“streaming”的搜索结果

Expert blueprint for open world games including chunk-based streaming (load/unload regions dynamically), floating origin (prevent precision jitter beyond 5000 units), HLOD (hierarchical LOD for distant meshes), persistent state (track entity changes across unloaded chunks), POI discovery systems (compass, markers), and threaded loading (prevent stutters). Use for RPGs, sandboxes, or exploration games. Trigger keywords: open_world, chunk_streaming, floating_origin, HLOD, persistent_state, POI_discovery, threaded_loading.

中文简介正在准备中。当前显示原文说明。

Expert blueprint for open world games including chunk-based streaming (load/unload regions dynamically), floating origin (prevent precision jitter beyond 5000 units), HLOD (hierarchical LOD for distant meshes), persistent state (track entity changes across unloaded chunks), POI discovery systems (compass, markers), and threaded loading (prevent stutters). Use for RPGs, sandboxes, or exploration games. Trigger keywords: open_world, chunk_streaming, floating_origin, HLOD, persistent_state, POI_discovery, threaded_loading.

中文简介正在准备中。当前显示原文说明。

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.

中文简介正在准备中。当前显示原文说明。

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.

中文简介正在准备中。当前显示原文说明。

Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.

中文简介正在准备中。当前显示原文说明。

Use when you need to write or review programmatic JDBC with Spring — including JdbcClient (Spring Framework 7+) as the default API, JdbcTemplate only where batch/streaming APIs require JdbcOperations, NamedParameterJdbcTemplate for legacy named-param code, parameterized SQL, RowMapper mapping to records, batch operations, transactions, safe handling of generated keys, DataAccessException handling, read-only transactions, streaming large result sets, and @JdbcTest slice testing. This should trigger for requests such as Review Java code for Spring JDBC (JdbcTemplate, JdbcClient, NamedParameterJdbcTemplate); Apply best practices for Spring JDBC data access in Java code; Detect and fix SQL injection risks in JDBC code; Improve transaction boundaries or exception handling for JDBC operations; Review JdbcClient usage in Spring Framework 7. Part of Plinth Toolkit

中文简介正在准备中。当前显示原文说明。

Enhancement-overlay decision protocol for STREAMING the output of long-running LLM / agent runs from the *backend*, not just wiring a typing animation in the UI. Activates when a coder agent must stream final tokens to a chat client, surface intermediate agent steps (which tool, which node, partial reasoning), emit custom tool-progress events, choose a transport (SSE vs WebSocket), or decide what to do when the client disconnects mid-stream. The langchain / langgraph skills mention stream modes but stop at "you can stream"; this skill encodes *what to stream, over what transport, and how to fail safely*.

中文简介正在准备中。当前显示原文说明。

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.

中文简介正在准备中。当前显示原文说明。

Expert Next.js performance optimization skill covering Core Web Vitals, image/font optimization, caching strategies, streaming, bundle optimization, and Server Components best practices. Use when optimizing Next.js applications for Core Web Vitals (LCP, INP, CLS), implementing next/image and next/font, configuring caching with unstable_cache and revalidateTag, converting Client Components to Server Components, implementing Suspense streaming, or analyzing and reducing bundle size. Supports Next.js 16 + React 19 patterns.

中文简介正在准备中。当前显示原文说明。

Applies pipes-and-filters for sequential data transformations. Use when data flows through discrete stages like ETL, streaming analytics, or CI/CD pipelines.

中文简介正在准备中。当前显示原文说明。

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

中文简介正在准备中。当前显示原文说明。

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.

中文简介正在准备中。当前显示原文说明。

Use when implementing real-time AI response streaming.

中文简介正在准备中。当前显示原文说明。

TanStack AI (alpha) provider-agnostic type-safe chat with streaming for OpenAI, Anthropic, Gemini, Ollama. Use for chat APIs, React/Solid frontends with useChat/ChatClient, isomorphic tools, tool approval flows, agent loops, multimodal inputs, or troubleshooting streaming and tool definitions.

中文简介正在准备中。当前显示原文说明。

Produce speech and clone voices with Fish Audio — its hosted TTS API (S2.1-Pro / S2-Pro / S1 model lineup, REST + WebSocket streaming, instant and persistent voice cloning) and its open-weight OpenAudio S1-mini / Fish-Speech models for self-hosting. Use this skill when an agent must generate narration or dialogue through Fish Audio, choose between Fish Audio's hosted models and open weights, clone a voice from reference audio, author emotion/tone/special markers for expressive delivery, estimate cost from UTF-8 bytes, wire real-time streaming for a voice agent, decide whether self-hosting beats the API, or review Fish Audio TTS output for production. Do not use it to pick a different provider — it covers Fish Audio specifically.

