Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ricneves-ai/flowgrammers-skillsnpx agentmods add skills/ricneves-ai/flowgrammers-skills/gcp-cloud-architectWrote 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/ricneves-ai/flowgrammers-skills/gcp-cloud-architect)<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/gcp-cloud-architect"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/gcp-cloud-architect/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/ricneves-ai/flowgrammers-skills/gcp-cloud-architect"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/gcp-cloud-architect.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 | $0.00073 | $0.03510 |
| Opus 5 | $0.00036 | $0.01755 |
| Sonnet 5 | $0.00015 | $0.00702 |
| Haiku 4.5 | $0.00007 | $0.00351 |
Grade A, and why
gcp-cloud-architect 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 — 447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GCP Cloud Architect
Projete arquiteturas Google Cloud escaláveis e econômicas para startups e empresas com templates de infraestrutura como código.
Fluxo de Trabalho
Passo 1: Coletar Requisitos
Coletar especificações da aplicação:
- Tipo de aplicação (web app, mobile backend, pipeline de dados, SaaS)
- Usuários esperados e requisições por segundo
- Restrições de orçamento (limite de gasto mensal)
- Tamanho da equipe e nível de experiência com GCP
- Requisitos de conformidade (LGPD, ANVISA, SOC 2)
- Requisitos de disponibilidade (SLA, RPO/RTO)
Passo 2: Projetar Arquitetura
Executar o designer de arquitetura para obter recomendações de padrão:
python scripts/architecture_designer.py --input requirements.json
Exemplo de saída:
{
"recommended_pattern": "serverless_web",
"service_stack": ["Cloud Storage", "Cloud CDN", "Cloud Run", "Firestore", "Identity Platform"],
"estimated_monthly_cost_usd": 30,
"pros": ["Low ops overhead", "Pay-per-use", "Auto-scaling", "No cold starts on Cloud Run min instances"],
"cons": ["Vendor lock-in", "Regional limitations", "Eventual consistency with Firestore"]
}
Selecionar dos padrões recomendados:
- Serverless Web: Cloud Storage + Cloud CDN + Cloud Run + Firestore
- Microsserviços no GKE: GKE Autopilot + Cloud SQL + Memorystore + Cloud Pub/Sub
- Pipeline de Dados Serverless: Pub/Sub + Dataflow + BigQuery + Looker
- Plataforma ML: Vertex AI + Cloud Storage + BigQuery + Cloud Functions
Veja references/architecture_patterns.md para especificações detalhadas dos padrões.
Ponto de verificação: Confirmar que o padrão recomendado corresponde à maturidade operacional da equipe e aos requisitos de conformidade antes de prosseguir para o Passo 3.
Passo 3: Estimar Custos
Analisar custos estimados e oportunidades de otimização:
python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000
Exemplo de saída:
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 · 447 lines · 73 tokens per session scan A 1929d399a50c
gcp-cloud-architect is a skill published in the GitHub repository ricneves-ai/flowgrammers-skills (112 stars, last pushed 3mo ago), licensed MIT. It adds 73 tokens to every session and 3,510 once invoked, about $0.0004 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 2026-09-03.
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