Read BEFORE troubleshooting or enhancing camera image quality. Diagnoses and enhances image quality from cameras connected via Image Acquisition Toolbox or USB Webcams support package. Discovers camera capabilities at runtime, analyzes captured images for quality issues (brightness, contrast, sharpness, noise, color balance, backlighting), suggests hardware setting adjustments tailored to the specific camera, and applies Image Processing Toolbox enhancement functions. Use when a user wants to improve camera image quality, troubleshoot dark/blurry/noisy/grainy/ overexposed/washed out/color cast images, or optimize camera settings.
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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
Design antennas, arrays, and PCB antennas using MATLAB Antenna Toolbox. Covers catalog antenna design and pattern analysis, custom antenna construction (customAntenna + shape.*), PCB antenna design (pcbStack + antenna.*), finite and infinite array design, AI-accelerated design exploration (AIAntenna, patternFromAI), and optimization (SADEA/TR-SADEA). Use when the user wants to design, create, model, analyze, optimize, or fabricate an antenna or array.
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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract fields or currents, compare MoM vs FEM, or control mesh for any RF PCB component. Invoke BEFORE writing sparameters() or solver code — API is non-obvious. SKIP: designing or creating components (use the specific matlab-design-pcb-* skill), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn).
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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
Build, import, analyze, tolerate, and optimize optical systems using the Optical Design and Simulation Library. Use when the user asks about optical systems, ray tracing, geometric optics, Zemax import, optical coatings, tolerancing, or optical design 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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
Generate, verify, refine, and accelerate C/C++ or CUDA code from MATLAB with MATLAB Coder, Embedded Coder, GPU Coder, or MATLAB Test. Also covers writing codegen-ready MATLAB code: language constraints, coder.* directives, and optimization patterns. Triggers on: codegen, MEX, deploy MATLAB as C/C++, GPU Coder, coder.screener, coder.config, coder.gpuConfig, coder.typeof, coder.runTest, matlabtest.coder.TestCase, SIL, embedded config, no dynamic memory, EnableMexProfiling, coder.timeit, coder.perfCompare, %#codegen, writing codegen-ready MATLAB, code generation readiness, coder.varsize, coder.unroll, coder.noImplicitExpansionInFunction, coder.ceval, coder.inline, coder.extrinsic, coder.const, coder.classSignature, class codegen limitations, temporal types codegen, DMA-off, stack-only, host-target InstructionSetExtensions, SIMDAcceleration, OptimizeReductions, host SIMD tuning, host OpenMP, codegen 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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
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。
matlab/matlab-agentic-toolkit☆ 1,1752026年10月14日 更新
Optimize Walmart Marketplace product listings for search visibility and conversion. Covers Walmart SEO, content quality scoring, rich media, and Walmart-specific listing requirements.
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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Optimize product titles for search visibility and click-through rate across e-commerce platforms. Platform-specific title rules for Amazon (200 chars), Etsy (140 chars), Walmart, Shopify SEO, and eBay.
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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Optimize e-commerce checkout flow to reduce cart abandonment. Friction analysis, payment method optimization, trust signals, and checkout UX best practices.
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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Cross-platform PPC strategy planner for ecommerce businesses. Analyzes your product and margins, recommends the right advertising platforms (Google Ads, Meta Ads, TikTok Ads), calculates ROAS targets, allocates budget across channels, and generates platform-specific campaign briefs with ad copy and creative direction. Two modes: (A) Build — design a multi-platform ad strategy from scratch, (B) Optimize — audit existing cross-platform campaigns and reallocate budget. Works for Shopify, WooCommerce, standalone stores, and marketplace sellers expanding to external traffic. 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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Etsy SEO analyzer and optimizer. Improve search visibility with title optimization, tag analysis, description scoring, and keyword research. Includes SEO scoring (0-100), long-tail keyword suggestions, and prioritized action plans. 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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Optimize e-commerce returns process and reduce return rates. Returns policy design, reverse logistics, root cause analysis, and customer retention through better returns experience.
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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Optimize Google Shopping campaigns and product feeds for maximum visibility and ROAS. Feed optimization, bidding strategy, campaign structure, and Performance Max integration.
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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Evaluate ecommerce price candidates using unit economics, historical observations, elasticity analysis, scenario modeling, and controlled experiments. Use when a seller asks what price to test, how price changes could affect contribution or revenue, how to estimate elasticity, how to optimize a bundle or tier, or how to design a price experiment across Amazon, Shopify, TikTok Shop, Walmart, eBay, or other channels. Do not claim a proven optimal price without sufficient clean data, and do not change live prices without explicit authorization.
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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Audit and optimize e-commerce landing pages for conversion. CTA placement, trust signals, page structure, copy optimization, and A/B testing strategy for product pages, collection pages, and campaign 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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Compare and optimize shipping rates across carriers and fulfillment methods. UPS, FedEx, USPS, DHL rate comparison, zone optimization, and shipping strategy to maximize 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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Optimize e-commerce product pages for search engine visibility. On-page SEO, structured data, page speed, mobile optimization, and content strategy for Google, Bing, and platform-specific 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。
nexscope-ai/eCommerce-Skills☆ 1,1642026年8月26日 更新
Optimize Linux system performance. Configure kernel parameters, analyze bottlenecks, and tune resources. Use when improving system 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。
BagelHole/DevOps-Security-Agent-Skills☆ 1,1632026年5月22日 更新
Administer MySQL/MariaDB databases. Configure replication and optimize performance. Use when managing MySQL deployments.
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。
BagelHole/DevOps-Security-Agent-Skills☆ 1,1632026年5月22日 更新
Build and deploy serverless functions on AWS Lambda. Configure triggers, manage permissions, and optimize performance. Use when implementing serverless 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。
BagelHole/DevOps-Security-Agent-Skills☆ 1,1632026年5月22日 更新
Auto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU metrics, and horizontal pod autoscaling. Handle traffic spikes, implement queue-based scaling, and optimize cost with spot instances for AI workloads.
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。
BagelHole/DevOps-Security-Agent-Skills☆ 1,1632026年5月22日 更新
Deploy, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and performance tuning for production RAG and semantic search workloads.
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。
BagelHole/DevOps-Security-Agent-Skills☆ 1,1632026年5月22日 更新