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 personamanagmentlayer/pcl --skill azure-expertgit clone --depth 1 https://github.com/personamanagmentlayer/pclWrote 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/personamanagmentlayer/pcl/azure-expert)<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/azure-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/azure-expert/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/personamanagmentlayer/pcl/azure-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/azure-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00983 |
| Opus 5 | $0.00016 | $0.00491 |
| Sonnet 5 | $0.00007 | $0.00197 |
| Haiku 4.5 | $0.00003 | $0.00098 |
Grade A, and why
azure-expert 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 5d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft Azure Expert
Expert guidance for Microsoft Azure cloud platform, services, and cloud-native architecture.
Core Concepts
- Azure Resource Manager (ARM)
- Virtual Machines and App Services
- Azure Functions (serverless)
- Azure Storage (Blob, Queue, Table)
- Azure SQL Database
- Cosmos DB
- Azure Kubernetes Service (AKS)
- Azure Active Directory
Azure CLI
# Login
az login
# Create resource group
az group create --name myResourceGroup --location eastus
# Create VM
az vm create \
--resource-group myResourceGroup \
--name myVM \
--image UbuntuLTS \
--admin-username azureuser \
--generate-ssh-keys
# Create App Service
az webapp create \
--resource-group myResourceGroup \
--plan myAppServicePlan \
--name myWebApp \
--runtime "NODE|14-lts"
# Create storage account
az storage account create \
--name mystorageaccount \
--resource-group myResourceGroup \
--location eastus \
--sku Standard_LRS
Azure Functions
import azure.functions as func
import logging
app = func.FunctionApp()
@app.function_name(name="HttpTrigger")
@app.route(route="hello")
def main(req: func.HttpRequest) -> func.HttpResponse:
logging.info('Python HTTP trigger function processed a request.')
name = req.params.get('name')
if not name:
try:
req_body = req.get_json()
name = req_body.get('name')
except ValueError:
pass
if name:
return func.HttpResponse(f"Hello, {name}!")
else:
return func.HttpResponse(
"Please pass a name",
status_code=400
)
@app.function_name(name="QueueTrigger")
@app.queue_trigger(arg_name="msg", queue_name="myqueue",
connection="AzureWebJobsStorage")
def queue_trigger(msg: func.QueueMessage):
logging.info(f'Python queue trigger function processed: {msg.get_body().decode("utf-8")}')
Cosmos DB
from azure.cosmos import CosmosClient, PartitionKey
endpoint = "https://myaccount.documents.azure.com:443/"
key = "YOUR_KEY"
client = CosmosClient(endpoint, key)
database = client.create_database_if_not_exists(id="myDatabase")
container = database.create_container_if_not_exists(
id="myContainer",
partition_key=PartitionKey(path="/userId")
)
# Create item
item = {
"id": "1",
"userId": "user123",
"name": "John Doe"
}
container.create_item(body=item)
# Query items
query = "SELECT * FROM c WHERE c.userId = @userId"
items = container.query_items(
query=query,
parameters=[{"name": "@userId", "value": "user123"}],
enable_cross_partition_query=True
)
for item in items:
print(item)
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.
- 5d ago Changed · +2 lines · +18 tokens per session 042a2ab8e37c
- 10d ago First seen · 175 lines · 15 tokens per session scan A 475e3a55b172
azure-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed 3d ago), licensed Apache-2.0. It adds 33 tokens to every session and 983 once invoked, about $0.0002 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 2026-08-30.
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