gws-modelarmor 是做什么的？
Google Model Armor：对用户生成的内容进行安全过滤。
Google Model Armor：对用户生成的内容进行安全过滤。
Google Model Armor 是一项安全技能，旨在对用户生成的内容进行过滤和审查。它支持在 AI 助手（如 Claude Code、Cursor、Codex 等）中集成，帮助开发者确保输入和输出的内容符合安全策略。该技能通过调用 Google Model Armor API 检测有害内容（如仇恨言论、暴力、色情等），并提供详细的违规报告。它适用于需要内容审核的聊天应用、内容平台或任何涉及用户交互的 AI 系统。使用该技能可以显著降低有害内容的风险，并符合内容安全合规要求。
npx skills add https://github.com/googleworkspace/cli/tree/main/skills/gws-modelarmorInstalled? Explore more 写作与编辑 skills: steipete/notion, langchain-ai/langchain, bytedance/podcast-generation · View all 6 →
Google Model Armor：对用户生成的内容进行安全过滤。
This repo contains 20 individual skills — each has its own dedicated page.
Google Workspace Admin SDK: Audit logs and usage reports.
Google Calendar: Manage calendars and events.
Google Calendar: Show upcoming events across all calendars.
Google Calendar: Create a new event.
Google Chat: Manage Chat spaces and messages.
Google Chat: Send a message to a space.
Google Classroom: Manage classes, rosters, and coursework.
Read and write Google Docs.
Google Docs: Append text to a document.
Google Drive: Manage files, folders, and shared drives.
Google Drive: Upload a file with automatic metadata.
Subscribe to Google Workspace events.
Google Workspace Events: Renew/reactivate Workspace Events subscriptions.
Google Workspace Events: Subscribe to Workspace events and stream them as NDJSON.
Read and write Google Forms.
Gmail: Send, read, and manage email.
Gmail: Forward a message to new recipients.
Gmail: Read a message and extract its body or headers.
Gmail: Reply to a message (handles threading automatically).
Gmail: Reply-all to a message (handles threading automatically).
Notion CLI/API for pages, Markdown content, data sources, files, comments, search, Workers, and raw API calls.
The agent engineering platform.
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
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