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Entity consistency check

Models build a picture of an entity from every mention across the web, not from your homepage. Inconsistent naming, stale descriptions on third-party profiles and contradictory claims produce a confused or wrong answer. This skill finds the contradictions feeding it.

CATEGORY
AI search (GEO)
FORMAT
entity-consistency-check.md
STEPS
6
PRICE
Free - no account
WHEN TO REACH FOR THIS

Use when assistants describe your company inaccurately, conflate you with another brand, or state an outdated fact about you.

The skill file

entity-consistency-check.md 
---
name: entity-consistency-check
description: Use when assistants describe your company inaccurately, conflate you with another brand, or state an outdated fact about you.
---

# Entity consistency check

Models build a picture of an entity from every mention across the web, not from your homepage. Inconsistent naming, stale descriptions on third-party profiles and contradictory claims produce a confused or wrong answer. This skill finds the contradictions feeding it.

## What you need first

- Every profile that describes you: directories, review sites, social bios, press pages
- Your own about and organization markup

## Method

1. Write the canonical facts once: legal name, trading name, one-sentence description, founding year, location, category.
2. Collect how each third-party source currently states each fact. Directory profiles created years ago are the usual source of stale claims.
3. Flag every contradiction, particularly category and description - being listed as one kind of tool in three places and another elsewhere is what produces vague answers.
4. Fix the sources you control first, then request corrections on the ones you do not, starting with the sources an assistant is most likely to have ingested.
5. Publish Organization structured data carrying the canonical facts and sameAs links to every profile you claim, so the graph is explicit rather than inferred.
6. Re-ask the assistants a month later and check whether the description has converged.

## What this produces

A fact-by-source matrix with contradictions marked, a correction queue ordered by source weight, and Organization markup that states the canonical version.

## Where this goes wrong

- Correcting your own site while leaving stale directory profiles that carry more weight
- Using several trading names inconsistently, which splits the entity
- Expecting immediate change - ingestion lags by weeks or months

---

From the QuQi skill library - https://www.quqi.io/skills/entity-consistency-check
Free to download · no account, no email

What you need first

  • Every profile that describes you: directories, review sites, social bios, press pages
  • Your own about and organization markup

Method

  1. 01 Write the canonical facts once: legal name, trading name, one-sentence description, founding year, location, category.
  2. 02 Collect how each third-party source currently states each fact. Directory profiles created years ago are the usual source of stale claims.
  3. 03 Flag every contradiction, particularly category and description - being listed as one kind of tool in three places and another elsewhere is what produces vague answers.
  4. 04 Fix the sources you control first, then request corrections on the ones you do not, starting with the sources an assistant is most likely to have ingested.
  5. 05 Publish Organization structured data carrying the canonical facts and sameAs links to every profile you claim, so the graph is explicit rather than inferred.
  6. 06 Re-ask the assistants a month later and check whether the description has converged.

What this produces

A fact-by-source matrix with contradictions marked, a correction queue ordered by source weight, and Organization markup that states the canonical version.

Where this goes wrong

  • Correcting your own site while leaving stale directory profiles that carry more weight
  • Using several trading names inconsistently, which splits the entity
  • Expecting immediate change - ingestion lags by weeks or months

Use this skill in your own AI

The download is a plain markdown file with the name and trigger in its frontmatter. Where an assistant supports skills it can load itself, that frontmatter is what it reads to decide this one applies.

Claude Code Save it as ~/.claude/skills/entity-consistency-check/SKILL.md and Claude loads it on its own when what you are doing matches the trigger line. Put it in .claude/skills inside a project instead if the whole team should have it.
Claude Upload the file in the skills section of your settings. Once it is there it applies itself in any conversation where the trigger fits, so you do not have to remember it exists.
ChatGPT There is no skills format to install into, so paste the file contents into a Project instruction or a Custom GPT instead. It then applies to every chat in that project rather than only the one you paste it into.
Anything else Paste the markdown into the chat before your question. It works in any assistant, it just has to be pasted again each time.

Questions about this skill

When is this the right fix rather than rewriting my about page?

When assistants describe you inaccurately, confuse you with another brand, or repeat a fact that stopped being true. Rewriting your own copy is the instinct, but models build the picture from every mention across the web, and a directory profile written four years ago can outweigh your homepage. The work is finding the contradictions, not polishing your own text.

What do I need in hand before starting?

The canonical facts written down once: legal name, trading name, one-sentence description, founding year, location, category. Then every profile that describes you, from directories to review sites, social bios and press pages. Skip the canonical list and you correct each source toward a slightly different version of the truth, leaving the entity as split as it was.

What do I end up with?

A fact-by-source matrix with contradictions marked, a correction queue ordered by how much weight each source carries, and Organization markup stating the canonical version with sameAs links to the profiles you claim. The queue is the working part. The matrix mostly serves to show that category and description, not name, are where the disagreement usually sits.

What ruins this most often?

Fixing your own site and stopping there, while the stale directory profiles that caused the wrong answer stay live. The other cost is impatience: ingestion lags by weeks or months, so re-asking the assistants the following week and seeing nothing tempts teams into abandoning a correction that was quietly working.

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