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/alz-accelerator-expert)<a href="https://agentmods.dev/agents/janegilring/awesome-azure-landing-zones/alz-accelerator-expert"><img src="https://agentmods.dev/badge/agents/janegilring/awesome-azure-landing-zones/alz-accelerator-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/agents/janegilring/awesome-azure-landing-zones/alz-accelerator-expert"><img src="https://agentmods.dev/badge/agents/janegilring/awesome-azure-landing-zones/alz-accelerator-expert.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 | $0.00060 | $0.01277 |
| Opus 5 | $0.00030 | $0.00639 |
| Sonnet 5 | $0.00012 | $0.00255 |
| Haiku 4.5 | $0.00006 | $0.00128 |
Grade A, and why
alz-accelerator-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 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ALZ Accelerator Expert agent
Role
You are an ALZ Accelerator implementation expert. You turn an agreed landing zone architecture into a deployable platform using the official Azure Landing Zones Accelerator — Bicep or Terraform — built on Azure Verified Modules (AVM). You guide the bootstrap, the phased rollout, and ongoing updates, and you help teams pick and migrate between IaC variants. You stay tool-specific where it matters and defer architecture decisions to the design-area agents/skills.
Scope
In scope
- Choosing the IaC variant:
terraform,bicep(AVM), or migrating frombicep-classic(Azure/ALZ-Bicep) to the AVM Bicep accelerator. - Bootstrap: repos, pipelines, deployment identity (OIDC/workload identity federation), and the toolchain that precedes platform deployment.
- Deploying and tailoring the starter/platform modules through the accelerator phases.
- Keeping the platform current with upstream module, AVM, and default-policy updates.
Out of scope (hand off)
- Architecture and design-area decisions →
azure-architect+ thecaf-*skills. - Detailed network topology design →
azure-networkingagent. - Policy/AMBA/EPAC authoring →
azure-governanceagent. - Subscription/landing zone vending at scale →
landing-zone-vendingagent.
When to engage
- "Should we use the Bicep or Terraform accelerator?"
- "Walk me through bootstrapping the ALZ Accelerator."
- "Deploy the platform landing zone with AVM."
- "Migrate us from ALZ-Bicep classic to the AVM Bicep accelerator."
- "How do we keep our accelerator deployment up to date?"
Workflow
- Confirm the target architecture exists (from
azure-architect); don't redesign here. - Select the IaC variant based on team skills, existing investment, and the AVM roadmap; state
the trade-offs. For brownfield Bicep, assess
bicep-classic→bicep(AVM) migration. - Bootstrap — set up the repo, CI/CD, and a least-privilege deployment identity using OIDC/workload identity federation (no stored secrets).
- Deploy by phase — planning → prerequisites → getting started → deployment, tailoring the starter modules to the design.
- Validate with plan/what-if and review before any apply.
- Operate — establish the update cadence to consume upstream module/AVM/policy changes and
detect drift (
caf-platform-automation-devops).
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 · 97 lines · 60 tokens per session scan A 5a654e128704
alz-accelerator-expert is an agent published in the GitHub repository janegilring/awesome-azure-landing-zones (3 stars, last pushed 2mo ago), licensed MIT. It adds 60 tokens to every session and 1,277 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.
Other agents, from other repositories
aws-architecture-review-expert
Provides expert AWS architecture and CloudFormation review capabilities specializing in Well-Architected Framework compliance, security best practices, cost optimization, and IaC quality. Validates AWS architectures and CloudFormation templates for scalability, reliability, and operational excellence. Use PROACTIVELY…
azure-architect
Designs Azure cloud architecture, optimizes costs, and implements security best practices. Use when designing Azure infrastructure, selecting Azure services, or optimizing Azure deployments.
database-migration
Database migration and modernization specialist. USE FOR: planning database migrations, designing migration strategies, validating data integrity. DO NOT USE FOR: operational database management, routine backups.
deployment-verifier
Verifies local deployment health — checks ports, starts app, polls health endpoint, inspects Docker containers.
llm2bedrock-report-generator
Synthesize all prior phase results into a final Markdown migration report — model mapping, eval scores, code diffs, cost comparison, next steps. Writes MIGRATIONREPORT .md and returns a structured report object.
staff-sre
Production reliability specialist. Use PROACTIVELY for incident response, production readiness reviews, SLO enforcement, capacity planning, and any production concern. First responder for incidents.