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Infrastructure · Version 1.1.0 · Reviewed 2026-08-02

Infrastructure Drift Detector

Review and harden drift detection and change attribution with evidence, explicit trade-offs, and a verification plan.

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

Finds and classifies drift between declared and live infrastructure, and decides what to reconcile.

₹99 one-time

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What this skill helps you do

  • Drift detection
  • Change attribution
  • Reconciliation policy

How Infrastructure Drift Detector works

You provide

Manifests, plans, and current runtime topology

It inspects

Reversibility and blast radius for drift detection

It decides

A change attribution change staged by risk

You verify

Platform-native health check after each stage

What it checks first

Infrastructure Drift Detector finds and classifies drift between declared and live infrastructure, and decides what to reconcile. Use it when the work involves Drift detection, Change attribution, Reconciliation policy.

  1. Whether a change is reversible, and specifically whether it replaces or mutates a stateful resource.
  2. Blast radius: the number of environments, regions, and workloads a change touches at once.
  3. Identity and permission scope of the executing principal.
  4. Drift between declared and actual state.

Failure modes it recognizes

  • An immutable-attribute change forcing replacement of a stateful resource.
  • A change applied to all environments simultaneously with no canary.
  • Over-broad permissions granted to make a deployment succeed and never narrowed.
  • Manual changes creating drift that the next apply silently reverts.

Answers it will reject

  • Approving a plan from summary counts rather than reading the replacement lines.
  • Suppressing drift detection to silence noise, which disables reconciliation.
  • Granting administrative rights as a debugging shortcut.

Decision rules it applies

  • Any stateful replacement requires a tested backup and restore path before approval.
  • Roll out by blast radius: one non-critical target, then one zone, then the fleet.
  • Grant the narrowest permission that completes the task, with an expiry.

Evidence it asks for

  • Diff the plan in machine-readable form and classify every action.
  • Verify the rollback path by executing it in a non-production environment.
  • Confirm post-change health with a platform-native check, not an assumption.

The method inside

  1. Establish what is actually true about drift detection from the supplied evidence, and mark what is missing.
  2. Identify the mechanism behind change attribution rather than restating the symptom.
  3. Choose the smallest defensible change for reconciliation policy, weighing impact, confidence, effort, and reversibility.
  4. Verify with platform-native checks

Deliverables

  • Drift detection assessment
  • Change attribution decision and action plan
  • Reconciliation policy verification checklist

Evidence requirements

  • Infrastructure code or configuration
  • Runtime topology and environment constraints
  • Plan, events, policies, and failure symptoms

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 Terraform plan always shows changes we did not make and the team has started ignoring the output.

Expected output

An ignored plan is worse than no plan, because real changes now hide in the noise. Classify each drift by owner: controller-managed fields should be ignored precisely, manual changes should be imported or reverted, and provider defaults should be pinned...

Boundaries and compatibility

Ideal for

  • Drift detection: produce a decision or artifact grounded in supplied evidence.
  • Change attribution: produce a decision or artifact grounded in supplied evidence.
  • Reconciliation policy: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Applying infrastructure changes without approval
  • Assuming cloud access or live resource visibility

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.