「pipe flow」の検索結果

Convert web articles or blog posts into slides through a content.json pipeline, translate or rebuild existing PPTX files onto a template, and edit an already-open PowerPoint deck with COM Automation (RefURL, overflow review). Use for article-to-slides conversion, deck translation, template-based rebuilds, or live COM editing of an open deck. Not for simply reading, inspecting, or lightly editing a .pptx file. Triggers on 記事をスライド化, スライド翻訳, 開いているパワポを編集, COM自動化, RefURL, content.json.

End-to-end pipeline for producing Vox-style explainer videos from a single topic prompt. One topic in, finished film out — script, keyframes (Seedream 5.0 Pro), animation (Gemini Omni Flash), voiceover (xAI TTS), music (MiniMax Music 2.6), all assembled locally with ffmpeg via the Atlas Cloud API. Use this skill whenever the user asks for an explainer video, a Vox-style video, a documentary short, an educational video essay, a "one prompt to video" pipeline, or wants to turn a topic/article/report into a narrated video with subtitles and music. Also trigger when the user mentions Atlas Cloud video pipelines, keyframe-to-animation workflows, or automated video essays — even if they don't say "Vox."

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 this skill when configuring Data Manager in CRM Analytics: enabling objects for sync, scheduling data sync runs, setting up remote connections to external databases, monitoring sync status and error logs, or troubleshooting connected object issues. Trigger keywords: data sync, connected objects, Data Manager, sync schedule, remote connection, Snowflake connector, sync error, incremental sync, CRM Analytics data pipeline. NOT for pushing external data in programmatically via the External Data API — use data/analytics-external-data. NOT for authoring dataflow nodes — use admin/analytics-dataflow-development.

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。

File-based workflow coordinator for Greek accounting. Defines processing pipelines, validation rules, and routine templates. No external APIs needed.

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。

Orchestrates single-task implementation pipeline: plan → test → build → review. Shipping is an explicit follow-up. Use for feature work, plan execution, or fixes scoped to a single task. NOT for green-field product builds (see mk:autobuild); NOT for auto-invoked workflow orchestration (see mk:workflow-orchestrator).

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。

Build production computer vision pipelines for object detection, tracking, and video analysis. Handles drone footage, wildlife monitoring, and real-time detection. Supports YOLO, Detectron2, TensorFlow, PyTorch. Use for archaeological surveys, conservation, security. Activate on "object detection", "video analysis", "YOLO", "tracking", "drone footage". NOT for simple image filters, photo editing, or face recognition APIs.

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。

Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.

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。

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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 the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).

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 Clay platform consultant for B2B data enrichment and workflow automation. Use when the user asks about Clay tables, waterfall enrichment, Clay credits, Clay AI columns, Claygent, enrichment workflows, Clay integrations, Clay exports, Clay table design, lead scoring in Clay, or building data pipelines in Clay. Also triggers on "Clay table", "enrichment waterfall", "Clay credits", "Claygent", "Clay AI column", "Clay export", "Clay providers", "enrich in Clay", "Clay column", "Clay formulas", "find emails", "email waterfall", "phone waterfall", "lead scoring", "Clay debugging", "Clay troubleshoot". Do NOT use for general CRM questions without Clay context, cold email copy (use cold-email-copy-playbook), or signal routing (use buying-window-signal-workflow).

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-level hydraulics covering open channel flow, pipe systems, hydraulic structures, pumps and turbines, flood routing, and stormwater management.

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-level fluid mechanics covering fluid statics, continuity, Bernoulli, Navier-Stokes, boundary layers, turbulence, pipe flow, and external aerodynamics.

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。

Orchestrator for agent-flow. Runs one issue or task through Implementer, Reviewer and QA as separate processes, with mechanical risk classification, a review-round cap and escalation to Needs Me, ending in a PR. Use for /implement <issue> or when asked to take an issue end to end ("have an agent take issue

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。

Processamento escalável de dados para workloads de ML. Execução em streaming em CPU/GPU, suporta Parquet/CSV/JSON/imagens. Integra-se com Ray Train, PyTorch, TensorFlow. Escala de uma única máquina para centenas de nós. Use para inferência em lote, pré-processamento de dados, carregamento de dados multi-modal ou pipelines distribuídos de ETL.

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。

Cloudflare Workers CLIでWorkers、KV、R2、D1、Vectorize、Hyperdrive、Workers AI、Containers、Queues、Workflows、Pipelines、Secrets Storeを開発・デプロイ・管理する。Wranglerコマンドを実行する前に使用し、最新の公式ドキュメントに基づく構文と安全規則を確認する。

Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.

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。

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.

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。

Структурированная 6-шаговая процедура для улучшения, реновации или перестройки существующих пайплайнов, отдельных папок проектов, структур документации или стек-технологий. Вызывается как "pipeline optimizer" (для целых тематических пайплайнов, например, пайплайнов разработки ПО, исследований или создания игр) или "project-folder optimizer" (для отдельных папок проектов внутри пайплайна, например, единичного инструмента ПО или проекта статьи). Активируется при выполнении таких задач, как "улучшить пайплайн X", "оптимизировать стек", "перестроить Y", "реновация", "рефакторинг пайплайна", "навести порядок в папке проекта", "улучшить структуру папки", "унифицировать конвенции", "консолидация документации", "интегрировать в существующую систему" или при любом существенном вмешательстве в устоявшиеся структуры. Обеспечивает анализ существующего фонда, уточнение целей, эскиз идеального состояния, план устранения разрывов, эмпирическое выявление проблемных мест и повторное тестирование с помощью свежих субагентов. Предотвращает появление параллельных стандартов, дублирование и сбои в пайплайне.

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。

Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster.

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。

You are a workflow automation expert specializing in creating efficient CI/CD pipelines, GitHub Actions workflows, and automated development processes. Design automation that reduces manual work, i...

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。

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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 Circleci — circleCI pipeline and workflow management. Covers pipeline status, workflow analysis, job logs, credit usage monitoring, orb management, and project configuration. Use when checking CI status, investigating build failures, analyzing credit consumption, or managing CircleCI orbs.

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。