559건 · 관련도순
Apache Airflow DAGs, operators, SLA monitoring, and workflow orchestration. Activate on: Airflow, DAG, operator, sensor, scheduler, task dependency, SLA, backfill, XCom. NOT for: dbt transformations (use dbt-analytics-engineer), streaming pipelines (use streaming-pipeline-architect).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reports how local Git branches are progressing toward canonical upstream inclusion as a compact terminal table plus a browser-rendered HTML report, with branch purpose, stack dependencies, Git Machete topology, ahead/behind counts, change-request status, and next action. Use when asked for upstreaming status, local branch submission progress, which branches have change requests, or what remains before they can land.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Cloudflare Workersのコードを本番運用品質のベストプラクティスに照らして作成・レビューする。新しいWorkerの実装、Workerコードのレビュー、wrangler.jsoncの設定、streaming・floating promises・global state・secrets・bindings・observabilityなどのanti-pattern確認で使用する。事前学習の記憶よりCloudflare公式ドキュメントからの取得を優先する。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
FFmpegを使用したマルチメディア処理の専門スキル。動画・音声の変換、編集、最適化を効率的に支援。フォーマット変換、コーデック選択、フィルタ適用、ストリーミング準備、ハードウェアアクセラレーションなど幅広い操作をカバー。Use when converting video/audio formats, transcoding codecs, trimming/cutting media, creating GIFs, extracting audio, adding watermarks, preparing for streaming (HLS/DASH), or optimizing media files for web/mobile.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use for AI SDK for Python async-generator tools, streaming tool output, subagent tools, PartialToolCallResult events, and custom tool aggregation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Non-streaming and streaming SSR, RouterClient/RouterServer, renderRouterToString/renderRouterToStream, createRequestHandler, defaultRenderHandler/defaultStreamHandler, HeadContent/Scripts components, head route option (meta/links/styles/scripts), ScriptOnce, automatic loader dehydration/hydration, memory history on server, data serialization, document head management.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Data Engineer IA — Expert en pipelines de données (ETL, data lakes, dbt, Airflow, streaming). Construit des pipelines fiables, scalables et auditable.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert en data engineering (ETL, Airflow, dbt, data lakes, streaming pipelines, data quality)
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert en Apache Kafka (producers, consumers, streams, connectors, schema registry)
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert en performance des agents IA (optimisation latence, streaming, caching, traitement par lots)
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when you need to write or review programmatic JDBC with Spring — including JdbcClient (Spring Framework 7+) as the default API, JdbcTemplate only where batch/streaming APIs require JdbcOperations, NamedParameterJdbcTemplate for legacy named-param code, parameterized SQL, RowMapper mapping to records, batch operations, transactions, safe handling of generated keys, DataAccessException handling, read-only transactions, streaming large result sets, and @JdbcTest slice testing. This should trigger for requests such as Review Java code for Spring JDBC (JdbcTemplate, JdbcClient, NamedParameterJdbcTemplate); Apply best practices for Spring JDBC data access in Java code; Detect and fix SQL injection risks in JDBC code; Improve transaction boundaries or exception handling for JDBC operations. Part of cursor-rules-java project
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Architecture-level decisions for putting a CDN in front of a web app's static assets, API responses, and file/media delivery: provider selection (hyperscaler vs. specialist $/GB), signed-URL / tokenized access for gating private content at the edge, cache invalidation strategy (versioned URLs vs. purge APIs), origin shield / tiered caching for high-miss-rate content, and CDN-layer geo-restriction. Use when deciding which CDN to put in front of a new or growing service, when private/paywalled files need edge delivery without an origin round-trip per request, or when purge/invalidation behavior is being designed rather than debugged. NOT for HTTP cache-control header syntax, Vary, stale-while-revalidate, or surrogate-key purge mechanics (see `cdn-cache-control-headers`); NOT for Cloudflare-specific product configuration once Cloudflare is already chosen (see `cloudflare`); NOT for video-specific transcoding, adaptive bitrate ladders, or streaming-protocol packaging (see `managed-video-streaming-pipeline`).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Spark, pandas, polars, DuckDB optimization for batch data processing. Activate on: batch processing, Spark optimization, polars, DuckDB, pandas performance, data frame, shuffle, partition, memory optimization. NOT for: streaming pipelines (use streaming-pipeline-architect), warehouse queries (use data-warehouse-optimizer).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Apache Airflow DAGs, operators, SLA monitoring, and workflow orchestration. Activate on: Airflow, DAG, operator, sensor, scheduler, task dependency, SLA, backfill, XCom. NOT for: dbt transformations (use dbt-analytics-engineer), streaming pipelines (use streaming-pipeline-architect).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build real-time streaming applications with Azure Event Hubs SDK for Java. Use when implementing event streaming, high-throughput data ingestion, or building event-driven architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.