597건 · 관련도순
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate or scaffold ASP.NET Core code — Razor Pages, Blazor components, MVC controllers, views, and Minimal API endpoints — without using ASP.NET Core CLI scaffolding/code-generation tools. Use when (1) adding CRUD pages, views, or API endpoints backed by Entity Framework (EF Core) and a database, (2) generating code to create, read, update, and delete data using a DbContext, (3) scaffolding UI components that match the project's existing CSS framework and coding patterns, or (4) creating data-driven forms, tables, and navigation for a model class. Do not use for non-ASP.NET projects or when CLI-based scaffolding is preferred.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when you need to add or review Flyway database migrations in a Micronaut application — micronaut-flyway, db/migration scripts, flyway.datasources.* configuration, and alignment with JDBC or Micronaut Data. This should trigger for requests such as Add or review Flyway migrations in a Micronaut project; Configure micronaut-flyway or db/migration layout; Add versioned Flyway SQL migrations for Micronaut; Review Micronaut database migration ordering; Configure Flyway datasources in a Micronaut project. Part of Plinth Toolkit
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Open-source FAIR biology data framework. Version artifacts (AnnData, DataFrame, Zarr), track lineage, validate via ontologies (Bionty), query datasets. Integrates with Nextflow, Snakemake, W&B, scVI. For scRNA-seq use scanpy; for ontology lookups use bionty.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guides compliance with Thailand's Personal Data Protection Act B.E. 2562 (2019). Covers consent framework, DPO requirements, PDPC enforcement, lawful bases for processing, cross-border transfer mechanisms, and data subject rights under the PDPA. Keywords: Thailand PDPA, PDPC, consent, DPO, cross-border transfers, data subject rights.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implements BYOD privacy compliance frameworks for personal device use in the workplace. Covers personal vs corporate data separation, MDM capabilities and limitations, employee consent requirements, data wiping boundaries, and monitoring restrictions on personal devices. Keywords: BYOD, mobile device management, MDM, personal device, data separation, containerisation, remote wipe, employee privacy.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build cloud backend applications with Encore — type-safe backend framework with built-in infrastructure. Use when someone asks to "build a backend", "Encore", "type-safe API framework", "backend with built-in infra", "auto-provision cloud resources", or "backend framework with databases built-in". Covers API definition, databases, pub/sub, cron, and auto-provisioned infrastructure.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Bias detection and mitigation, fairness metrics, privacy frameworks, consent models, transparency requirements, and accountability structures for data science practice. Covers algorithmic bias sources, disparate impact testing, differential privacy, GDPR principles, model cards, datasheets for datasets, responsible AI frameworks, and the organizational governance needed to make ethics actionable. Use when auditing models for bias, designing privacy-preserving systems, establishing governance processes, or evaluating the social impact of data-driven decisions.
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.
Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell data.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Audit research data management infrastructure -- score FAIR principles compliance (Findable, Accessible, Interoperable, Reusable) across all sub-principles, evaluate data governance frameworks and lifecycle management, assess metadata schema quality (Dublin Core, DataCite, DDI.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when setting up or auditing how compliance documentation is structured, collected, and preserved for regulatory audit in Salesforce FSC — covering KYC data collection workflows, AML screening integration setup, audit trail configuration, and regulatory reporting readiness. Triggers: KYC form setup, AML integration configuration, compliance data collection, audit trail setup, regulatory documentation workflow, Field Audit Trail configuration, Setup Audit Trail, Event Monitoring, Discovery Framework, FSC KYC objects, Identity Document setup, Party Identity Verification. NOT for security implementation, NOT for designing AML/KYC architecture (use architect/aml-kyc-process-architecture), NOT for configuring who can access deal or client data (use admin/compliant-data-sharing-setup).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Great Expectations — great Expectations data quality framework analysis. Covers expectation suite management, validation result review, data docs generation, checkpoint execution, datasource configuration, and batch analysis. Use when reviewing data quality results, managing expectation suites, investigating validation failures, or auditing data quality configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Java의 tinystruct로 터미널과 웹에서 함께 호출할 기능을 구현합니다. 시작 스크립트 생성부터 API, 데이터 저장, 테스트까지 개발 절차를 안내합니다.
Context7 MCP로 라이브러리와 프레임워크의 설정, API, 코드 예시를 조사합니다. 가져온 최신 문서를 바탕으로 답변하며, 자료가 있으면 지정 버전을 우선합니다.
Build and review C#/.NET APIs and business backends using concrete implementation patterns. Cover asynchronous operations, service dependencies, database access, configuration, caching, and tests to structure application code and examine quality and performance issues.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build table data processing with TanStack Table v9 while keeping data and column definitions stable. The skill guides type inference, which determines types automatically, row identity, optional features, and checks for missing APIs.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build Table v9 tables in Angular using injectTable and FlexRender. Guidance covers signal-driven data updates, reusable table components, and connections to TanStack Query for data fetching and TanStack Virtual for displaying large tables.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build and render Table v9 tables in Vue with guidance on keeping data updates reactive, reusing shared table components, and connecting TanStack Query for data fetching or TanStack Virtual for displaying large tables.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Create and render Table v9 tables in Solid while preserving reactive data updates. Get guidance on reusable components, Query data integration, and virtualization, which renders only part of a table at a time.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Create and update Handsontable guide pages with consistent page metadata, headings, framework-specific examples, and sidebar entries. Follow the documentation site's writing conventions and generate JavaScript examples from TypeScript sources where required.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.