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Maintenance · Version 1.3.0 · Reviewed 2026-08-02

Deprecation Debt Tracker

Reduce change risk for deprecated surface inventory and consumer telemetry with evidence, explicit trade-offs, and a verification plan.

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

Finds deprecated APIs, flags, schemas, endpoints, and compatibility shims, then turns them into telemetry-backed removal plans.

₹99 one-time

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What this skill helps you do

  • Deprecated surface inventory
  • Consumer telemetry
  • Removal sequencing

How Deprecation Debt Tracker works

You provide

Current state, consumer inventory, and target state

It inspects

Coexistence and rollback viability for deprecated surface inventory

It decides

A consumer telemetry sequence in reversible increments

You verify

Shadow comparison reports divergence rather than assuming zero

What it checks first

Deprecation Debt Tracker finds deprecated APIs, flags, schemas, endpoints, and compatibility shims, then turns them into telemetry-backed removal plans. Use it when the work involves Deprecated surface inventory, Consumer telemetry, Removal sequencing.

  1. Whether the old and new paths can coexist, which determines if incremental migration is possible at all.
  2. The true consumer inventory, including internal jobs, scripts, and integrations not visible in the main codebase.
  3. Data volume and the time the migration takes at production scale, not sample scale.
  4. Whether the change is backward compatible for data written by the previous version during rollout.
  5. The rollback path, and specifically whether it remains available after the first irreversible step.

Failure modes it recognizes

  • A migration validated on a sample that takes hours on production volume and holds a lock throughout.
  • Dual-write divergence where one write succeeds and the other fails, with no reconciliation.
  • A backfill that races with live writes and overwrites newer values with older ones.
  • Removing the old path before all consumers migrated, discovered by a quarterly batch job weeks later.
  • A schema change that is forward compatible but not backward compatible, blocking rollback.
  • Enum or type widening that older readers cannot parse, breaking during a partial rollout.

Answers it will reject

  • A big-bang cutover with a maintenance window, which concentrates all risk into one unrehearsed moment.
  • Migrating and refactoring simultaneously, which makes failures impossible to attribute.
  • Treating the migration as done at cutover rather than after the old path is removed and verified unused.
  • Skipping the shadow-read comparison because the new implementation "obviously" matches.

Decision rules it applies

  • Use expand-migrate-contract: add the new shape, write both, migrate readers, then remove the old shape.
  • Every increment must be independently verifiable and independently revertible.
  • Keep the old path observable until traffic proves equivalence; remove it only on evidence of zero use.
  • Prefer additive schema changes; a removal is a separate, later, deliberately scheduled change.

Evidence it asks for

  • Run shadow reads comparing old and new outputs, and report the divergence rate rather than assuming zero.
  • Instrument usage of the deprecated path with a caller identifier so removal can be proven safe.
  • Rehearse the migration on a production-sized copy and record the actual duration and lock behavior.

The method inside

  1. Establish what is actually true about deprecated surface inventory from the supplied evidence, and mark what is missing.
  2. Identify the mechanism behind consumer telemetry rather than restating the symptom.
  3. Choose the smallest defensible change for removal sequencing, weighing impact, confidence, effort, and reversibility.
  4. Define rollback and post-upgrade observation

Deliverables

  • Deprecated surface inventory assessment
  • Consumer telemetry decision and action plan
  • Removal sequencing verification checklist

Evidence requirements

  • Current and target versions
  • Dependency graph and changelogs
  • Tests, compatibility constraints, and rollout environment

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

Find everything preventing removal of our v1 API and create a plan that avoids breaking unknown consumers.

Expected output

Inventory runtime calls, generated clients, documentation, flags, and internal compatibility adapters. Add version telemetry before setting dates, then remove by consumer cohort with an explicit exception and escalation process...

Boundaries and compatibility

Ideal for

  • Deprecated surface inventory: produce a decision or artifact grounded in supplied evidence.
  • Consumer telemetry: produce a decision or artifact grounded in supplied evidence.
  • Removal sequencing: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Blindly upgrading across multiple major versions
  • Assuming semantic versioning guarantees compatibility

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.