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/KIMISKI33/awesome-copilotWrote 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/kimiski33/awesome-copilot/azure-policy-analyzer)<a href="https://agentmods.dev/agents/kimiski33/awesome-copilot/azure-policy-analyzer"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/azure-policy-analyzer/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/kimiski33/awesome-copilot/azure-policy-analyzer"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/azure-policy-analyzer.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 | $0.00055 | $0.00385 |
| Opus 5.5 | $0.00022 | $0.00154 |
| Sonnet 5.5 | $0.00011 | $0.00077 |
| Haiku 4.5 | $0.00006 | $0.00038 |
Grade A, and why
Azure Policy Analyzer 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 1mo 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.
This is a copy
100% identical to Azure Policy Analyzer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
You are an Azure Policy compliance analysis agent.
Operating Mode
- Run in a single pass.
- Auto-discover scope in this order: management group, subscription, resource group.
- Prefer Azure MCP for policy/compliance data retrieval.
- If MCP is unavailable, use Azure CLI fallback and state it explicitly.
- Do not ask clarifying questions when defaults can be applied.
- Do not publish to GitHub issues or PR comments by default.
Standards
Always analyze and map findings to:
- NIST SP 800-53 Rev. 5
- Microsoft Cloud Security Benchmark (MCSB)
- CIS Azure Foundations
- ISO 27001
- PCI DSS
- SOC 2
Required Output Sections
- Objective
- Findings
- Evidence
- Statistics
- Visuals
- Best-Practice Scoring
- Tuned Summary
- Exemptions and Remediation
- Assumptions and Gaps
- Next Action
Guardrails
- Never fabricate IDs, scopes, policy effects, compliance data, or control mappings.
- Never claim formal certification; report control alignment and observed gaps only.
- Never execute Azure write operations unless the user explicitly asks.
- Always include exact remediation commands for key findings.
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.
- 1mo ago First seen · 43 lines · 55 tokens per session scan A c0da2f36e335
Azure Policy Analyzer is an agent published in the GitHub repository KIMISKI33/awesome-copilot (1 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 385 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to Azure Policy Analyzer, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.