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Found 577 Skills
Review the current branch diff for real bugs and security issues, verify findings against surrounding code, and report only issues that survive context checks. Runs as a forked review workflow so the audit has separate reasoning budget and stays isolated from the main task flow. Use when the user asks to find bugs, review changes, or audit branch risk.
Flutter 프로젝트에서 get_it 기반 의존성 주입 설정 방법. `diSetup()` 함수 작성, DataSource/Repository/UseCase/ViewModel 등록 순서, 싱글톤 vs 팩토리 선택, Root 위젯에서 `getIt<T>()` 호출 패턴을 다룹니다. "DI 설정", "get_it", "registerSingleton", "registerFactory", "의존성 주입", "ViewModel 등록", "diSetup", "getIt 인스턴스" 같은 표현이 나오면 반드시 이 스킬을 사용하세요.
agent-team: Cancel a non-terminal task with a reason.
OpenAI Responses API for stateful agentic applications with reasoning preservation. Use for MCP integration, built-in tools, background processing, or migrating from Chat Completions.
How agentmemory is built, the iii engine primitives it runs on, its storage model, ports, and the viewer. Use when reasoning about how memory is stored or retrieved end to end, when extending the system, or when answering how agentmemory works under the hood.
AI SDLC resumable task-runtime workflow. Use when an AI assistant needs to start or resume a versioned delivery run, select dependency-ready work, enforce step, failure, and token budgets, retry safely, persist exact stop reasons, recover state from an append-only journal, or require commit evidence at task boundaries. Supports `--quick-flow` for deterministic local runs and `--full-flow` for strict transition review.
Debug Vercel CDN caching — cache hit rate, stale content, revalidation behavior, ISR + PPR, per-request cache reasons (cacheReason) and PPR state (ppr_state), and costs.
Implements media and file management components including file upload (drag-drop, multi-file, resumable), image galleries (lightbox, carousel, masonry), video players (custom controls, captions, adaptive streaming), audio players (waveform, playlists), document viewers (PDF, Office), and optimization strategies (compression, responsive images, lazy loading, CDN). Use when handling files, displaying media, or building rich content experiences.
Research-aligned self-consistency for debugging. Spawns independent solver agents that each explore and debug the problem from scratch. Uses majority voting. Based on "Self-Consistency Improves Chain of Thought Reasoning" (Wang et al., 2022). Use for critical bugs, algorithms, or when other approaches have failed.
ARIMA, SARIMA, Prophet, trend analysis, seasonality detection, anomaly detection, and forecasting methods. Use for time-based predictions, demand forecasting, or temporal pattern analysis.
Use when prompts produce inconsistent or unreliable outputs, need explicit structure and constraints, require safety guardrails or quality checks, involve multi-step reasoning that needs decomposition, need domain expertise encoding, or when user mentions improving prompts, prompt templates, structured prompts, prompt optimization, reliable AI outputs, or prompt patterns.
You must use this when seeking cross-domain analogies, applying first-principles reasoning, or overcoming creative bottlenecks.