Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add GoogleCloudPlatform/gemini-cloud-assist-mcp --skill autocloud-operatorgit clone --depth 1 https://github.com/GoogleCloudPlatform/gemini-cloud-assist-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/googlecloudplatform/gemini-cloud-assist-mcp/autocloud-operator)<a href="https://agentmods.dev/skills/googlecloudplatform/gemini-cloud-assist-mcp/autocloud-operator"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/gemini-cloud-assist-mcp/autocloud-operator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/googlecloudplatform/gemini-cloud-assist-mcp/autocloud-operator"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/gemini-cloud-assist-mcp/autocloud-operator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00115 | $0.01099 |
| Opus 5.5 | $0.00046 | $0.00440 |
| Sonnet 5.5 | $0.00023 | $0.00220 |
| Haiku 4.5 | $0.00012 | $0.00110 |
Grade A, and why
autocloud-operator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cloud Operator
Delegate GCP work (questions, design, Terraform/Kubernetes/Helm generation and review, resource management, rollouts, incidents, costs) to the Cloud Operator Agent via ask_cloud_operator on the autocloud MCP server. Keep using it for GCP follow-ups in the same conversation.
Preconditions
- MCP connected: if
ask_cloud_operatorisn't available, tell the user the autocloud MCP server is not connected or not authenticated, and how to connect it in this client. Do not silently fall back to runninggcloudyourself.
Calling ask_cloud_operator
Make one call per logical request. Calls can run for up to 30 minutes: don't cancel, retry, or duplicate a slow call.
project:projects/<project_id>, resolved from the project named by the user, then the default in the user's GCP preferences, thengcloud config get-value project. If still unknown (empty or(unset)), ask.userQuery: the user's prompt as-is, followed by:- on the first call of a conversation (no
contextId), the user's full GCP preferences under aUser preferences:heading (from a<gcp_preferences>block in context, or~/.config/cloud-operator/preferences.mdif it exists), then the lineAlso apply my saved preferences from your memory.; - the complete, verbatim contents of every referenced local file, diff, or error log, each under a heading with its path. The operator cannot see the local filesystem, so never summarize, abbreviate, or truncate them.
- Secrets exception: never send credential files (
.env, service-account key JSON, kubeconfig,*.tfstate) or secret values. Replace passwords, tokens, API keys, and private keys with<REDACTED>(for.env/*.tfvars, send variable names with redacted values), and tell the user you did. - external doc links as-is (don't fetch them yourself).
- on the first call of a conversation (no
agentId: omit unless the user or their preferences name one (short ID,locations/<loc>/agents/<id>, or a full resource name). A full resource name (projects/<p>/locations/...) is valid only when<p>is the call'sproject; when targeting a different project, omit it and tell the user the request went to their personal agent in that project.contextId: thecontext_idfrom the previous response, for follow-ups (pass the sameagentIdtoo). Send only files that changed since the last turn. Start a new session (omitcontextId) when the target project changes.- Errors: on session or token-expiry errors, drop
contextId, re-include preferences and current files, and start one clean turn; if the failed turn may have changed resources, tell the user and ask before re-sending. On a timeout, report it and don't re-send unless the user asks. On 401/403, tell the user to re-authenticate the autocloud MCP server in this client.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago Changed · +4 tokens per session 70e03fc91c44
- 7d ago First seen · 37 lines · 111 tokens per session scan A ecd881979a62
autocloud-operator is a skill published in the GitHub repository GoogleCloudPlatform/gemini-cloud-assist-mcp (69 stars, last pushed 2d ago), licensed Apache-2.0. It adds 115 tokens to every session and 1,099 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-13.
Other skills, from other repositories
cloud-run
Manage Cloud Run services and jobs.
agentcore-investigation
Investigate Bedrock AgentCore runtime sessions via CloudWatch Logs Insights — resolve session/trace IDs, query OTEL spans, filter noise, build timelines. Use when debugging AgentCore agent sessions, tracing tool calls, or analyzing latency.
n8n-self-hosting
Deploy a production self-hosted n8n end-to-end to a fresh Linux VM over SSH, using Docker Compose behind a Caddy reverse proxy with automatic HTTPS. Use whenever the user wants to self-host, install, set up, provision, or deploy n8n on their own server/VPS/box (Hetzner, DigitalOcean, AWS EC2, bare metal, etc.) — in…
kubernetes
Deploy, manage, and debug Kubernetes in production — Deployments, Services, Gateway API, Service Mesh (Istio/Linkerd/Cilium), eBPF observability (Cilium Hubble), security hardening (Pod Security Standards, OPA/Kyverno, seccomp, runtime security with Falco/Tetragon), Helm, HPA, PDB, topology spread, and debugging. Use…
zdx-investigate-multi-app-outage
Diagnose a multi-application outage scoped to one location by correlating ZDX alerts, affected devices, and shared cloud-path hops. Identifies the devices affected at a specific office, compares the per-application network path across multiple SaaS apps to surface the common network bottleneck, and produces an…
gcp-expert
Expert-level Google Cloud Platform, services, and cloud architecture. Use when the user mentions Google Cloud, Cloud Functions, BigQuery, or Firestore.