Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/google-agent-platform-tuning
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: devops, ml, agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/agent-platform-tuning
What's inside
- Skill name
agent-platform-tuning- Description
- Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).
- License
- Apache-2.0
- Metadata
- version: 1.0.1 · category: AiAndMachineLearning
- Instructions
- 794 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Agent Skills spec issues
- body: 794 lines (spec recommends under 500)
Files (12)
- SKILL.md
- data_prep.md · references/
- hf_datasets.md · references/
- models.md · references/
- requirements.txt · references/
- tuning_guide.md · references/
- calculate_cost.py · scripts/
- cancel_tuning_job.py · scripts/
- list_models.py · scripts/
- monitor_tuning_job.py · scripts/
- prepare_dataset.py · scripts/
- tune_open_model.py · scripts/
SKILL.md (first lines)
# Agent Platform Model Tuning
## Overview
This skill provides procedural knowledge for fine-tuning Large Language Models
(both Open Models and Gemini Models) using Agent Platform's tuning service. It
covers the entire lifecycle from environment setup and data preparation to job
configuration, monitoring, and deployment.
## Workflow Decision Tree
1. **Project & Region Verification Check**: Has the user provided the Google
Cloud project and region?
- **No** → **STOP tool execution immediately**. Do NOT run verification
commands (`gcloud services list`, `gcloud projects get-iam-policy`), do
NOT create resources, and do NOT begin dataset preparation. Prompt the
user to specify or confirm the project and region (e.g. "Could you
please specify which Google Cloud project and region you would like to
use?").
- If the user's inquiry is solely to check or verify environment
readiness (APIs, IAM, service agents), ask ONLY for the project and
region. Do NOT ask for the model category.
- If the user is requesting a tuning workflow and also omitted whether
they want to tune an Open Model or a Gemini Model, you may ask both
questions together.
- **Yes** → Proceed.
2. **Model Category Identification**: Has the user explicitly stated whether
they want to tune an **Open Model** or a **Gemini Model**?
- **No** →
- **EXCEPTION for Environment Verification Inquiries:** If the user is
only asking to check or verify that the environment, APIs, IAM
permissions, or service agents are ready for tuning, do NOT ask for
the model category. Verify the environment once the project and
region are known and confirm readiness.
- Otherwise, **STOP tool execution**. Ask the user if they want to
tune an Open Model or a Gemini Model. **General Setup and
Prerequisite Inquiries (e.g., "What environment setup is
needed?"):** If the user asks what environment setup, prerequisites,
APIs, or permissions are needed to start fine-tuning, and has not
yet chosen a model category:
* Describe the setup requirements (APIs, IAM permissions/service
agents, and Python SDKs).
* Regarding Cloud Storage: state that an existing Cloud Storage bucket
is needed for datasets and artifacts (e.g.,
`gs://<existing-bucket>`). **CRITICAL:** Do NOT instruct the user to
create a bucket, do NOT output a `gcloud storage buckets create`
command in setup instructions, and do NOT assume a non-existent
bucket exists (users may not have bucket creation permissions and
will provide their own existing bucket).
* You MUST explicitly conclude your response by asking whether they
want to tune an **Open Model** or a **Gemini Model**. Never provide
setup instructions without asking for the model category choice.
(Note: if they ask to actively check or verify a project whose ID or
region is missing, ask for the project and region first without
running tool calls).
- If the user provides a specific tuning purpose, you should recommend
three models: one Open Model, one Gemini Model, and a third generally
recommended choice. Briefly list the pros and cons of each (e.g., Gemini
models might be more expensive, etc.). **CRITICAL:** You must read
`references/models.md` during this step and only recommend models
explicitly listed in that catalog. Never recommend uncataloged or
unsupported models like `google/gemma-2-9b-it`, `gemma-2`, or `Mistral`
— only recommend supported models such as Gemma 3
(`google/gemma3@gemma-3-12b-it`), Qwen 3 (`qwen/qwen3@qwen3-8b`), or
Llama 3.1 (`meta/llama3_1@llama-3.1-8b`). For Gemini models, ONLY
recommend `gemini-2.5-flash` (recommended for general/coding/chat) or
`gemini-2.5-pro`. Never recommend `gemini-1.5-flash-002`,
`gemini-1.5-pro-002`, or `gemini-1.5-flash`, which are deprecated and
unsupported by the tuning service. If the user names a model that is not
in the catalog, follow the fallback rule in that catalog. Do not proceed
with model configuration until the category is confirmed.
