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Creates Terraform configuration for Google Cloud Monitoring notification channels, including email, Slack, and Pub/Sub, and attaches channels to existing alert policies. It also checks Pub/Sub topic compatibility and publishing permissions when inspecting the cloud environment.

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• Configuring email or Slack alert notifications
• Adding notification channels to existing alert policies
• Checking Pub/Sub topic compatibility and publishing permissions

Design a shared data platform across Google Cloud, AWS, and Azure for analytics and AI. The skill turns requirements into architecture diagrams, infrastructure code, deployment instructions, and validation checks using Apache Iceberg and BigQuery data agents.

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• Designing a data platform across multiple clouds
• Planning data ingestion and AI serving components
• Preparing infrastructure code and deployment instructions

Automate Cloudflare Browser Rendering operations through Rube MCP, a connection for agent tools. The skill discovers supported actions, verifies an active connection, and executes tasks using the latest tool input requirements.

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• Finding available Cloudflare Browser Rendering actions
• Checking the service connection before a task
• Running multiple operations in a workflow

Sign in to a cloud provider’s command-line tool using a verification URL and one-time code approved on the user’s device. Check installation and account identity, save the login, and run commands within that user’s permissions.

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• Sign in to a cloud CLI from a separate device
• Check whether required CLIs and helpers are installed
• Verify the cloud account before running commands

Plan and carry out agent deployments on Google Cloud using agents-cli. The guide covers deployment targets, permissions, secrets, automated build and deployment pipelines, verification, and recovery procedures for agents built with supported frameworks.

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• Comparing Agent Runtime, Cloud Run, and GKE
• Setting up automated build and deployment pipelines
• Configuring secrets and service account permissions

Operate ArvanCloud (arvancloud.ir) through its REST APIs, including CDN and DNS records, domains, cache purge, WAF and rate limits, Cloud Server (IaaS v3, v1 and the undocumented v2 backups), Object Storage, Edge Computing, Cloud Container, VOD, Live and Video Ads, plus Let's Encrypt DNS-01 certificates via acme.sh dns_arvan. Use when the user wants to list, create, change or delete anything on ArvanCloud, take an account inventory, find out which account a key belongs to, check quota or usage, or debug an ArvanCloud API error. Also trigger on hosts like napi.arvancloud.ir, ecc.{region}.arvanapis.ir, storage.arvanapis.ir, dejban.arvancloud.ir, an "Apikey" Authorization header, the dns_arvan plugin, or one of the user's ArvanCloud-hosted domains.

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为Cloud Worker创建并选择预装工具的镜像，验证启动时间和会话运行状态。验证失败时恢复原镜像选择，并在获得明确批准后删除旧镜像。

• 创建预装所需工具的镜像
• 比较镜像变更前后的启动时间
• 确认新镜像上的会话正常运行

Automate Big Data Cloud operations through Rube MCP, a connection for agent tools. The skill finds available actions, checks their required inputs and connection status, and executes them using Composio's toolkit.

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• Finding available Big Data Cloud tools
• Checking current tool input requirements
• Automating operations after verifying the connection

Set up AWS CloudTrail to record activity across accounts, protect audit logs, and alert on sensitive operations. Includes guidance for querying past events with Athena or CloudTrail Lake and checking log integrity during investigations.

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• Set up audit logging across AWS accounts
• Investigate suspicious API activity
• Configure alerts for sensitive operations

Estimate AWS costs before deployment, analyze spending trends, and investigate metrics and logs with CloudWatch. The skill guides cost reviews, alert setup, and operational improvements through connected tools, with additional integrations for audits and security assessments.

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• Estimating monthly AWS costs before deployment
• Investigating unexpected charges and spending trends
• Setting up CloudWatch alarms and investigating logs

Use CloudFox to inspect AWS and Azure resources through read-only queries. Identify exposed endpoints, secrets, permissions, and role trust relationships, then organize findings into files for reviewing configuration weaknesses and potential paths to broader access.

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• Inventorying an unfamiliar AWS or Azure account
• Finding internet-facing resources
• Mapping role trust relationships and permissions

Evaluate Google Cloud workloads against built-in best practices or custom organizational rules using Workload Manager. Use public client libraries or the REST API to run checks, review violations and scanned resources, and export results to BigQuery.

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• Evaluate workloads against Google Cloud best practices
• Inspect rules for SAP and SQL Server workloads
• Run evaluations using custom organizational rules

Inspect Google Cloud Filestore usage and free space, then propose capacity increases or decreases based on configured thresholds and storage tier limits. Apply resizing after confirmation to address low space or reduce excess capacity.

