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FinOps · Version 1.6.0 · Reviewed 2026-08-02

File Storage Lifecycle Advisor

Reduce waste without harming reliability in class selection and lifecycle rules with evidence, explicit trade-offs, and a verification plan.

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

Designs storage classes, lifecycle transitions, and deletion so object storage cost tracks value.

₹99 one-time

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What this skill helps you do

  • Class selection
  • Lifecycle rules
  • Deletion safety

How File Storage Lifecycle Advisor works

You provide

Cost breakdown by tag, utilization data, and growth trend

It inspects

Unit cost and idle capacity behind class selection

It decides

A lifecycle rules action with a reliability guardrail

You verify

Cost per unit of business work tracked after the change

What it checks first

File Storage Lifecycle Advisor designs storage classes, lifecycle transitions, and deletion so object storage cost tracks value. Use it when the work involves Class selection, Lifecycle rules, Deletion safety.

  1. Unit cost per business transaction rather than total spend, since total rises with healthy growth.
  2. The split between compute, storage, network egress, and managed-service premiums.
  3. Idle versus utilized capacity, which separates a sizing problem from an architecture problem.
  4. Whether cost scales with traffic, with data retained, or simply with elapsed time.

Failure modes it recognizes

  • Storage growing indefinitely because nothing was ever given a lifecycle or expiry policy.
  • Cross-zone traffic billed in both directions between services that could have been zone-aligned.
  • Orphaned resources such as unattached volumes, idle load balancers, and old snapshots with no owner.
  • Log and metric retention growing until observability costs exceed the workload it observes.
  • Reserved capacity committed before the workload shape was stable.

Answers it will reject

  • Cutting redundancy to save money, which trades a predictable bill for an unpredictable outage.
  • Optimizing the largest line item when a smaller one has worse unit economics and faster growth.
  • 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, because waste compounds and discounts do not.
  • Every cost reduction states its reliability guardrail and how a regression would be detected.

Evidence it asks for

  • Break cost down by tag and service, and report cost per thousand units of business work.
  • Compare requested against used resources over a full business cycle.
  • Track the trend of unit cost, since flat unit cost during growth is the success condition.

The method inside

  1. Map the artifact, actors, boundaries, and invariants relevant to class selection.
  2. Trace concrete failure or abuse paths for lifecycle rules; do not report checklist items without a mechanism.
  3. Prioritize deletion safety 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

  • Class selection assessment
  • Lifecycle rules decision and action plan
  • Deletion safety 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

Our object storage bill grows every month and we have never deleted anything since launch.

Expected output

Never deleting means you pay indefinitely for objects nobody reads. Analyze access age distribution, transition cold objects to cheaper classes automatically, and set expiry on genuinely disposable classes such as temporary exports and old logs...

Boundaries and compatibility

Ideal for

  • Class selection: produce a decision or artifact grounded in supplied evidence.
  • Lifecycle rules: produce a decision or artifact grounded in supplied evidence.
  • Deletion safety: 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.