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 BagelHole/DevOps-Security-Agent-Skills --skill azure-vmsgit clone --depth 1 https://github.com/BagelHole/DevOps-Security-Agent-SkillsWrote 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/bagelhole/devops-security-agent-skills/azure-vms)<a href="https://agentmods.dev/skills/bagelhole/devops-security-agent-skills/azure-vms"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/azure-vms/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/bagelhole/devops-security-agent-skills/azure-vms"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/azure-vms.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Supply Chain · line 26 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- high Tool Misuse · line 26 Tool calls are chained to bypass individual safety checks or escalate capabilities beyond what any single tool call would allow.Fix: Limit tool chaining depth and validate the output of each tool before passing it to the next. Require explicit user approval for multi-step chains.
- high Privilege Escalation · line 395 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 447 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Privilege Escalation · line 26 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
- medium Privilege Escalation · line 191 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
- medium Rogue Agent · line 98 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00027 | $0.03723 |
| Opus 5 | $0.00014 | $0.01861 |
| Sonnet 5 | $0.00005 | $0.00745 |
| Haiku 4.5 | $0.00003 | $0.00372 |
Grade A, and why
azure-vms 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 7d 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 — 508 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Virtual Machines
Deploy and manage Azure VMs, availability sets, scale sets, custom images, and managed disks. Covers VM creation, sizing, disk management, auto-scaling, and Terraform configurations for production environments.
When to Use
- You need full control over the operating system and runtime environment.
- Your application requires specific OS configurations or kernel modules.
- You are running legacy applications that cannot be containerized.
- You need GPU-accelerated compute for ML training or rendering.
- You need high-availability compute with availability zones or scale sets.
Prerequisites
# Install Azure CLI
curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash
# Login and set subscription
az login
az account set --subscription "my-subscription-id"
# Create resource group
az group create --name compute-rg --location eastus
# List available VM sizes in a region
az vm list-sizes --location eastus --output table
# List available VM images
az vm image list --output table
az vm image list --publisher Canonical --offer 0001-com-ubuntu-server-jammy --all --output table
VM Creation
Linux VM with SSH Key
az vm create \
--resource-group compute-rg \
--name myapp-vm \
--image Ubuntu2204 \
--size Standard_D4s_v5 \
--admin-username azureuser \
--generate-ssh-keys \
--vnet-name myapp-vnet \
--subnet app-subnet \
--nsg "" \
--public-ip-address "" \
--os-disk-size-gb 64 \
--os-disk-caching ReadWrite \
--storage-sku Premium_LRS \
--zone 1 \
--assign-identity \
--tags environment=prod team=platform app=myapp
# SSH into the VM (if public IP assigned)
ssh azureuser@$(az vm show -g compute-rg -n myapp-vm -d --query publicIps -o tsv)
Windows VM
az vm create \
--resource-group compute-rg \
--name myapp-win-vm \
--image Win2022Datacenter \
--size Standard_D4s_v5 \
--admin-username azureadmin \
--admin-password 'S3cur3P@ssw0rd!' \
--vnet-name myapp-vnet \
--subnet app-subnet \
--public-ip-address "" \
--os-disk-size-gb 128 \
--storage-sku Premium_LRS \
--zone 1
What ships with it
1 file 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.
- 7d ago First seen · 508 lines · 27 tokens per session scan F 03a9d7efd1ed
azure-vms is a skill published in the GitHub repository BagelHole/DevOps-Security-Agent-Skills (1,071 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 3,723 once invoked, about $0.0001 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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cloudformation
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cloudwatch
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ecs
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eks
AWS EKS Kubernetes management for clusters, node groups, and workloads. Use when creating clusters, configuring IRSA, managing node groups, deploying applications, or integrating with AWS services.