agent-platform-prompt-management — Claude Code skill: prompt
Manage prompts in Agent Platform: create them, list and retrieve them, select a version, or delete them. Use it when your workflow relies on managed Agent Platform prompts.
npx skills add google/skills --skill agent-platform-prompt-management -a claude-codeWhat agent-platform-prompt-management does
The skill uses the Agent Platform Python SDK. It can list prompts, retrieve one by ID, and assemble its template with variables. You can also request a specific version with version_id.
You need Google Cloud authentication with ADC, plus google-cloud-aiplatform and google-genai; run the snippets with python3. Creating a prompt requires confirmation of its parameters. Deletion requires explicit confirmation of the prompt ID. This skill is for Agent Platform prompts, not model training or endpoint deployment. Install it if you manage prompts in Agent Platform from Claude Code, Gemini CLI, or Codex.
What it helps with
- create a managed prompt in Agent Platform
- list prompts and inspect their IDs
- retrieve a prompt at a chosen version
- assemble a template with its variables
- delete a prompt after confirming its ID
Example prompts for the agent
- List the prompts in Agent Platform for my project.
- Retrieve prompt `PROMPT_ID` at version `2` and assemble it with the `text` variable.
- Create a prompt with this template and model, then ask me to confirm before creating it.
How to install agent-platform-prompt-management
1Skills CLI (Vercel)
npx skills add google/skills --skill agent-platform-prompt-management -a claude-code2Manually: put the files in place
~/.claude/skills/agent-platform-prompt-management/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/agent-platform-prompt-management/
1Skills CLI (Vercel)
npx skills add google/skills --skill agent-platform-prompt-management -a codex2Manually: put the files in place
.agents/skills/agent-platform-prompt-management/SKILL.mdFor all projects use ~/.agents/skills/
Manually: put the files in place
.cursor/skills/agent-platform-prompt-management/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install google/skills agent-platform-prompt-management2Manually: put the files in place
.github/skills/agent-platform-prompt-management/SKILL.md1Skills CLI (Vercel)
npx skills add google/skills --skill agent-platform-prompt-management -a gemini-cli2Platform CLI
gemini skills install https://github.com/google/skills --path skills/cloud/agent-platform-prompt-managementManually: put the files in place
.devin/skills/agent-platform-prompt-management/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set172
The whole set →Similar
Questions about agent-platform-prompt-management
How do I install agent-platform-prompt-management in Claude Code?
Run npx skills add google/skills --skill agent-platform-prompt-management -a claude-code. Configure Google Cloud ADC and check the Python dependencies before using it.
What does agent-platform-prompt-management do?
It manages Agent Platform prompts: listing and retrieving them, assembling templates, selecting versions, creating prompts, and deleting them.
What does the skill need to run?
It needs Google Cloud ADC and the google-cloud-aiplatform and google-genai packages. Run its Python snippets with python3; prompt creation and deletion require confirmation.
Source text
SKILL.md · Apache-2.0
---
name: agent-platform-prompt-management
metadata:
version: "1.0.0"
category: AiAndMachineLearning
description: >-
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.
---
## 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](references/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.
© google · Apache-2.0 · google/skills