cost-optimization

Overview of cost-optimization skill

What the cost-optimization skill does

The cost-optimization skill gives an AI agent a practical framework for reducing cloud spend across AWS, Azure, GCP, and OCI without treating cost cutting as a blind “delete things” exercise. It focuses on the decisions teams actually make: improving cost visibility, right-sizing resources, choosing better pricing models, and tightening architecture patterns that create avoidable spend.

Who should install this skill

This cost-optimization skill is best for platform engineers, cloud architects, FinOps-minded teams, SREs, and engineering managers who need structured cost review guidance. It is especially useful when you want an agent to turn a broad goal like “reduce our AWS bill” into a more systematic optimization plan.

Real job-to-be-done

Most users do not need a generic cloud cost checklist. They need help identifying where waste is likely, what optimization levers exist, which tradeoffs matter, and how to sequence changes safely. This skill is strongest when you want a repeatable review lens for performance optimization, budget control, or multi-cloud governance.

Why this skill is different from a plain prompt

A plain prompt may produce generic cost-saving ideas. The cost-optimization skill is better because it gives the agent a defined optimization framework:

• visibility first
• right-sizing second
• pricing model selection
• architecture-level cost changes

That structure matters because many teams try to optimize spend before they can attribute it, measure it, or compare alternatives.

What is actually inside

The repository evidence shows a compact but useful skill:

• SKILL.md with the main framework
• references/tagging-standards.md with actionable tagging standards

That means this is not a heavy automation package. It is a decision-support and analysis skill, with the strongest practical value in planning, auditing, and guided recommendations.

Best-fit and misfit cases

Best fit:

• cloud bill review
• rightsizing discussions
• reserved capacity or savings plan planning
• tagging and chargeback cleanup
• cost-optimization for Performance Optimization where spend and efficiency must be balanced

Weak fit:

• exact billing calculations from raw provider exports
• automated remediation
• provider-specific deep implementation runbooks
• teams that cannot provide any inventory, usage, or tagging context

How to Use cost-optimization skill

Install the cost-optimization skill

Install it from the repository with:

npx skills add https://github.com/wshobson/agents --skill cost-optimization

If your environment uses a different skill loader, add the skill from:

https://github.com/wshobson/agents/tree/main/plugins/cloud-infrastructure/skills/cost-optimization

Read these files first

For a fast install decision, read in this order:

1. plugins/cloud-infrastructure/skills/cost-optimization/SKILL.md
2. plugins/cloud-infrastructure/skills/cost-optimization/references/tagging-standards.md

SKILL.md gives the optimization model. The tagging reference matters because poor tagging is often the blocker that prevents useful cost analysis.

What inputs the skill needs to work well

The cost-optimization skill becomes much more useful when you provide concrete operating context, such as:

• cloud provider and account/subscription/project structure
• monthly spend by service
• utilization signals for compute, storage, and databases
• existing reservations, savings plans, or commitments
• tagging coverage and tag standards
• performance or reliability constraints
• whether the goal is quick savings, long-term governance, or both

Without this context, the output will stay high level.

Best prompt shape for cost-optimization usage

Do not ask only:

Help me reduce cloud costs.

Ask with enough structure for the skill to reason:

Use the cost-optimization skill. Review our AWS spend for a SaaS platform. Prioritize actions by savings potential, risk, and implementation effort. Constraints: production latency cannot degrade, RDS is business-critical, and we already use some Savings Plans. Focus on EC2, EBS, RDS, S3, and data transfer. Also assess whether our tagging is sufficient for chargeback.

This produces better output because it defines:

• provider
• workloads
• constraints
• services in scope
• optimization priorities
• governance expectations

Turn a rough goal into a complete request

A good pattern is:

1. State the business goal
   Example: reduce spend by 15% in 90 days.

2. Name the environment
   Example: AWS production and staging accounts.

3. Define constraints
   Example: no downtime, no performance regression, no multi-quarter migrations.

4. Supply evidence
   Example: top services by cost, idle resource concerns, poor tags, or underused instances.

5. Ask for ranked output
   Example: quick wins, medium-effort changes, and strategic changes.

Practical workflow for first-time use

A strong first-pass workflow is:

1. Ask the skill to assess visibility and tagging maturity.
2. Ask it to identify likely waste categories by provider and service.
3. Ask it to separate no-regret actions from risky actions.
4. Ask it to map recommendations to effort, savings potential, and operational risk.
5. Only then ask for provider-specific implementation ideas.

This order avoids jumping into reserved instance or deletion advice before basic hygiene is understood.

Use the framework in the intended order

The underlying framework is the main value of this cost-optimization guide:

• Visibility
• Right-Sizing
• Pricing Models
• Architecture Optimization

Users often skip straight to pricing discounts. In practice, better visibility and right-sizing usually improve decision quality first. For example, buying commitments before fixing idle capacity can lock in bad patterns.

When the tagging reference matters most

references/tagging-standards.md is especially important if:

• you cannot attribute costs cleanly
• teams argue over ownership
• chargeback/showback is weak
• the agent needs to recommend governance improvements, not just infra tweaks

Useful tags called out in the repo include:

• Environment
• Owner
• CostCenter
• Project
• ManagedBy

If your estate lacks these, the skill should be used first to improve visibility, not to promise precision savings.

