agentleFS
phatnguyen03022001phatnguyen03022001/agent-skills/cloud-run-basics/SKILL.md

cloud-run-basics

Skill2 starsChanged 3 months agoApache-2.0View on GitHub

Use when a task involves deploying, configuring, troubleshooting, securing, scaling, or cost-optimizing Google Cloud Run services, jobs, or worker pools.

7 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

10 rules. 0 are common, 8 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 7 edited versions we read keep these.

  • 8

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Treat Google Cloud account, project ID, region, resource type, service identity, current revision, exposure, and billing impact as explicit …

    line 10
  2. Very specific:

    Before a consequential change, confirm the active account/project, region, target service/job/worker pool, current resource state, …

    line 14
  3. Distinctive:

    Do not silently enable APIs, broaden IAM, make a service public, create infrastructure, trigger builds, or enable paid/unknown-cost …

    line 16
  4. Distinctive:

    Prefer dedicated least-privilege service accounts and approved secret storage.

    line 22
  5. Very specific:

    Prefer scale-to-zero for bursty workloads when requirements allow it.

    line 26
  6. Distinctive:

    Do not add VPC connectors, NAT, load balancers, CDN, static IPs, Cloud SQL, GPUs, larger instances, or CI/CD as generic best practice.

    line 28
  7. Distinctive:

    Prefer deterministic image inputs.

    line 34
  8. Distinctive:

    Do not equate API/CLI success with application correctness.

    line 40
  9. Distinctive:

    Stop on unresolved project/account identity, region/resource, write authority, exposure intent, destructive replacement, IAM expansion, …

    line 42
  10. Distinctive:

    Before unfamiliar flags or Preview behavior, inspect current CLI help and official documentation.

    line 44

“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Cloud Run Basics

Core invariant

Treat Google Cloud account, project ID, region, resource type, service identity, current revision, exposure, and billing impact as explicit live state. Read before write; do not trust old conversation or local defaults.

Pre-write gate

Before a consequential change, confirm the active account/project, region, target service/job/worker pool, current resource state, IAM/network/secrets/traffic effects, and authorization.

Do not silently enable APIs, broaden IAM, make a service public, create infrastructure, trigger builds, or enable paid/unknown-cost features merely to make deployment easier.

Runtime and identity

HTTP containers must listen on 0.0.0.0:$PORT. Use services for request/event workloads, jobs for run-to-completion work, and worker pools for continuous pull-based processing.

Prefer dedicated least-privilege service accounts and approved secret storage. Never place credentials in source-controlled files or command history. Public invocation must be explicit.

Cost and infrastructure

Prefer scale-to-zero for bursty workloads when requirements allow it. Keep min-instances=0 unless availability/latency justifies always-on capacity, and bound max-instances when fan-out can create cost or downstream pressure.

Do not add VPC connectors, NAT, load balancers, CDN, static IPs, Cloud SQL, GPUs, larger instances, or CI/CD as generic best practice. Verify current Google Cloud pricing when cost matters; do not assume a short operation is free.

gcloud run deploy --source may invoke Cloud Build and create artifacts. Treat it as cloud execution with IAM and billing effects.

Deployment and verification

Prefer deterministic image inputs; immutable digests are useful for controlled releases. Run repository-designated checks before deployment when available.

Flow:

inspect -> verify app -> review config/cost -> deploy -> inspect revision -> verify health/auth -> verify traffic

Do not equate API/CLI success with application correctness. Keep local tests, image correctness, deploy success, revision health, traffic behavior, application acceptance, security, and cost review separate.

Stop on unresolved project/account identity, region/resource, write authority, exposure intent, destructive replacement, IAM expansion, paid/unknown-cost operation without approval, or required verification failure.

Before unfamiliar flags or Preview behavior, inspect current CLI help and official documentation.

Upstream

Adapted from Google Cloud Run skill guidance, with additional fail-closed identity, IAM, cost, and verification rules for agent-driven workflows.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.