azure-policy

azure-policy is a skill for Claude Code, Codex from MicrosoftDocs/Agent-Skills. It costs 107 tokens per session (7,331 once invoked), scanned A, original, CC-BY-4.0.

A reference for creating and troubleshooting Azure Policy rules. Azure Policy is Microsoft's system for checking and enforcing how cloud resources are configured.

In plain words
What is it for?
Use it to write JSON policies, machine configuration rules, Terraform or Gatekeeper policies, and policy checks in CI/CD pipelines.
Why use it?
It helps express infrastructure and compliance requirements as rules that can be checked consistently. It also covers policy-as-code and related deployment workflows.

Skill for Claude CodeCodex

Part of the azure-agent-skills plugin — 148 skills shipped together , and of azure-agent-skills

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.

agentmods
npx agentmods add skills/microsoftdocs/agent-skills/azure-policy
Any agent
npx skills add MicrosoftDocs/Agent-Skills --skill azure-policy
Clone the repo
git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills

Made for: Claude Code, Codex.

Or install azure-agent-skills, the plugin that ships this one along with the rest of its 148 skills.

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-policy

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoftdocs/agent-skills/azure-policy.svg)](https://agentmods.dev/skills/microsoftdocs/agent-skills/azure-policy)
Your own site
<a href="https://agentmods.dev/skills/microsoftdocs/agent-skills/azure-policy"><img src="https://agentmods.dev/badge/skills/microsoftdocs/agent-skills/azure-policy.svg" alt="Measured on agentmods" height="20"></a>
Per session 107 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,331 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00107 $0.07331
Opus 5 $0.00053 $0.03666
Sonnet 5 $0.00021 $0.01466
Haiku 4.5 $0.00011 $0.00733

Measured yesterday against content hash 0e00bc1dfb84, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

azure-policy 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 yesterday.

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-policy/SKILL.md · 249 lines

The source is not reproduced here

Licensed CC-BY-4.0

The repository is licensed CC-BY-4.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. yesterday First seen · 249 lines · 107 tokens per session scan A 0e00bc1dfb84

Subscribe to this mod's changes

azure-policy is a skill published in the GitHub repository MicrosoftDocs/Agent-Skills (733 stars, last pushed 4d ago), licensed CC-BY-4.0. It adds 107 tokens to every session and 7,331 once invoked, about $0.0005 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.

Related

Other skills, from other repositories

Azure Microsoft Playwright Testing Ts

Run Playwright tests at scale using Azure Playwright Workspaces (formerly Microsoft Playwright Testing). Use when scaling browser tests across cloud-hosted browsers, integrating with CI/CD pipeline...

mayurrathi/awesome-agent-skills · 43 tokens

agentic-actions-auditor

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.

sickn33/agentic-awesome-skills · 63 tokens

github-actions-injection

GitHub Actions ${{ }} expression injection — attacker-controlled context (issue/PR title, body, branch name, commit message) substituted into run: steps, unsafe pullrequesttarget + PR-head checkout, GITHUBTOKEN scope abuse, artifact/cache poisoning, action tag-vs-SHA pinning.

PurpleAILAB/Decepticon · 65 tokens

babysit

Same-session monitoring loop for PRs, CI runs, tickets, and deployments using the monitorstart / monitorupdate / autonudgestop MCP tools. The loop re-injects your check instructions into THIS session on an idle interval — same context, same tools — and works from dashboard chat, Slack threads, and Discord DMs. Use…

kirodotdev/KiroCrew · 137 tokens

cicd

CI/CD pipeline attack category — poisoned pipeline execution, GitHub Actions expression injection, self-hosted runner abuse, secrets/OIDC exfil. Routing skill: fingerprint the CI provider + workflow surface, then load the matching leaf.

PurpleAILAB/Decepticon · 49 tokens

meta-long-running-build-watchdog

Watches a long-running command via tmux, lets sub-agent diagnose failures and propose a fix, and records the diagnosis to memory. Designed for overnight model fine-tunes, CI image builds, or repeated regression suites that may fail intermittently.

opensquilla/opensquilla · 131 tokens