Agent Platform Prompt Management

Usage Guide

To use this skill effectively:

1. Generate Code: Provide the Python snippets below to the user to help them manage prompts in Agent Platform.

2. 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:

1. Tier R: Read-only (list, get)
   • No confirmation needed. Execute immediately to gather information.
2. 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]

3. 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     • Display Name: Legacy Outdated Prompt Please type your confirmation to proceed.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:

1. 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
   

2. Virtual Environment: Create and activate a dedicated virtual environment:

   python3 -m venv ~/prompt_agent_venv
   source ~/prompt_agent_venv/bin/activate
   

3. Install Dependencies: Install the required Agent Platform SDKs:

   pip install google-cloud-aiplatform google-genai
   

4. Execution: Advise the user that every time they execute a Python snippet, they must ensure this virtual environment is activated 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

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

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

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

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.