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Skills azure-monitor-query-py
📦
azure-monitor-query-py
Content revision r2 Safe ⚙️ External commands🔑 Env variables
Query Azure Monitor Data with Python
Azure Monitor queries require correct clients, credentials, resource identifiers, time ranges, and response handling. This skill provides focused Python and Kusto patterns for logs and metrics.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "azure-monitor-query-py" from https://skillstore.io/skills/sickn33-azure-monitor-query-py.md and its manifest at https://skillstore.io/api/skills/sickn33-azure-monitor-query-py/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "azure-monitor-query-py". Query AppRequests for the last hour and summarize results by status code.
Expected outcome:
- Authenticates with DefaultAzureCredential and opens a LogsQueryClient.
- Queries the workspace over a one-hour relative time range.
- Returns counts grouped by result code and reports partial results when present.
Using "azure-monitor-query-py". Retrieve CPU metrics every five minutes and include average and maximum values.
Expected outcome:
- Uses the configured Azure resource URI and Percentage CPU metric.
- Requests five-minute granularity with average and maximum aggregations.
- Presents each timestamp with the available aggregate values.
Using "azure-monitor-query-py". Prepare recent exception data for analysis in pandas.
Expected outcome:
Queries the exception table, maps returned columns and rows into a DataFrame, and notes when no result table is available.
Security Audit
Safev5 • 7/23/2026 Open versioned report
The 31 external-command alerts are false positives caused by Markdown fences and inline code formatting; none performs Ruby or shell backtick execution. The two environment reads retrieve documented Azure resource identifiers for intended SDK calls, with no credential disclosure or unrelated transmission. No prompt injection or other semantic security issue was found.
1
Files scanned
261
Lines analyzed
0
Review items
0
False positives ignored
Risk Factors
⚙️ External commands (31)
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🔑 Env variables (2)
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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APA citation
sickn33. (2026). azure-monitor-query-py security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-azure-monitor-query-py/audits/5BibTeX citation
@techreport{sickn33-sickn33-azure-monitor-query-py-2026,
author = {sickn33},
title = {azure-monitor-query-py security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-azure-monitor-query-py/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "azure-monitor-query-py security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-azure-monitor-query-py/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-azure-monitor-query-py:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: High 55
Architecture
85
Maintainability
87
Content
69
Community
83
Spec Compliance
What You Can Build
Investigate application failures
Build Log Analytics queries that summarize requests, exceptions, status codes, and slow operations over a selected period.
Review resource performance
Query Azure resource metrics with selected aggregations, time granularity, and dimension filters.
Prepare monitoring data
Convert query results into DataFrames for analysis, reporting, and comparison across time ranges.
Try These Prompts
Create a basic log query
Show a Python example that queries {table} in my workspace for the last {hours} hours using DefaultAzureCredential.Query a resource metric
Create a Python metrics query for {metric_names} on {resource_uri} with {granularity} granularity and {aggregation} aggregation.Build resilient batch queries
Design batch log queries for {tables} over {time_range}. Include partial-result and failure handling, then summarize each returned table.Design an asynchronous analysis
Design an asynchronous Python workflow for {workspace_ids} using {kusto_query}. Handle partial results, close clients, and prepare tables for {analysis_goal}.Best Practices
- Use explicit time ranges and suitable granularity to control query volume.
- Handle partial results and failures before processing returned tables.
- Close asynchronous clients and credentials after each completed workflow.
Avoid
- Do not assume example workspace identifiers or resource URIs match your environment.
- Do not request broad time ranges when a focused interval answers the question.
- Do not process response tables without checking status and table availability.
Frequently Asked Questions
Does this skill execute Azure queries?
No. It provides Python and Kusto patterns that require your Azure environment, credentials, and execution.
Which Azure data sources are covered?
It covers Log Analytics workspace logs and Azure Monitor metrics for resource URIs.
How does authentication work?
The examples use DefaultAzureCredential from the Azure Identity package.
Can it handle multiple log queries?
Yes. It demonstrates LogsBatchQuery and response handling for multiple queries.
Does it support asynchronous clients?
Yes. It shows asynchronous log and metrics client imports, awaited queries, and client cleanup.
Can results be analyzed with pandas?
Yes. It shows how to map a returned log table into a pandas DataFrame.
Developer Details
Author
sickn33License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/azure-monitor-query-pyRef
f9e2c34b4f19c7f3e6b0a1e93227b5f77cc12526
Maintenance freshness
7/26/2026
Usage
8 downloads · 141 views
File structure
📄 SKILL.md
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