f*ck slop", "deslop", "de-slop this", "remove the AI tells", "humanize this", "make this not sound like AI", or invokes /fuck-slop. Also use before publishing any agent-drafted prose.
Use when app feels slow, memory grows, battery drains, or diagnosing ANY performance issue. Covers memory leaks, profiling, Instruments workflows, retain cycles, performance optimization.
Use when build times are slow, investigating build performance, analyzing Build Timeline, identifying type checking bottlenecks, enabling compilation caching, or optimizing incremental builds - comprehensive build optimization workflows including Xcode 26 compilation caching
ONLY use when user explicitly says 'deep research', 'exhaustive', 'comprehensive report', or 'thorough investigation'. Slower and more expensive than parallel-web-search. For normal research/lookup requests, use parallel-web-search instead.
Use when designing or reviewing concurrent Python code — selecting between asyncio, threads, or multiprocessing; structuring cancellation and deadline propagation; bounding fan-out and backpressure. Also use when diagnosing race conditions, deadlocks, slow throughput, or thread/task leaks under load.
Create distinctive, bold UI designs that avoid generic AI aesthetics. This skill should be used when users want frontend components with strong visual identity, creative typography, intentional color palettes, and production-grade animations - specifically to avoid the bland, safe, homogeneous "AI slop" that plagues most generated interfaces.