「batch」の検索結果

Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Informed by production schedulers with 15+ years experience. Includes TOC/drum-buffer-rope, SMED, OEE analysis, disruption response frameworks, and ERP/MES interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.

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Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

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Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

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Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale.

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Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.

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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.

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Scan recent git commits for changes that affect user-facing behavior, then draft or update the corresponding documentation pages. Use when docs have fallen behind code changes, after a batch of features lands, or when preparing a release. Trigger keywords - update docs, draft docs, docs from commits, sync docs, catch up docs, doc debt, docs behind, docs drift.

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Use this skill when importing Excel, CSV, or pasted rows with nuxt-ui-tools as a package consumer. Covers defineSpreadsheetSchema (typed context, chained text/number/date/boolean/select columns, columns depending on the columns above (options, defaults, rules per row), groups and dynamic groups built from the context, exact matching, option sources shared with forms, unknown-value policies, rules and levels, validate, row identity with duplicates and stored records, output), useSpreadsheetImport (headless models, onSubmit with batches and rejections), the UiSpreadsheetImport* parts, useSpreadsheetSteps with custom steps, and the ready-made UiSpreadsheetImport wizard.

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Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

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Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

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Delegate coding tasks to OpenAI Codex CLI agent. Use for building features, refactoring, PR reviews, and batch issue fixing. Requires the codex CLI and a git repository.

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Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

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生成Windows批处理脚本，通过多维度检测（进程、全盘文件、注册表、已安装程序）来识别向日葵、TeamViewer等远程控制软件，并确保编码兼容性与执行稳定性。

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Expert AI art prompt engineer for Midjourney and Stable Diffusion. Generates high-quality prompts including unified batch illustrations, marketing designs, interactive compositions, and structured framework prompts with translations.

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用于编写VBA宏，批量处理Excel中的超链接。支持将绝对路径转换为相对路径以解决共享问题，或根据文件夹名称批量创建指向本地文件夹的超链接，并自动校验文件存在性。

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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

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B2B content writing with daily workflows and batching systems across Sales/HR/Fintech/Ops Tech

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自动从知乎热榜选题、调用 AI 生成原创回答并保存为草稿，支持自定义话题关键词、写作风格和批量生成。 Draft Zhihu answers automatically: picks hot questions, generates original answers via AI, and saves them as drafts — with custom topic filters, writing style, and batch support. Never publishes.

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Creates and refines Founder Story and brand narrative content for DTC/independent stores selling founder-driven products (e.g. handcrafted leather, artisan sauces, small-batch goods). Use whenever the user mentions founder story, brand story, about page, origin story, artisan brand, handcrafted brand, "who we are" copy, brand voice, mission/vision for a product brand, landing page hero narrative, PDP brand block, or wants to differentiate through authenticity and founder-led storytelling—even if they do not say "founder story" explicitly. Output structured narrative frameworks, placement guidance, and ready-to-use copy aligned with DTC best practices.

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Gate scheduled work on Claude usage limits — /mxm-tasks schedule, run-cycle, scheduled task fire time, background batch dispatch. Checks 5-hour and 7-day usage before firing and sleeps until reset when over threshold.

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Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

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You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.

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Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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。