'data loading' 검색 결과

CesiumJS 3D Tiles - Cesium3DTileset, compressed and CAD-style glTF content, MVTDataProvider, UrlTemplate3DTilesDataProvider, styling, metadata, feature picking, voxels, point clouds, I3S, Gaussian splats, clipping. Use when a task involves loading 3D Tiles or Mapbox Vector Tiles, draping vector tiles on terrain, rendering KHR meshopt/CAD content, styling or querying features, working with voxels or point clouds, or clipping spatial data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Import structured data into Neo4j — LOAD CSV, CALL IN TRANSACTIONS, neo4j-admin database import full (offline bulk), apoc.load.csv/json, apoc.periodic.iterate, driver batch writes. Covers method selection, header file format, type coercion, null handling, ON ERROR modes, CONCURRENT TRANSACTIONS, pre-import constraint setup, and post-import validation. Use when importing CSV/JSON/Parquet files, migrating relational data to graph, or bulk-loading large datasets. Does NOT handle unstructured document/PDF/vector chunking pipelines — use neo4j-document-import-skill. Does NOT handle live app write patterns (MERGE/CREATE) — use neo4j-cypher-skill. Does NOT handle neo4j-admin backup/restore/config — use neo4j-cli-tools-skill.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

PHPUnit and Pest patterns for any PHP project: test structure, naming, data providers, test doubles (mocks/stubs/fakes), fixtures, and coverage targets. Stack-agnostic — referenced by every PHP plugin in the marketplace. Use this skill to: - Structure unit and integration tests with PHPUnit or Pest consistently. - Drive cases with data providers / datasets instead of copy-pasted test bodies. - Use test doubles with discipline — mock collaborators, not the system under test. - Set up and tear down fixtures cleanly and aim for a meaningful coverage target. Do NOT use this skill for: - PHP language idioms — see php-foundation:php-conventions. - Composer / autoloading — see php-foundation:composer-tooling. - Framework-specific test helpers (Laravel RefreshDatabase/actingAs, Symfony WebTestCase/KernelTestCase) — those are injected by the framework plugin's QA phase.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Next.js project structure, App Router conventions, file-based routing primitives, layouts, error boundaries, metadata, image and font optimization, configuration. Apply when implementing or modifying Next.js features. Use this skill to: - Pick the correct file convention (page/layout/loading/error/not-found/route/template/default). - Structure a feature within the App Router tree. - Set up metadata for SEO and OpenGraph. - Configure next.config.js for headers, redirects, image domains. - Use built-in fonts and images correctly. Do NOT use this skill for: - Server vs Client component boundaries (see server-component-patterns). - Data fetching patterns (see nextjs-data-fetching). - Complex routing (parallel/intercepting routes — see nextjs-routing). - Testing (see nextjs-testing).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

TanStack Router best practices for type-safe routing, file-based routing, data loading, search params, and navigation in React. Use when building React SPAs with complex routing, implementing type-safe search params, setting up route loaders, integrating with TanStack Query, or configuring code splitting and preloading.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Manage ML datasets with the datasets ecosystem — loading, streaming, preprocessing, versioning, and sharing. Use when data handling (not modeling) is the bottleneck.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Develop or review dygo metadata loading, YAML decoding, JSON Schemas, validation, naming, Field types, registries, routes, and persisted metadata contracts. Use for framework-level metadata behavior rather than authoring one Business App Entity.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement HTTP data fetching in Angular v20+ using resource(), httpResource(), and HttpClient. Use for API calls, data loading with signals, request/response handling, and interceptors. Triggers on data fetching, API integration, loading states, error handling, or converting Observable-based HTTP to signal-based patterns.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build local BLAST databases and run searches using NCBI BLAST+ command-line tools. Use when running >50 queries, building custom databases with -parse_seqids and -taxid, downloading prebuilt NCBI databases via update_blastdb.pl, choosing -task variants (megablast/dc-megablast/blastn/blastn-short), tuning soft/hard masking, scaling threads, or extracting hits with blastdbcmd. Encodes BLAST v5 vs v4 database format, taxonomy filtering, makeblastdb pitfalls.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build local BLAST databases and run searches using NCBI BLAST+ command-line tools. Use when running >50 queries, building custom databases with -parse_seqids and -taxid, downloading prebuilt NCBI databases via update_blastdb.pl, choosing -task variants (megablast/dc-megablast/blastn/blastn-short), tuning soft/hard masking, scaling threads, or extracting hits with blastdbcmd. Encodes BLAST v5 vs v4 database format, taxonomy filtering, makeblastdb pitfalls.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data. Use when: scraping websites, crawling entire sites, extracting web content, converting HTML to markdown, building web scrapers, handling dynamic JavaScript content, bypassing anti-bot protection, extracting structured data from web pages, or when encountering "content not loading", "JavaScript rendering issues", or "blocked by bot detection". Keywords: firecrawl, firecrawl api, web scraping, web crawler, scrape website, crawl website, extract content, html to markdown, site crawler, content extraction, web automation, firecrawl-py, firecrawl-js, llm ready data, structured data extraction, bot bypass, javascript rendering, scraping api, crawling api, map urls, batch scraping

