「lab」の検索結果

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.

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Optimize RF PCB dimensions for bandwidth, return loss, or area via patternsearch and surrogateopt with constraints. TRIGGER: user asks to optimize an RF PCB component for performance (bandwidth, return loss, insertion loss, area) or apply constraints to a design. Invoke BEFORE writing optimization code — RF PCB Toolbox has a built-in optimize() function that differs from generic fmincon/ga approaches. SKIP: designing a component from scratch without an optimization objective (use the specific matlab-design-pcb-* skill), EM analysis without optimization (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material).

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Detect and validate GPU availability for MATLAB GPU computing. Use when the user can't use their GPU, or is setting up or selecting a GPU. Triggers on: gpuDevice, GPU setup, check GPU, GPU not found, GPU not working, can't use GPU, GPU not available, unable to find a supported GPU device, compatible GPU, canUseGPU, validateGPU.

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Show all installed MATLAB products and support packages for a given MATLAB installation folder. Use when listing, checking, or verifying what products or support packages are in a MATLAB installation.

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Reads from, writes to, and manages relational databases using MATLAB Database Toolbox. Use when connecting to databases, reading data with sqlread or fetch, filtering with rowfilter, writing with sqlwrite, updating with sqlupdate, executing SQL statements, managing transactions with commit and rollback, mapping MATLAB classes to tables with ORM (Mappable, ormread, ormwrite, ormupdate), or performing any database operation from MATLAB. Triggers on: database, SQL, sqlread, sqlwrite, sqlupdate, fetch, execute, rowfilter, RowFilter, ORM, Mappable, ormread, ormwrite, ormupdate, orm2sql, transaction, commit, rollback, Database Toolbox, PostgreSQL, MySQL, SQLite, SQL Server, Oracle, database connection, database table, query database, insert data, update rows, delete rows, stored procedure, prepared statement, odbc, databaseConnectionOptions, datasource, data source, DSN, connection string, multithreaded, parallel.

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Connect MATLAB to Databricks via Spark (Databricks Connect) or JDBC (Database Toolbox). Use when setting up the MATLAB Interface for Databricks, configuring authentication (OauthU2M, OauthM2M, PAT), creating Spark sessions with getDatabricksSession(), reading Unity Catalog tables with server-side filtering, creating JDBC connections with databricks.JDBCConnection or StandaloneJDBCConnection, connecting to SQL Warehouses, selecting JDBC drivers (Simba/OSS), or writing data back to Databricks. Triggers on: Databricks Connect, Spark from MATLAB, getDatabricksSession, .databrickscfg, databricks.JDBCConnection, StandaloneJDBCConnection, SQLWarehouse, Databricks JDBC, Databricks cluster, large table server-side filtering.

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Writes MATLAB performance tests using the matlab.perftest.TestCase framework. Use when asked to write, create, or add performance tests for MATLAB code, benchmark functions, measure execution time with statistical rigor, or use runperf.

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Generate and structure MATLAB unit tests using matlab.unittest and matlab.uitest features, including class-based tests, parameterized testing, fixtures, mocking, and app testing with gestures. Use when writing, generating, or adding tests, creating test classes, adding test methods, parameterizing tests, setting up fixtures, mocking dependencies, or testing App Designer apps. Do NOT use for running tests, collecting coverage, or CI/CD configuration.

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Generate or improve MATLAB help text (documentation comments) for a function, class, or script file following MathWorks standards (H1 line, syntax paragraphs, See Also, 75-char lines). Read BEFORE writing MATLAB help — default patterns (Inputs:/Outputs: lists, block comments, uppercase See Also) produce non-conforming output. Use when writing, rewriting, fixing, or reviewing MATLAB help comments or function documentation.

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Generate correct MATLAB code using the Symbolic Math Toolbox. Use when the user asks for symbolic computations, analytical solutions, symbolic differentiation/integration, equation solving, or converting symbolic results to numeric MATLAB functions. Also use when converting differential equations to transfer functions or state-space form, extracting PDE coefficients (pdeCoefficients), symbolic-to-C code generation (matlabFunction + codegen), symbolic matrix variables (symmatrix), physical units and constants (symunit, newUnit), or rewriting/combining algebraic expressions (rewrite, combine).

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Review MATLAB code for quality, performance, maintainability, and adherence to MathWorks coding standards. Uses check_matlab_code and matlab_coding_guidelines. Use when reviewing code, checking style, finding code smells, assessing quality, or preparing code for handoff or publication.

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Import PyTorch, ONNX, or Keras 3 / TensorFlow 2.16+ deep learning models into MATLAB as dlnetwork objects. Use when importing .pt2 exported programs, traced .pt files, .onnx models, or Keras 3 models via matlabsaver. Covers importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromKeras, importNetworkFromTensorFlow, torch.export.export, PyTorchInputSizes, InputDataFormats, matlabsaver, tf_keras downgrade, numeric validation against PyTorch or ONNX Runtime, and placeholder/custom layer implementation. Applies when user mentions any of these functions, file formats, or encounters import errors, unsupported operator warnings, 0 learnables, or uninitialized networks.

