「stream」の検索結果

Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.

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Use when adding or fixing sound in Godot 4.7: audio buses and effects, volume sliders, 'too many sounds', combat audio with hundreds of enemies, sounds clipping or distorting, 3D sound too quiet or not panning, reverb zones not working, occlusion, adaptive or interactive music (AudioStreamInteractive, layers, stingers), music loops with gaps, SFX that repeat, AudioStreamRandomizer, AudioStreamGenerator, import settings, or importing AI-generated music, SFX and voice from Scenario or ElevenLabs.

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Build dependency network and critical path from a matter plan. Produce an interactive Gantt, flag near-critical tasks, and run what-if cascade scenarios when delays occur — showing programme impact and drafting communications. Produces filtered workstream or jurisdiction views for local counsel. Trigger on: 'build a timeline', 'Gantt chart', 'critical path', 'what if X is delayed', 'what moves if', 'schedule impact', 'how does this affect the programme', 'when do we finish', 'can we still close on time', 'if we miss this deadline', 'run a what-if', 'visualise the plan', 'Germany timeline', 'what does the Employment workstream look like', 'timeline for local counsel', 'just show me the [workstream] tasks'.

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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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Expert knowledge for Azure Stream Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building ASA jobs with Event Hubs/Kafka, Cosmos/SQL outputs, ML/UDF queries, autoscale, or IoT Edge clusters, and other Azure Stream Analytics related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Factory (use azure-data-factory), Azure Event Hubs (use azure-event-hubs), Azure Functions (use azure-functions).

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Applies Geoffrey Moore's chasm-crossing strategy for B2B tech products moving from visionary early adopters to pragmatist mainstream. Use when a product has early traction but stalls before mainstream adoption, when planning a beachhead/niche strategy, when designing whole-product offerings, when positioning against established competitors, or when scaling from innovator usage to industry standard. Triggers include 'stuck between early adopters and mainstream', 'we need a beachhead', 'pragmatist customers won't buy', 'how do we go from 10 to 1000 customers'. NOT for PLG/freemium SaaS (Slack, Notion, Cursor), pure consumer apps, two-sided marketplaces, or AI-native products with bottoms-up viral adoption - their dynamics break the visionary-to-pragmatist sequence.

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Use when the user runs /gsd-workstreams or asks to list, create, switch, status, progress, complete, or resume parallel workstreams for concurrent milestone work. The active one is tracked in the GSD_WS variable.

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Validate and stream file uploads securely with Validation and S3 streaming in NestJS. Use when implementing secure file uploads, validation, or S3 streaming in NestJS.

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Build event streaming and real-time data pipelines with Kafka, Pulsar, Redpanda, Flink, and Spark. Covers producer/consumer patterns, stream processing, event sourcing, and CDC across TypeScript, Python, Go, and Java. When building real-time systems, microservices communication, or data integration pipelines.

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Use when you need to apply functional programming principles in Java — including writing immutable objects and Records, pure functions, functional interfaces, lambda expressions, Stream API pipelines, Optional for null safety, function composition, higher-order functions, pattern matching for instanceof and switch, sealed classes/interfaces for controlled hierarchies, Stream Gatherers for custom operations, currying/partial application, effect boundary separation, and concurrent-safe functional patterns. This should trigger for requests such as Improve the code with Functional Programming; Apply Functional Programming; Refactor the code with Functional Programming; Refactor Java code to use streams or Optionals safely; Improve immutability and pure functions in Java. Part of Plinth Toolkit

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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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Use when streaming durable workflow updates to a UI in real time — live order status pages that animate as steps complete, AI agent token streaming from a function to the browser, log tailing for long-running jobs, or human-in-the-loop approval flows that publish a prompt and wait for a user reply. Covers Inngest v4 native realtime: defining typed channels, publishing from inside step.run, minting subscription tokens via server actions, and consuming the stream from React/Next.js client components.

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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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Video/audio/image processing with FFmpeg and ImageMagick. Tools: FFmpeg (video/audio), ImageMagick (images). Capabilities: format conversion, encoding (H.264/H.265/VP9/AV1), streaming (HLS/DASH), filters, effects, thumbnails, watermarks, batch processing, hardware acceleration (NVENC/QSV). Actions: convert, encode, resize, crop, compress, extract, merge, stream, transcode media. Keywords: FFmpeg, ImageMagick, video encoding, audio extraction, image resize, thumbnail, watermark, HLS, DASH, H.264, H.265, VP9, AV1, codec, bitrate, framerate, resolution, aspect ratio, filter, overlay, concat, trim, fade, batch processing. Use when: converting video/audio formats, encoding with specific codecs, generating thumbnails, creating streaming manifests, extracting audio from video, batch processing images, adding watermarks, optimizing file sizes.

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Fix "Failed to load video" errors when network requests succeed (200/206 status). Use when: (1) Video element shows error but DevTools shows successful requests, (2) Videos download correctly via curl but fail in browser, (3) Range requests work but video won't play, (4) Building CDN/media server for video streaming. The root cause is often missing Accept-Ranges header which browsers need for video seeking and streaming.

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Cloudflare Workers Runtime APIs including Fetch, Streams, Crypto, Cache, WebSockets, and Encoding. Use for HTTP requests, streaming, encryption, caching, real-time connections, or encountering API compatibility, response handling, stream processing errors.

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Streams change data capture from PostgreSQL into Redpanda or Kafka using Redpanda Connect's postgres_cdc input, which reads the WAL through logical replication (pgoutput). Use when configuring postgres_cdc (formerly pg_stream), setting up wal_level=logical, replication slots, and publications, enabling an initial snapshot before streaming, or troubleshooting slot growth and WAL accumulation. Also covers Redpanda Enterprise destination features such as Iceberg Topics, Tiered Storage, and server-side Schema ID Validation, since postgres_cdc itself requires a Redpanda Enterprise license.

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Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

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Data pipeline specialist for ETL design, data quality, CDC patterns, and batch/stream processingUse when "data pipeline, etl, cdc, data quality, batch processing, stream processing, data transformation, data warehouse, data lake, data validation, data-engineering, etl, cdc, batch, streaming, data-quality, dbt, airflow, dagster, data-pipeline, ml-memory" mentioned.

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AG-UI (Agent-User Interaction Protocol) is an open, event-based protocol that streams an AI agent's text, tool calls, state and lifecycle events to a frontend over HTTP and Server-Sent Events. Use when the user wants to build an AG-UI server, connect an agent or framework (LangGraph, Mastra, CrewAI, Pydantic AI) to a React or custom UI, stream agent progress and state, or use CopilotKit with AG-UI.

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抖音直播带货 (商家 / 主播 / 直播间运营 + 千川 / 巨量引擎广告投放 + 选品 + 流量场承接 + 合规) (Douyin livestream commerce — 抖音直播带货运营 (主播运营 + 千川投放 + 选品 + 公域私域转化 + 合规)) Master OS — automated mastery of Douyin livestream commerce — 抖音直播带货运营 (主播运营 + 千川投放 + 选品 + 公域私域转化 + 合规): top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on Douyin livestream commerce — 抖音直播带货运营 (主播运营 + 千川投放 + 选品 + 公域私域转化 + 合规) problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「抖音直播」「抖音直播带货」「直播带货」「直播电商」「直播间运营」

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AI Manipulation Defense System implementation with Midstream, AgentDB, and lean-agentic

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。

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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。

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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。