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 DauQuangThanh/hanoi-rainbow --skill google-cloudgit clone --depth 1 https://github.com/DauQuangThanh/hanoi-rainbowWrote 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/dauquangthanh/hanoi-rainbow/google-cloud)<a href="https://agentmods.dev/skills/dauquangthanh/hanoi-rainbow/google-cloud"><img src="https://agentmods.dev/badge/skills/dauquangthanh/hanoi-rainbow/google-cloud/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/dauquangthanh/hanoi-rainbow/google-cloud"><img src="https://agentmods.dev/badge/skills/dauquangthanh/hanoi-rainbow/google-cloud.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 | $0.00178 | $0.01784 |
| Opus 5 | $0.00089 | $0.00892 |
| Sonnet 5 | $0.00036 | $0.00357 |
| Haiku 4.5 | $0.00018 | $0.00178 |
Grade A, and why
google-cloud 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 9d 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Cloud Platform (GCP)
Core Capabilities
Provides expert guidance for Google Cloud Platform across all major services:
- Compute Services - Compute Engine (VMs), Cloud Run, Cloud Functions, App Engine
- Container & Kubernetes - Google Kubernetes Engine (GKE), Artifact Registry, Cloud Build
- Storage Services - Cloud Storage (buckets), Persistent Disk, Filestore
- Database Services - Cloud SQL, Cloud Spanner, Firestore, Bigtable, Memorystore
- Data & Analytics - BigQuery, Dataflow, Dataproc, Pub/Sub, Composer
- Networking - VPC, Cloud Load Balancing, Cloud CDN, Cloud Armor, Cloud Interconnect
- Security & IAM - Identity and Access Management, Secret Manager, Cloud KMS, Security Command Center
- Infrastructure as Code - Terraform Google provider, Deployment Manager, Config Connector
Key Principles
General Best Practices
- Follow least privilege - Use IAM roles with minimal required permissions
- Enable monitoring - Configure Cloud Monitoring and Logging for all services
- Use managed services - Prefer GKE Autopilot, Cloud SQL, Cloud Run over self-managed
- Implement IaC - Use Terraform or Deployment Manager for reproducible infrastructure
- Tag resources - Apply labels for cost allocation and organization
- Design for HA - Use regional resources and multi-zone deployments
- Secure by default - Enable encryption, use private IPs, configure VPC Service Controls
- Optimize costs - Use committed use discounts, autoscaling, and appropriate resource sizing
Architecture Patterns
- Multi-tier applications: VPC + Cloud Load Balancer + GKE/Cloud Run + Cloud SQL
- Data pipelines: Pub/Sub → Dataflow → BigQuery with Cloud Storage staging
- Serverless APIs: Cloud Run + Cloud SQL + Secret Manager + Cloud Armor
- Hybrid connectivity: VPN or Cloud Interconnect + Shared VPC + Private Google Access
When to Use What
- Compute Engine: Full VM control, Windows workloads, lift-and-shift migrations
- GKE: Containerized applications, microservices, Kubernetes workloads
- Cloud Run: Stateless HTTP services, event-driven processing, auto-scaling needs
- Cloud Functions: Event handlers, webhooks, simple integrations
- Cloud SQL: Relational databases with minimal management
- Cloud Spanner: Global distributed SQL, strong consistency across regions
- BigQuery: Data warehouse, analytics, large-scale SQL queries
- Firestore: Document database, real-time sync, mobile/web apps
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.
- 9d ago First seen · 168 lines · 178 tokens per session scan A 869b804aeece
google-cloud is a skill published in the GitHub repository DauQuangThanh/hanoi-rainbow (16 stars, last pushed 7mo ago), licensed MIT. It adds 178 tokens to every session and 1,784 once invoked, about $0.0009 per session on Opus 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 2026-08-31.
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