We find that the evolution of cooperation differs markedly across base models, with societies of Cla
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。
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We find that the evolution of cooperation differs markedly across base models, with societies of Cla
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 a project follows a structured operating model with: two work lanes (Domain, System), unresolved work tracked as Epic, bounded execution tracked as Ticket, role-based behavior (architect, runner), helper-backed SQLite workflow tables, inbox and outbox files as task and result bodies.
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。
SOTA Computer Vision Expert (2026). Specialized in YOLO26, Segment Anything 3 (SAM 3), Vision Language Models, and real-time spatial 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。
Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations.
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 user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models (\"blockrun\", \"use grok\", \"use gpt\", \"da...
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。
Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability.
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 patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js ...
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。
Azure Cosmos DB SDK for Java. NoSQL database operations with global distribution, multi-model support, and reactive patterns.
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。
Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom 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。
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
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。
Model sports rules, event formats, prediction types, scoring implications, lock rules, data requirements, and provider constraints for FriendlyBet. Use when adding or comparing sports such as football, basketball, American football, tennis, tournaments, leagues, playoffs, brackets, weekly picks, or World Cup-specific logic.
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。
Coordinate FriendlyBet company-level strategy, CEO handoff, department orchestration, HR/agent-quality escalation, operating-model decisions, multi-agent synthesis, roadmap tradeoffs, decision rights, quality gates, and updates to the virtual company system. Use when Eyal asks to involve the company, CEO, leadership, strategy, operations, several departments, or named executive agents such as Strategy Director, Chief of Staff, or Operating System Lead.
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 CI/CD stages, secrets model, and service-aware pipeline strategy with execution verification gate
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。
Design database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for any database paradigm.
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。
Bu Flutter template'inde uctan uca yeni feature iskelesi kurar — lib/feature/<ad>/ klasor yapisi, Freezed state + Cubit, StatelessWidget ya da StatefulWidget+ViewModel view, BlocProvider yerlesimi (global state_initialize mi lokal mi), TypedGoRoute, LocaleKeys cevirileri, AppPaddings/textTheme/colorScheme token'lari ve zorunlu <feature>.md modul dokumani. Kullanici "yeni feature ekleyelim", "su sayfayi projeye gore yaz", "cubit + state + view kur", "feature iskeleti cikar", "scaffold a feature" dediginde kullan.
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。
Explain how email and Google Calendar work for OpenClaw agents, including the distinction between agent email and owner email, how gog and the Google Workspace skill are used, where related credentials/config live, and how to troubleshoot common setup or access issues. Use when someone asks how an OpenClaw agent accesses Gmail/Google Workspace/Calendar, where credentials are stored, how to use the agent inbox, how to give the agent write access to the owner's calendar, or how to guide another agent/user through the email or calendar setup model.
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。
Report AI token usage and estimated costs. Use when: owner asks about costs today/yesterday/this week, per session, or per model. Shows main session, cron jobs, and subagents. Answers: 'how much did today cost?', 'how much was this session?', 'what was last week's spend?'
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。
Set up a monday.com account for an OpenClaw agent and work with monday.com boards, items, and updates via the GraphQL API or MCP server. Use when: creating a monday.com workspace for a PA, connecting the PA to monday.com, querying boards and items, creating or updating items, troubleshooting monday.com API access, self-registering an agent on monday.com via HATCHA agent verification, or integrating with monday.com workflows. Covers GraphQL cookbook, column types, MCP configuration, and HATCHA self-registration. Works with any LLM model.
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。
Step-by-step setup and troubleshooting for connecting an owner's Google Calendar to an OpenClaw agent with read and write access. Use when: setting up calendar access for the first time, fixing read-only access, re-authenticating a broken Google connection, explaining the difference between the owner's Google account and the agent's Google account, how an OpenClaw agent accesses Gmail or Google Workspace, where credentials are stored, how to use the agent inbox, how to give the agent write access to the owner's calendar, or guiding another agent or user through the email or calendar setup model.
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 working with Cube Dev — cube.dev semantic layer management — monitor deployments, data models, pre-aggregations, query performance, and API health. Use when inspecting cube schemas, debugging slow queries, reviewing pre-aggregation builds, or auditing API usage.
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 working with Contentful — contentful headless CMS management covering space and environment inventory, content type analysis, entry and asset monitoring, locale configuration, webhook tracking, API key auditing, and usage quota monitoring. Use when reviewing content models, investigating publishing issues, monitoring API usage, or auditing space access.
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 working with Cursor — cursor AI-powered editor management and team analytics. Covers team seat management, usage tracking, model configuration, rules file analysis, project settings review, and workspace configuration. Use when managing Cursor team licenses, reviewing AI feature adoption, or analyzing Cursor workspace and rules configurations.
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 working with Census — census reverse ETL management — monitor syncs, destinations, models, source connections, and sync run health. Use when debugging sync failures, inspecting record delivery, auditing destination mappings, or reviewing sync 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。
Use when working with Baseten — baseten ML deployment platform management covering model inventory, deployment status, autoscaling configuration, inference call history, GPU allocation, environment management, and performance metrics. Use for comprehensive Baseten workspace assessment and ML serving 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。