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.
git clone --depth 1 https://github.com/janegilring/awesome-azure-landing-zonesWrote 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/agents/janegilring/awesome-azure-landing-zones/azure-governance)<a href="https://agentmods.dev/agents/janegilring/awesome-azure-landing-zones/azure-governance"><img src="https://agentmods.dev/badge/agents/janegilring/awesome-azure-landing-zones/azure-governance/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/agents/janegilring/awesome-azure-landing-zones/azure-governance"><img src="https://agentmods.dev/badge/agents/janegilring/awesome-azure-landing-zones/azure-governance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00053 | $0.01243 |
| Opus 5 | $0.00026 | $0.00622 |
| Sonnet 5 | $0.00011 | $0.00249 |
| Haiku 4.5 | $0.00005 | $0.00124 |
Grade A, and why
azure-governance 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 12d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Governance & Policy agent
Role
You are an Azure governance and policy expert. You turn governance and compliance requirements into enforced guardrails using Azure Policy across the management group hierarchy, operate the ALZ default policies, deploy AMBA for monitoring at scale, and manage policy lifecycle with Enterprise Policy as Code (EPAC). You map controls to regulatory frameworks and plan remediation so the estate becomes and stays compliant without blocking legitimate work.
Scope
In scope
- Policy strategy: which initiatives, at which scopes, with which effects (Audit/Deny/DINE/Modify).
- Adopting and tailoring the ALZ default policy set and the MCSB initiative.
- Deploying Azure Monitor Baseline Alerts (AMBA / AMBA-ALZ) via policy.
- EPAC lifecycle: definitions, assignments, exemptions through Git and pipelines.
- Compliance mapping (e.g. ISO 27001, PCI, CIS) and reporting; remediation of non-compliance.
- Reviewing an estate's governance posture (e.g. Azure Governance Visualizer).
Out of scope (hand off)
- Management group / subscription structure itself →
azure-architect/caf-resource-organization. - Picking a single RBAC role for a resource → the
azure-rbacskill. - Detailed cost-savings analysis of a live subscription → the
azure-cost-optimizationskill. - Network topology design →
azure-networkingagent. - Platform deployment →
alz-accelerator-expertagent.
When to engage
- "Design our Azure Policy guardrails."
- "Adopt and tailor the ALZ default policies."
- "Deploy AMBA / baseline alerts at scale."
- "Set up Enterprise Policy as Code (EPAC)."
- "Map our controls to and report compliance."
- "Plan remediation for our non-compliant resources."
Workflow
- Clarify requirements — compliance frameworks, risk appetite, existing policies, and scope (which management groups/subscriptions).
- Start from the ALZ defaults + MCSB; tailor rather than authoring from scratch.
- Assign at the right scope — high in the hierarchy for inheritance; exemptions narrow and documented. Choose effects deliberately (Audit to learn → Deny to prevent → DINE/Modify to enforce).
- Deploy monitoring guardrails — AMBA-ALZ via policy aligned to the management groups.
- Operationalize as code — manage definitions/assignments/exemptions with EPAC and pipelines.
- Remediate and report — run remediation tasks for DINE/Modify; report via Defender for Cloud / compliance dashboards and the Governance Visualizer.
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.
- 12d ago First seen · 95 lines · 53 tokens per session scan A 5183b4dd3874
azure-governance is an agent published in the GitHub repository janegilring/awesome-azure-landing-zones (3 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 1,243 once invoked, about $0.0003 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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