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.
npx skills add ivegamsft/basecoat --skill azure-policygit clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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/skills/ivegamsft/basecoat/azure-policy)<a href="https://agentmods.dev/skills/ivegamsft/basecoat/azure-policy"><img src="https://agentmods.dev/badge/skills/ivegamsft/basecoat/azure-policy/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/skills/ivegamsft/basecoat/azure-policy"><img src="https://agentmods.dev/badge/skills/ivegamsft/basecoat/azure-policy.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 | $0.00081 | $0.00310 |
| Opus 5 | $0.00041 | $0.00155 |
| Sonnet 5 | $0.00016 | $0.00062 |
| Haiku 4.5 | $0.00008 | $0.00031 |
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 5d 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.
What it actually says
Azure Policy & Governance Skill
Author Azure governance controls through custom policy definitions, policy initiatives, remediation automation, and compliance reporting.
Reference Files
| File | Contents |
|---|---|
references/workflow.md |
6-step authoring workflow: identify → define → bundle → remediation → KQL queries → framework mapping |
references/guardrails.md |
Authoring guardrails and agent pairing guidance |
policy-definition-template.md |
Custom Azure Policy definition JSON |
initiative-definition-template.md |
Policy initiative (set) definition |
remediation-task-template.md |
DeployIfNotExists remediation task |
compliance-report-template.md |
Azure Resource Graph and KQL compliance queries |
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 28 lines · 81 tokens per session scan A 51eea8ea11fe
azure-policy is a skill published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 310 once invoked, about $0.0004 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.
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