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 ancoleman/ai-design-components --skill deploying-on-azuregit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote 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/ancoleman/ai-design-components/deploying-on-azure)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/deploying-on-azure"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/deploying-on-azure/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/ancoleman/ai-design-components/deploying-on-azure"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/deploying-on-azure.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 | $0.00045 | $0.03946 |
| Opus 5 | $0.00023 | $0.01973 |
| Sonnet 5 | $0.00009 | $0.00789 |
| Haiku 4.5 | $0.00005 | $0.00395 |
Grade A, and why
deploying-on-azure 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 9d 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 — 452 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Patterns
Design and implement Azure cloud architectures following Microsoft's Well-Architected Framework and best practices for service selection, cost optimization, and security.
When to Use
Use this skill when:
- Designing new applications for Azure cloud
- Selecting Azure compute services (Container Apps, AKS, Functions, App Service)
- Architecting storage solutions (Blob Storage, Files, Cosmos DB)
- Integrating Azure OpenAI or Cognitive Services
- Implementing messaging patterns (Service Bus, Event Grid, Event Hubs)
- Designing secure networks with Private Endpoints
- Applying Azure governance and compliance policies
- Optimizing Azure costs and performance
Core Concepts
Service Selection Philosophy
Azure offers 200+ services. Choose based on:
- Managed vs. IaaS - Prefer fully managed services (lower operational burden)
- Cost Model - Consumption vs. dedicated capacity
- Integration Requirements - Microsoft 365, Active Directory, hybrid cloud
- Control vs. Simplicity - More control = more operational overhead
Azure Well-Architected Framework (Five Pillars)
| Pillar | Focus | Key Practices |
|---|---|---|
| Cost Optimization | Maximize value within budget | Reserved Instances, auto-scaling, lifecycle management |
| Operational Excellence | Run reliable systems | Azure Policy, automation, monitoring |
| Performance Efficiency | Scale to meet demand | Autoscaling, caching, CDN |
| Reliability | Recover from failures | Availability Zones, multi-region, backup |
| Security | Protect data and assets | Managed Identity, Private Endpoints, Key Vault |
Reference references/well-architected.md for detailed pillar implementation patterns.
Compute Service Selection
Decision Framework
Container-based workload?
YES → Need Kubernetes control plane?
YES → Azure Kubernetes Service (AKS)
NO → Azure Container Apps (recommended)
NO → Event-driven function?
YES → Azure Functions
NO → Web application?
YES → Azure App Service
NO → Legacy/specialized → Virtual Machines
What ships with it
13 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.
- examples/bicep/container-apps/main.bicep 8.5 KB
- examples/sdk/python/azure-openai-rag.py 11 KB runs code
- outputs.yaml 14 KB
- references/ai-integration.md 21 KB
- references/compute-services.md 22 KB
- references/database-selection.md 2.1 KB
- references/governance-compliance.md 3.0 KB
- references/identity-access.md 2.4 KB
- references/messaging-patterns.md 1.5 KB
- references/networking-architecture.md 2.4 KB
- references/security-architecture.md 1.2 KB
- references/storage-patterns.md 1.9 KB
- references/well-architected.md 16 KB
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.
- 9d ago First seen · 452 lines · 45 tokens per session scan A 3d8a0bd8c6df
deploying-on-azure is a skill published in the GitHub repository ancoleman/ai-design-components (519 stars, last pushed 9mo ago), licensed MIT. It adds 45 tokens to every session and 3,946 once invoked, about $0.0002 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 2026-08-30.
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