Agent Platform Prompt Management

Usage Guide

To use this skill effectively:

1. Execute Operations via Python: Run the Python snippets below using run_command in the execution environment to manage prompts in Agent Platform on behalf of the user. Do not delegate execution to the user or claim lack of access once approved.

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.

   • Every parameter in the card must trace back to something the user said. The target model is a user choice, not a default: if the user did not name one, ASK before building the card. Do not carry over the model that appears in the examples here or in references/create.md.

   • Gold Standard Example — for a user who said "create a prompt called Customer Support Greeting for gemini-2.5-pro with the template Hello {{user_name}}, how can I help...":

     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. 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

3. 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", "PROMPT_ID", and "MODEL_ID"). You MUST dynamically replace these placeholders with the actual Project ID, Region, Prompt ID, and target model values provided in the user's prompt (or discovered context) before generating or providing the scripts. If the user did not supply one of these, ask -- a placeholder is never satisfied by guessing a plausible value.