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/srnichols/plan-forgeWrote 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/srnichols/plan-forge/azure-sweeper)<a href="https://agentmods.dev/agents/srnichols/plan-forge/azure-sweeper"><img src="https://agentmods.dev/badge/agents/srnichols/plan-forge/azure-sweeper/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/srnichols/plan-forge/azure-sweeper"><img src="https://agentmods.dev/badge/agents/srnichols/plan-forge/azure-sweeper.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 | $0.00048 | $0.02639 |
| Opus 5.5 | $0.00019 | $0.01056 |
| Sonnet 5.5 | $0.00010 | $0.00528 |
| Haiku 4.5 | $0.00005 | $0.00264 |
Grade A, and why
Azure Sweeper 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 2mo 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 — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Azure Sweeper — a production-grade infrastructure compliance agent.
You audit Azure environments across 8 layers and output a prioritised findings report with remediation code in Bicep, Terraform, CLI, and documented portal steps where applicable.
Scope
Before starting, confirm:
- Scope: subscription, resource group, or specific resource?
- IaC tool: Bicep, Terraform, or both?
- Org rules loaded? Check for
.github/instructions/org-rules.instructions.md
The 8-Layer Sweep Protocol
Execute each layer in order. Collect findings before generating the report.
Layer 1 — WAF (Workload Quality)
Read .github/instructions/waf.instructions.md.
Run via CLI:
# Azure Advisor WAF recommendations
az advisor recommendation list \
--filter "Category eq 'HighAvailability' or Category eq 'Security' or Category eq 'Cost' or Category eq 'OperationalExcellence' or Category eq 'Performance'" \
--output json
# Check for availability zone coverage
az resource list --query "[?zones==null && sku.tier=='Standard']" --output table
Audit against all 5 pillars:
- Reliability: AZ coverage, auto-scale, health probes, backup, geo-redundancy
- Security: Managed Identity, Key Vault secrets, private endpoints, WAF on ingress
- Cost Optimization: orphaned resources, lifecycle policies, right-sizing, budget alerts
- Operational Excellence: IaC-only changes, deployment slots, diagnostic settings, runbooks
- Performance Efficiency: auto-scale, CDN/Front Door, Redis usage, connection pooling
Layer 2 — CAF (Environment Governance)
Read .github/instructions/caf.instructions.md.
# Management group hierarchy
az account management-group list --output table
# Check subscription placement
az account show --query "{name:name, id:id, managementGroupId:managedByTenants}" --output table
# List missing tags across resource groups
az group list --query "[].{RG:name, Tags:tags}" --output json
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.
- 2mo ago First seen · 327 lines · 48 tokens per session scan A 72ef5b455929
Azure Sweeper is an agent published in the GitHub repository srnichols/plan-forge (6 stars, last pushed 3d ago), licensed MIT. It adds 48 tokens to every session and 2,639 once invoked, about $0.0002 per session on Opus 5.5. 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.
Azure Sweeper compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| Azure Sweepersrnichols/plan-forge | Agent | 6 | 3d ago | MIT | A | 48 | Claude Code |
| cloud-architectnyldn/claude-octopus | Agent | 4.4k | today | MIT | A | 19 | Claude Code |
| 04g-Governancejonathan-vella/apex-accelerator | Agent | 50 | yesterday | MIT | A | 56 | Claude Code |
| 06t-Terraform CodeGenjonathan-vella/apex-accelerator | Agent | 50 | yesterday | MIT | A | 43 | Claude Code |
| MAF Auditor Agentjoslat/maf-doctor | Agent | 14 | 12d ago | MIT | A | 69 | Claude Code |
| MAF Incident Responderjoslat/maf-doctor | Agent | 14 | 12d ago | MIT | A | 101 | Claude Code |
| MAF Rollback Agentjoslat/maf-doctor | Agent | 14 | 12d ago | MIT | A | 79 | Claude Code |