「etl」の検索結果

Search, score, and compare flights with jetlag impact analysis.

日本語の概要は準備中です。原文の説明を表示しています。

将法律文本（合同、法规、规章或司法意见）的诠释性歧义审查转化为精美的交付物。可生成多页面网站（默认）、单页面交互式网站、Microsoft Word 文档、PowerPoint 演示文稿或 LaTeX/PDF。当用户持有压力测试结果、歧义审查或"这将在何处被诉"场景分析，并希望发布、演示或分享时使用。触发词包括"发布审查报告"、"据此制作报告"、"将其转化为网站/演示文稿/简报/Word 文档"、"制作 Netlify 网站"、"制作这些歧义点的幻灯片"、"渲染场景"、"打包这份压力测试"、"生成 LaTeX 版本"等。与歧义压力测试技能（底层分析）配套使用，但也适用于任何结构化或半结构化的歧义分析。视觉设计有明确风格倾向，但用户可覆盖颜色、字体和品牌标识。大多数格式需要 Python 和可写的文件系统；单文件 HTML 在主机两者皆无时仍可运行。

日本語の概要は準備中です。原文の説明を表示しています。

Data pipeline architecture patterns for ETL/ELT design, orchestration, and data quality frameworks

日本語の概要は準備中です。原文の説明を表示しています。

Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.

日本語の概要は準備中です。原文の説明を表示しています。

Predicts ADMET properties using ADMETlab 3.0 (119 platform features, including 77 prediction models with modeled-endpoint uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB druglikeness filters. Use when filtering compounds for drug-likeness, prioritizing leads by predicted safety, or building an in-house ADMET QSAR model.

日本語の概要は準備中です。原文の説明を表示しています。

Plan database migrations before executing them: risk assessment, dependency mapping, multi-service sequencing, rollback budgets, and stakeholder communication plans. Use when deciding HOW to migrate, not when writing the actual DDL. NOT for: writing migration SQL (use database-migration-manager), data ETL pipelines (use data-migration-specialist), query optimization, or ORM configuration.

日本語の概要は準備中です。原文の説明を表示しています。

Subagent that scans CopilotKit + AG-UI releases shipped in (and just after) the report window, diffs the git tags to extract what each release actually fixed, and returns a fix-map the weekly-report writer cross-checks against open issues. Catches issues that are quietly already-fixed in a shipped release, and is the authoritative source for the "current release vX.Y.Z" version claims. Invoked by weekly-report (spawned in parallel with the Discord/GitHub pulls); runs as a general-purpose subagent so the orchestrator's context stays small.

日本語の概要は準備中です。原文の説明を表示しています。

Kit de ferramentas abrangente para desenvolvimento com a biblioteca CocoIndex. Use quando os usuários precisarem criar pipelines de transformação de dados (flows), escrever funções personalizadas ou operar flows via CLI ou API. Abrange a construção de workflows ETL para processamento de dados de IA, incluindo incorporação de documentos em bancos de dados vetoriais, construção de grafos de conhecimento, criação de índices de busca ou processamento de fluxos de dados com atualizações incrementais.

日本語の概要は準備中です。原文の説明を表示しています。

Catalog and selection guide for Exasol tools, extensions, connectors, integrations, and architecture patterns. Use when the primary intent is comparison, discovery, support-status research, or architecture selection rather than executing a workflow; hand operational work to the selected dedicated skill. Covers deploy, load, explore, enrich, surface, and scale capability families, including named products with no dedicated skill of their own such as Lakehouse Turbo, the Exasol MCP Server, Governed SQL / Text-to-SQL MCP Server, Agent Control Plane, Extension Manager, Terraform and Ansible tooling, and BI, ETL, and warehouse integrations such as Databricks, SAP, Kafka, Power BI, and Tableau.

日本語の概要は準備中です。原文の説明を表示しています。

Set up and configure WorkOS AuthKit authentication with Convex backend. Use when integrating AuthKit, configuring JWT providers, setting up environment variables, or implementing sign in and sign out flows with React and Vite. Supports Netlify deployment.

