agent-platform-endpoint-management
Manages Agent Platform serving endpoints
Install / Use
npx skills add google/skills --skill agent-platform-endpoint-managementInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
OperationsSupported Platforms
Tags
Our assessment of agent-platform-endpoint-management
agent-platform-endpoint-management scores 83/100 on our quality scale, 245th of 339 Operations skills we index.
Its SKILL.md is 6.0 KB long, well organised into 13 sections with 6 code examples: a thorough specification that gives an agent plenty to work with.
With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 3 days ago, so agent-platform-endpoint-management is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
agent-platform-endpoint-management compared with similar skills
All 4 of these similar skills score higher than agent-platform-endpoint-management; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| agent-platform-endpoint-management (this skill)by google | 83 | 20.3k | 3d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 5d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 5d ago | SKILL.md |
Frequently asked questions
- How do I install agent-platform-endpoint-management?
- Run
npx skills add google/skills --skill agent-platform-endpoint-management. The install tabs above show the steps for each supported agent. - Which AI agents does agent-platform-endpoint-management work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is agent-platform-endpoint-management safe to use?
- It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is agent-platform-endpoint-management still maintained?
- The repository was last updated 3 days ago, so agent-platform-endpoint-management is actively maintained.
Skill content
View source on GitHubname: agent-platform-endpoint-management metadata: version: "1.0.0" category: AiAndMachineLearning description: >- Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.
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:
- Tier R: Read-only (
list,describe,get)- No confirmation needed. Execute immediately to gather information.
- 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.
- Requires interactive confirmation with 'Yes'/'No' options. The
confirmation prompt MUST contain the exact, literal command string with
all required flags (e.g.
- 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
describefirst, 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.
- Requires explicit typed confirmation (e.g. "I confirm" or "Yes,
delete it"). Ask for confirmation IMMEDIATELY — before any pre-flight
checks (don't
Phase 0: Environment Setup
CRITICAL: Before running any commands, you MUST ensure the environment is correctly initialized by following these steps:
-
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 -
Set Project: Configure the active project for subsequent commands:
gcloud config set project $PROJECT_ID -
Region: Always specify
--region=$LOCATION_IDon each command below. Do NOT useglobal. 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=$LOCATION_ID
(Optional) For pagination, you MUST use --limit=$LIMIT to restrict the total
number of returned endpoints. You can also append --page-size=$PAGE_SIZE to
control API chunking, or --page-token=$PAGE_TOKEN for next pages.
[!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
describeuntil 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.adminorownerrole 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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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
