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概要と使いどころ
Alibaba Cloud SLS (Simple Log Service) provider for obz. Supports metrics (PromQL), logs (SLS Query), and traces across project/store pairs. Requires AccessKey auth and provider-specific flags like --project, --logstore, --metricstore, and --trace-logstore. This skill should be used when the user mentions "SLS", "Alibaba Cloud", "obz -p sls", or needs to configure SLS provider instances.
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 operating Inngest API resources from the terminal with `npx inngest-cli@latest api`: Cloud/local run debugging, event-run lookup, function traces, function invocation, app syncs, webhooks, environments, keys, account checks, and Insights queries. Provides prescriptive command routing for agents: which CLI command to run for a run ID, event ID, app ID, function ID, Cloud environment, API key, missing ID, or potentially mutating operation. Use `inngest-cli` for dev server setup/general CLI workflows and `inngest-api` only when raw REST API v2 docs or OpenAPI fallback are needed.
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。
用户咨询腾讯云产品资源、AWS、阿里云等多云资源时，查看智能顾问架构图、架构目录、架构详情、架构评估结果、绘制架构图、开通智能顾问时、AI智能巡检、AI容量监测、AI混沌演练、AI云诊断、主动预警、架构健康度、云运维问答、云资源查询、云成本优化、安全合规、云资源盘点、闲置资源检查、云产品最佳实践等AIOps、ChatOps、CloudOps操作时使用。
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。
Makers 开发专家团后端工程师 Skill — Edge Functions (V8)、 Cloud Functions (Node.js/Go/Python)、Middleware、KV/Blob 存储开发。 触发词：后端 API、Edge Function、Cloud Function、Middleware、 KV 存储、Blob 存储、Express、FastAPI、Gin、鉴权、数据库。
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。
Run AI agent tasks on a Volcengine (火山引擎) cloud phone via the Mobile Use Agent OpenAPI. Use when the user asks to drive, automate, operate, or test an Android app on a cloud phone for enterprise use cases (e.g. reply to WeCom customer messages, add leads in a CRM, clock in on DingTalk, check invoicing stats, query inventory in a supply-chain app, ship e-commerce orders, approve OA requests) or personal ones (open 小红书 and search, place an order, check nearby places on a map), or to check status, fetch result, cancel, or list a Mobile Use run. Requires one-time setup to store Volcengine AK/SK locally; ProductId and PodId can be saved as a default device during setup, the user prompt is provided per run. Supports optional GPS injection (GpsInfo) with user consent (auto-asked only for location-related 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。
Use when assessing cloud infrastructure for security misconfigurations, IAM privilege escalation paths, S3 public exposure, open security group rules, or IaC security gaps. Covers AWS, Azure, and GCP posture assessment with MITRE ATT&CK mapping.
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 polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid flowchart, sequenceDiagram, and stateDiagram input; inspect repository evidence when the diagram must reflect real code. Use when the user asks to visualize system architecture, infrastructure, cloud/security/network topology, technical workflows, API call sequences, request lifecycles, data pipelines, ETL/ELT, data lineage, state machines, or to convert/beautify Mermaid. Also use for Archify, interactive or animated HTML diagrams, インタラクティブ図, 動く構成図. When an editable .drawio file is required, use the draw.io workflow instead and treat Archify HTML only as a supplement.
Generate draw.io editable diagrams (.drawio, .drawio.svg) from text, images, or Excel. Orchestrates 3-agent workflow (Analysis → Manifest → SVG generation) with quality gates. Use when creating architecture diagrams, flowcharts, sequence diagrams, or converting existing images to editable format. Supports Azure/AWS cloud icons. Triggers on draw.io, drawio, ダイアグラム, アーキ図, フローチャート, シーケンス図.
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browser_use, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle hooks, MCP server setup, or monitoring/observability with Laminar or OpenLIT. Also trigger for questions about browser-use installation, prompting strategies, or sensitive data handling. Do NOT use this for Cloud API/SDK usage or pricing — use the cloud skill instead. Do NOT use this for directly automating a browser via CLI commands — use the browser-use skill instead.
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。
Exploit Server-Side Request Forgery (SSRF) vulnerabilities in applications hosted on AWS to access the highly sensitive Instance Metadata Service (IMDS). This allows an attacker to steal valid IAM roles and temporary security credentials, leading to catastrophic cloud account compromise.
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。
Exploit Server-Side Request Forgery (SSRF) vulnerabilities on Amazon Web Services (AWS) EC2 instances to access the highly sensitive Instance Metadata Service (IMDS). Circumvent basic protections and extract temporary IAM access keys, escalating privileges comprehensively across the AWS Cloud environment.
