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 ricmmartins/azure-sre-agent-skills --skill 03-capacity-planninggit clone --depth 1 https://github.com/ricmmartins/azure-sre-agent-skillsWrote 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/ricmmartins/azure-sre-agent-skills/03-capacity-planning)<a href="https://agentmods.dev/skills/ricmmartins/azure-sre-agent-skills/03-capacity-planning"><img src="https://agentmods.dev/badge/skills/ricmmartins/azure-sre-agent-skills/03-capacity-planning/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/ricmmartins/azure-sre-agent-skills/03-capacity-planning"><img src="https://agentmods.dev/badge/skills/ricmmartins/azure-sre-agent-skills/03-capacity-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.02558 |
| Opus 5 | $0.00023 | $0.01279 |
| Sonnet 5 | $0.00009 | $0.00512 |
| Haiku 4.5 | $0.00005 | $0.00256 |
Grade A, and why
capacity-planning 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 12d 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 — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Capacity Planning
Purpose
Analyze current resource utilization, quota consumption, and growth trends to predict capacity risks and recommend scaling actions before limits are hit.
When to use this skill
- User asks "will our infrastructure handle the traffic spike?"
- User asks about quotas, limits, or capacity
- Pre-event planning (Black Friday, product launch, marketing campaign)
- Quarterly capacity review
- After hitting a quota or throttling limit
Pre-check
Confirm with the user:
- Scope: which subscriptions and regions
- Time horizon: when is the expected load increase? (default: 30 days)
- Expected growth factor (e.g., 2x, 5x, 10x current load)
- Critical workloads to prioritize
Assessment procedure
Step 1: Quota utilization
Check current quota usage across all critical resource providers.
az vm list-usage --location <region> -o table
az network list-usages --location <region> -o table
az storage account list --query "length(@)"
Check for:
- vCPU quotas: Total and per-family (Dv5, Ev5, etc.) — flag if > 70% utilized
- Public IPs: Usage vs. limit
- Load balancers: Usage vs. limit
- Network interfaces: Usage vs. limit
- Storage accounts per subscription: Usage vs. 250 limit
- App Service plans per region
- AKS clusters per subscription
Build a quota utilization table. Use Unicode emoji characters directly (🟢🟡🔴) — never use emoji shortcodes like :green_circle: or :red_circle:.
| Resource | Region | Used | Limit | Utilization | Risk |
|---|---|---|---|---|---|
| Total vCPUs | East US | 85 | 100 | 85% | 🔴 |
| Dv5 vCPUs | East US | 32 | 50 | 64% | 🟡 |
| Public IPs | East US | 8 | 20 | 40% | 🟢 |
Step 2: Compute capacity
Analyze current compute utilization and headroom.
- VM utilization (last 14 days):
- Average and P95 CPU across all VMs
- Average and P95 memory (if available via Log Analytics)
- Flag VMs consistently > 80% CPU or memory
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.
- 12d ago First seen · 252 lines · 45 tokens per session scan A 6212e53726ad
capacity-planning is a skill published in the GitHub repository ricmmartins/azure-sre-agent-skills (70 stars, last pushed 18d ago), licensed MIT. It adds 45 tokens to every session and 2,558 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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