Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Agent Platform Model Registry

ASecurity

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

36 stars
0 votes
0 copies
0 views
Added 9/22/2026
devopsgobash

Security Analysis

A100/100

Scanned 9/22/2026

Install to Claude Code

$npx -y skills add NVlabs/Skill2Env --skill agent-platform-model-registry --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Agent Platform Model Registry?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Agent Platform Model Registry
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/nvlabs-agent-platform-model-registry/badge)](https://www.skillsdirectory.com/skills/nvlabs-agent-platform-model-registry)

More formats (shields.io, HTML) on the badges page.

Download with Pro
Files
SKILL.md
---
name: agent-platform-model-registry
metadata:
  category: AiAndMachineLearning
description: >-
  Agent Platform Model Registry Management. Use when you need to upload, list,
  describe, update, or delete machine learning models (and their versions)
  in the Agent Platform Model Registry. Don't use for model training, model
  deployment to endpoints, or managing non-Agent Platform models.
---

# Agent Platform Model Registry Management

## Overview

This skill provides instructions for managing machine learning models in the
Agent Platform Model Registry. It covers listing models, describing model
details, uploading new models or versions, updating metadata, and deleting
models.

## 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 (`upload`, `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 check if the model is deployed to endpoints 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`.

## 1. Listing Models (Tier R)

Use this command to discover existing models in the registry and retrieve their
numeric IDs. No confirmation is required.

```bash
gcloud ai models list \
    --region=$LOCATION_ID
```

## 2. Describing a Model (Tier R)

Retrieve the full metadata for a specific model or version. No confirmation is
required.

```bash
gcloud ai models describe $MODEL_ID \
    --region=$LOCATION_ID
```

To target a specific version:

```bash
gcloud ai models describe ${MODEL_ID}@${VERSION_ID} \
    --region=$LOCATION_ID
```

## 3. Uploading a Model (Tier M)

Register a new model or a new version of an existing model. This is a
long-running operation.
**Action requires an inline confirmation card before proceeding.**

### Example: Uploading a Custom Model

```bash
gcloud ai models upload \
    --region=$LOCATION_ID \
    --display-name="my-custom-model" \
    --container-image-uri="gcr.io/my-project/my-model:latest" \
    --artifact-uri="gs://my-bucket/path/to/artifacts"
```

> [!IMPORTANT] This is a Tier M operation — see [Safety & Confirmation Tiers]
> above.

To upload a new version of an existing model, use the `--parent-model` flag or
specify the parent model ID.

## 4. Updating a Model (Tier M)

Update metadata fields like display name, description, or labels.
**Action requires an inline confirmation card before proceeding.**

```bash
gcloud ai models update $MODEL_ID \
    --region=$LOCATION_ID \
    --display-name="new-display-name" \
    --description="Updated description"
```

> [!IMPORTANT] This is a Tier M operation — see [Safety & Confirmation Tiers]
> above.

## 5. Deleting a Model (Tier D)

Permanently delete a Model and all its versions.
**Action requires explicit typed confirmation before proceeding.**

```bash
gcloud ai models delete $MODEL_ID \
    --region=$LOCATION_ID
```

> [!WARNING] This operation is irreversible. All model versions must be
> undeployed from all Endpoints before deletion.

Attribution

NVlabsNVlabs
View sourceMore from NVlabs →
SSkills DirectorySkills Directory

Know which skills are safe — weekly.

Best new skills + every skill we flagged as malicious. From the team that scanned 103,619.

Join free

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Know which skills are safe — weekly.

Best new skills + every skill we flagged as malicious. From the team that scanned 103,619.

Join free

Related Skills

Terraform Module Library

Build reusable Terraform modules for AWS, Azure, and GCP infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.

397921 votes

sematext-otel

Wire a service's OpenTelemetry output to Sematext Cloud. Walks through region, App-type, instrumentation flow (managed OTLP endpoint vs Sematext Agent), and signal selection (traces/metrics/logs), then produces the exact env-var block and points at a runnable reference example in this repo. Invoke when instrumenting a new app for Sematext.

01 votes

Deployment Patterns

Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications. Use when setting up deployment infrastructure or planning releases.

2648130 votes

Babysit

Watch a pull request or review cycle until it is ready to merge. Use when asked to babysit, monitor, or keep checking PR comments, reviews, and CI until all actionable issues are resolved.

945230 votes

V7 Roster

Interact with the Paperclip control plane API for task coordination and governance. Use when checking assignments, updating issue status, posting comments, delegating work, managing routines, or calling Paperclip API endpoints.

813270 votes
View all in devops →