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FinOps · Version 1.2.0 · Reviewed 2026-08-02

Cost-Aware Architecture Reviewer

Reduce waste without harming reliability in cost curve analysis and scaling economics with evidence, explicit trade-offs, and a verification plan.

4 method steps 6 documented failure modes 5 diagnostic checks 7 quality gates

Reviews architecture decisions for the cost curve they create as usage grows.

₹99 one-time

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What this skill helps you do

  • Cost curve analysis
  • Scaling economics
  • Trade-off framing

How Cost-Aware Architecture Reviewer works

You provide

Cost breakdown by tag, usage data, and growth trend

It inspects

Unit cost and idle capacity behind cost curve analysis

It decides

A scaling economics action with a reliability guardrail

You verify

Cost per thousand requests tracked after the change

What it checks first

Cost-Aware Architecture Reviewer reviews architecture decisions for the cost curve they create as usage grows. Use it when the work involves Cost curve analysis, Scaling economics, Trade-off framing.

  1. Unit cost per business transaction rather than total spend, because total spend rises with healthy growth.
  2. The split between compute, storage, network egress, and managed-service premiums.
  3. Idle versus utilized capacity, which distinguishes a sizing problem from an architecture problem.
  4. Whether cost scales with traffic, with data retained, or with time — each has a different lever.
  5. Cross-zone and cross-region traffic, which is frequently the largest unattributed line item.

Failure modes it recognizes

  • Over-provisioned requests in a scheduler reserving capacity that is never used but is fully billed.
  • Log and metric retention growing without a policy until observability costs exceed the workload.
  • Cross-AZ chatter between services that could be zone-aligned, billed per gigabyte in both directions.
  • Orphaned resources — unattached volumes, idle load balancers, old snapshots — with no owner.
  • A development environment running production-sized infrastructure continuously.
  • Data egress from object storage to the internet where a CDN would serve the same bytes far cheaper.

Answers it will reject

  • Cutting cost by reducing redundancy, which trades a predictable bill for an unpredictable outage.
  • Optimizing the largest line item when a smaller one has the worse unit economics and faster growth.
  • Committing to reserved capacity before the workload shape is stable.
  • Reporting savings without a reliability guardrail, so a regression is discovered by customers.

Decision rules it applies

  • Attribute cost to a team or product before optimizing; unattributed cost never gets reduced.
  • Prefer eliminating waste over renegotiating price — waste compounds and discounts do not.
  • Any cost reduction must state its reliability and performance guardrail and how a regression is detected.
  • Rightsize using p95 utilization over a full business cycle, not a single day.

Evidence it asks for

  • Break cost down by tag, namespace, and service, and report cost per thousand requests.
  • Compare requested versus used resources over a representative window.
  • Track the trend of unit cost, since a flat unit cost during growth is success.

The method inside

  1. Map the artifact, actors, boundaries, and invariants relevant to cost curve analysis.
  2. Trace concrete failure or abuse paths for scaling economics; do not report checklist items without a mechanism.
  3. Prioritize trade-off framing findings by impact, likelihood, confidence, and cost of correction.
  4. Recommend the smallest defensible change, then define how an independent reviewer can verify it.

Deliverables

  • Cost curve analysis assessment
  • Scaling economics decision and action plan
  • Trade-off framing verification checklist

Evidence requirements

  • Itemized cost and usage data
  • Traffic, utilization, growth, and commitments
  • SLOs, architecture, and unit economics

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Review this design for cost. It uses managed services heavily to reduce operational burden.

Expected output

Managed services trade a flat operational cost for a variable usage cost, so the question is where the curves cross at your projected volume. The item to examine here is per-request pricing on the hot path, which is cheap at current volume and dominant at 10x...

Boundaries and compatibility

Ideal for

  • Cost curve analysis: produce a decision or artifact grounded in supplied evidence.
  • Scaling economics: produce a decision or artifact grounded in supplied evidence.
  • Trade-off framing: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Cutting redundancy without an SLO decision
  • Presenting list prices as realized savings

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.