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agent-platform-prompt-management

google

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Hardened

This skill has been hardened by Chainguard

Last changed

This version passed the hardening gate. Hardening updated the skill content and independently checked the resulting changes. Classified findings before hardening: 5. Classified findings closed: 0. Classified findings remaining: 5. Unclassified scanner findings remaining: 0. Review findings closed: 1. Review findings remaining: 16.


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SKILL.md

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SKILL.md

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SKILL.md

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SKILL.md

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references/create.md

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SKILL.md

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.

  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...":

  3. Tier D: Destructive & Irreversible (delete)

    • Requires explicit typed confirmation before executing prompt deletion, to prevent accidental permanent loss of production prompt assets.

    • 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:

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.

    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.

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")
# 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.

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.
  • 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.

Install

Install with chainctl
chainctl skill install public/google/agent-platform-prompt-management:latest
Get started with chainctl
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Provenance

Upstream sourcehttps://github.com/google/skills
Upstream commit748af9bd7e9cd4bd8285d58f6969614b09b0cab3
OCI reference

skills.cgr.dev/public/github.com/google/skills/cloud/agent-platform-prompt-management:latest

License

Apache-2.0

Files

HARDENING.md

LICENSE

SKILL.md

references/create.md


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