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。
Execute lateral movement within Microsoft Entra ID (formerly Azure AD) and Microsoft 365 environments. Use this skill to traverse cloud resources using compromised user tokens, managed identities, Primary Refresh Tokens (PRT), and application permissions (Service Principals) to achieve Global Administrator 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。
Abuse Azure Managed Identities from compromised Azure Virtual Machines (VMs), Functions, or App Services to seamlessly request valid, highly-privileged Azure AD access tokens and laterally move throughout the cloud environment without requiring explicit credentials.
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。
Exploit AI assistants equipped with web-browsing capabilities or internal API plugins to perform Server-Side Request Forgery (SSRF). This skill details injecting prompts that force the LLM to request sensitive internal endpoints, such as underlying cloud metadata services or internal networks.
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。
Cloudflare Workers edge compute platform — Wrangler CLI, KV, D1, R2, Durable Objects, Queues, Workers AI
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。
Google Cloud guidance — core services, IAM, VPC networking, GKE/Cloud Run choices, BigQuery, and cost control.
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。
Cloudflare guidance — DNS, CDN caching, WAF, Workers, Pages, Zero Trust, and edge performance tuning.
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。
Understanding and optimizing cloud/PaaS pricing — cost models, common traps, and FinOps habits — vendor-neutral.
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。
Deploy cloud access security brokers — shadow IT discovery, SaaS governance, and cloud data protection.
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。
Secure cloud environments — IAM, posture management, logging, and multi-account architecture across providers.
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 and manage Volcengine cloud resources using the Volcengine CLI (`ve` command). Supports all Volcengine services including ECS, VPC, CLB, RDS, Redis, and more. Trigger this skill whenever the user asks to create, query, modify, or delete cloud resources on Volcengine, mentions the `ve` command, says "volcengine CLI", or describes infrastructure tasks such as "create an ECS instance", "set up a VPC", "list security groups", "allocate an EIP". Also trigger on Chinese prompts mentioning "火山引擎" or "火山" (e.g., "火山引擎上有哪些 ECS"、"查一下我火山的云服务器"、 "火山引擎创建一个 VPC"、"火山的 Redis 实例列一下"). Also trigger when the user encounters errors from `ve` commands and needs troubleshooting help. Also use for TOS bucket/object operations, tosutil (sometimes written tosutils), Ark CLI / arkcli model discovery, inference, generation, endpoints, fine-tuning, plans, or usage, and TLS (日志服务) / volclog log search, analysis, ingest, export, or LogCollector collection, through `ve tosutil`, `ve arkcli` and `ve volclog`.
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。
Deploy a local project directory or Git repository to Volcengine as a running, reachable cloud service. USE WHEN: deploy to Volcengine, deploy to 火山引擎/火山, deploy this repo/project, publish current code, launch the app, run it in the cloud, expose it as a service, deploy to ECS/VKE/veFaaS, run on ECS, push to VKE, deploy as serverless/FaaS, or the user wants the agent to choose a Volcengine hosting target. If the user only asks which Volcengine deployment target to choose, use `volcengine-prepare` skill first. Not for creating a single standalone resource — use `volcengine-cli` skill for that.
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。
Creates Pulumi infrastructure-as-code projects in Python, defines cloud resources (AWS, Azure, GCP), configures ESC environments for secrets management, sets up OIDC authentication for secure deployments, and builds multi-language component resources. Use when creating Pulumi Python projects, writing infrastructure code, configuring cloud providers, managing secrets with Pulumi ESC, setting up OIDC for Pulumi, automating infrastructure deployments with Python, creating reusable Pulumi components in Python, or configuring Python toolchains (pip, poetry, uv) for Pulumi. Also use when the user mentions pyproject.toml with Pulumi, component_provider_host, or Python virtual environments for infrastructure code.
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 cloud infrastructure through natural language conversations with Pulumi Neo, an AI agent for platform engineers. Enables infrastructure analysis, resource provisioning, stack deployment, and configuration management via conversational AI. Use when creating Neo tasks, requesting infrastructure analysis, automating cloud deployments, managing infrastructure as code (IaC), provisioning AWS/Azure/GCP resources, managing infrastructure through natural language prompts, reviewing PRs with Neo, handling Neo approval workflows, or checking Neo task status and events. Also use when the user mentions "Pulumi Neo", "Neo task", "Neo agent", or wants AI-assisted infrastructure 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。