Use cloud-cost-review

Review actual cloud spend from a cost export (AWS CUR or Data Exports, GCP billing export, Azure cost details) and produce a ranked savings report

Review actual cloud spend from a cost export (AWS CUR or Data Exports, GCP billing export, Azure cost details) and produce a ranked savings report — idle and unattached resources, oversized instances backed by utilisation evidence, storage tiering, data transfer hot spots, commitment coverage and untagged spend — each finding with a monthly saving computed from the bill, a confidence level and an ease rating.

Reach for it when the user shares a cost CSV and says "where are we wasting money", "review our AWS bill", "why did the cloud bill jump this month", "find savings in our GCP/Azure spend", or "should we buy savings plans".

Install it

npx skilldrop-cli install cloud-cost-review                 # Claude Code, your user folder
npx skilldrop-cli install cloud-cost-review --project       # Claude Code, this repo
npx skilldrop-cli install cloud-cost-review --ide cursor    # or kiro, codex, antigravity, copilot

It is part of the SRE / on-call pack: --pack sre-oncall installs it with its neighbours.

It ships scripts, so it needs Python 3 (standard library only, nothing to install). What they may touch is declared in its manifest.

Ask for it

Say it the way you would to a colleague. Requests like these route to it:

"Here's our AWS CUR for the last two months — where are we wasting money?"
"Why did our Azure bill jump in September? Cost export attached"
"Review this GCP billing export for idle resources, untagged spend and committed use coverage"
"Should we buy more savings plans? Here's the cost and usage report"

Requests like these belong to a different skill, so it shouldn't answer them:

"Estimate what the new search service will cost to run at 10x our current traffic"
"Our log volume is out of control — design what we should log, sample, and alert on"
"Write the postmortem for the runaway batch job that burned $40k last weekend"

If another skill answers instead, ask for this one by name: "use cloud-cost-review".

Check what you get

A good result:

Every amount traces to the script output or to arithmetic shown in the finding. No list prices from memory, and no "industry average" savings percentages.
Rightsizing needs utilisation evidence. An instance finding without CPU and memory data goes under Evidence needed, not in the ranked table.
Each finding has a monthly saving, a confidence level and an ease rating, or sits in Evidence needed with what to collect.
Ranked by saving × ease, and sequenced so waste removal happens before any commitment purchase.
The month-over-month change is explained by named movers, not described as "costs went up".
Untagged share is reported both against all spend and against spend that has a resource id, because data transfer and support lines often can't be tagged.
Excluded lines are stated. Tax, credits, refunds and commitment fees are listed separately so the review doesn't hide credits that mask waste.

See a worked example

acme aws september

Use something else when

Estimating cost before launch, or projecting at 3× or 10× growth. Use capacity-cost-model.
Designing telemetry or a logging budget from scratch. Use observability-plan, though this skill flags logging cost as a hot spot.
Writing up an incident, including a cost spike from a runaway job. Use postmortem-generator.
Reporting AI tool usage or spend by user. Use ai-usage-report.
Defining business KPIs for a feature or product. Use success-metrics.

SKILL.md, the instructions the agent reads
Its page on the site
Related: ai-usage-report, capacity-cost-model, observability-plan, postmortem-generator, success-metrics

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