Use Autohand Code with cloud cost skill guidance to review resource usage, billing signals, orphaned assets, and savings recommendations.
Find waste and right-size resources from evidence
Cloud FinOps Delivery and operations Operate Analysis
autohand -p "Analyze these cloud cost signals and propose safe savings with validation steps"
A cost report with likely savings, resource evidence, risks, and owner-ready actions.
Analyze cloud costs with Autohand Code is a FinOps workflow that reviews cost data, resource utilization, orphaned assets, right-sizing opportunities, and safe savings actions. ### At a glance | Question | Answer | | --- | --- | | Best for | cloud bills that need evidence, idle resources, oversized services, storage lifecycle gaps, and cost-review reports | | Primary inputs | Billing export, cost dashboard, or resource list; Utilization metrics, tags, owners, and retention policies; Savings target and services that must stay untouched | | Autohand Code returns | A cost report with likely savings, resource evidence, risks, and owner-ready actions. | | Avoid when | cost data is unavailable or the team cannot identify resource owners | ### How Autohand Code handles this workflow 1. Groups spend by service, owner, environment, and trend where data allows it. 2. Finds orphaned, idle, oversized, or mis-tiered resources. 3. Ranks savings by risk and operational effort. 4. Returns validation and rollback steps for every recommended action. ### Best inputs - Billing export, cost dashboard, or resource list - Utilization metrics, tags, owners, and retention policies - Savings target and services that must stay untouched ### Strong prompt autohand -p "Analyze these cloud cost signals and propose safe savings with validation steps" ### Autohand Code CLI options - Use `/skills use azure-cost-optimization` or the matching cloud cost skill when available. - Run `autohand -p "Analyze these cloud cost signals and propose safe savings with validation steps"` with cost evidence. - Use `/mcp` for approved billing or resource inventory tools rather than pasting sensitive exports. ### Review before accepting A useful report ties each recommendation to resource evidence, expected savings, risk, owner, and verification path. ### Source and validation signals Autohand AI maintains this workflow as first-party product guidance for Autohand Code. Use the [Autohand CLI Playbook](https://github.com/autohandai/code-cli/blob/main/docs/AUTOHAND_PLAYBOOK.md), [CLI reference](/docs/working-with-autohand-code/cli-reference.html), and [configuration reference](https://github.com/autohandai/code-cli/blob/main/docs/config-reference.md) when choosing between interactive mode, command mode, auto-mode, feature-enabled /goal, /settings, skills, MCP, and permission settings. The related resources below link to product docs and tutorials for the workflow, and the final answer should name repository-specific files, commands, outputs, or docs that a reviewer can verify. ### Frequently asked questions ### What is Analyze cloud costs with Autohand Code? Analyze cloud costs with Autohand Code is a FinOps workflow that reviews cost data, resource utilization, orphaned assets, right-sizing opportunities, and safe savings actions. ### When should a team use Analyze cloud costs? Use it when cloud spend needs concrete owner-ready actions rather than a generic cost summary. ### What evidence should reviewers check for Analyze cloud costs? A useful report ties each recommendation to resource evidence, expected savings, risk, owner, and verification path.
Skill Skilled: Azure Cost Optimization Use cost analysis and right-sizing guidance. https://skilled.autohand.ai/skill/azure-cost-optimization Guide Cost Optimization Reduce spend with measurable evidence. /docs/guides/cost-optimization.html Guide Observability Use metrics to validate utilization claims. /docs/guides/sre/observability.html