---
name: consistency-audit
description: "Whether a message architecture's pillars are actually being said the same way across reps and channels weeks after it was written — the sustainment audit's shape, applied to messaging instead of a kaizen event. Use when: A message architecture has been live long enough to check whether reps and channels are actually still using it consistently, not just whether it was written. You want to catch message drift — a claim getting ahead of its actual proof, or each channel restating a number differently — before it becomes the norm. You want to close a gap the message architecture itself flagged when it was first built (a pillar deliberately held back as unproven). Not for: The message architecture was just published — give it real time in market before auditing it."
---
<!-- Auto-generated from content/templates.ts by scripts/generate-skills.ts -- do not edit this file directly. Edit the kata's guide content and regenerate. -->

# Consistency audit

Whether a message architecture's pillars are actually being said the same way across reps and channels weeks after it was written — the sustainment audit's shape, applied to messaging instead of a kaizen event.

Family: Standard work · Format: .xlsx · Domain: commercial

## What it is

A message architecture written once and never checked again drifts, the same way any standard does — a rep rounds a number up, marketing gets ahead of the evidence, an unproven pillar quietly becomes a headline claim. This audit is the sustainment audit's exact shape, applied to a message architecture: restate what it was supposed to ensure, get a checklist of specific, verifiable practices, and see honestly which are still holding.

## When to use it

Use it when:

- A message architecture has been live long enough to check whether reps and channels are actually still using it consistently, not just whether it was written.
- You want to catch message drift — a claim getting ahead of its actual proof, or each channel restating a number differently — before it becomes the norm.
- You want to close a gap the message architecture itself flagged when it was first built (a pillar deliberately held back as unproven).

Not when:

- The message architecture was just published — give it real time in market before auditing it.

## How to fill it in

- **originalObjective** — What was the message architecture supposed to ensure — which pillars, in what language?
- **checks** — Drafted from what the message architecture was supposed to ensure — verify what's actually still holding across reps and channels.
- **narrative** — Drafted from the checklist actually built.

## What good looks like

The example below audits the Beacon Analytics message architecture sixty days after it was published — including whether the pillar it deliberately held back as unproven has stayed out of real marketing claims, and finding a real drift where it hasn't.

Full worked example, on-screen and as a downloadable .xlsx: https://www.katafacts.com/katas/consistency-audit

## Common mistakes

- **Auditing a message architecture that was never actually rolled out to reps or channels.** — This audit checks whether real usage has drifted from a real standard — there's nothing to check if the message was never actually put into use.
- **Marking a practice as holding without actually checking the live sales deck, site copy, or a real call.** — The audit only has value if it reflects what's actually being said, not a hopeful assumption that the message architecture is being followed.

## What it connects to

Upstream:

- **Message architecture** (`message-architecture`) — The architecture's own pillars and proof points are exactly what this audit checks against reality — including whether an unproven pillar has quietly crept into claims anyway.

## Where AI helps

Judgement — stays with you:

- Deciding how much time to give a message architecture in market before auditing it
- Deciding what to do about a pillar that's drifted from its proven language

Analysis — AI helps:

- Drafting specific, verifiable checks from a description of what the message architecture was supposed to ensure
- Drafting the narrative from the checklist actually built

Drudgery — automated:

- Tallying how many practices are still holding
- Identifying which practices are at risk
- Exporting to xlsx in the house format

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Consistency audit is licensed [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Attribution: Katafacts (katafacts.com).

## Using this skill

Apply this method as part of whatever broader task, instructions, or deliverable you're already working on -- it's a method to use, not a standalone conversation to start. There is no generation tool for this catalogue yet, so draft the artifact's actual content yourself, following the fields above, the same way a person filling this out by hand would. The canonical guide page and a downloadable worked example (.xlsx) are at https://www.katafacts.com/katas/consistency-audit.
