Install the "cloud-run-gpu-image-update-quota-bypass" agent skill from https://github.com/divinevideo/divine-mobile/tree/main/.agents/skills/cloud-run-gpu-image-update-quota-bypass into .claude/skills/cloud-run-gpu-image-update-quota-bypass/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-gpu-image-update-quota-bypass", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "cloud-run-gpu-image-update-quota-bypass" agent skill from https://github.com/divinevideo/divine-mobile/tree/main/.agents/skills/cloud-run-gpu-image-update-quota-bypass into .agents/skills/cloud-run-gpu-image-update-quota-bypass/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-gpu-image-update-quota-bypass", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "cloud-run-gpu-image-update-quota-bypass" agent skill from https://github.com/divinevideo/divine-mobile/tree/main/.agents/skills/cloud-run-gpu-image-update-quota-bypass into .cursor/skills/cloud-run-gpu-image-update-quota-bypass/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-gpu-image-update-quota-bypass", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "cloud-run-gpu-image-update-quota-bypass" agent skill from https://github.com/divinevideo/divine-mobile/tree/main/.agents/skills/cloud-run-gpu-image-update-quota-bypass into .gemini/skills/cloud-run-gpu-image-update-quota-bypass/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-gpu-image-update-quota-bypass", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "cloud-run-gpu-image-update-quota-bypass" agent skill from https://github.com/divinevideo/divine-mobile/tree/main/.agents/skills/cloud-run-gpu-image-update-quota-bypass into .github/skills/cloud-run-gpu-image-update-quota-bypass/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-gpu-image-update-quota-bypass", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "cloud-run-gpu-image-update-quota-bypass" agent skill from https://github.com/divinevideo/divine-mobile/tree/main/.agents/skills/cloud-run-gpu-image-update-quota-bypass into .opencode/skills/cloud-run-gpu-image-update-quota-bypass/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-gpu-image-update-quota-bypass", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
cloud-run-gpu-image-update-quota-bypass
GitHub stars
266
Token cost
~1k tokens
SKILL.md length
261 words
Files
1
Skills in repo
103
Repo updated
First seen
Licence
MPL-2.0
At a glance
Fix Cloud Run GPU deployment failures caused by quota errors.
The service already exists and is running with a GPU
SKILL.md covers Problem, Context / Trigger Conditions, Solution and Verification, plus 3 more sections
Calls gcloud and docker
You only need to update the container image
What it does
Cloud Run GPU Image Update Quota Bypass is an agent skill from divinevideo/divine-mobile. Fix Cloud Run GPU deployment failures caused by quota errors. Use when: (1) gcloud run deploy fails with "You do not have quota for using GPUs with zonal redundancy" AND "You do not have quota for using GPUs without zonal redundancy", (2) The service already exists and is running with a GPU, (3) You only need to update the container image, not change GPU config. Uses gcloud run services update --image instead of gcloud run deploy to bypass quota re-validation on existing GPU services.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud, covering Containers and Deployment. It works with Cloud Run and Google Cloud. The licence is MPL-2.0.
When your agent uses it
The service already exists and is running with a GPU
You only need to update the container image
Not change GPU config
Example prompts
“You do not have quota for using GPUs with zonal redundancy”
“You do not have quota for using GPUs without zonal redundancy”
“/cloud-run-gpu-image-update-quota-bypass”
Requirements
Docker
What it can do on your machine
Read from SKILL.md and the folder at commit c3d6f7e. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
gcloud
docker
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
docs.google.com
g.co
cloud.google.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Cloud Run GPU Image Update Quota Bypass loads about 1k tokens when it runs. Until then it costs about 134 tokens; SKILL.md has 261 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~134
When it runs· the whole SKILL.md, loaded when a task matches
~1k
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
Download SKILL.mdSave it as .claude/skills/cloud-run-gpu-image-update-quota-bypass/SKILL.md (or your agent's skills folder).
name
cloud-run-gpu-image-update-quota-bypass
description
Fix Cloud Run GPU deployment failures caused by quota errors. Use when:
(1) `gcloud run deploy` fails with "You do not have quota for using GPUs with zonal redundancy"
AND "You do not have quota for using GPUs without zonal redundancy",
(2) The service already exists and is running with a GPU,
(3) You only need to update the container image, not change GPU config.
Uses `gcloud run services update --image` instead of `gcloud run deploy` to bypass
quota re-validation on existing GPU services.
author
Claude Code
version
1.0.0
date
2026-02-07
Cloud Run GPU Image Update - Quota Bypass
Problem
When deploying updated container images to an existing Cloud Run service with GPU (e.g., NVIDIA L4),
gcloud run deploy fails with quota errors even though the service is already running with a GPU.
The quota check blocks both zonal and non-zonal redundancy configurations, making it impossible
to deploy updated code.
Context / Trigger Conditions
gcloud run deploy returns:
metadata.annotations[run.googleapis.com/maxScale]: You do not have quota for
using GPUs with zonal redundancy.
Followed by:
metadata.annotations[run.googleapis.com/maxScale]: You do not have quota for
using GPUs without zonal redundancy.
The GPU service already exists and has a running revision
You're trying to deploy an updated container image, not change GPU configuration
The deploy script uses gcloud run deploy with --gpu flags
Solution
Instead of gcloud run deploy (which re-validates all resource quotas), use
gcloud run services update which only updates the specified fields on the existing service:
bash
# Instead of this (fails with quota error):
gcloud run deploy divine-transcoder \
--image gcr.io/PROJECT/divine-transcoder \
--region us-central1 \
--gpu 1 --gpu-type nvidia-l4 \
--cpu 4 --memory 16Gi \
...
