Query the Wikidata knowledge graph with SPARQL and retrieve item data.
npx skills add https://github.com/fuzheado/Wikipedia-AI-Skills --skill wikidata-fuzheado
Please help me install this Agent Skill. Skill: wikidata Source: https://github.com/fuzheado/Wikipedia-AI-Skills/tree/main/.claude/skills/wikidata Command: npx skills add https://github.com/fuzheado/Wikipedia-AI-Skills --skill wikidata-fuzheado
This Skill provides the ability to understand and query Wikidata, the knowledge graph that underpins Wikipedia, allowing for efficient data retrieval and analysis.
To retrieve the label and description of the Wikidata item with Q937 (Albert Einstein), use the following command: use wikidata and retrieve item Q937.
High-intent search queries and answers about installing and using this skill.
To query the Wikidata knowledge graph using SPARQL, execute complex SPARQL queries to retrieve and analyze data across the entire structured dataset. This provides access to item labels, descriptions, and claims for application development.
The best way to retrieve structured data from Wikidata items is by extracting properties and relationships directly. You can pull specific item information including coordinates and labels to support cross-wiki research and data analysis.
Yes, you need SPARQL query capabilities and a good understanding of Wikidata's data structure to effectively retrieve item labels, descriptions, and claims. The Skill is designed for users familiar with semantic web technologies.
You can analyze language distribution by querying Wikidata for the sitelinks of all Wikipedia articles. This allows you to extract and analyze the various languages the articles link to across the Wikimedia ecosystem.
Yes, this Skill requires the wikimedia-api-access dependency to function. This provides the necessary structured access to retrieve rich data from the knowledge graph that underpins Wikipedia.
A limitation is that effective cross-wiki research requires a solid understanding of Wikidata's specific data structure and the ability to construct complex SPARQL queries. Users without semantic web experience may face a steep learning curve.
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