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 reganomalley/claudia --skill claudia-infrastructuregit clone --depth 1 https://github.com/reganomalley/claudiaWrote 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/reganomalley/claudia/claudia-infrastructure)<a href="https://agentmods.dev/skills/reganomalley/claudia/claudia-infrastructure"><img src="https://agentmods.dev/badge/skills/reganomalley/claudia/claudia-infrastructure/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/reganomalley/claudia/claudia-infrastructure"><img src="https://agentmods.dev/badge/skills/reganomalley/claudia/claudia-infrastructure.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 | $0.00110 | $0.01341 |
| Opus 5 | $0.00055 | $0.00671 |
| Sonnet 5 | $0.00022 | $0.00268 |
| Haiku 4.5 | $0.00011 | $0.00134 |
Grade A, and why
claudia-infrastructure 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 12d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claudia Infrastructure Domain
Overview
This skill helps you pick where and how to run your software. Most projects are over-infrastructured -- your goal is the simplest setup that meets your actual requirements, not the one that looks best on a resume.
Where Should This Run?
What are you deploying?
├── Static site (HTML, SPA, docs)
│ └── Vercel, Netlify, Cloudflare Pages (free tier is enough for most)
├── Web app (server-rendered, full-stack)
│ ├── Simple / solo dev → Railway, Render, Fly.io
│ ├── Scaling / team → ECS Fargate, Cloud Run, App Engine
│ └── Enterprise / complex → Kubernetes (EKS, GKE)
├── API service (REST, GraphQL, gRPC)
│ ├── Sporadic traffic → Lambda, Cloud Functions, Cloudflare Workers
│ ├── Steady traffic → Container on Fly.io, Cloud Run, ECS
│ └── High throughput → Dedicated instances behind ALB
├── Data pipeline (ETL, batch processing)
│ ├── Simple / scheduled → Lambda + EventBridge, Cloud Functions + Scheduler
│ ├── Complex / multi-step → Step Functions, Cloud Workflows, Airflow
│ └── Big data → EMR, Dataproc, Spark on Kubernetes
└── ML inference
├── Low traffic → Lambda (small models), Cloud Run + GPU
├── Real-time → SageMaker endpoints, Vertex AI, dedicated GPU instances
└── Batch → SageMaker Batch Transform, Vertex AI Batch Prediction
The Cloud Provider Question
There is no universally "best" cloud. There's the best cloud for your situation.
- AWS: Most services, most mature, largest community. If you have no strong reason to pick something else, AWS is the safe default. But the console is a maze and IAM will make you cry.
- GCP: Best developer experience for data and ML workloads. BigQuery is unmatched. GKE is the best managed Kubernetes. But smaller service catalog and less enterprise presence.
- Azure: The answer when your company already runs on Microsoft -- Active Directory, .NET, Office 365. Enterprise integration is its moat. Developer experience is improving but still trails.
- Self-host: When you need full control, cost predictability, or data sovereignty. Hetzner, OVH, bare metal. Be honest about your ops capacity -- this means you're the on-call team.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 107 lines · 110 tokens per session scan A 261161fdb56b
claudia-infrastructure is a skill published in the GitHub repository reganomalley/claudia (4 stars, last pushed 6mo ago), licensed MIT. It adds 110 tokens to every session and 1,341 once invoked, about $0.0006 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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