「poi」の検索結果

Trigger when: (1) User mentions "manimgl" or "ManimGL" or "3b1b manim", (2) Code contains `from manimlib import *`, (3) User runs `manimgl` CLI commands, (4) Working with InteractiveScene, self.frame, self.embed(), ShowCreation(), or ManimGL-specific patterns. Best practices for ManimGL (Grant Sanderson's 3Blue1Brown version) - OpenGL-based animation engine with interactive development. Covers InteractiveScene, Tex with t2c, camera frame control, interactive mode (-se flag), 3D rendering, and checkpoint_paste() workflow. NOT for Manim Community Edition (which uses `manim` imports and `manim` 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。

Build industrial-grade SCADA/HMI dashboards in MATLAB following industrial-HMI conventions (ISA-101-aligned): gray-field philosophy, alarms at source, write safeguards, fixed-range trends, drill-down layout. Produces a real App Designer app (.mlapp, or plain-text .m+.xml on R2026b+) by handing serialization to the matlab-build-app skill when available, and falls back to a programmatic .m app otherwise. Use when wrapping OPC UA / Modbus / MQTT / OSI PI / PI AF monitoring scripts into a live operator app, building plant overviews, designing operator dashboards, or any time a user asks for a "SCADA dashboard", "HMI", "plant dashboard", "operator screen", or "industrial monitoring app" in MATLAB. Trigger on: SCADA, HMI, industrial dashboard, plant overview, operator screen, uigauge, uilamp, alarm banner, gray-field, ISA-101, OPC UA dashboard, setpoint, write safeguards, alarm visualization, OSIsoft PI, AVEVA PI, PI Server, PI Data Archive, PI AF, PI Asset Framework, piclient, afclient.

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。

Discover OPC UA servers, connect MATLAB clients, and browse/navigate server nodes using opcuaserverinfo, the Local Discovery Service (LDS), opcua, connect, setSecurityModel, certificate-trust functions, findNodeById, opcuanode, and Namespace/Children traversal. Use when finding OPC UA servers on the network, querying endpoints and security policies, connecting to a server, authenticating with username/password or certificates, configuring security modes, handling certificate-trust or hostname-mismatch errors, troubleshooting failed connections or empty discovery, inspecting an OPC UA certificate (.der/.pem), browsing an address space, finding nodes by name or NodeId, navigating node hierarchies, invoking method nodes, or batch-processing large namespaces. Trigger on: opcuaserverinfo, LDS, opcua, opc.ua.Client, setSecurityModel, opc.ua.trustServerCertificate, OPC UA certificate, findNodeById, opcuanode, browse OPC UA, find node, OPC UA namespace, OPC UA method node, Industrial Communication Toolbox.

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。

Translate NI-DAQmx C function signatures into correct calldaqlib MATLAB calls. Use when the user mentions calldaqlib, any DAQmx* C function name (DAQmxCfgSampClkTiming, DAQmxExportSignal, DAQmxSetStartTrigRetriggerable, DAQmxGetSampClkRate, etc.), or needs NI-DAQmx functionality not exposed by the daq object. Covers: projection rules (taskHandle implicit, output pointers become return values, buffer-size args, enum-as-string), multi-task semantics, start() clobber, device-level empty-daq workaround, dictionary returns, string getter placeholder, array getter placeholder. Trigger contexts: low-level DAQ, escape hatch, retriggerable acquisition, shared timebase, export signal, connect terminals, external sample clock, trigger configuration, NI driver, C function translation.

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。

Turn raw MATLAB code into a published .mltbx toolbox — full pipeline from scope definition through packaging and release. Drives 8 phases with human checkpoints, enforcing ordering and dependencies. Use when asked to package, create a toolbox, or run the files-to-package pipeline.

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。

Speed up local parfor, parfeval, or spmd by switching to a thread-based parallel pool. Trigger when a user describes slow or disappointing local parallel performance, even if they don't mention threads. Symptoms: parfor on a laptop/workstation is slower than expected or "only slightly faster than for"; parfor scales poorly with the number of workers; ticBytes/tocBytes, the Parallel Pool dashboard, mpiprofile, or system tools show large per-worker data transfer; large broadcast variables or sliced inputs make iterations slow; opening a process pool dominates a short workload; user mentions serialisation or data transfer overhead. Also trigger on any question about whether code or a function works on a thread pool. For non-pool MATLAB performance work (vectorisation, preallocation, profiling), defer to matlab-optimize-performance.

