232 件 ・ 関連度順
概要と使いどころ
Map evidence-based connections between a wellbeing initiative and specific academic learning outcomes. Use when justifying wellbeing programmes, integrating SEL, or linking pastoral and academic work.
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。
Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says "programmatic SEO", "pages at scale", "dynamic pages", "template pages", "generated pages", or "data-driven SEO".
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。
Code generator skills that produce production-ready Swift code for common app components. Use when user wants to add logging, analytics, onboarding, review prompts, networking, authentication, paywalls, settings, persistence, error monitoring, CI/CD pipelines, localization, push notifications, deep linking, testing, accessibility, widgets, feature flags, app icons, image caching, pagination, HTTP caching, share cards, social export, subscription lifecycle, referral systems, watermarks, streak tracking, milestone celebrations, what's new screens, lapsed user re-engagement, usage insights, variable rewards, consent flows, account deletion, permission priming, force updates, state restoration, debug menus, offline queues, feedback forms, announcement banners, quick win sessions, Spotlight indexing, App Clips, screenshot automation, background processing, app extensions, data export, or SwiftUI preview sample data and variant matrices.
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。
Expert knowledge for Azure Managed Lustre development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when mounting AML filesystems, linking Blob, using AKS CSI, setting quotas, or tuning Lustre performance, and other Azure Managed Lustre related development tasks. Not for Azure NetApp Files (use azure-netapp-files), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager).
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 affiliate blog posts and landing pages for SEO issues. Triggers on: "audit my blog post for SEO", "check my SEO", "SEO review", "improve my rankings", "SEO checklist", "on-page SEO audit", "keyword optimization check", "why isn't my page ranking", "SEO score", "content quality audit", "check my meta tags", "internal linking audit", "quick SEO wins".
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 stack navigation, type-safe routes, deep linking, and URL-based routing with React Navigation in React Native. Use for React Navigation route configuration; defer unrelated performance, notification, build, and styling work.
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。
Write or review manual Zephyr test cases with 1-condition-per-TC granularity, Module_Action on Screen when Condition naming, platform prefix rules, and High/Normal/Low priority classification. Use for test-case authoring and review; defer Jira traceability, linking, and pushing cases to Zephyr.
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。
Trigger only when the user explicitly requests live Jira or Zephyr retrieval, existing-link inspection, linking authored test cases, label updates, or stale-link audits. Do not trigger for analysis-only prompts such as 'Analyze the acceptance criteria for TICK-4521', supplied acceptance criteria, test-case authoring, or AC-to-test 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。
Generate Zephyr test cases from Jira stories: parse acceptance criteria and business rules, impact-analyze existing TCs (update vs. create new), and draft correctly named test cases. Use for AC-to-test generation; defer post-generation Jira linking and manual test-case quality review.
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。
Implement route configuration, go_router/deep linking, and named routes in Flutter. Use for route declarations, route guards, and URL-to-screen mapping; defer transition-only animation, state-transfer/BLoC questions, auto_route-specific setup, and generic app-bar controls.
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。
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
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。
Plan multi-part content series: structure, cross-linking, cadence.
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。
Flowcharts are composed of **nodes** (geometric shapes) and **edges** (arrows or lines). The Mermaid code defines how nodes and edges are made and accommodates different arrow types, multi-directional arrows, and any linking to and from subgraphs.
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。
Implement SAFe methodology in Jira. Use when creating Epics, Features, Stories with proper hierarchy, acceptance criteria, and parent-child linking.
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。
MS data processing with PyOpenMS for LC-MS/MS proteomics and metabolomics — mzML/mzXML I/O, signal processing (smoothing, peak picking, centroiding), feature detection/linking, peptide/protein ID with FDR, untargeted metabolomics. Use matchms for simple spectral matching.
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 planning a topic cluster (hub + spokes) for a new content area. The agent researches the space, identifies the hub topic, maps the spokes, and produces a specific content plan with internal linking strategy.
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。
Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt 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。
Create 4D construction simulations by linking BIM models with project schedules.
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。
Manages digital garden notes, link structures, and health metrics. Use when curating a knowledge base, pruning stale notes, or tracking content maturity.
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。
Group related keywords into topic clusters. Create content hub architecture recommendations and internal linking strategies.
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 Flair for NLP annotation, embeddings, text/sequence model prediction, corpus loading, training/fine-tuning, HunFlair biomedical NER/linking, and production troubleshooting.
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。
Conduct LINDDUN privacy threat modeling across all seven categories: Linking, Identifying, Non-repudiation, Detecting, Data Disclosure, Unawareness, and Non-compliance. Includes DFD-based analysis, threat trees, privacy-specific mitigation strategies, and integration with STRIDE security threat modeling.
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。
Manages the organisational DPIA register tracking all Data Protection Impact Assessments across the enterprise. Covers DPIA lifecycle management, status tracking, review scheduling, Art. 35(11) periodic reassessment, and supervisory authority reporting. Implements a centralised register linking DPIAs to RoPA entries, risk registers, and mitigation plans. Keywords: DPIA register, DPIA tracking, Art. 35(11), review schedule, DPIA lifecycle, centralised register, DPIA portfolio management.
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。
Complete guide to LINDDUN privacy threat modeling methodology covering seven threat categories: Linking, Identifying, Non-repudiation, Detecting, Data Disclosure, Unawareness, and Non-compliance. Includes DFD-based analysis, threat tree catalogs, mitigation mapping to privacy design patterns, and step-by-step process.
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。