Agent Platform Prompt Management

Usage Guide

To use this skill effectively:

• Generate Code: Provide the Python snippets below to the user to help

them manage prompts in Agent Platform.

• No File System Search: Do not try to find Python files or scripts on the

file system for these operations.

Safety & Confirmation Tiers (CRITICAL)

Before executing any commands or scripts on behalf of the user, you must adhere

to the following safety tiers based on the action requested, to prevent

accidental mutation or permanent deletion of prompt resources:

• Tier R: Read-only (list, get)
• No confirmation needed. Execute immediately to gather information.
• Tier M: Mutating & Reversible (create)

• Requires interactive confirmation with 'Yes'/'No' options before

executing prompt creation, to prevent unintended resource proliferation

or misconfiguration. The confirmation prompt must clearly explain the

proposed prompt creation and its key parameters (e.g., display name,

template text, target model). Natural-language paraphrases without

specifying the parameters are not sufficient.

• Same-turn restriction: Do not execute the creation code in the same

turn as presenting the confirmation prompt. Stop and wait for the user's

reply; only execute after explicit 'Yes' / approval.

• Gold Standard Example:

> I will create a prompt in Agent Platform with the following

> parameters. Please confirm this information before I proceed:

>

> * Display Name: Customer Support Greeting

> * Target Model: gemini-2.5-pro

> * Template Text: "Hello {{user_name}}, how can I help..."

>

> Do you confirm? [Yes/No]

• Tier D: Destructive & Irreversible (delete)

• Requires explicit typed confirmation (e.g. "I confirm" or "Yes,

delete it") before executing prompt deletion, to prevent accidental

permanent loss of production prompt assets. Ask for confirmation before

any pre-flight checks.

• Same-turn restriction: NEVER execute in the same turn as asking for

typed confirmation. Wait for the user to reply in a new turn.

• Gold Standard Example:

> I will permanently delete the following prompt from Agent Platform.

> This action is irreversible. Please explicitly type your confirmation

> (e.g., "I confirm") before I proceed:

>

> * Prompt ID: prompt_12345abc

> * Display Name: Legacy Outdated Prompt

>

> Please type your confirmation to proceed.

Phase 0: Environment Setup

CRITICAL: Before the user runs any of the Python snippets below, you MUST

advise them to ensure the environment is correctly initialized by following

these steps:

• Google Cloud Authentication: Authenticate with your Google Cloud account

and configure active Application Default Credentials (ADC) for Agent

Platform access:

    gcloud auth login
    gcloud auth application-default login

• Python Dependencies: This skill needs google-cloud-aiplatform and

google-genai. Do not create a virtual environment — it starts empty

and hides packages the environment already provides, forcing a redundant

install. Probe, and install only what is missing:

    python3 -c "import vertexai, google.genai" \
      || pip install google-cloud-aiplatform google-genai

• Execution: Run Python snippets with a plain python3. There is no

environment to activate first.

> [!TIP]

>

> Placeholder Parameter Replacement: The Python scripts below use uppercase

> string placeholders (like "PROJECT_ID", "LOCATION_ID", and "PROMPT_ID").

> You MUST dynamically replace these placeholders with the actual Project

> ID, Region, and Prompt ID values provided in the user's prompt (or discovered

> context) before generating or providing the scripts.

1. Managing Prompts via Agent Platform SDK

The SDK provides a high-level Prompt class in the preview module.

Create a Prompt (Tier M)

Use when you need to create a new managed prompt in Agent Platform.

• Reference: See create.md for detailed

instructions and Python snippets.

List Prompts (Tier R)

import vertexai
from vertexai.preview import prompts

vertexai.init(project="PROJECT_ID", location="LOCATION_ID")

all_prompts = prompts.list()
for p in all_prompts:
    print(f"Name: {p.display_name}, ID: {p.prompt_id}")

Retrieve and Use a Prompt (Tier R)

import vertexai
from vertexai.preview import prompts

vertexai.init(project="PROJECT_ID", location="LOCATION_ID")

retrieved_prompt = prompts.get(prompt_id="PROMPT_ID")
# Versions are supported: prompts.get(prompt_id="PROMPT_ID", version_id="2")

# Assemble with variables (kwargs must match template variable names)
assembled = retrieved_prompt.assemble_contents(text="The quick brown fox...")
print(assembled)

Delete a Prompt (Tier D)

CRITICAL: You must pass the numeric prompt ID (e.g.,

"1234567890123456789") to prompts.delete(). The SDK constructs the full

resource path internally using the project and location from vertexai.init().

Confirmation Required: As a Tier D (Destructive) operation, the agent MUST

pause and request explicit, high-friction typed re-confirmation of the prompt ID

from the user before generating or providing the deletion code. The action is

irreversible.

> [!IMPORTANT]

>

> **NEVER pre-emptively provide or execute any deletion code before receiving

> the user's response in a new turn.** You must never speculate or assume that

> confirmation will be given. Asking for confirmation and providing the code in

> a single parallel turn is a severe safety violation.

import vertexai
from vertexai.preview import prompts

vertexai.init(project="PROJECT_ID", location="LOCATION_ID")

prompts.delete(prompt_id="PROMPT_ID")

2. Best Practices

• Idempotency:
• Tier R (List, Get): Inherently idempotent.
• Tier D (Delete): Re-running a delete on a non-existent or already

deleted resource returns NOT_FOUND. Treat this as success.

• Placeholders: Use the standard placeholder syntax (variable name

enclosed in double curly braces) in your prompt templates.

• Versioning: Always tag or record version IDs when making updates to

production prompts.

• Model Reference: Specify the target model ID (e.g., gemini-2.5-pro)

when creating the prompt to ensure consistency.

• Underlying Schema: When using the Dataset API, always use the correct

metadata_schema_uri and nested metadata structure to ensure the prompt

is recognized by Agent Platform Studio and the Prompts SDK.