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 MATLAB errors and unexpected behavior. Breakpoints, workspace inspection, try-catch diagnostics, and common error patterns. Use when debugging functions, tracing errors, inspecting variables, or diagnosing runtime failures.

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。

Reviews MATLAB fixed-point (fi) code for performance, code generation efficiency, and correctness. Identifies antipatterns and suggests idiomatic improvements. Use when reviewing fi, fimath, numerictype, or quantizenumeric code.

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。

Amazon profit margin calculator for sellers. Calculate cost breakdowns, profit margins, break-even points, and get pricing recommendations. Supports single product analysis and batch calculations. Input product cost, shipping, FBA fees, and get instant profitability analysis. No API key required. Use when: (1) evaluating new product profitability before sourcing, (2) diagnosing existing product margins, (3) adjusting pricing strategy, (4) analyzing multiple SKUs at once.

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。

Shopify/DTC product differentiation strategy tool. Analyze competitor stores, extract pain points from reviews, identify brand positioning opportunities, and generate actionable differentiation strategies. Includes DTC-specific metrics like CAC, LTV, and brand story analysis. No API key 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。

E-commerce warehouse and inventory optimization advisor. Analyzes inventory health, calculates safety stock and reorder points, performs ABC analysis, evaluates fulfillment costs, and provides actionable recommendations for improving efficiency. Supports all major fulfillment models: Self-fulfillment, Amazon FBA/FBM, Walmart WFS, 3PL, Shopify Fulfillment, TikTok Shop, Dropshipping, and Hybrid setups. No API key required. Use when: (1) reducing stockouts or overstock, (2) calculating safety stock levels, (3) optimizing warehouse costs, (4) improving Amazon IPI score, (5) analyzing inventory KPIs.

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。

Customer loyalty and rewards — points systems, VIP tiers, referral programs, app selection

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。

E-commerce product description generator for any platform. Generates optimized titles, bullet points, descriptions, and backend keywords using competitor research + keyword scoring + FABE copywriting. Two modes: (A) Create — generate listing from product specs with optional competitor analysis, (B) Optimize — improve existing listing with keyword gap analysis. Supports Amazon, eBay, Walmart, Shopify, Etsy, TikTok Shop, Lazada, Shopee. No API key required. Use when: (1) writing a new product listing, (2) analyzing what makes competitors rank, (3) improving an underperforming listing.

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。

E-commerce content marketing strategy planner. Generates content calendars, topic ideas, and platform-specific strategies by analyzing customer reviews, trends, competitor content, and SEO opportunities. Two modes: (A) Build — create a full content strategy from scratch, (B) Audit — analyze existing content and find gaps. Supports TikTok, Instagram, YouTube, Pinterest, blog/SEO, and Amazon A+. No API key required. Use when: (1) planning content for a new product launch, (2) building a content calendar, (3) finding viral content ideas, (4) analyzing competitor content strategies, (5) extracting customer pain points for content topics.

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。

Product review analysis and customer feedback intelligence. Pain point identification, praise pattern analysis, feature request extraction, sentiment analysis, and product improvement insights. Use when the user asks about review analysis, customer feedback, product reviews, or sentiment analysis.

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。

Identify underserved market gaps and unmet customer needs in e-commerce. Analyzes competitor blind spots, review pain points, search demand without adequate supply, and emerging customer segments.

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 and strengthen your e-commerce brand identity. Brand positioning, messaging, visual identity guidelines, and brand consistency across sales channels and marketing touchpoints.

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 and manage vLLM for high-throughput LLM inference. Configure continuous batching, tensor parallelism, quantization, and OpenAI-compatible API endpoints for production LLM serving.

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。

Configure Azure VNets, NSGs, and Azure Firewall. Implement hub-spoke topology and private endpoints. Use when designing Azure network 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。

Generate the post-EXECUTE closeout packet for a plan or phase. Includes archive-readiness classification, drift signal scoring, commit checkpoint recommendation, and move-on next-state recommendation.

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。

CloudBase MCP reference. Use when connecting local or remote MCP, calling tools from the shell with mcporter, reading tool schemas, choosing the domestic or international endpoint, setting site, region, cloud mode, or plugin flags, or contributing a fix to the open-source MCP server, skills, or 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。

Generate API documentation from code. Use when the user wants to document APIs, create API reference, generate endpoint documentation, or needs help with OpenAPI/Swagger specs.

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。

API design patterns and conventions for this project. Covers RESTful URL naming, response format standards, error handling, and authentication requirements. Use when writing or reviewing API endpoints, designing new APIs, or making decisions about request/response formats.

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。