667건 · 관련도순
Implement WebSocket gateways with Socket.io and Server-Sent Events endpoints in NestJS. Use when building chat features, live feeds, or choosing between WebSocket and SSE for real-time communication.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Full-stack backend architecture and frontend-backend integration guide. TRIGGER when: building a full-stack app, creating REST API with frontend, scaffolding backend service, building todo app, building CRUD app, building real-time app, building chat app, Express + React, Next.js API, Node.js backend, Python backend, Go backend, designing service layers, implementing error handling, managing config/auth, setting up API clients, implementing auth flows, handling file uploads, adding real-time features (SSE/WebSocket), hardening for production. DO NOT TRIGGER when: pure frontend UI work, pure CSS/styling, database schema only.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build event streaming and real-time data pipelines with Kafka, Pulsar, Redpanda, Flink, and Spark. Covers producer/consumer patterns, stream processing, event sourcing, and CDC across TypeScript, Python, Go, and Java. When building real-time systems, microservices communication, or data integration pipelines.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement real-time features using Convex reactive queries that automatically update when data changes, enabling live collaboration, instant updates, and reactive UIs without manual polling. Use when building live dashboards, implementing collaborative editing, creating chat applications, showing real-time notifications, building activity feeds, implementing presence indicators, creating reactive search, or any feature requiring instant data synchronization across clients.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Computer vision for bio-image preprocessing, feature detection, real-time microscopy. Color conversion, morphology, contour/blob detection, template matching, optical flow on fluorescence/brightfield. 10-100× faster than pure Python via C++. Use scikit-image for scientific morphometry/regionprops; OpenCV for real-time, video, classical feature extraction.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implements real-time WebSocket communication with connection management, room-based messaging, and horizontal scaling. Use when building chat systems, live notifications, collaborative tools, or real-time dashboards.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks about "WebSocket in Bun", "real-time communication", "Bun.serve websocket", "ws server", "socket connections", "pub/sub", "broadcasting messages", "WebSocket upgrade", or building real-time applications with Bun.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Symfony UX LiveComponent for reactive server-rendered UI -- components that re-render via AJAX on user interaction, zero JavaScript required. Use when building live search, real-time filtering, dynamic forms, inline validation, dependent selects, auto-save, polling, deferred/lazy rendering, or any UI that updates itself based on user input. Code triggers: AsLiveComponent, LiveProp, LiveAction, data-model, data-loading, data-live-action-url, ComponentWithFormTrait, LiveListener, emit, defer, lazy, polling. Also trigger when the user asks "how to build a search that filters as I type", "how to validate a form in real-time", "how to make a reactive component in PHP", "how to build dependent selects", "how to defer component rendering", "how to communicate between components via emit", "how to bind a form to a LiveComponent". Do NOT trigger for static reusable UI without reactivity (use twig-component), pure client-side JS behavior (use stimulus), or page-level navigation (use turbo).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Hotwire Turbo for Symfony UX -- SPA-like speed with zero JavaScript. Covers Drive (navigation), Frames (partial page sections), and Streams (multi-target updates). Use when building ajax navigation, lazy-loaded sections, inline editing, pagination without reload, modals from the server, flash messages via streams, or real-time updates via Mercure/SSE. Code triggers: turbo-frame, turbo-stream, data-turbo-frame, data-turbo, data-turbo-action, turbo-stream-source, TurboStreamResponse, <twig:Turbo:Frame>, <twig:Turbo:Stream:Append>, <twig:Turbo:Stream:Replace>, turbo:before-fetch-request. Also trigger when the user asks "how to update part of the page without reload", "how to make navigation feel like SPA", "how to lazy-load a section", "how to do inline editing", "how to push real-time updates from server", "how to use Mercure with Turbo". Do NOT trigger for client-side JS behavior (use stimulus), server-rendered reactive components (use live-component), or reusable static UI (use twig-component).