「index」の検索結果

When the user wants to analyze Google Search Console data, use the GSC API, or interpret search performance. Also use when the user mentions "GSC," "Search Console," "indexing report," "Core Web Vitals," "Enhancements," "Insights report," "search performance," "search queries," "search performance report," "URL inspection," "impressions," "CTR," "average position," "index coverage," "GSC data analysis," "Search Console API," or "searchanalytics.query." When the user wants to rewrite title tags (not only report on them), use title-tag. For meta description rewrites, use meta-description.

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。

When the user wants to build an SEO data analysis system, monitor indexing/traffic/keywords/backlinks, or set up benchmarks. Also use when the user mentions "SEO data analysis," "SEO monitoring," "article database," "traffic benchmark," "penalty recovery," "SEO work document," "SEO dashboard," "keyword tracking," "ranking monitoring," "indexing report," or "backlink monitoring." For GSC API, use google-search-console.

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。

Audit technical SEO site-wide by script: crawl, indexation, Web Vitals. A single page → page-seo-analysis. "why isn't Google indexing my pages"

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 blueprint for player mortality loops: progress-index checkpoints, soul graves, ghost/spirit layers, I-frame restitution, world-progress persistence, and death analytics. Use when implementing respawn, shrine checkpoints, corpse-run retrieval, or second-chance mechanics. Keywords revival, respawn, checkpoint, soul grave, ghost mode, I-frames, death analytics, progress index.

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。

Technical SEO audit across 9 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow protocol. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".

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。

App Intents for Siri, Shortcuts, Spotlight, and Apple Intelligence integration including intent modes, interactive snippets, visual intelligence, and entity indexing. Use when implementing Siri integration, App Shortcuts, or Spotlight indexing.

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 knowledge for Azure Speech in Foundry Tools development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using STT/TTS, custom voice or avatars, Speech containers, Voice Live, or telephony/WebRTC streaming, and other Azure Speech in Foundry Tools related development tasks. Not for Azure Content Understanding in Foundry Tools (use azure-content-understanding), Azure AI Vision (use azure-ai-vision), Azure AI Video Indexer (use azure-video-indexer), Azure Translator (use azure-translator).

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 knowledge for Azure AI Document Intelligence development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using AnalyzeDocument APIs, custom/classification models, containers, managed identities, or v4.0 migrations, and other Azure AI Document Intelligence related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure AI Vision (use azure-ai-vision), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer).

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 knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns. Use when using Face detection, identification, verification, liveness, PersonGroup/Directory, or Face API quotas, and other Azure AI Face related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence).

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 knowledge for Azure AI Vision development including decision making, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when using Image Analysis, Read OCR containers, smart-crop thumbnails, background removal, or video frame analysis, and other Azure AI Vision related development tasks. Not for Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Immersive Reader (use azure-immersive-reader).

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 knowledge for Azure AI Search development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building indexes, skillsets, indexers, vector/semantic search, or RAG knowledge bases with Azure AI Search, and other Azure AI Search related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Cosmos DB (use azure-cosmos-db).

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。

Pull Google Search Console data and perform search performance analysis. Use when asked about search rankings, clicks, impressions, CTR, index coverage, Core Web Vitals, or sitemap status. Trigger phrases: "search console", "GSC", "search performance", "clicks and impressions", "CTR analysis", "index coverage", "core web vitals", "URL inspection", "sitemap status", "ranking data", "search queries", "keyword positions".

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。

Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For US legal or regulatory questions use gov; for papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.

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。

Search an index of public repositories, GitHub issues, merged pull requests, repository READMEs, and curated documentation sites. Use when a programming question needs external documentation or upstream evidence.

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。

Integrate Elasticsearch and implement search index Sync patterns in NestJS. Use when integrating Elasticsearch or implementing search index sync in NestJS.

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。

Diagnose database latency with explain plans, index ownership, and query-shape review. Use when a query is slow, an index is missing, or scans and N+1 patterns appear.

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。

把带时间戳的 narration.json 合成为中文解说音频。使用 MiMo TTS（mimo-v2.5-tts）或 Fish Audio（s2.1-pro-free）或显式配置的通用 IndexTTS HTTP 服务逐段生成语音， 按时间窗动态适配语速并处理响度；输入输出时间线上的旁白，产出 tts_segments 与 tts_meta.json。 外发说明：每段旁白文字会发给所选 TTS 服务（MiMo / Fish Audio / 用户自托管的 IndexTTS），--voice-ref 的参考音频会发给 MiMo。 另含实验性的英译中 dub 路径：只在显式选择 dub 模式并传 --confirm-voice-rights 时运行，会把源视频音频发到 MiMo ASR， 并以原说话人的声音为参考经 MiMo voiceclone 克隆配音；只可用于用户有权使用、且说话人同意被克隆声音的内容。 触发词：配音、语音合成、TTS、解说配音、 voiceover、text to speech、旁白配音。

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。

Index at Creation Time

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 ManagedCode.MarkItDown when a .NET application needs deterministic document-to-Markdown conversion for ingestion, indexing, summarization, or content-processing workflows. USE FOR: ManagedCode.MarkItDown integration; document ingestion flows; Office or rich-text conversion to Markdown; indexing and summarization pipelines. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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 you need framework-agnostic SQL guidance — schema naming, relational table design, query readability, indexes, transactions, database security, migrations, testing, and monitoring — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Review SQL schema or migrations; Improve SQL query performance and readability; Design relational tables and indexes; Review database transaction, security, or monitoring practices. Part of Plinth Toolkit

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 you need framework-agnostic MongoDB and non-relational database query guidance — document schema design, collection modeling, JSON Schema validation, indexes, aggregation pipelines, query performance, consistency trade-offs, transactions, and operational safety — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Design MongoDB document schemas; Review MongoDB queries and indexes; Improve aggregation pipeline performance; Model non-relational data access patterns; Review NoSQL consistency and transaction trade-offs. Part of Plinth Toolkit

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 you need to design or implement MongoDB data access in Spring Boot — including document modeling, Spring Data Mongo repositories/templates, indexing, optimistic concurrency, and error handling. This should trigger for requests such as Add MongoDB in Spring Boot; Review Spring Data Mongo design; Improve error handling for Mongo writes; Model MongoDB documents for a Spring Boot service; Configure Spring Data MongoDB indexes or transactions. Part of Plinth Toolkit

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 you need MongoDB persistence in Micronaut — including @MongoRepository design, document modeling, indexes, query patterns, and error handling. This should trigger for requests such as Add MongoDB in Micronaut; Review Micronaut Data Mongo design; Improve error handling for Micronaut Mongo operations; Model MongoDB documents for a Micronaut service; Configure Micronaut MongoDB codecs indexes or transactions. Part of Plinth Toolkit

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。

Security-first SOP for multi-tenant RAG systems. Activate when a calling agent is building, reviewing, or debugging any retrieval pipeline whose vector store is shared across more than one user, organisation, workspace, customer, or permission scope. Encodes the single non-negotiable rule — **filter at the vector store query, never after retrieval / never after rerank** — together with the per-vendor query-time filter APIs (Pinecone namespaces + `$eq`/`$in`, Weaviate `multiTenancyConfig` + tenant handle, Qdrant `is_tenant` payload index + `Filter.must`, Chroma `where`, pgvector RLS), and the cross-framework adapters (LlamaIndex `MetadataFilters`, LangChain `filter=` dict). Frame the work as preventing CVE-2024-41892 / EchoLeak / Slack-AI-class cross-tenant leakage, not as "adding a filter for relevance".

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。