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 jonathan-vella/apex-accelerator --skill apex-azure-computegit clone --depth 1 https://github.com/jonathan-vella/apex-acceleratorWrote 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/jonathan-vella/apex-accelerator/apex-azure-compute)<a href="https://agentmods.dev/skills/jonathan-vella/apex-accelerator/apex-azure-compute"><img src="https://agentmods.dev/badge/skills/jonathan-vella/apex-accelerator/apex-azure-compute/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/jonathan-vella/apex-accelerator/apex-azure-compute"><img src="https://agentmods.dev/badge/skills/jonathan-vella/apex-accelerator/apex-azure-compute.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 | $0.00097 | $0.01228 |
| Opus 5.5 | $0.00039 | $0.00491 |
| Sonnet 5.5 | $0.00019 | $0.00246 |
| Haiku 4.5 | $0.00010 | $0.00123 |
Grade A, and why
apex-azure-compute 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 22d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Compute Skill
Recommend Azure VM sizes, VM Scale Sets (VMSS), and configurations by analyzing workload type, performance requirements, scaling needs, and budget. No Azure subscription required — all data comes from public Microsoft documentation and the unauthenticated Retail Prices API.
When to Use This Skill
- User asks which Azure VM or VMSS to choose for a workload
- User needs VM size recommendations for web, database, ML, batch, HPC, or other workloads
- User wants to compare VM families, sizes, or pricing tiers
- User asks about trade-offs between VM options (cost vs performance)
- User needs a cost estimate for Azure VMs without an Azure account
- User asks whether to use a single VM or a scale set
- User needs autoscaling, high availability, or load-balanced VM recommendations
- User asks about VMSS orchestration modes (Flexible vs Uniform)
Rules
- Always verify against live docs — call
web_fetchagainstlearn.microsoft.combefore finalizing recommendations; warn the user whenweb_fetchfails.web_fetchmeans any available page-fetch tool; prefermcp_azure-mcp_documentation(microsoft_docs_fetch) for Learn pages - Availability and quota — before recommending a size for a deployment, confirm SKU availability and quota headroom with
apex-azure-quotas(SKU availability); neither guarantees allocation capacity - Default to General Purpose D-series when workload type is unclear
- Default region follows the canonical declaration in copilot-instructions.md; prices vary by region
- Default to single VM when scaling needs are unclear; recommend VMSS only when autoscale, fleet, or mixed-size requirements are explicit
- VMSS pricing = VM pricing × instance count (no extra VMSS charge)
- Reservation pricing is recommended for long-lived production VMs (1y/3y commitments)
- No deployment — this skill recommends sizes; for provisioning use
apex-azure-prepare
What ships with it
4 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.
- 22d ago Changed · +1 lines aa8d790c48bd
- 23d ago First seen · 70 lines · 97 tokens per session scan A 7ec556721855
apex-azure-compute is a skill published in the GitHub repository jonathan-vella/apex-accelerator (50 stars, last pushed yesterday), licensed MIT. It adds 97 tokens to every session and 1,228 once invoked, about $0.0004 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 2026-09-23.
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