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feat: enhance SurfSense with new skills, blog section, and improve SEO metadata
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- Added multiple new skills to skills-lock.json from the repository `aaron-he-zhu/seo-geo-claude-skills`. - Introduced `fuzzy-search` dependency in package.json for improved search functionality. - Updated pnpm-lock.yaml to include the new `fuzzy-search` package. - Enhanced SEO metadata across various pages, including canonical links and descriptions for better search visibility. - Improved layout and structure of several components, including the homepage and changelog, to enhance user experience.
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# Knowledge Panel & Wikidata Optimization Guide
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Detailed instructions for Knowledge Panel optimization, Wikidata entry management, and AI entity resolution.
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## Knowledge Panel Optimization
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### Claiming and Editing
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1. **Google Knowledge Panel**: Claim via Google's verification process (search for entity -> click "Claim this knowledge panel")
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2. **Bing Knowledge Panel**: Driven by Wikidata and LinkedIn -- update those sources
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3. **AI Knowledge**: Driven by training data -- ensure authoritative sources describe entity correctly
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### Common Knowledge Panel Issues
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| Issue | Root Cause | Fix |
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|-------|-----------|-----|
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| No panel appears | Entity not in Knowledge Graph | Build Wikidata entry + structured data + authoritative mentions |
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| Wrong image | Image sourced from incorrect page | Update Wikidata image; ensure preferred image on About page and social profiles |
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| Wrong description | Description pulled from wrong source | Edit Wikidata description; ensure About page has clear entity description in first paragraph |
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| Missing attributes | Incomplete structured data | Add properties to Schema.org markup and Wikidata entry |
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| Wrong entity shown | Disambiguation failure | Strengthen unique signals; add qualifiers; resolve Wikidata disambiguation |
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| Outdated info | Source data not updated | Update Wikidata, About page, and all profile pages |
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## Wikidata Best Practices
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### Creating a Wikidata Entry
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1. **Check notability**: Entity must have at least one authoritative reference
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2. **Create item**: Add label, description, and aliases in relevant languages
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3. **Add statements**: instance of, official website, social media links, founding date, founders, industry
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4. **Add identifiers**: official website (P856), social media IDs, CrunchBase ID, ISNI, VIAF
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5. **Add references**: Every statement should have a reference to an authoritative source
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**Important**: Wikipedia's Conflict of Interest (COI) policy prohibits individuals and organizations from creating or editing articles about themselves. Instead of directly editing Wikipedia: (1) Focus on building notability through independent reliable sources (press coverage, industry publications, academic citations); (2) If you believe a Wikipedia article is warranted, consider engaging an independent Wikipedia editor through the Requested Articles process; (3) Ensure all claims about the entity are verifiable through third-party sources before any Wikipedia involvement.
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### Key Wikidata Properties by Entity Type
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| Property | Code | Person | Org | Brand | Product |
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|----------|------|:------:|:---:|:-----:|:-------:|
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| instance of | P31 | human | organization type | brand | product type |
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| official website | P856 | yes | yes | yes | yes |
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| occupation / industry | P106/P452 | yes | yes | -- | -- |
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| founded by | P112 | -- | yes | yes | -- |
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| inception | P571 | -- | yes | yes | yes |
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| country | P17 | yes | yes | -- | -- |
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| social media | various | yes | yes | yes | yes |
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| employer | P108 | yes | -- | -- | -- |
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| developer | P178 | -- | -- | -- | yes |
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## AI Entity Optimization
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### How AI Systems Resolve Entities
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```
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User query -> Entity extraction -> Entity resolution -> Knowledge retrieval -> Answer generation
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```
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AI systems follow this pipeline:
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1. **Extract** entity mentions from the query
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2. **Resolve** each mention to a known entity (or fail -> "I'm not sure")
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3. **Retrieve** associated knowledge about the entity
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4. **Generate** response citing sources that confirmed the entity's attributes
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### Signals AI Systems Use for Entity Resolution
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| Signal Type | What AI Checks | How to Optimize |
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|-------------|---------------|-----------------|
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| **Training data presence** | Was entity in pre-training corpus? | Get mentioned in high-quality, widely-crawled sources |
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| **Retrieval augmentation** | Does entity appear in live search results? | Strong SEO presence for branded queries |
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| **Structured data** | Can entity be matched to Knowledge Graph? | Complete Wikidata + Schema.org |
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| **Contextual co-occurrence** | What topics/entities appear alongside? | Build consistent topic associations across content |
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| **Source authority** | Are sources about entity trustworthy? | Get mentioned by authoritative, well-known sources |
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| **Recency** | Is information current? | Keep all entity profiles and content updated |
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### Entity-Specific GEO Tactics
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1. **Define clearly**: First paragraph of About page and key pages should define the entity in a way AI can quote directly
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2. **Be consistent**: Use identical entity description across all platforms
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3. **Build associations**: Create content that explicitly connects entity to target topics
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4. **Earn mentions**: Third-party authoritative mentions are stronger entity signals than self-description
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5. **Stay current**: Outdated entity information causes AI to lose confidence and stop citing
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