中文简介正在准备中。当前显示原文说明。

You are an expert in the Vercel AI SDK, the TypeScript toolkit for building AI-powered applications. You help developers integrate LLMs (OpenAI, Anthropic, Google, Mistral, Ollama) with React Server Components, streaming UI, tool calling, structured output with Zod schemas, RAG pipelines, multi-step agents, and edge-compatible AI features — the standard way to add AI to Next.js, Nuxt, SvelteKit, and any Node.js app.

中文简介正在准备中。当前显示原文说明。

音乐制作 / 混音 (音乐制作 / 混音 (Music Production & Mixing) — 录音棚与卧室工作室里把一首歌从编曲/录音/编程做到混音/母带成品的工程+艺术认知操作系统，面向制作人(producer)、混音师(mixing engineer)、母带工程师(mastering engineer)、beatmaker、唱作人/bedroom producer，以及想入行/服务这行(录音棚、plugin 厂商、sample 公司)的视角。覆盖: (a) 第一性张力 — **服务歌曲/情绪 (serve the song / emotion-first: 技术只为打动人，'if it sounds good it is good'，用耳朵不用眼睛) ⇄ 技术正确/工程纪律 (technical correctness: gain staging 增益结构、headroom 余量、相位 phase、监听校准、LUFS 响度规范)**; **黄金耳朵/直觉混音 (mix by ears, reference-driven, 不看分析仪) ⇄ 看表/分析仪/规则 (mix by metrics: EQ 曲线、频谱仪 spectrum analyzer、相关计 correlation meter)**; **少即是多/减法混音 (subtractive, 'less is more', 录好源头 = 混音成功一半) ⇄ 重度处理/'we'll fix it in the mix' (heavy processing, 后期补救)**; **In-the-box 全数字 (ITB: DAW + 插件，召回方便，bedroom 可达专业) ⇄ 模拟硬件/outboard (analog console + 硬件，'mojo'/谐波染色 vs 召回噩梦)**; **人性化/groove/不完美 (humanize, push/pull, 'the feel') ⇄ 量化/网格/修音 (quantize to grid, pitch-correct, 'in the pocket' 靠编辑)**; (b) 核心工作流 / pipeline (最标准、最易蒸高质量+CLI 化) — 编曲制作 arrangement/production → 录音/编程 tracking/programming → 编辑 editing (comping 选段/quantize/pitch-correct/time-align) → 混音 mixing (gain staging → balance 平衡 → EQ → compression → 空间 reverb/delay → 自动化 automation → 总线/母线处理 bus/mix-bus) → 母带 mastering (响度/EQ/限制 limiting/dither/排序+间隔) → 交付 delivery (DDP/streaming spec/stems); (c) 工具栈 — DAW (Pro Tools 录音棚标准/Ableton Live 电子+现场/Logic Pro Mac 性价比/FL Studio beatmaker/Cubase/Studio One/Reaper); 插件 (EQ: FabFilter Pro-Q/SSL/API; 压缩: 1176/LA-2A/SSL bus comp 及其复刻 Waves/UAD/Plugin Alliance; 混响: Valhalla/Lexicon/Bricasti; 调音: Auto-Tune/Melodyne; 限制器 limiter: Pro-L 2/Ozone); 硬件 (监听音箱 monitors: Yamaha NS-10/Genelec; 声学处理 acoustic treatment; 转换器 converters: Apollo/RME; 话筒 mics: U47/SM7B/57); 采样/音色 (Splice/sample packs/Kontakt/Serum 合成器); (d) 知识正典 — Mixing Secrets for the Small Studio (Mike Senior)、The Mixing Engineer's Handbook / Recording Engineer's Handbook (Bobby Owsinski)、Zen and the Art of Mixing (Mixerman)、The Art of Mixing (David Gibson 可视化)、Modern Recording Techniques、Sound on Sound 杂志、Mix With The Masters 大师课、Pensado's Place; (e) figures/流派 — 混音大师 (Chris Lord-Alge CLA 摇滚/Andrew Scheps 'Stadium' 3-bus/Tony Maserati/Manny Marroquin/Serban Ghenea 流行隐形混音/Michael Brauer multing); 制作人 (Rick Rubin 减法/氛围、Quincy Jones、Dr. Dre 完美主义、Max Martin 流行结构、Jack Antonoff、Finneas bedroom→Grammy、Metro Boomin/trap、Timbaland、Pharrell); 母带 (Bob Katz K-system/响度战争批判、Bob Ludwig、Greg Calbi); 教育者 (Mike Senior、Pensado、Warren Huart Produce Like A Pro、Dan Worrall 技术深挖); (f) 行业话术/黑话 — gain staging/headroom/LUFS/true peak/comping/bouncing/printing/stems/DI/reamp/sidechain/parallel compression 并行压缩/mid-side/bus/aux/send-return/dry-wet/transient/sibilance/de-ess/pumping/mud 浑浊/harsh 刺耳/boxy/muddy/in the pocket/the pocket/quantize/swing/groove/vibe/mojo/reference track/A/B/recall/print/glue 胶水; (g) 争议/批判 — 响度战争 loudness war (Bob Katz/Loudness Penalty/streaming 归一化 LUFS 终结了吗)、修音/Auto-Tune 之争 (artistic vs cheating)、ITB vs 模拟玄学 (硬件 'warmth' 是否安慰剂、null test 盲测)、preset/AI 混音 (iZotope/LANDR/sample-based 是否毁了 craft)、bedroom producer 民主化 vs 录音棚消亡、'loudness'/over-compression、plugin 复刻 vs 真硬件、Spotify normalization 对母带的影响、过度依赖 reference/抄袭; (h) 创意 vs 技术张力是本行业 deep tacit 知识的核心 — 大量隐性 '听感' 知识难以言传，靠 reference/学徒/千小时积累。不含: 现场扩声 live sound/PA、音乐理论/作曲 composition (虽相关但聚焦录音棚后期制作)、配乐/film scoring (虽相关但聚焦歌曲制作)、纯硬件电子工程/合成器 DIY、音乐商业/版权/发行 (虽相关但聚焦制作技艺本身)。) Master OS — automated mastery of 音乐制作 / 混音 (Music Production & Mixing) — 录音棚与卧室工作室里把一首歌从编曲/录音/编程做到混音/母带成品的工程+艺术认知操作系统，面向制作人(producer)、混音师(mixing engineer)、母带工程师(mastering engineer)、beatmaker、唱作人/bedroom producer，以及想入行/服务这行(录音棚、plugin 厂商、sample 公司)的视角。覆盖: (a) 第一性张力 — **服务歌曲/情绪 (serve the song / emotion-first: 技术只为打动人，'if it sounds good it is good'，用耳朵不用眼睛) ⇄ 技术正确/工程纪律 (technical correctness: gain staging 增益结构、headroom 余量、相位 phase、监听校准、LUFS 响度规范)**; **黄金耳朵/直觉混音 (mix by ears, reference-driven, 不看分析仪) ⇄ 看表/分析仪/规则 (mix by metrics: EQ 曲线、频谱仪 spectrum analyzer、相关计 correlation meter)**; **少即是多/减法混音 (subtractive, 'less is more', 录好源头 = 混音成功一半) ⇄ 重度处理/'we'll fix it i

