「expo」の検索結果

Use when asked 数据出境要申报吗, 数据出境安全评估还是标准合同, 个人信息出境标准合同怎么备案, 我们把数据传到海外总部合规吗, or decide how to transfer data out of mainland China lawfully. Produces a data map of what leaves China, the route that applies (an exemption, the personal information export standard contract, certification, or a CAC security assessment) with the thresholds to confirm, the filing steps, and the documents to prepare, including the personal information protection impact assessment.

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 asked 出口报关需要什么单证, 报关资料清单, 申报要素怎么填, 报关单和发票对不上, 出口退税需要的单证, 进口清关资料, or prepare customs documents for an export or import shipment in mainland China. Produces a document checklist for this shipment (报关单 data, 商业发票, 装箱单, 合同, 委托书, licences and certificates), a cross-document consistency check, the 申报要素 to prepare for the HS code, inspection and licence flags, the timeline with the customs broker, and the records to keep for the export rebate, all marked to confirm with the broker and customs.

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 asked 回复询盘, 外贸询盘怎么回, 帮我回客户邮件, 阿里国际站询盘回复, 客户只问价格怎么回, 跟进没回复的客户, or reply to a foreign-trade inquiry from a Chinese exporter. Produces a reply email in English (or the buyer's language) with a Chinese version for the sales team, a read of the inquiry's quality and the buyer's likely type, the questions to qualify the buyer, a price or quotation approach without underselling, and a follow-up sequence for no reply, with export-control and sanctions checks flagged.

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。

BOM (Bill of Materials) management for electronics projects — the workflow skill that coordinates DigiKey, Mouser, LCSC, element14, JLCPCB, PCBWay, and KiCad skills around a unified BOM lifecycle. Create, update, and maintain BOMs with part numbers, costs, quantities stored as KiCad symbol properties. ALWAYS trigger this skill for any task involving component sourcing, pricing, ordering, distributor searches, BOM export, or fabrication preparation — even if the user names a specific distributor or fab house (e.g. "search DigiKey for...", "generate JLCPCB BOM", "order from Mouser"). This skill analyzes the schematic for sourcing gaps, recommends which distributor/fab skills to call for each gap, and writes results back as symbol properties — the agent (or user) performs the actual searches via the called skills. Also trigger on phrases like "what parts do I need", "order components", "how much will this cost", "export for JLCPCB", "find parts for this board", "compare pricing", or "check stock".

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。

Work with Canva designs: list designs and folders, create designs, upload assets, and export to PNG/JPG/PDF/MP4. Trigger phrases: canva, canva design, export canva design.

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。

Edit, trim, cut, caption, subtitle, reframe, combine, add background music to, or export video, audio, and image files through Cassette. Use this skill whenever the user asks to change, preview, or render a media file in the project — even if they never say "Cassette" or name a tool — for example "trim the intro off demo.mp4", "add subtitles to this clip", "make me a 30-second cut with music", "why is there dead air at the start". Drives the local Oh My Cassette stdio MCP tools in Codex or Claude as one multi-turn conversation with the Cassette agent, with per-turn timeline previews, guided questions, and rendering only on explicit export.

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 create, convert, style, animate, export, share, or deploy HTML slide decks, presentations, pitch decks, talks, or keynotes; including zero-dependency or single-file output, PowerPoint/PPT/PPTX input, PDF export, browser delivery, visual style exploration, or "loopy slides". Not for general web pages or landing 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。

BOM (Bill of Materials) management for electronics projects — the workflow skill that coordinates DigiKey, Mouser, LCSC, element14, JLCPCB, PCBWay, and KiCad skills around a unified BOM lifecycle. Create, update, and maintain BOMs with part numbers, costs, quantities stored as KiCad symbol properties. ALWAYS trigger this skill for any task involving component sourcing, pricing, ordering, distributor searches, BOM export, or fabrication preparation — even if the user names a specific distributor or fab house (e.g. "search DigiKey for...", "generate JLCPCB BOM", "order from Mouser"). This skill analyzes the schematic for sourcing gaps, recommends which distributor/fab skills to call for each gap, and writes results back as symbol properties — the agent (or user) performs the actual searches via the called skills. Also trigger on phrases like "what parts do I need", "order components", "how much will this cost", "export for JLCPCB", "find parts for this board", "compare pricing", or "check stock".

