Agent Platform Prompt Management logo

Agent Platform Prompt Management

OrganizationPopular
google
agent-platform-prompt-management

Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.

Overview

Publishergoogle
Repositoryskills
Skill nameagent-platform-prompt-management
Stars
20.1K
Forks
1.6K
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by google on GitHub. Read the source before you install it.

Installation

Install the Agent Platform Prompt Management AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/google/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/cloud/agent-platform-prompt-management .claude/skills/agent-platform-prompt-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Platform Prompt Management in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Platform Prompt Management on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Platform Prompt Management is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

    bash
    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:

    bash
    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.

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)

python
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)

python
import vertexai
from vertexai.preview import prompts

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

retrieved_prompt = prompts.get(prompt_id="PROMPT_ID")
# Attributes on retrieved Prompt:
# - retrieved_prompt.prompt_id (e.g. "123456789...")
# - retrieved_prompt.prompt_data (template text string)
# - retrieved_prompt.model_name (target model)
# - retrieved_prompt.prompt_name (display name, or
#   retrieved_prompt._dataset.display_name)
# 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 executing the deletion code. The action is irreversible. Once the user replies with typed confirmation (e.g., "I confirm"), proceed immediately to execute the deletion code via run_command.

[!IMPORTANT]

NEVER pre-emptively 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 running the code in a single parallel turn is a severe safety violation.

python
import vertexai
from vertexai.preview import prompts

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

prompts.delete(prompt_id="PROMPT_ID")

Verification After Deletion

When the user asks to list prompts or check that a deleted prompt is gone, list the prompts and explicitly state whether the deleted prompt ID is present. If it is not found, explicitly confirm: "I have verified that the prompt with ID <PROMPT_ID> is no longer present in the project."

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: A prompt is created against a target model ID, which the snippets carry as the "MODEL_ID" placeholder. Like the other placeholders it is MUST-replace, and it is replaced from what the user said -- if they named no model, ask. Do not substitute a plausible current model such as gemini-2.5-pro.
  • 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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Agent Platform Prompt Management AI skill do?

Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.

Why use Agent Platform Prompt Management on TypingMind?

Because you install it once and use it with any model. Agent Platform Prompt Management is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Platform Prompt Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/google/skills/tree/main/skills/cloud/agent-platform-prompt-management. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Agent Platform Prompt Management?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Platform Prompt Management?

As many as you like. As long as a model supports skills, you can use Agent Platform Prompt Management with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Platform Prompt Management AI skill free?

Yes. It is published on GitHub by google under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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