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Debug and troubleshoot WorkOS AuthKit authentication issues with Convex. Use when authentication fails, JWT validation errors occur, user identity returns null, email claims are missing, admin access checks fail, or sign in button does not work. Supports Netlify deployment.

日本語の概要は準備中です。原文の説明を表示しています。

Set up and configure WorkOS AuthKit authentication with Convex backend. Use when integrating AuthKit, configuring JWT providers, setting up environment variables, or implementing sign in and sign out flows with React and Vite. Supports Netlify deployment.

日本語の概要は準備中です。原文の説明を表示しています。

Debug and troubleshoot WorkOS AuthKit authentication issues with Convex. Use when authentication fails, JWT validation errors occur, user identity returns null, email claims are missing, admin access checks fail, or sign in button does not work. Supports Netlify deployment.

日本語の概要は準備中です。原文の説明を表示しています。

Make public, read heavy Convex + Vite pages load fast on first visit, return visit and in app navigation. Use when a public page feels slow, when adding a new public page, analytics, images, markdown or other heavy dependencies, when touching index.html, netlify.toml, _headers, _redirects or vite.config.ts, or when the user mentions "slow", "load time", "LCP", "bundle size", "waterfall", "websocket handshake", "cache headers", "thumbnails" or "far from the deployment".

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Review someone else's PR through an architectural/strategic lens — does it shift design, raise complexity, or quietly change precedent? Drives a brief reflective discussion with the user, then posts a concise review comment via `gh`. Defers line-level and bug-hunting concerns to AI review bots and the PR author.

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Create an Estuary derivation that continuously aggregates metrics (daily totals, running counts, min/max, lifetime revenue) using reduction annotations. Use for real-time dashboards, continuous materialised views, and replacing batch ETL aggregations with streaming. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "aggregation derivation", "derivation to sum daily totals", "running-count derivation", "transformation for min/max per group", "derive lifetime metrics", "aggregate-by-date derivation", or "real-time-dashboard derivation".

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Quietly reuse and improve verified coding lessons across agents. Use for a nontrivial debugging or implementation problem where an earlier solution could help, when a Blaze offer or receipt appears, or when the user asks to inspect, install, update, contribute to, or link Blaze. Check applicability, verify locally, and close the lookup with an honest outcome and contribution disposition without adding routine user-visible narration.

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Bu template'in konvansiyonlarina gore degisen dosyalari denetler — Cubit+Freezed state kullanimi, servis/locator yerlesimi, view tipi secimi, dort-durum ele alinisi, tasarim token'lari (renk/tipografi/padding/radius), LocaleKeys, TypedGoRoute, zorunlu <feature>.md ve very_good_analysis kurallari. Kullanici "degisiklikleri incele", "bu PR'i review et", "projeye uygun mu", "mimari kontrol", "review my changes" dediginde kullan.

日本語の概要は準備中です。原文の説明を表示しています。

Designs event-driven architectures, webhook systems, API chaining flows, ETL pipelines, and integration patterns between services.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with Census — census reverse ETL management — monitor syncs, destinations, models, source connections, and sync run health. Use when debugging sync failures, inspecting record delivery, auditing destination mappings, or reviewing sync schedules.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with Aws Glue — aWS Glue crawler management, ETL job run analysis, Data Catalog exploration, and schema registry management. Covers crawler schedules, job performance metrics, database and table inventory, partition analysis, and connection health.

日本語の概要は準備中です。原文の説明を表示しています。

Expert en data warehousing (Snowflake, BigQuery, Redshift, star schema, slowly changing dimensions)

日本語の概要は準備中です。原文の説明を表示しています。

Data pipeline architecture, ETL/ELT patterns, data modeling, and production data platform design

日本語の概要は準備中です。原文の説明を表示しています。

Apache Airflow, dbt, Prefect, Dagster, and modern data orchestration for production data pipelines

日本語の概要は準備中です。原文の説明を表示しています。