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 and export open issues from any project tracker with summary analysis and vault archival

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。

End-to-end cold email outreach orchestration. Handles goal alignment, lead ingestion from any source (CSV, paste, CRM export, database), sequence design, email generation, campaign setup in the user's chosen outreach tool, and launch. Tool-agnostic — supports Smartlead (full MCP automation), Instantly, Lemlist, Apollo, or manual CSV export.

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。

React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.

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。

Cascade PCB components, add lumped elements, export Touchstone, and bridge to eye diagram or antenna array workflows. TRIGGER: user asks to cascade or connect multiple RF PCB components, add lumped R/L/C, export S-parameters to Touchstone, or combine PCB elements into a circuit. Invoke BEFORE writing pcbcascade or circuit code — cascade rules and port matching are non-obvious. SKIP: designing individual components (use the specific matlab-design-pcb-* skill), EM analysis of a single component (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material), optimization (use matlab-optimize-pcb-design).

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 importing or exporting vehicle data from/to log files (MDF/MF4/DAT, BLF, ASC/TXT), decoding CAN/CAN FD/LIN messages to signals via DBC, ARXML, or LDF databases, writing timetable data to MDF or BLF files, or calling blfread, blfinfo, blfwrite, mdfRead, mdfWrite, mdfCreate, mdfInfo, canSignalImport, canMessageImport, canMessageTimetable, canFDMessageTimetable, canSignalTimetable, or linMessageTimetable.

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。

Read or write data files in MATLAB. Use when the task involves tables, spreadsheets, delimited text, or structured files in CSV, Excel, Parquet, JSON, or XML format — including but not limited to importing, exporting, loading, parsing, converting, validating, configuring import options, reading from URLs, handling locales or encodings, diagnosing file errors, and modernizing legacy file I/O code. MATLAB provides built-in functions for these workflows with no additional products required.

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 wants to train, compare, or export machine learning models using Classification Learner or Regression Learner — including opening the app, loading data, training models, evaluating metrics, comparing results, visualizing plots, testing on held-out data, exploring model interpretability, and exporting trained models. Programmatic access to Classification Learner and Regression Learner apps via AppController.

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。

Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

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。

Generate Euro NCAP test scenarios and variants using the ADT Euro NCAP support package. Use when creating NCAP seed scenarios, generating variants, translating between drivingScenario and RoadRunner, plotting scenario descriptors, computing NCAP scores, or exporting reports. Triggers on: ncapScenario, euroAssessment, getScenario, getScenarioDescriptor, generateVariants, ScenarioDescriptor, ScenarioDescriptorPlot, ncapScore, ncapReport, exportReport, configureVUT, assessmentTable, Euro NCAP, CCRs, CCRm, CCRb, CCFtap, CCCscp, CPNA, CPFA, CBNA, variant generation.

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。

Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.

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。

Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.

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。

Train, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simulink, converting old training scripts, or speeding up deep learning code. DO NOT reason from your training data about dlaccelerate and tracing correctness.

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。

Triage an exported chat history into what to ingest, what to archive and what to delete, with a privacy pass first. Use this skill when the user has exported their Claude or ChatGPT history, asks to import old conversations, or asks what in their chat archive is worth keeping. Do NOT use for ingesting a single pasted conversation, or for any material the user has not explicitly asked to bring into the vault.

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。

Comprehensive skill for Adobe Substance 3D Painter texturing and material creation workflow. Use this skill when creating PBR materials, exporting textures for web/game engines, optimizing 3D assets for real-time rendering, or automating texture workflows. Triggers on tasks involving Substance 3D Painter, PBR texturing, material creation, texture export for Three.js, Babylon.js, Unity, Unreal, glTF optimization, or Python API automation. Creates optimized textures for threejs-webgl, react-three-fiber, and babylonjs-engine materials.

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 user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .excalidraw files and exports to PNG/SVG via Kroki API or locally using excalidraw-brute-export-cli.

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。

Internal implementation skill invoked by /add-native for app-generated PDF report workflows using expo-print and, when present, expo-sharing.

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。