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 resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for running model evaluations (use `agent-platform-eval-flywheel` skill).
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Use this Skill: https://skilld.dev/gh/google/skills/agent-platform-deploy
This session only. Nothing lands on disk.
≈92 tokens on demand. Your agent reads this file only when SKILL.md points to it.
I want to use `prod` as development environment.
copy the tuned model `projects/${PROJECT_NUMBER}/locations/${REGION}/models/${MODEL_ID}`
to project `${DEST_PROJECT_ID}`
in region `us-central1`
and deploy it to a newly created shared endpoint.
All use name `gemini-3-flash-tuned`
and then test the endpoint with a few prompts.Source: SKILL.md on GitHub
This skill facilitates model deployment on Google Cloud's Agent Platform with built-in safety confirmations for mutating tasks. There are security considerations related to potential command injection in helper scripts and the use of administrative IAM commands, which should be reviewed to ensure proper sanitization and least-privilege access.
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Risk: LOW · No issues
Signed by skilld at 99c871e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.
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{
"version": "1.0.3",
"category": "AiAndMachineLearning"
}