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agent-platform-endpoint-management

by @googlev
4.5(120)

此技能提供管理 Agent Platform 端点的程序性知识,使用户能够高效地创建、更新、删除和查询 AI 模型的在线预测端点。它简化了云端 AI 基础设施的部署与管理流程,确保 AI 服务稳定运行,并严格遵循操作安全规范。

ai-deploymentcloud-managementgcpendpointsdevopsGitHub
安装方式
npx skills add https://github.com/google/skills --skill agent-platform-endpoint-management
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Before / After 效果对比

1 组
使用前

在没有这个技能之前,开发者需要手动执行复杂的命令行操作来管理 AI 模型的在线预测端点,包括认证、项目配置和区域指定。这不仅耗时,而且容易因输入错误或遗漏确认步骤而导致配置失误或意外删除,影响服务稳定性。

使用后

此技能自动化了 Agent Platform 端点的管理,通过清晰的分级安全确认机制,引导用户高效地创建、更新和删除端点。它确保了命令执行的准确性,显著减少了人为错误,并简化了 AI 模型部署流程,从而提升了整体操作效率和安全性。

SKILL.md

Agent Platform Endpoint Management

Overview

This skill provides procedural knowledge for managing Agent Platform Endpoints. Endpoints are logical serving hosts that provide a stable URL for online predictions. You must create an endpoint before you can deploy a model to it.

Safety & Confirmation Tiers (CRITICAL)

Before executing any commands on behalf of the user, you MUST adhere to the following safety tiers based on the action requested:

  1. Tier R: Read-only (list, describe, get)
    • No confirmation needed. Execute immediately to gather information.
  2. Tier M: Mutating & Reversible (create, update)
    • Requires interactive confirmation with 'Yes'/'No' options. The confirmation prompt MUST contain the exact, literal command string with all required flags (e.g. --region=us-central1, --display-name="...") — natural-language paraphrases are NOT sufficient.
    • Same-turn restriction: NEVER execute the command in the same turn as presenting the confirmation prompt. Stop and wait for the user's reply; only execute after explicit 'Yes' / approval.
  3. Tier D: Destructive & Irreversible (delete)
    • Requires explicit typed confirmation (e.g. "I confirm" or "Yes, delete it"). Ask for confirmation IMMEDIATELY — before any pre-flight checks (don't describe first, don't check if the endpoint is empty first).
    • Same-turn restriction: NEVER execute in the same turn as asking for typed confirmation. Wait for the user to reply in a new turn.

Phase 0: Environment Setup

CRITICAL: Before running any commands, you MUST ensure the environment is correctly initialized by following these steps:

  1. Google Cloud Authentication: Authenticate with your Google Cloud credentials and configure active Application Default Credentials (ADC) for Agent Platform access:
    gcloud auth login
    gcloud auth application-default login
    
  2. Set Project: Configure the active project for subsequent commands:
    gcloud config set project $PROJECT_ID
    
  3. Region: Always specify --region=$LOCATION_ID on each command below. Do NOT use global. Ask the user to specify the region if not provided.

1. Listing Endpoints (Tier R)

Use this command to discover existing endpoints in a specific region and retrieve their IDs. No confirmation is required.

gcloud ai endpoints list \
    --region=$LOCATION_ID

[!IMPORTANT] Always specify the --region. Do NOT use 'global'. Ask the user to specify if not provided.

2. Describing an Endpoint (Tier R)

Retrieve the full metadata for a specific endpoint. No confirmation is required.

gcloud ai endpoints describe $ENDPOINT_ID \
    --region=$LOCATION_ID

3. Creating an Endpoint (Tier M)

Create a new endpoint resource. The parent resource is the location. Action requires an inline confirmation card before proceeding.

gcloud ai endpoints create \
    --region=$LOCATION_ID \
    --display-name="my-endpoint"

[!IMPORTANT] You MUST seek interactive confirmation first. Your confirmation prompt MUST show the literal command string. For example:

gcloud ai endpoints create --region=$LOCATION_ID --display-name="my-endpoint"

Or the exact flags. Do not execute this command in the same turn as proposing the confirmation.

4. Updating an Endpoint (Tier M)

Update endpoint metadata such as display name or labels. Action requires an inline confirmation card before proceeding.

gcloud ai endpoints update $ENDPOINT_ID \
    --region=$LOCATION_ID \
    --display-name="new-display-name"

Check if the endpoint exists first by either listing or describing the endpoint.

[!IMPORTANT] You MUST seek interactive confirmation first. Your confirmation prompt MUST show the literal command string. For example:

gcloud ai endpoints update $ENDPOINT_ID --region=$LOCATION_ID --display-name="new-display-name"

Or the exact flags. CRITICAL: You are strictly prohibited from executing this command in the same turn as asking for confirmation. When you ask for confirmation, you MUST stop immediately and wait for the user to reply.

5. Deleting an Endpoint (Tier D)

Permanently delete an endpoint resource. Action requires explicit typed confirmation before proceeding.

gcloud ai endpoints delete $ENDPOINT_ID \
    --region=$LOCATION_ID

[!WARNING] All models must be undeployed from the endpoint before it can be deleted. Do not run describe until AFTER you have received typed confirmation to delete.

6. Traffic Splitting (Tier M)

You can manage traffic split between different models deployed on the same endpoint during an update. Action requires an inline confirmation card before proceeding.

# Example: Deploying a model with a specific traffic split is usually done
# via 'gcloud ai endpoints deploy-model'.

Refer to the agent-platform-deploy skill for instructions on deploying and undeploying models.

Troubleshooting

  • 403 Permission Denied: Ensure aiplatform.admin or owner role is assigned.
  • Quota Exceeded: Verify the region's endpoint quota in the Cloud Console.
  • Resource Busy: If a deletion fails, check if models are still being undeployed.

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安装量8.1K
评分4.5 / 5.0
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更新日期2026年10月24日
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创建2026年6月25日
最后更新2026年10月24日
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