cost-analysis

metadata	{"api_version":"azuresre.ai/v2","kind":"Skill"}
name	cost-analysis
description	Use when an operator or a scheduled task requests a periodic cloud-cost / spend audit of the Zava Learning resource group — identify the top cost drivers, week-over-week trend, idle or oversized resources, and concrete savings opportunities. Read-only; produces findings for a report.
tools	["RunAzCliReadCommands","GetAzCliHelp","SearchMemory","ExecutePythonCode","microsoft-learn_microsoft_docs_search"]

Zava Learning — Cloud Cost Analysis

Resource Group: @@RG@@. Read-only audit — never resize, deallocate, or delete a resource. This is a weekly spend posture review. Recommend optimisations for a human to apply; change nothing.

1. Pull actual spend (preferred path)

Use Cost Management for real billed amounts, scoped to the RG:

• This week vs. last week by resource: az costmanagement query --type ActualCost --timeframe Custom --time-period from=<start> to=<end> --scope "/subscriptions/<sub>/resourceGroups/@@RG@@" --dataset-grouping name=ResourceId type=Dimension --dataset-aggregation totalCost.name=Cost totalCost.function=Sum (run it for the current 7-day window and the prior 7-day window, then diff per ResourceId).
• Or month-to-date by service: same query grouped by ServiceName. If az costmanagement is missing or returns an auth error (the agent identity lacks Cost Management Reader), FALL BACK to az consumption usage list --start-date <d> --end-date <d> filtered to the RG. Record which data source you used so the report is honest about provenance.

2. If billing data is unavailable, estimate from inventory

As a last resort (no Cost Management and no consumption access), build an estimate:

• Inventory the RG: az resource list -g @@RG@@ --query "[].{name:name,type:type,sku:sku}".
• Note the cost-bearing resources (PostgreSQL Flexible Server SKU, the reporting VM SKU + managed disks, Container Apps environments + per-app replicas/scale, Application Gateway tier + capacity units, Log Analytics ingestion, Key Vault, ACR SKU, public IPs).
• Use microsoft-learn_microsoft_docs_search / known Azure retail pricing to produce a rough, clearly-labelled estimate, not a billed figure. State the assumption explicitly.

3. Find waste and right-sizing opportunities (read-only signals)

• Idle/oversized: VMs that are deallocated yet still incurring disk cost; disks not attached to any VM (az disk list -g @@RG@@ --query "[?managedBy==null]"); over-provisioned VM/DB SKUs vs. observed CPU/memory; Container Apps with high min-replicas but low traffic.
• Orphaned: unattached public IPs, empty App Gateway backend pools, unused NICs, old ACR images.
• Trend: any ResourceId whose week-over-week cost rose sharply — flag it with the Δ%.

4. Produce the findings table

For each driver/opportunity output a row: Resource (type) · This week $ · Last week $ · Δ% · Finding · Severity · Recommendation. Severity is impact-based: a sharp WoW spike or a clearly idle/ oversized paid resource is SEV2; smaller tidy-ups are SEV3. Sort by this-week spend (and severity). Also produce a posture summary (total RG spend this week, WoW delta, the single biggest saving) and a prioritized recommendations list with rough monthly savings where you can estimate them.

5. Hand off to the branded report

This skill does not remediate. Pass the posture summary, the findings rows (each with its severity), the spend numbers, and the recommendations to the zava-audit-report skill, which renders the single branded, downloadable PowerPoint deck (top cost drivers chart + findings table) and returns its download link. Surface that link to the operator.