Build search applications with vector, hybrid, and semantic search capabilities.
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。
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概要と使いどころ
Build search applications with vector, hybrid, and semantic search capabilities.
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。
Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.
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。
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search.
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。
Master AngularJS to Angular migration, including hybrid apps, component conversion, dependency injection changes, and routing migration.
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。
Production-grade Android app development guide covering native (Kotlin/Java), cross-platform (Flutter, RN, KMM), and hybrid architectures.
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。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Team operations dashboard template — Linear/Asana-clean hybrid with sprint status hero, 4-segment progress bar, workstream cards, chronological activity stream with colored event badges, right-rail with today's schedule + team-presence + upcoming milestones. For team status snapshots, OKR reviews, "team this week" all-hands views.
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。
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search.
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。
Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.
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 search applications with vector, hybrid, and semantic search capabilities.
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。
Master AngularJS to Angular migration, including hybrid apps, component conversion, dependency injection changes, and routing migration.
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。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Decides whether and how to polish a draft genome assembly to raise consensus accuracy (QV) with read-type-matched tools - Racon and medaka (ONT consensus), dorado polish, Polypolish and pypolca (Illumina, repeat-aware), Pilon (legacy short-read), NextPolish/NextPolish2, Hapo-G (haplotype-aware), ntEdit, and DeepPolisher/PEPPER-Margin-DeepVariant for human. Covers the do-not-polish-HiFi rule, the medaka basecaller-model footgun, held-out Merqury QV as the only honest stop signal, and the haplotype-collapse trap. Use when correcting homopolymer indels or residual SNPs in a long-read assembly, deciding if a HiFi assembly needs polishing, or choosing an ONT vs hybrid vs short-read polishing chain.
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。
Detect horizontal gene transfer (HGT / LGT) using compositional methods (GC%, codon usage, tetranucleotide z-scores via SIGI-HMM, AlienHunter, IslandViewer 4, IslandPath-DIMOB), phylogenetic-incongruence methods (AvP, HGTphyloDetect, ALE / GeneRax / AleRax reconciliation, RANGER-DTL), and BLAST-distribution methods (HGTector v2, DarkHorse, Alien Index). Use when screening prokaryote genomes for genomic islands and HGT events, distinguishing HGT from incomplete lineage sorting / differential gene loss / hybridization, mapping donor lineages via phylogenetic placement, separating eukaryotic HGT from contamination, ruling out gBGC as a false signal, or quantifying DTL rates with ALE/GeneRax on bacterial trees.
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。
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
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 the user asks the economic + operational tradeoffs of broker-mediated freight vs direct shipper relationships — margin difference, capital + operational cost, sales effort, payment terms, relationship investment, when to pursue direct, and the hybrid model. Reference industry research on freight broker margins.
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。
Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical. Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "service area", or "multi-location".
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 search applications with vector, hybrid, and semantic search capabilities.
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。
Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.
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。
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search.
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。
Master AngularJS to Angular migration, including hybrid apps, component conversion, dependency injection changes, and routing migration.
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。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Production pipeline for ASCII art video — any format. Converts video/audio/images/generative input into colored ASCII character video output (MP4, GIF, image sequence). Covers: video-to-ASCII conversion, audio-reactive music visualizers, generative ASCII art animations, hybrid video+audio reactive, text/lyrics overlays, real-time terminal rendering. Use when users request: ASCII video, text art video, terminal-style video, character art animation, retro text visualization, audio visualizer in ASCII, converting video to ASCII art, matrix-style effects, or any animated ASCII output.
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。
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
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。