- **Yes** → Proceed.
3. **Environment Check**: Has the environment (Auth, APIs, IAM, Venv) been
initialized?
- **No** → Go to [Phase 0: Environment & IAM Setup](#phase-0).
- **Yes** → Proceed.
4. **Dataset Status**: Is the dataset ready in JSONL format, **is its structure
valid for tuning**, and is it uploaded to Google Cloud Storage?
```
- **No** → Go to [Phase 1: Dataset Preparation & Upload](#phase-1).
- **Yes** → Proceed.
```
5. **Column Selection Confirmation**: Have you presented the columns to the
user and confirmed the mapping?
- **No** → **STOP**. You must show samples and get user confirmation on
column mapping as described in Phase 1.0 before proceeding.
- **Yes** → Proceed.
6. **Configuration**: Has the user provided the target model and
hyperparameters, or explicitly agreed to your recommendations?
- **No** → Go to
[Phase 2: Model Configuration & Recommendation](#phase-2).
- **Yes** → Proceed.
7. **Job Status**: Has the tuning job been submitted?
```
- **No** → Go to
[Phase 3: Tuning Job Execution](#phase-3-tuning-job-execution).
- **Yes** → Proceed.
```
8. **Job Completion**: Is the tuning job complete?
```
- **No** → Go to [Phase 4: Monitoring](#phase-4-monitoring).
- **Yes** → Proceed.
```From google/skills, Apache-2.0.
More from google/skills
- 0.865score
google-ads-api-account-diagnostics
google-ads-api-teamOfficial
Diagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due…
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.861score
secops-triage
Google LLCOfficial
Expert guidance for security alert triage in Google SecOps.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.861score
secops-detection-engineering
Google LLCOfficial
Author, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.861score
secops-hunt
Google LLCOfficial
Expert guidance for proactive threat hunting in Google SecOps.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.861score
secops-cases
Google LLCOfficial
Manage Google Security Operations (SecOps) SOAR cases throughout their lifecycle.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.861score
secops-investigate
Google LLCOfficial
Expert guidance for deep security incident and entity investigations in Google SecOps.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.824score
google-ads-api-quickstart
google-ads-api-teamOfficial
Guides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a…
SkillBFreshness: B★ 21.5KClaude Code +9 - 0.819score
google-ads-api-mcp-setup
google-ads-api-teamOfficial
Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server.
SkillBFreshness: B★ 21.5KClaude Code +9 - 0.815score
ima-dai-sdk
Google LLCOfficial
Integrates the Google Interactive Media Ads (IMA) Dynamic Ad Insertion (DAI) SDK into websites, web apps, mobile apps, or TV apps.
SkillBFreshness: B★ 21.5KClaude Code +9 - 0.815score
ima-sdk-client-side
Google LLCOfficial
Supports Interactive Media Ads (IMA) SDK.
SkillBFreshness: B★ 21.5KClaude Code +9 - 0.699score
gcloud
googleOfficial
Provides safety-critical validation, guardrails, and data reduction for gcloud CLI operations across Google Cloud Platform (GCP) services and infrastructure.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.699score
agent-platform-deploy
googleOfficial
Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up…
SkillAFreshness: A★ 21.5KClaude Code +9
Signals
- Stars
- 21,542
- Forks
- 1,821
- Open issues
- 21
- Last commit (this folder)
- Oct 8, 2026 (22 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.0.1
- License
- Apache-2.0
- Repository
- github.com/google/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
More from google
- 0.699score
retrieving-developer-knowledge
googleOfficial
Searches, retrieves, and synthesizes official Google developer documentation across Google Cloud, AI/Gemini, Android, Chrome, Web, Flutter, Go, Firebase, and…
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.699score
data-manager-api-setup
googleOfficial
Guides developers through client library installation and authentication setup steps for the Data Manager API.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.699score
agent-platform-migrate-from-ai-studio
googleOfficial
Guides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI).
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.699score
gcloud
googleOfficial
Provides safety-critical validation, guardrails, and data reduction for gcloud CLI operations across Google Cloud Platform (GCP) services and infrastructure.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.699score
google-cloud-recipe-onboarding
googleOfficial
Guides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource.
SkillAFreshness: A★ 21.5KClaude Code +9 - 0.699score
agent-platform-deploy
googleOfficial
Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up…
SkillAFreshness: A★ 21.5KClaude Code +9
Cite this page
agent-platform-tuning skill. Agent Mart. https://agentmart.dev/skills/google-agent-platform-tuning (last updated 2026-10-24)