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Notion 페이지를 Markdown으로 조회, 생성, 수정하고 데이터를 필터링하거나 검색합니다. 파일과 댓글 작업, Workers 생성과 배포 및 실행 로그 확인도 지원합니다.

• Markdown으로 페이지를 생성하고 수정합니다
• 데이터베이스 기록을 조건별로 추립니다
• 페이지를 검색하고 댓글을 확인합니다

Swift 6.2 마이그레이션과 동시성 설계를 돕습니다. MainActor로 상태를 보호하고 데이터 경쟁 컴파일 오류, 프로토콜 준수, 고부하 계산의 명시적 백그라운드 실행을 다룹니다.

• 기존 앱을 Swift 6.2로 마이그레이션
• 데이터 경쟁 컴파일 오류 해결
• 고부하 계산을 백그라운드로 분리

React 18/19 화면 구성 요소의 구현과 검토를 지원합니다. 상태 관리, 데이터 조회, 폼, 로딩·오류 표시, 서버와 브라우저의 경계, 접근성 설계를 다룹니다.

• React 화면 구성 요소 검토하기
• 공유 상태를 둘 위치 결정하기
• 폼과 데이터 조회 방식 설계하기

Kotlin Coroutines와 Flow로 Android 및 Kotlin Multiplatform의 비동기 작업과 데이터 갱신을 구현하고 병렬 실행, 화면 상태, 취소, 오류 처리와 테스트를 다룹니다.

• 여러 데이터를 병렬로 불러옵니다
• StateFlow로 화면 상태를 관리합니다
• 검색 입력을 조절하고 통신을 재시도합니다

FAISS로 대규모 벡터에서 유사한 데이터를 검색하도록 돕습니다. 인덱스 선택과 저장, GPU 사용을 안내하고 검색 속도·정확도·메모리 사용량을 조정합니다.

• 대규모 벡터 유사도 검색 구현
• 속도·정확도·메모리에 맞는 인덱스 선택
• GPU를 이용한 일괄 검색

Notion 페이지와 데이터베이스를 검색하고 수정하며 Markdown 읽기와 쓰기, 파일 업로드를 수행합니다. 외부 데이터 정기 동기화와 이벤트 연동용 Workers도 만듭니다.

• 회의 메모를 Notion에 저장합니다
• 지정한 상태의 데이터를 찾습니다
• 이미지와 자료를 업로드합니다

Audit page loading and choose resource hints, browser instructions for fetching files or preparing connections early. Use measurements to identify delays, then suggest preload, preconnect, prefetch, or dns-prefetch for critical assets, external services, and likely next-page resources.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing early loading of key images and fonts
• Preparing connections to external services
• Prefetching resources for likely next pages

Measure how Google Tag Manager affects page loading and rendering. Identify costly tags, triggers, and requests, then guide cleanup, asynchronous loading, or a move to server-side processing based on observed performance problems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate slow pages using GTM
• Review unused tags and triggers
• Check asynchronous script loading