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Generate materials for card sorting studies. Creates detailed lists of content items (cards) for user research and information architecture validation.
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SOC 職業分類に基づく
| name | card-sorting-generate |
| description | Generate materials for card sorting studies. Creates detailed lists of content items (cards) for user research and information architecture validation. |
| required_roles | {"scribe":"roles/scribe.viewer"} |
| personas | ["information-architect","ux-researcher","content-strategist"] |
Prepare the materials necessary for a card sorting study. This skill analyzes content within a directory to generate a list of "cards" representing topics or pages, which can be used in open or closed card sorting exercises to validate categorization.
PATH - The content source directory (e.g., "/help-center")DEPTH - (Optional) Depth of directory traversal to select cards (default: 2)SAMPLE_SIZE - (Optional) Maximum number of cards to generate (default: 50)OUTPUT_FORMAT - (Optional) Output format: "csv", "json", "print-ready" (default: "csv")Scan the PATH to identify potential content items.
Select a representative sample of content items.
SAMPLE_SIZE, use a sampling strategy (e.g., top traffic, strategic importance, or random distribution) to reduce the set.Prepare the data for each card.
Format the list into the requested OUTPUT_FORMAT.
A CARD_SORT_DATASET in the specified OUTPUT_FORMAT.
Example (CSV):
ID,Label,Description,Url
1,How to Reset Password,Instructions for account recovery,/auth/reset
2,Pricing Plans,Overview of subscription tiers,/pricing
3,API Keys,Managing developer credentials,/settings/api
Normalize named entities and concept variants into canonical forms using controlled vocabularies or standard taxonomies.
Analyze vocabulary overlap and identify named entities unique to domain/document corpora.
Transform lengthy documents into a semantic tree structure. It extracts sections, summaries, and hierarchies optimized for use with Large Language Models (LLMs).
Design formal ontologies using OWL/RDFS. Defines classes, properties, and relationships for complex semantic modeling.
Systematic cataloging of information assets. Creates comprehensive inventories or card sorting materials from content.
Generate JSON-LD structured data for web content. Maps content to Schema.org types to improve search engine understanding and rich result eligibility.