azure-resource-diagnostics

azure-resource-diagnostics is a skill for Claude Code, Codex from aiappsgbb/awesome-gbb. It costs 210 tokens per session (1,172 once invoked), scanned A, original, MIT.

A checker for Azure diagnostic settings across resources in an Azure resource group. Diagnostic settings send resource logs or metrics to destinations such as Log Analytics, Event Hubs, or Storage.

In plain words
What is it for?
Use it to audit resource groups, optionally limit the check to selected Azure resource types, count configured and unconfigured resources, and support Threadlight OBS-106 checks.
Why use it?
It shows which resources have no configured destination, making gaps in logging easier to find before a pilot or landing-zone handover.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to audit resource groups, optionally limit the check to selected Azure resource types, count configured and unconfigured resources, and support Threadlight OBS-106 checks.

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Install with agentmods
npx agentmods add skills/aiappsgbb/awesome-gbb/azure-resource-diagnostics
Install

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.

Any agent
npx skills add aiappsgbb/awesome-gbb --skill azure-resource-diagnostics
Clone the repo
git clone --depth 1 https://github.com/aiappsgbb/awesome-gbb

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for azure-resource-diagnostics

README.md
[![agentmods](https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/azure-resource-diagnostics/github.svg)](https://agentmods.dev/skills/aiappsgbb/awesome-gbb/azure-resource-diagnostics)
Your own site
<a href="https://agentmods.dev/skills/aiappsgbb/awesome-gbb/azure-resource-diagnostics"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/azure-resource-diagnostics/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.

agentmods 80×15 button for azure-resource-diagnostics

Your own site · 80×15
<a href="https://agentmods.dev/skills/aiappsgbb/awesome-gbb/azure-resource-diagnostics"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/azure-resource-diagnostics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 210 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,172 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00210 $0.01172
Opus 5 $0.00105 $0.00586
Sonnet 5 $0.00042 $0.00234
Haiku 4.5 $0.00021 $0.00117

Measured 9d ago against content hash 52ed0b109264, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

azure-resource-diagnostics 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.

The scan reads SKILL.md. This mod also ships 3 executable files (references/python/__init__.py, references/python/__main__.py, references/python/probe.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/azure-resource-diagnostics/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

azure-resource-diagnostics

Audits Azure diagnostic-settings coverage at a resource group scope.

When to use

  • threadlight v0.5.x needs to flip OBS-106 from kind: manual to kind: sibling-skill — this skill's probe() is the sibling.
  • Pre-pilot review: confirm a candidate Foundry RG routes its resource logs somewhere (Log Analytics / Event Hubs / Storage) before a customer pilot.
  • Spoke landing-zone check: detect resources that have no diagnostic settings configured at all.

Probing an RG

from azure_resource_diagnostics.probe import probe

result = probe(
    subscription_id="<sub-id>",
    resource_group="<rg>",
    # target_resource_types=["storage_account", "key_vault"],  # optional OBS-106 filter
)
# result["resources"]                          → list of {id, name, type, configured, destinations, setting_count}
# result["summary"]["total_resources"]         → int (after type filter)
# result["summary"]["configured_count"]        → int (≥1 destination set)
# result["summary"]["unconfigured_count"]      → int (no destination)
# result["summary"]["target_resource_types_filter"] → list[str] | None (echo of applied filter)
# result["summary"]["confidence"]              → 0.0..1.0
# result["summary"]["probe_error"]             → str | None
# result["findings"]                           → list of no-diagnostic-settings findings
# result["manifest_path"]                      → path to JSON manifest on disk

target_resource_types (the OBS-106 sibling-contract input) is an optional list of resource-type tokens. Matching is robust: each token is normalized (lowercased, non-alphanumerics stripped) and matched as a substring of the normalized ARM type, so both raw ARM types (Microsoft.Storage/storageAccounts) and snake_case logical kinds (storage_account) select the same resources. When omitted (default), every resource in the RG is probed. The applied filter is echoed back in summary.target_resource_types_filter.

The probe never raises. If the RG resource listing is denied (RBAC missing), the probe still returns a shape with probe_error populated and confidence: 0.0. Resource types that don't support diagnostic settings (Monitor returns 404) are treated as having no destinations, not as a denial.

Read the full file on GitHub · 116 lines

Files

What ships with it

6 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.

Changes

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.

  1. 9d ago First seen · 116 lines · 210 tokens per session scan A 52ed0b109264

Subscribe to this mod's changes

azure-resource-diagnostics is a skill published in the GitHub repository aiappsgbb/awesome-gbb (5 stars, last pushed 2d ago), licensed MIT. It adds 210 tokens to every session and 1,172 once invoked, about $0.0011 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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