1,471 件 ・ 関連度順
概要と使いどころ
Conducting systematic, scoping, and narrative literature reviews. Covers PRISMA/PRISMA-ScR protocols, search strategy (Boolean, MeSH), database selection (PubMed, Scopus, Web of Science, Embase), screening, data extraction, evidence synthesis (narrative, meta-analysis, thematic), and reporting. Use when planning or executing a formal literature review.
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Guide for choosing and creating scientific visualizations for publications and talks. Covers chart-type selection by data structure, color theory for accessibility/print, figure composition, journal formatting (Nature, Cell, ACS), and common pitfalls. Consult when visualizing data or preparing submission figures.
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。
Inspect or save reusable FF&E library products through reviewed, guarded transactions. Use for explicit library imports, corrections or recovery; adopted selections and workbook reconciliation belong to master-schedule.
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 a product, selection or FF&E schedule against sourced evidence and flag discrepancies, unknowns and stale specifications. Use to check product data; not to repair records, certify compliance or generate cut sheets.
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。
Provides workflows to write, debug, and optimize prompts for LLMs, including few-shot example selection, chain-of-thought structuring, system prompt design, and template composition. Use when the user asks to write or improve a prompt, wants help with few-shot examples, chain-of-thought, system prompts, prompt templates, or asks how to get better results from an LLM.
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。
Provides dependency injection patterns for Spring Boot projects, including constructor-first design, optional collaborator handling, bean selection, and wiring validation. Use when creating services and configurations, replacing field injection, or troubleshooting ambiguous or fragile Spring wiring.
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 fonts in the Shift font editor. Use for questions about the font, glyph, source, selection, or view open in the running Shift app (through its local MCP server), for reading, authoring, or compiling saved .shift documents and other font files with shift-cli, and for font concepts such as contours, components, masters, and variable fonts.
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。
When the user needs to design or evaluate system architecture — service boundaries, data models, API contracts, infrastructure topology, database selection, or dependency analysis. Also activate for "design the system", "how should I architect this", "monolith vs microservices", or architecture decision records.
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。
Compare and analyze contractor bids. Score proposals, identify scope gaps, and recommend selections.
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-powered contractor matching and selection for construction projects. Analyze contractor capabilities, past performance, certifications, and project requirements to recommend optimal matches.
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。
Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill. For finding or exploring data, answering questions about the data, or generating SQL, load the databricks-data-discovery skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI tasks.
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 reference: PhotosUI. Query for PhotosPicker, PHLivePhotoView, photo 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。
Swift Charts patterns — marks, axes, selection, styling, composition, Chart3D, accessibility, and Audio Graph. Use when building or improving charts in SwiftUI.
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Selects and routes to the right architecture paradigm. Use when choosing patterns for a new system or comparing trade-offs before making architecture decisions.
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。
Assess whether to escalate models. Use when evaluating reasoning depth.
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 choosing the model for a medical-imaging study. Picks a paper-grounded architecture family (CNN/ViT, U-Net/nnU-Net, detection, SAM/foundation, GNN), then vets the concrete repo or checkpoint for licence, version pin, weight provenance and benchmark overlap.
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。
Renamed to /model-selection in v6 (removed in v7).
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。
Renamed to /model-selection in v6 (removed in v7).
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 building or auditing a radiomics or tabular clinical-ML prediction model with a classical learner (LASSO, SVM, random forest, XGBoost and similar). Enforces nested CV, dimensionality control, in-fold feature selection, feature stability, calibration and external validation.
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。
Operate Fugue workflows, FugueSQL, backend selection, and notebook magics for pandas and distributed dataframe execution.
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 face-alignment installation, import checks, landmark-detection workflows, and detector-backend 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。
Use the faster-whisper package for CTranslate2-backed Whisper transcription, model selection, CPU/CUDA setup, audio utilities, VAD, timestamps, and conversion guidance.
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, inspect, and reuse Featuretools automated feature engineering workflows for EntitySets, DFS, feature matrices, primitive authoring, feature inspection, and selection.
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Guides Earth2Studio weather and climate inference workflows, data access, model and component selection, output/checkpoint handling, extension, and optional REST serving with backend-aware validation.
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。