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When the user wants to improve crawlability, fix orphan pages, or optimize site structure for search engines. Also use when the user mentions "crawlability," "crawl budget," "orphan pages," "internal links," "site structure," "site crawlability," "infinite scroll," "pagination," "masonry SEO," "AI crawler optimization," "GPTBot crawlability," "ClaudeBot crawlability," or "content not indexed." For internal links, use internal-links.

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Expert knowledge for Azure DevTest Labs development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing lab VM images, ARM/CI-CD automation, RBAC/Key Vault security, hub-spoke networking, or quotas, and other Azure DevTest Labs related development tasks. Not for Azure Lab Services (use azure-lab-services), Azure Dev Box (use azure-dev-box), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).

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Enable nullable reference types in a C# project and systematically resolve all warnings. USE FOR: adopting NRTs in existing codebases, file-by-file or project-wide migration, fixing CS8602/CS8618/CS86xx warnings, annotating APIs for nullability, cleaning up null-forgiving operators, upgrading dependencies with new nullable annotations. DO NOT USE FOR: projects already fully migrated with zero warnings (unless auditing suppressions), fixing a handful of nullable warnings in code that already has NRTs enabled, suppressing warnings without fixing them, C# 7.3 or earlier projects. INVOKES: Get-NullableReadiness.ps1 scanner script.

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Generate MATLAB Grader assessment item sets. Use when the user asks to create MATLAB Grader assessment items, generate MATLAB assessment materials, build MATLAB homework assessment items, QTI 3 portable assessment items, or mentions "grader assessment items". Produces complete assessment item folders with description, solution, template, tests, Function call blocks, and optional QTI 3 interchange files.

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Use when designing or validating GitLab CI/CD and automatic release lifecycles, inspecting pipeline and job state read-only, composing non-interactive merge-request commands, or setting up protected refs and release credentials. Also covers reusable components and inputs, GitLab Functions, gitlab-ci-local, glab command composition, and GitLab Flavored Markdown. For pipeline execution or retry requests, provide inspection and command drafting while leaving execution to the operator.

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MATLAB R2026a testing, validation, and CI workflow for matlab.unittest, MATLAB Test, Simulink Test, coverage, artifact generation, GitHub Actions, and open-source reproducibility. Use whenever MATLAB work needs verification, regression tests, CI, GitHub publication, or acceptance criteria.

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MATLAB R2026a agentic workflow router. Use this whenever the user asks for MATLAB, Simulink, .m/.mlx/.slx work, toolbox-driven engineering, paper reproduction, simulation, code generation, data analysis, control, robotics, signal/image/AI workflows, or wants an end-to-end automated MATLAB task with validation. For Simulink tasks on this machine, default to a visible workflow: open MATLAB/Simulink windows first so the user can watch modeling, simulation, tuning, and plotting progress.

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Configure Salesforce Translation Workbench and translate custom labels, picklist values, field labels, page layout sections, or the Experience Cloud language switcher. Triggers: 'how to add a language to Salesforce', 'translate custom labels', 'Translation Workbench setup', 'picklist value translation', 'RTL language support'. NOT for creating the Custom Label records or referencing them from Apex/LWC — use admin/custom-label-management. NOT for locale formatting and RTL layout inside a component — use lwc/lwc-internationalization. Also: CustomObjectTranslation, objectTranslation file, GlobalValueSetTranslation, StandardValueSetTranslation, LanguageSettings, enableTranslationWorkbench, locale code, end-user language, platform-only language, data translation.

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Custom Labels for i18n, configuration strings, and UI text: translation workbench, Apex System.Label, LWC @salesforce/label imports, 1,000-char limit. NOT for translating picklist values, field labels or layouts — use admin/multi-language-and-translation. NOT for config values in custom metadata or custom settings — use admin/custom-metadata-types.

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Manage Confluence collaboration surface via the confluence-as wrapper: comments, attachments, labels, watchers. Triggers: 'add comment to page 12345', 'upload attachment to page 12345', 'label page 12345 as urgent', 'watch page 12345'. Inline-vs-footer comment safety enforced. NOT for page CRUD (mk:confluence-page); NOT for bulk ops (mk:confluence-bulk).

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Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).

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Pull Request / Merge Request を作成するときに必ず参照する。`gh pr create`/`glab mr create` で PR/MR を作る、コミット済みの作業をレビューに出す、並列・stacked 作業の各ブランチで PR を起こす、といった場面で使う。リポジトリの pull_request_template/merge_request_template を決定論スクリプトで検出して優先し、テンプレの骨組み（見出し・チェックリスト・順序）を改変せず入力箇所を埋めるだけにする（作成前に骨組み照合ゲートで機械検証）。無ければ汎用観点で本文を構成。本文の素材は対象リポジトリの git 差分のみに限定し、他リポジトリ・他タスクの内容を混入させない。draft 既定。head が保護ブランチ（GitHub 上・origin/HEAD の既定ブランチ、main・master・develop・trunk・release 系など）のときだけ push と作成の前にユーザー承認を取り、それ以外は確認せず push して作成する。GitHub(gh) 基本、GitLab(glab) 等にも対応。