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Official agent skill

Agent Platform Endpoint Management

by google in google/skills

Manages Agent Platform serving endpoints. An agent skill from google/skills.

OfficialApache-2.0Auto-check passedData & Analytics

Install Agent Platform Endpoint Management

skills CLI
$ npx skills add google/skills --skill agent-platform-endpoint-management -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install google/skills agent-platform-endpoint-management --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cloud/agent-platform-endpoint-management .claude/skills/agent-platform-endpoint-management && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agent-platform-endpoint-management
GitHub stars
21k
Token cost
~1.5k tokens
SKILL.md length
668 words
Files
1
Skills in repo
145
Repo updated
First seen
Licence
Apache-2.0

At a glance

Manages Agent Platform serving endpoints. An agent skill from google/skills.

  • Works in 7 steps: Environment Setup → Listing Endpoints (Tier R) → Describing an Endpoint (Tier R) → …
  • You need to create
  • SKILL.md covers Overview, Safety & Confirmation Tiers…, Phase 0: Environment Setup and 1. Listing Endpoints (Tier R), plus 6 more sections
  • Calls gcloud

What it does

Agent Platform Endpoint Management is an agent skill from google/skills, published by the product's own GitHub organization. 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.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Machine learning. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.

When your agent uses it

  • You need to create
  • Delete serving endpoints for model deployment on Agent Platform
  • Troubleshooting endpoint permission
  • Resource busy errors

Example prompts

  • “Use the agent-platform-endpoint-management skill to manage Agent Platform serving endpoints. An agent skill from google/skills”
  • “/agent-platform-endpoint-management”

Requirements

  • A credential in PAGE_TOKEN

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Environment Setup
  2. Listing Endpoints (Tier R)
  3. Describing an Endpoint (Tier R)
  4. Creating an Endpoint (Tier M)
  5. Updating an Endpoint (Tier M)
  6. Deleting an Endpoint (Tier D)
  7. Traffic Splitting (Tier M)

What it can do on your machine

Read from SKILL.md and the folder at commit 8a1ac05. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gcloud

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gcloud, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agent Platform Endpoint Management loads about 1.5k tokens when it runs. Until then it costs about 90 tokens; SKILL.md has 668 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from google/skills at commit 8a1ac05, republished under its Apache-2.0 licence (© google). 668 words, ~1,544 tokens.

Download SKILL.mdSave it as .claude/skills/agent-platform-endpoint-management/SKILL.md (or your agent's skills folder).
name
agent-platform-endpoint-management
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.
metadata.version
1.0.0
metadata.category
AiAndMachineLearning

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:

    bash
    gcloud auth login
gcloud auth application-default login

  2. Set Project: Configure the active project for subsequent commands:

    bash
    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.

bash
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.

bash
gcloud ai endpoints describe $ENDPOINT_ID \
    --region=$LOCATION_ID
Show full SKILL.md (287 more words)Show less

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.

bash
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:

bash
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.

bash
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:

bash
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.

bash
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.

bash
# 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.

© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/cloud/agent-platform-endpoint-management of google/skills.

Open the folder on GitHubat commit 8a1ac05

Compare with similar skills

Agent Platform Endpoint Management next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agent Platform Endpoint Management compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agent Platform Endpoint Management this skillgoogle/skills21k—~1.5kAutomated safety check: PassApache-2.0
Scikit LearnzLanqing/codex-claude-academic-skills4.6k17 repos~3.9kAutomated safety check: PassBSD-3-Clause
Senior Data ScientistRaidriar7170/hermes-skilleval1256 repos~1.4kAutomated safety check: PassMIT
Agentic Kaggle WorkflowFrankS-IntelLab/agentic-kaggle-skill188—~4kAutomated safety check: PassMIT
Retention Analysisliangdabiao/claude-data-analysis-ultra-main2901 repos~1.3kAutomated safety check: NotesNone
Geomlitalo-goncalves/geoML108—~4.2kAutomated safety check: PassGPL-3.0

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Categories

Questions about Agent Platform Endpoint Management

What does Agent Platform Endpoint Management do?

Manages Agent Platform serving endpoints. An agent skill from google/skills. Agent Platform Endpoint Management is an agent skill from google/skills, published by the product's own GitHub organization. Manages Agent Platform serving endpoints.

When should I use Agent Platform Endpoint Management?

Agent Platform Endpoint Management fits situations like: you need to create; delete serving endpoints for model deployment on Agent Platform; troubleshooting endpoint permission; resource busy errors.

How do I install Agent Platform Endpoint Management in Claude Code?

Run `npx skills add google/skills --skill agent-platform-endpoint-management -a claude-code`. Or copy the skill folder (skills/cloud/agent-platform-endpoint-management in google/skills) into .claude/skills/agent-platform-endpoint-management in your project. Claude Code loads it when a task matches its description.

How do I install Agent Platform Endpoint Management in Codex?

Run `npx skills add google/skills --skill agent-platform-endpoint-management -a codex`. Or copy the skill folder (skills/cloud/agent-platform-endpoint-management in google/skills) into .agents/skills/agent-platform-endpoint-management in your project. Codex loads it when a task matches its description.

Can I use Agent Platform Endpoint Management in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill agent-platform-endpoint-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-platform-endpoint-management, .gemini/skills/agent-platform-endpoint-management, .github/skills/agent-platform-endpoint-management and .opencode/skills/agent-platform-endpoint-management in your project.

What does Agent Platform Endpoint Management need to run?

Going by SKILL.md and its folder, Agent Platform Endpoint Management needs the command-line tools its instructions call (gcloud). Our summary lists: A credential in PAGE_TOKEN.

Does Agent Platform Endpoint Management access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Agent Platform Endpoint Management safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agent Platform Endpoint Management use?

Agent Platform Endpoint Management is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Platform Endpoint Management use?

About 1.5k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Agent Platform Endpoint Management?

Skills that share tags, products or a category with Agent Platform Endpoint Management: Scikit Learn (zLanqing/codex-claude-academic-skills, 4.6k stars), Senior Data Scientist (Raidriar7170/hermes-skilleval, 125 stars), Agentic Kaggle Workflow (FrankS-IntelLab/agentic-kaggle-skill, 188 stars) and Retention Analysis (liangdabiao/claude-data-analysis-ultra-main, 290 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Platform Endpoint Management?

google (a GitHub organization, an official publisher) maintains it in google/skills, which has 20,994 GitHub stars. The repository holds 145 skills in this directory. The repository was last updated on October 6, 2026.

Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.