Extract and normalize structured data from web content.
npx skills add https://github.com/tiween/tiween --skill data-extractor-tiween
Please help me install this Agent Skill. Skill: data-extractor Source: https://github.com/tiween/tiween/tree/main/.claude/skills/data-extractor Command: npx skills add https://github.com/tiween/tiween --skill data-extractor-tiween
Extracting valuable structured information from raw web content is time-consuming and error-prone. This skill solves this by intelligently extracting and enhancing data, making it easier to analyze and utilize.
Run the 'data-extractor' skill on your crawled data file 'enhance-plays.json'.
High-intent search queries and answers about installing and using this skill.
To extract structured data from raw web content, you need a tool that automates intelligent parsing and format normalization. This skill processes raw crawled files to identify roles, clean names, and structure information for easier analysis.
You can normalize formats and identify roles in partially parsed web data by applying AI-assisted text analysis rules. The tool enhances existing extracted information by applying specific patterns and name cleaning rules to refine the output.
Yes, you can use this skill to enhance data from web crawlers for cultural content. It is specifically designed to process partially parsed files, such as those containing details about Tunisian plays, by extracting and enriching the information.
To run the data-extractor skill, you need a crawled data file like 'enhance-plays.json' and must define specific patterns and name cleaning rules. These prerequisites ensure the text analysis accurately extracts and normalizes the target information.
Yes, this skill works without external dependencies, relying entirely on its internal scripts to perform data extraction. You only need to provide the target raw web content file and the required extraction patterns to begin processing.
The best way to clean and structure partially parsed web data is through AI-assisted parsing that applies specific name cleaning rules. This approach automates format normalization and role identification, transforming raw crawled content into structured, usable information.
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