# Use this (updates image on existing service):
gcloud run services update divine-transcoder \
--region us-central1 \
--image gcr.io/PROJECT/divine-transcoder:latest
Key differences:
gcloud run deploy creates a new service or replaces the full configuration, triggering quota checks
gcloud run services update --image only updates the container image on the existing service,
preserving all existing GPU/CPU/memory configuration without re-validating quotas
Verification
bash
# Verify new revision is active
gcloud run revisions list --service SERVICE_NAME --region REGION --limit=3
# Check the service is serving traffic
gcloud run services describe SERVICE_NAME --region REGION --format='value(status.url)'
Example
bash
# Build and push updated image
docker build --platform linux/amd64 -t gcr.io/my-project/divine-transcoder .
docker push gcr.io/my-project/divine-transcoder
# Update only the image (bypasses GPU quota re-validation)
gcloud run services update divine-transcoder \
--region us-central1 \
--image gcr.io/my-project/divine-transcoder:latest
# Output:
# Deploying...
# Creating Revision...done
# Routing traffic...done
# Service [divine-transcoder] revision [divine-transcoder-00010-vf4] has been deployed
Notes
This only works for existing services that already have GPU configured
If you need to change GPU type, CPU, memory, or other settings, you'll need to
request additional quota via https://g.co/cloudrun/gpu-quota
First-time GPU deployments in a region get automatic quota of 3 GPUs (non-zonal)
Quota increases for non-zonal redundancy are granted more quickly than zonal
If deploy scripts use gcloud run deploy, consider adding a fallback to
gcloud run services update --image when quota errors are detected
Cloud Run GPU Image Update Quota Bypass next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
Cloud Run GPU Image Update Quota Bypass compared with similar skills
Skill
Stars
Used in
Tokens
Auto-check
Licence
Repo updated
Cloud Run GPU Image Update Quota Bypass this skilldivinevideo/divine-mobile
Deploy this repository to a new Google Cloud project using the repo's existing Cloud Run, Cloud Run Jobs, Cloud SQL, Secret Manager, and Artifact Registry scripts.
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini Enterprise", "publish to Gemini Enterprise", or needs guidance on the…
Art direction for any content — reads text, PDF, Word, HTML, PPT, then proposes 2-3 creative directions with photography style, mood, and visual language.
Questions about Cloud Run GPU Image Update Quota Bypass
What does Cloud Run GPU Image Update Quota Bypass do?
Fix Cloud Run GPU deployment failures caused by quota errors. Cloud Run GPU Image Update Quota Bypass is an agent skill from divinevideo/divine-mobile. Fix Cloud Run GPU deployment failures caused by quota errors.
When should I use Cloud Run GPU Image Update Quota Bypass?
Cloud Run GPU Image Update Quota Bypass fits situations like: the service already exists and is running with a GPU; you only need to update the container image; not change GPU config.
How do I install Cloud Run GPU Image Update Quota Bypass in Claude Code?
Run `npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a claude-code`. Or copy the skill folder (.agents/skills/cloud-run-gpu-image-update-quota-bypass in divinevideo/divine-mobile) into .claude/skills/cloud-run-gpu-image-update-quota-bypass in your project. Claude Code loads it when a task matches its description.
How do I install Cloud Run GPU Image Update Quota Bypass in Codex?
Run `npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a codex`. Or copy the skill folder (.agents/skills/cloud-run-gpu-image-update-quota-bypass in divinevideo/divine-mobile) into .agents/skills/cloud-run-gpu-image-update-quota-bypass in your project. Codex loads it when a task matches its description.
Can I use Cloud Run GPU Image Update Quota Bypass in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add divinevideo/divine-mobile --skill cloud-run-gpu-image-update-quota-bypass -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cloud-run-gpu-image-update-quota-bypass, .gemini/skills/cloud-run-gpu-image-update-quota-bypass, .github/skills/cloud-run-gpu-image-update-quota-bypass and .opencode/skills/cloud-run-gpu-image-update-quota-bypass in your project.
What does Cloud Run GPU Image Update Quota Bypass need to run?
Going by SKILL.md and its folder, Cloud Run GPU Image Update Quota Bypass needs the command-line tools its instructions call (gcloud and docker). Our summary lists: Docker.
Does Cloud Run GPU Image Update Quota Bypass access the network?
SKILL.md names 3 domains. As links in the text: docs.google.com, g.co and cloud.google.com. This is read from the text; nothing was executed.
Is Cloud Run GPU Image Update Quota Bypass safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Cloud Run GPU Image Update Quota Bypass use?
Cloud Run GPU Image Update Quota Bypass is published under the MPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Cloud Run GPU Image Update Quota Bypass use?
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Cloud Run GPU Image Update Quota Bypass?
Skills that share tags, products or a category with Cloud Run GPU Image Update Quota Bypass: Research To Deploy (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars), Devops (nicepkg/auto-company, 195 stars) and Broccoli Oss GCP Deploy (besimple-oss/broccoli, 285 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cloud Run GPU Image Update Quota Bypass?
divinevideo (a GitHub organization) maintains it in divinevideo/divine-mobile, which has 266 GitHub stars. The repository holds 103 skills in this directory. The repository was last updated on October 10, 2026.
Source: divinevideo/divine-mobile on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