中文简介正在准备中。当前显示原文说明。

Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.

中文简介正在准备中。当前显示原文说明。

Expert guide for Vercel AI SDK (Core, UI, RSC), streaming structured data, multi-provider model switching, tool calling loops, and React 19/Next.js 15 AI engineering / Panduan ahli Vercel AI SDK, streaming data terstruktur, dan integrasi AI pada React 19/Next.js 15.

中文简介正在准备中。当前显示原文说明。

Expert guide for Generative UI architectures, ephemeral dynamic interfaces, and real-time streaming of React Server Components (RSC) driven by Gemini 4 Pro / Panduan ahli arsitektur Generative UI, antarmuka dinamis efemeral, dan streaming RSC real-time yang didorong oleh Gemini 4 Pro.

中文简介正在准备中。当前显示原文说明。

Designs streaming platforms for Kafka, Flink, CDC, and lakehouse ingestion. Use when planning event backbones, CDC pipelines, schema governance, or real-time lakehouse delivery.

中文简介正在准备中。当前显示原文说明。

Vercel AI SDK for building chat interfaces with streaming. Use when implementing useChat hook, handling tool calls, streaming responses, or building chat UI. Triggers on useChat, @ai-sdk/react, UIMessage, ChatStatus, streamText, toUIMessageStreamResponse, addToolOutput, onToolCall, sendMessage.

中文简介正在准备中。当前显示原文说明。

Implement a JSON-RPC 2.0 A2A server with full task lifecycle management (submitted/working/completed/failed/canceled/input-required), SSE streaming, and push notifications. Use when implementing an agent that participates in multi-agent A2A workflows, building a backend for an Agent Card, adding A2A protocol support to an existing agent or service, or deploying an agent that must interoperate with other A2A-compliant agents.

中文简介正在准备中。当前显示原文说明。

OpenAI GPT Image generation and editing (gpt-image-2, 1.5, 1, mini). Text-to-image, mask-based inpainting, multi-reference composition, multi-turn conversational editing via Responses API, streaming with partial images. This skill should be used when generating or editing images via OpenAI's image models, when near-perfect text rendering in images is needed, when mask-based region-aware editing is required, when multi-turn conversational image editing is desired, or when streaming progressive image delivery is needed. Complements nano-banana-pro (Gemini) as a parallel image generation backend.

中文简介正在准备中。当前显示原文说明。