Example prompt for multi-cloud reviews

Use the cost-optimization skill to compare AWS and Azure spend controls for a company running dev, staging, and production across both clouds. Identify common waste patterns, provider-specific pricing levers, tagging gaps, and governance controls. Rank recommendations by expected savings, implementation complexity, and operational risk.

This works well because the skill explicitly covers AWS, Azure, GCP, and OCI.

Example prompt for performance-sensitive systems

For cost-optimization for Performance Optimization, be explicit:

Use the cost-optimization skill to review our production compute and database spend. Do not recommend changes that would reduce p95 latency or resiliency. Focus on rightsizing, storage class choices, autoscaling policies, reservations, and non-critical environment cleanup. Show which actions are safe for performance-sensitive workloads and which need benchmarking first.

This prevents the agent from suggesting cost cuts that are technically cheaper but operationally harmful.

What good output should look like

A useful response from this cost-optimization skill should include:

• current likely waste areas
• missing data that blocks better recommendations
• prioritized actions
• savings levers by service type
• governance fixes such as tagging or budgets
• risks and assumptions

If the answer is just a generic list of cloud savings tips, give the skill more environment detail.

cost-optimization skill FAQ

Is this cost-optimization skill beginner friendly

Yes, if you already know your cloud estate at a basic level. The framework is easy to follow, but the output quality depends on whether you can provide spend, ownership, and utilization context. Beginners can still use it for guided reviews and to learn the main optimization levers.

Is it better than an ordinary prompt

Usually yes for structured analysis. The skill gives the agent a better mental model than a blank prompt, especially around sequencing: visibility before governance, governance before pricing decisions, and pricing before deeper architecture changes.

Does it automate cloud changes

No. Based on the repository evidence, this is a guidance skill, not an automation tool. It helps an agent reason about optimization strategy and recommendations. You still need provider tooling and team review to implement changes.

Which cloud providers does it fit

The skill explicitly covers:

• AWS
• Azure
• GCP
• OCI

That makes it useful for both single-cloud and multi-cloud discussions, though highly provider-specific implementation details may still require follow-up prompts.

When should I not use cost-optimization

Skip this skill if your need is:

• exact invoice reconciliation
• detailed billing export parsing
• policy-as-code enforcement
• direct remediation scripts
• provider-specific implementation depth with no strategic analysis

In those cases, use provider-native billing tools or a more operationally specialized skill.

Can I use it for ongoing governance, not just one-off savings

Yes. The tagging standards reference makes the skill useful for setting up repeatable cost controls, especially around ownership, chargeback, and reporting discipline. It is a good fit when you want cost reviews to become part of normal platform operations.

How to Improve cost-optimization skill

Give the skill real spend and usage evidence

The fastest way to improve cost-optimization usage is to provide real signals:

• top 10 cost drivers
• underutilized resources
• storage growth
• idle environments
• current commitment coverage
• tagging gaps

The skill is only as specific as the evidence you provide.

Separate quick wins from structural fixes

Ask the agent to split recommendations into:

• immediate cleanup
• pricing/commitment changes
• architecture improvements
• governance improvements

This matters because these categories have different risk and time horizons. Mixing them together leads to weak prioritization.

Be explicit about what cannot change

Common failure mode: the first output suggests actions that hurt reliability or performance. Prevent that by stating hard constraints:

• no latency regression
• no reduction in HA posture
• no changes during freeze windows
• no long-term commitments for unstable workloads

This is especially important when using cost-optimization for Performance Optimization.

Improve tagging before asking for precision

If your cloud environment has inconsistent or missing tags, ask the skill to solve that first. The reference file makes clear that ownership and cost attribution are foundational. Better tagging improves every later recommendation, from dashboards to cleanup targeting.

Ask for ranked recommendations, not idea dumps

Use prompts like:

Rank actions by savings potential, confidence, effort, and operational risk.

That simple instruction usually improves output quality more than asking for “more detail.” It forces decision-ready recommendations instead of a broad brainstorm.

Request assumptions and missing data

A strong follow-up is:

List the assumptions behind each recommendation and what additional data would confirm or reject it.

This helps you distinguish:

• likely wins
• speculative suggestions
• items blocked by poor observability

Iterate by service, not by the whole estate

If the first pass is too broad, narrow the next prompt to one area:

• EC2 / VM fleets
• databases
• object storage
• Kubernetes
• data transfer
• non-production environments

The cost-optimization skill is more useful when focused on a clear cost domain instead of trying to optimize everything at once.

Compare current state to target operating model

Ask the skill to evaluate both:

• what should be cut now
• what governance process should exist going forward

Example:
Use the cost-optimization skill to identify immediate savings and propose a quarterly cost review process with tagging enforcement, budget alerts, and ownership reporting.

This turns the skill from a one-time advisor into a better operating model designer.

Watch for common low-quality outputs

Refine the prompt if the response:

• recommends commitments without utilization history
• suggests deleting resources without owner validation
• ignores tagging and visibility gaps
• treats dev and production the same
• focuses only on compute while missing storage or transfer costs

These are signs the model needs better context or tighter scope.

Use repository context, then add your environment

Start with the repository’s framework and tagging standard, then layer in your actual estate. That is the best way to get value from the cost-optimization skill: use the built-in structure as the analysis lens, but make your prompts specific enough that the recommendations become actionable.