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• Check free space across Filestore instances
• Increase capacity when storage is running low
• Reduce excess capacity on eligible storage tiers

Find and synthesize official Google developer documentation for platforms including Google Cloud, Gemini, Android, and Firebase. Retrieve command syntax, API details, permissions, and product comparisons through Developer Knowledge, then turn the findings into practical technical answers.

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• Checking gcloud commands and flags
• Looking up API syntax and required permissions
• Comparing Google products and architectures

Design security controls for Google Cloud Agent Gateway, covering incoming client requests and outgoing agent tool calls. Produce architecture diagrams, configuration files, deployment commands, and validation scripts using Model Armor, IAP, and Agent Registry.

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• Design incoming and outgoing agent communication controls
• Prepare Model Armor filters and tool access policies
• Generate scripts to check authentication and allowed tool calls

Design a Google Cloud system for data analysis or machine learning with AI agents. Turn requirements into product choices, an architecture diagram, infrastructure configuration, deployment instructions, and validation steps, with user reviews between phases.

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• Design a data analysis system with multiple AI agents
• Choose Google Cloud products for analytical requirements
• Prepare an architecture diagram and deployment guide

Configure Cloud Logging within one Google Cloud project. Set storage locations, retention periods, routing rules, and viewing permissions; create metrics from logs; and adjust stored volume through exclusions or sampling, which retains only a portion of entries.

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• Set regional log storage and retention periods
• Restrict access to sensitive logs
• Count specific errors with logs-based metrics

Automate Big Data Cloud operations through Rube MCP, a connection for agent tools. The skill finds available actions, checks their required inputs and connection status, and executes them using Composio's toolkit.

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• Finding available Big Data Cloud tools
• Checking current tool input requirements
• Automating operations after verifying the connection

Design cloud architectures and migration plans for AWS, Azure, and GCP. Produce service diagrams, selection rationale, security designs, cost estimates, and recovery strategies, with deployment and rollback plans that account for availability and operational monitoring.

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• Design a cloud architecture and explain service choices
• Plan a cloud migration and cutover checks
• Review cloud spending and resource sizes

Inspect and manage Tencent Cloud resources with tccli, its command line tool. Covers servers, networking, DNS, certificates, permissions, monitoring, and application deployment, with supporting scripts for login and identifying the current cloud instance.

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• Checking Lighthouse and CVM server status
• Reviewing domain expiry dates and SSL certificates
• Inspecting security groups and access permissions

Build and deploy AI agents on Cloudflare Workers using the Agents SDK. Supports persistent conversation state, live WebSocket connections, scheduled tasks, and tool integration, with guidance for connecting browser or React chat interfaces.

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• Build a chatbot that preserves conversation history
• Connect a live chat interface through WebSockets
• Schedule reminders and recurring background tasks

Build remote MCP servers, which let AI agents call external tools, on Cloudflare Workers. This skill covers server code, tool definitions, OAuth authentication, local testing, deployment, and connecting a Codex client.

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• Building a remote MCP server
• Adding OAuth authentication to MCP tools
• Exposing external APIs as tools for AI agents

Coordinate Cloud Claw workflows from launching an agent deployment to managing its virtual machine. It routes work to focused skills for setup, starting and stopping machines, viewing logs, renewing usage, and accessing dashboards through local altllm commands.

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• Launch an agent deployment and manage it afterward
• Inspect, start, or stop an existing virtual machine
• Review logs and access a deployment dashboard

Use this skill when you develop, design, build, deploy, debug, migrate, or troubleshoot CloudBase (腾讯云开发, 云开发, TCB, 微信云开发) projects — Web, 微信小程序, 小程序, uni-app, mobile (iOS, Android, Flutter, React Native). Covers UI (页面, 界面, 表单, dashboard, prototype, 原型); auth (登录, 注册, OAuth, publishable key); databases (NoSQL 文档数据库, MySQL 关系型数据库, PostgreSQL/CloudBase PG, app.rdb(), queryPgDatabase/managePgDatabase, CRUD, security rules); 云函数/cloud functions (serverless, scf_bootstrap); CloudRun (云托管, Dockerfile); 云存储; built-in AI (内置大模型, AI 对话, streaming, 流式输出, 图片生成, generateText, streamText, createModel, generateImage, TokenHub, Hunyuan, DeepSeek, GLM, Kimi, Token Credits 资源包, 小程序成长计划); third-party/custom model onboarding (第三方大模型接入, 大模型调用, LLM API); AI agent (智能体, AG-UI, LangGraph); ops troubleshooting (巡检, 诊断, 日志); spec workflow (需求文档, 技术方案, requirements, tasks.md). Do NOT use for non-CloudBase projects, pure frontend without CloudBase, or self-hosted backends without CloudBase.

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