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Transcribes and analyzes speech with the Deepgram API: pre-recorded audio, real-time streaming, text-to-speech and voice agents. Use when a user asks to convert speech to text, implement real-time transcription, add speaker labels or summaries to a recording, detect languages, build a voice agent with turn detection, or integrate Deepgram SDKs (JavaScript or Python).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expertise in real-time multiplayer networking, lag compensation, and authoritative server architectureUse when "multiplayer game, netcode, client-server game, P2P networking, lag compensation, rollback networking, game server, matchmaking, lobby system, player synchronization, state replication, dedicated server, authoritative server, tick rate, network prediction, interpolation, extrapolation, GGPO, lockstep, real-time multiplayer, networking, multiplayer, gamedev, realtime, client-server, p2p, netcode, synchronization, lag-compensation, matchmaking" mentioned.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Specialist in creating size-optimized real-time audio-visual demos and procedural artUse when "demoscene, size coding, 64k intro, 4k intro, 1k intro, tiny code, shader golf, shader minification, procedural demo, bytebeat, pouet, demo party, real-time procedural, demoscene, size-coding, 64k-intro, 4k-intro, shader-optimization, procedural, webgl, graphics" mentioned.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
数据工程 — 数据平台从业者的认知操作系统, 覆盖把数据从源系统搬运成可靠 / 可查询 / 可信赖形态供分析 / ML / 数据产品消费的全生命周期 (生成 → 摄取 → 存储 → 转换 → 服务 + 安全/数据管理/DataOps/数据架构/编排/软件工程 六条暗流, Reis & Housley 框架): 摄取与集成 (批 + CDC 变更数据捕获 Debezium + EL 工具 Fivetran/Airbyte/Meltano/dlt + Kafka Connect + schema drift) / 存储与文件表格式 (对象存储数据湖 + 列存 Parquet/ORC/Arrow/Avro + 开放表格式 Apache Iceberg/Delta Lake/Apache Hudi + lakehouse + 分区/compaction) / 转换与建模 (ELT dbt/SQLMesh + Spark + 维度建模 Kimball + Inmon + Data Vault + 大宽表 OBT + 渐变维 SCD + 增量模型 + 语义/指标层) / 编排与工作流 (Apache Airflow/Dagster/Prefect/Mage/Kestra/Apache DolphinScheduler + DAG + 幂等 + 回填 backfill + 数据资产调度) / 批流与实时 (Apache Kafka/Apache Flink/Spark Structured Streaming/Kinesis/Pulsar/Redpanda + Lambda vs Kappa + watermark/窗口/exactly-once + 流式 SQL Materialize/RisingWave + 实时 OLAP ClickHouse/Apache Druid/Apache Pinot/StarRocks/Apache Doris) / 数仓与查询引擎 (Snowflake/BigQuery/Redshift/Databricks SQL/Trino/Presto/DuckDB/Polars + 存算分离 + MPP) / 数据质量测试与可观测性 (dbt tests/Great Expectations/Soda + 数据契约 + Monte Carlo data downtime + 新鲜度/量/schema 异常检测) / 数据治理编目与血缘 (DataHub/Amundsen/OpenMetadata/Unity Catalog + 列级血缘 + PII 分类 + 访问控制 + GDPR) / DataOps 与可靠性 (数据 CI/CD + 转换版本控制 + 环境隔离 + 幂等重处理 + 数据 SLA/SLO + 计算存储 FinOps) / 数据架构范式 (现代数据栈 + lakehouse + data mesh + data fabric + 去中心化 vs 中心化所有权) / 分析工程角色 (dbt 时代连接数据工程与分析的桥) — 不含 数据科学/ML 建模本身 (是下游消费者) / BI 仪表盘制作 (serving 下游) / 数据分析报表为终点 / 'data engineer = 跑 Hadoop 的' 过时窄化 / 通用后端应用开发 (平行学科) (Data Engineering — the cognitive operating system of practitioners who design, build, and operate the data platform: moving data from source systems into reliable, queryable, trustworthy form for analytics / ML / products, covering (a) the data engineering lifecycle (generation → ingestion → storage → transformation → serving, with the undercurrents security / data management / DataOps / data architecture / orchestration / software engineering — Reis & Housley framing), (b) ingestion & integration (batch + CDC change-data-capture with Debezium, EL tools Fivetran / Airbyte / Meltano / dlt, Kafka Connect, API + file + database sources, schema drift handling), (c) storage & file/table formats (object storage data lakes, columnar formats Parquet / ORC / Arrow / Avro, open table formats Apache Iceberg / Delta Lake / Apache Hudi, lakehouse architecture, partitioning / compaction / Z-ordering), (d) transformation & modeling (ELT with dbt / SQLMesh, Spark, dimensional modeling Kimball, Inmon CIF, Data Vault, One Big Table / wide tables, normalization vs denormalization, slowly changing dimensions, incremental models, the semantic / metrics layer), (e) orchestration & workflow (Apache Airflow, Dagster, Prefect, Mage, Kestra, Apache DolphinScheduler, DAGs, idempotency, backfills, data-aware / asset-based scheduling), (f) batch vs streaming & real-time (Apache Kafka, Apache Flink, Spark Structured Streaming, Kinesis / Pulsar / Redpanda, the Lambda vs Kappa debate, watermarks / windowing / exactly-once, streaming SQL Materialize / RisingWave, real-time OLAP ClickHouse / Apache Druid / Apache Pinot / StarRocks / Apache Doris), (g) warehouses & query engines (Snowflake, BigQuery, Redshift, Databricks SQL, Trino / Presto, DuckDB, Polars, decoupled storage & compute, MPP), (h) data quality, testing & observability (dbt tests, Great Expectations, Soda, data contracts, Monte Carlo / data downtime, freshness / volume / schema anomaly detection, unit / integration testing of pipelines), (i) data governance, catalog & lineage (DataHub, Amundsen, OpenMetadata, Unity Catalog, column-level lineage, PII / data classification, access control, GDPR / data privacy), (j) DataOps & reliability (CI/CD for data, version control of transformations, environments, idempotent reprocessing, SLAs / SLOs for data, cost / FinOps for compute & storage), (k) data architecture paradigms (modern data stack, data lakehouse, data mesh, data fabric, decentralized vs centralized ownership), (l) the analytics engineering role (the dbt-era bridge between data engineering and analysis); N
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Lark/Feishu real-time event listening / subscribing / consuming: stream events as NDJSON via `lark-cli event consume <EventKey>` (covers IM message receive, reactions, chat member changes, etc.). Use for Lark bots, real-time message processing, long-running subscribers, streaming webhook/push handlers. Supports `--max-events` / `--timeout` bounded runs and a stderr ready-marker contract — designed for AI agents running as subprocesses.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Query and analyze Google Trends real-time hot topics and trending searches for a specified time range and country/region. Triggered by: Google Trends, hot topics, real-time trending, popular trends, current hot searches, recent trending, viral topics, trending searches, trend discovery, market trends, what's popular, trending now, breakout topics.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Simulates a real user searching on Amazon's storefront to get real-time keyword ranking and search results page data. Use when the user mentions Amazon product search, search result scraping, keyword ranking on search pages, ASIN ranking position check, competitor discovery, search page price comparison, sponsored product analysis, new product monitoring, or storefront search simulation. Even if the user does not explicitly mention "search simulation", trigger this skill whenever their need involves real-time Amazon search results, product ranking data, or storefront SERP analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for building real-time collaboration features using WebSockets, WebRTC, CRDTs (Yjs, Automerge), and Liveblocks / Panduan ahli untuk fitur kolaborasi real-time.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Real-time log monitoring, crash detection, and auto-hotfixing code without human intervention / Pemantauan log real-time, deteksi kerusakan, dan perbaikan kode hotfix otomatis tanpa intervensi manusia.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for Server-Sent Events (SSE), WebSockets, and Streaming Architectures. Covers real-time data push, Socket.IO, Hono WebSocket, and AI response streaming / Panduan ahli streaming real-time.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for Generative UI architectures, ephemeral dynamic interfaces, and real-time streaming of React Server Components (RSC) driven by Gemini 4 Pro / Panduan ahli arsitektur Generative UI, antarmuka dinamis efemeral, dan streaming RSC real-time yang didorong oleh Gemini 4 Pro.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for in-memory Abstract Syntax Tree (AST) code knowledge graphs, real-time symbol dependency mapping, refactoring blast radius calculation, and dead code eradication / Panduan ahli graf pengetahuan AST kode in-memory, pemetaan dependensi simbol real-time, kalkulasi radius dampak refaktor, dan pembersihan kode mati.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for Affective Computing, emotional AI, and real-time sentiment analysis through native multimodal tokens (voice intonation and facial micro-expressions) / Panduan ahli komputasi afektif, AI emosional, dan analisis sentimen real-time melalui token multimodal native.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Enhanced web search and real-time content retrieval via Grok API with forced tool routing. Use when: (1) Web search / information retrieval / fact-checking, (2) Webpage content extraction / URL parsing, (3) Breaking knowledge cutoff limits for current information, (4) Real-time news and technical documentation, (5) Multi-source information aggregation. Triggers: "search for", "find information about", "latest news", "current", "fetch webpage", "get content from URL". IMPORTANT: This skill REPLACES built-in WebSearch/WebFetch with Grok Search tools.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.