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Visualize user paths and interactions. Creates flowcharts representing user journeys to complete specific tasks.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | user-flow-generate |
| description | Visualize user paths and interactions. Creates flowcharts representing user journeys to complete specific tasks. |
| required_roles | {"scribe":"roles/scribe.editor"} |
| personas | ["information-architect","ux-designer","product-manager"] |
Generate a visual representation of the path a user takes through the system to complete a specific task. This skill maps steps, decision points, and interactions to validate information architecture and user experience.
TASK - The specific user goal or task to map (e.g., "Reset Password", "Purchase Subscription")START_POINT - The entry point for the user (e.g., "Home Page", "Login Screen")END_POINT - The success state or final destination (e.g., "Dashboard", "Thank You Page")CONTENT_PATH - (Optional) The content directory to reference for available pages (e.g., "/docs")HAPPY_PATH_ONLY - (Optional) Boolean, whether to focus only on the ideal success path (default: false)OUTPUT_FORMAT - (Optional) Output format: "mermaid", "plantuml", "text-description" (default: "mermaid")Analyze the defined TASK to understand the user's intent and required steps.
Map the sequence of interactions from START_POINT to END_POINT.
CONTENT_PATH is provided, validate that steps correspond to existing pages or sections.If HAPPY_PATH_ONLY is false, identify potential alternative paths and error states.
Convert the mapped path into the requested OUTPUT_FORMAT.
For Mermaid:
graph TD or flowchart LR.A USER_FLOW_DIAGRAM in the specified OUTPUT_FORMAT.
Example (Mermaid):
graph TD
Start[Home Page] -->|Click Login| Login[Login Screen]
Login -->|Enter Credentials| Auth{Authenticated?}
Auth -->|Yes| Dashboard[Dashboard]
Auth -->|No| Error[Show Error]
Error --> Login
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.