entity-optimizer

name	entity-optimizer
description	Build entity presence in Knowledge Graph, Wikidata, AI systems for brand recognition and citations. 实体优化/知识图谱
version	9.0.0
license	Apache-2.0
compatibility	Claude Code, skills.sh, ClawHub, Vercel Labs, Cursor, Windsurf, Codex CLI, Amp, Gemini CLI, Kimi Code, Qwen Code, CodeBuddy
homepage	https://github.com/aaron-he-zhu/seo-geo-claude-skills
when_to_use	Use when optimizing entity presence for Knowledge Graph, Wikidata, or AI engine disambiguation. Also for brand entity canonicalization.
argument-hint	<entity name or brand>
metadata	{"author":"aaron-he-zhu","version":"9.0.0","geo-relevance":"high","tags":["seo","geo","entity-optimization","knowledge-graph","knowledge-panel","brand-entity","wikidata","entity-disambiguation","实体优化","エンティティ","엔티티","entidad-seo"],"triggers":["optimize entity presence","build knowledge graph","entity audit","establish brand entity","entity disambiguation","Google doesn't know my brand","no knowledge panel","establish my brand as an entity","get a Google knowledge card","how to get a knowledge panel","how to build brand entity","实体优化","知识图谱","品牌实体","知识面板","品牌词","品牌词优化","品牌搜不到","没有知识面板","Google不认识我的品牌","エンティティ最適化","ナレッジパネル","엔티티 최적화","지식 패널","구글이 내 브랜드 모르는데?","지식 패널 만들려면?","optimización de entidad","panel de conocimiento","otimização de entidade"]}

Entity Optimizer

Audits, builds, and maintains entity identity across search engines and AI systems. Entities — the people, organizations, products, and concepts that search engines and AI systems recognize as distinct things — are the foundation of how both Google and LLMs decide what a brand is and whether to cite it.

Why entities matter for SEO + GEO:

• SEO: Google's Knowledge Graph powers Knowledge Panels, rich results, and entity-based ranking signals. A well-defined entity earns SERP real estate.
• GEO: AI systems resolve queries to entities before generating answers. If an AI cannot identify an entity, it cannot cite it — no matter how good the content is.

What This Skill Does

Audits entity presence across Knowledge Graph, Wikidata, Wikipedia, and AI systems; maps all 6 signal categories (47 signals); produces a gap analysis, building plan, and disambiguation strategy.

Quick Start

Start with one of these prompts. Finish with a canonical entity profile and a handoff summary using the repository format in Skill Contract.

Entity Audit

Audit entity presence for [brand/person/organization]

How well do search engines and AI systems recognize [entity name]?

Build Entity Presence

Build entity presence for [new brand] in the [industry] space

Establish [person name] as a recognized expert in [topic]

Fix Entity Issues

My Knowledge Panel shows incorrect information — fix entity signals for [entity]

AI systems confuse [my entity] with [other entity] — help me disambiguate

Skill Contract

Expected output: an entity audit, a canonical entity profile, and a short handoff summary ready for memory/entities/.

• Reads: the entity name, primary domain, known profiles, topic associations, and prior brand context from CLAUDE.md and the shared State Model when available.
• Writes: a user-facing entity report plus a reusable profile that can be stored under memory/entities/.
• : canonical names, sameAs links, disambiguation notes, and entity gaps to , , and .