「hybrid」の検索結果

Audit, redesign, generate, and improve IEEE manuscript figures, tables, captions, result presentation, plotting scripts, visual polish, hybrid Python/R plus vector-editor workflows, publication-ready matplotlib house style, and layout using routed visual-evidence checks. Use when checking or creating plot readability, axes, legends, line overlap, table structure, metric reporting, captions, grayscale accessibility, IEEE one-column/two-column layout, figure/table placement, claim-evidence mapping, reviewer first-impression risks, matplotlib/seaborn or ggplot2 figure code, SVG/PDF/TIFF/PNG export, Illustrator/Inkscape/PowerPoint/Figma finishing plans, or IEEE-style engineering evidence graphics.

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。

Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).

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 advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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。

Provides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.

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。

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.

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。

Assessment of pseudonymization techniques and re-identification risk. Covers tokenization, hashing, encryption-based pseudonymization, and hybrid approaches. Includes re-identification risk scoring using the motivated intruder test, quantitative metrics (marketer, journalist, prosecutor models), and linkage attack resilience evaluation. References ENISA 2019 pseudonymization report.

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。

Jacky Motion 2.2 Hybrid：把中文口播稿变成可录屏的信息动画单文件 HTML。可选纯 HTML 手动推进（16:9 或 3:4）或配合 SRT 自动播放（16:9，含 B-roll 录屏画框）。流程为审稿、分镜、锁风格、装配与视觉验收；七种重点风格共享同一套版式、动效与质量门禁。

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Use whenever you need to understand how this theme works — adding pages, managing content, configuring the site, using partials/components/modules, project architecture, scripts, or styling/theming (Tailwind v4, Bootstrap 5, or a hybrid — verify which). Use for ANY question about the structure, usage, or customization of the template or theme.

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Build recommendation systems with collaborative filtering, matrix factorization, hybrid approaches. Use for product recommendations, personalization, or encountering cold start, sparsity, quality evaluation issues.

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Retrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query. Use when the task starts with a corpus or index that must be searched; use context-ranking when candidate chunks already exist and only need ordering.

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。

Think and work like an expert Machine Learning Engineer. Use when a task calls for Machine Learning Engineer judgment. Reasons from decision-policy framing, Google's Rules of ML, point-in-time data, and prefill/decode inference physics through GBDT/PyTorch baselines, vLLM/SGLang/KServe serving with FP8/AWQ quantization, hybrid-retrieval RAG, RAGAS and human-validated LLM judges, OpenTelemetry GenAI tracing, and post-Omnibus EU AI Act obligations while treating train-serve skew, temporal leakage, prompt injection, LLM nondeterminism, and degenerate feedback loops as first-class failure modes.

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。

Think and work like an expert High-Performance Computing Specialist. Use when a task calls for High-Performance Computing Specialist judgment. Reasons from NUMA topology and hybrid MPI+OpenMP+CUDA decomposition through Slurm fairshare/backfill job design, strong/weak scaling (Amdahl/Gustafson), Darshan/mpiP/Nsight profiling, and parallel HDF5/MPI-IO on Lustre while treating I/O storms, collectives bottlenecks, and rank-binding mistakes as first-class failure modes.

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Provider-independent workflow for producing terminal, IDE, documentation, browser, desktop, and application demonstration videos. Use when choosing authentic capture, browser automation, synthetic UI, or hybrid treatment; scripting actions and narration; resetting demo state; protecting secrets and personal data; directing cursor/callouts; creating crop variants; and reviewing workflow truth, readability, accessibility, and provenance.

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。

Provider-independent production workflow for AI-assisted fashion campaigns, lookbooks, editorial fashion films, ecommerce/editorial hybrids, social cutdowns, virtual try-on assets, generated model/lifestyle ads, and retouched fashion visuals; use when an agent must plan, prompt, produce, review, localize, or deliver fashion imagery or video while preserving garment truthfulness, model consent, fit representation, claims substantiation, platform compliance, accessibility, and fashion QA.

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。

Produce audio-first podcast episodes with generative tools — design the show and episode format (interview, narrative, news brief, two-host conversational), write scripts for the ear, decide between fully-synthetic and hybrid (recorded human + synthetic) production and meet the disclosure duty each triggers, cast and direct multi-voice TTS for consistency and chemistry, build episode structure (cold open, intro/outro, segments, ad slots), assemble and edit, clear music and SFX rights, hit podcast loudness and delivery standards, ship metadata/chapters/transcripts through RSS, and pass platform AI-content policy and QA before publishing. Use this skill whenever the deliverable is a podcast episode or a podcast show bible, or when an agent must make production, rights, disclosure, or delivery decisions for spoken-word audio. Not for music tracks, single-voice notification prompts, or video where picture leads (route audio-for-video to a video skill).

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。

Provider-independent production workflow for AI agents creating game trailers and promos, including announcement, gameplay, launch, DLC/update, store-page videos, social cutdowns, and generated/engine-capture hybrid trailers. Use when planning, scripting, capturing, generating, editing, localizing, reviewing, or QAing game marketing videos where gameplay truthfulness, platform/store constraints, ratings, accessibility, claims, CTA metadata, and rights provenance matter.

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 to plan, direct, troubleshoot, and hand off provider-independent live or hybrid livestream event productions, including run of show, crew, capture, audio, graphics, switching, guests, encoding, ingest, transport choices, latency, redundancy, accessibility, moderation, monitoring, incidents, recording, and delivery.

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。

Provider-independent workflow for AI agents producing documentary-style montages, archive-driven timelines, interview-supported sequences, nonprofit or advocacy shorts, historical explainers, and hybrid generated/archive edits. Use for editorial thesis development, research/source logs, fact-checking, archive rights, synthetic reenactment disclosure, chronology, interview selects, lower thirds, generated b-roll direction, music restraint, captions, sensitive subjects, review escalation, delivery variants, and documentary QA.

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 modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

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Hybrid fingerprint + LLM pipeline for bug classification, deduplication, and ticket generation. Normalizes CI logs, creates stable fingerprints, clusters near-duplicates, then uses LLM for severity classification and ticket writing. Includes bug reporting templates and severity/priority matrix. Use when: "bug triage," "classify bugs," "failure analysis," "auto-classify," "CI failures," "bug report," "defect template." Not for: runtime self-healing of one flaky locator — use test-reliability. Not for: designing new tests from production telemetry — use observability-driven-testing. Related: qa-metrics, qa-dashboard, ci-cd-integration, qa-project-context.

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Author and maintain MANUAL and hybrid test cases and suites in TestRail, Xray (Jira), Zephyr Scale, and Qase. Covers test-case anatomy (title, preconditions, steps, expected results, test data), suite/section organization, bulk authoring from user stories and acceptance criteria, ambiguous-step linting, CSV/API import-export payloads per tool, requirement traceability and coverage gaps, review hygiene, and when a manual case should graduate to automation. Use when: "write a test case," "manual test case," "TestRail case," "Xray test," "Zephyr Scale case," "Qase case," "import CSV into TestRail," "lint these steps," "traceability report," "should this be automated." Not for: Generating automated TEST CODE — that is ai-test-generation. Sprint-level WHAT-to-test selection — that is test-planning. Related: ai-test-generation, test-planning, exploratory-testing, qa-project-context.

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。