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entity-audit

Audit brand entity facts AI engines trust: Wikidata, Knowledge Panel. "is our Knowledge Panel accurate"

plugins/indranilbanerjee/digital-marketing-pro/skills/entity-audit/SKILL.md

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# /digital-marketing-pro:entity-audit

> **Script location.** If your host does not set `${CLAUDE_PLUGIN_ROOT}`, the scripts are in this plugin's `scripts/` folder, next to `skills/`. Run them with Python 3.10 or newer: `python`, or `python3` where `python` is not found (macOS, many Linux systems).

## Purpose

Audit brand entity data consistency across the platforms that AI engines use as knowledge sources. Check Wikidata entries, Google Knowledge Panel accuracy, Wikipedia presence and notability, and industry directory listings for consistency. Inconsistent entity data degrades AI engine trust and visibility — when knowledge sources disagree about basic facts like the official website, founding date, headquarters location, or industry classification, AI engines either omit the brand entirely or present conflicting information. This command provides a systematic, platform-by-platform audit with specific discrepancies flagged and a prioritized fix plan ordered by impact on AI visibility.

## Input Required

The user must provide (or will be prompted for):

- **Brand/entity name**: The exact name of the brand, organization, person, or product to audit — must match the entity as it should appear in knowledge sources. If the brand has known aliases or former names, include those for cross-referencing
- **Entity type**: `Organization`, `Person`, `Product`, or `Brand` — determines which properties are checked and which directory types are relevant. Organizations check founding date, headquarters, industry; Products check manufacturer, launch date, category; Persons check role, affiliation, notable works