「processing」の検索結果

⚠️ External API Notice: This skill sends queries to api.neurodoc.app for processing.

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。

Advanced calendar skill with natural language processing, automatic reminders, and multi-channel notifications

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。

⚠️ External API Notice: This skill sends queries to api.neurodoc.app for processing.

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。

Automatically assess task complexity and adjust reasoning level. Triggers on every user message to evaluate whether extended thinking (reasoning mode) would improve response quality. Use this as a pre-processing step before answering complex questions.

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 the user asks to run Gemini CLI for code review, plan review, or big context (>200k) processing. Ideal for comprehensive analysis requiring large context windows. Uses Gemini 3 Pro by default for state-of-the-art reasoning and coding.

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。

Converts XLSX spreadsheets, including multi-sheet workbooks, into CSV files that can be read and grepped directly. Use whenever an .xlsx report needs processing — exports from Xero, Cryptio, bank statements, or any tool that delivers spreadsheet 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。

Review all unreviewed documents in Hubdoc. Use when reviewing, processing or publishing Hubdoc receipts and bills.

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。

Summarizes raw background check data into structured executive reports with risk categorization (GREEN/YELLOW/RED). Use when processing criminal records, court filings, employment/education verification, sanctions screening, or adverse media for pre-employment screening, executive due diligence, or investment-grade investigations.

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。

依据 RGPD 第 28 条、EDPB 07/2020 和 02/2024 号指南、2021 年标准合同条款（CCT）（执行决定 2021/914）、EDPB 01/2020 号建议（Schrems II 之后的补充措施）以及《欧盟条例 (UE) 2024/1689》（《人工智能条例》），对数据处理协议（DPA）进行系统性分析。生成逐条款的 结构化报告（18 个条款：13 项强制 + 5 项补充），附 🟢/🟡/🔴 诊断、可直接插入的 救济条款、国际传输的详细分析、《人工智能条例》核验以及应向供应商提出的问题。 触发词："analyse de DPA"、"audit DPA"、"vérifier un DPA"、"DPA fournisseur"、 "data processing agreement"、"art. 28 RGPD"、"sous-traitant RGPD"、"négociation DPA"、 "review DPA"、"conformité contrat sous-traitance"。

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。

AI合同风控官 - 智能合同审查与法律风险检测专家级工具。支持多国法律体系（中国/美国/英国/新加坡/德国/日本/澳大利亚/加拿大/欧盟），可批量处理合同文档。 当用户需要：合同审查、合同风险检测、合同条款分析、法律文书审核、采购合同审核、销售合同审查、 劳动合同检查、合作协议评审、违约风险提示、合同比对、法务辅助、合同审计、批量合同审核、 外贸合同审查、国际合同合规、NDA保密协议审核、服务合同审查、租赁合同检查、股权转让协议审核、 借款担保合同审查 时触发此技能。

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。

Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

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。

Apache Spark 4.0.2 best practices for PySpark and Scala distributed data processing

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。

Routes data engineering tasks to the correct DE expert agent. Use when user requests data pipeline design, DAG authoring, SQL modeling, stream processing, or warehouse optimization.

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。

Design Kafka consumer groups that survive rebalances, hit the right delivery guarantee (at-most/at-least/exactly-once), and handle poison messages without stalling the topic. Use when picking a partition assignment strategy (Range vs Sticky vs Cooperative-Sticky vs the new KIP-848 protocol), tuning heartbeat / session / max.poll.interval timeouts, choosing manual vs auto offset commits, designing dead-letter or retry topics, or migrating from Classic to the next-gen Consumer protocol. NOT for Kafka cluster ops (broker tuning, partition reassignment), schema design (Avro/Protobuf/Schema Registry), or stream processing topology (use a kafka-streams 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。

Process, analyze, and visualize geospatial data at scale. Handles drone imagery, GPS tracks, GeoJSON optimization, coordinate transformations, and tile generation. Use for mapping apps, drone data processing, location-based services. Activate on "geospatial", "GIS", "PostGIS", "GeoJSON", "map tiles", "coordinate systems". NOT for simple address validation, basic distance calculations, or static map embeds.

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 in turning data visualizations into compelling video and animation content for social media and marketing. Activate on: data commercial, animated chart, data storytelling video, chart animation, Remotion data video, Motion Canvas, Flourish animation, D3 animation, data viz social media, dashboard recording, data narrative video. NOT for: static data visualization (use data-viz-2025), general video editing (use video-processing-editing), full video production pipeline (use ai-video-production-master).

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。

Decompose DAGs into execution chains using width bounds, stratification, virtual nodes, and matching. Use when minimizing workflow lanes in dependency graphs. NOT for cyclic graphs, generic scheduling, or one-off queries with no preprocessing payoff.

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 data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).

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。

Warehouse cost reduction, auto-scaling, query optimization, and lifecycle policies for data infrastructure. Activate on: data cost, warehouse credits, cost reduction, auto-scaling, lifecycle policy, cold storage, cost monitoring, resource optimization. NOT for: query performance tuning (use data-warehouse-optimizer), batch job optimization (use batch-processing-optimizer).

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。

Executes DAG workflows with parallel wave processing, agent spawning, context isolation, permission enforcement, and full execution tracing. Use when running a planned DAG, managing concurrent agent execution, enforcing isolation boundaries, or tracing execution for debugging. Activate on "execute DAG", "run workflow", "spawn agents", "parallel execution", "execution trace", "agent isolation". NOT for planning DAGs (use dag-planner), validating outputs (use dag-quality), or matching skills (use dag-skills-matcher).

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 in color theory, palette harmony, and perceptual color science for computational photo composition. Specializes in earth-mover distance optimization, warm/cool alternation, diversity-aware palette selection, and hue-based photo sequencing. Activate on "color palette", "color harmony", "warm cool", "earth mover distance", "Wasserstein", "LAB space", "hue sorted", "palette matching". NOT for basic RGB manipulation (use standard image processing), single-photo color grading (use native-app-designer), UI color schemes (use vaporwave-glassomorphic-ui-designer), or color blindness simulation (accessibility specialists).

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 audio transcription pipelines with Whisper, Deepgram, and AssemblyAI including speaker diarization and real-time streaming. Activate on: transcription, speech-to-text, diarization, audio processing, meeting transcripts. NOT for: text-to-speech synthesis (voice-audio-engineer), music generation (ai-engineer).

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。

Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.

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。

Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

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。