Does it link terms to the source code?

Yes, one of the core execution phases involves a code cross-reference check to match extracted terms with actual identifiers found in your repository.

How does the skill identify relevant domain terms?

It analyzes Slack threads and message history using the Claude Opus model to detect recurring business concepts, industry-specific terminology, and context-heavy definitions.

Where is the generated glossary stored?

By default, the skill writes the structured glossary to docs/domain/glossary.md, though the output location can be configured during the scope definition phase.

Can I provide my own reference documents?

Yes, you can use the --refs flag to include local Markdown files or Google Docs/Sheets URLs to help guide the term extraction process.

Ubiquitous Language Extractor

Name: Ubiquitous Language Extractor
Author: thkt

bythkt

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Herramientas de Colaboración

Automates the extraction of domain-specific terminology from Slack conversations to generate and maintain a structured project glossary.

The Ubiquitous Language Extractor bridges the gap between informal team communication and formal technical documentation by scanning Slack channels for key terms and domain concepts. It leverages Claude's reasoning capabilities to harvest conversations, identify ubiquitous language, cross-reference terms with existing code identifiers, and generate a structured Markdown glossary. This ensures that developers, product owners, and stakeholders remain aligned on business logic and terminology throughout the development lifecycle.

Características Principales

01Structured Markdown output with confidence markers and source citations

02Support for external reference materials including Markdown and Google Docs

03Automated domain term extraction using Claude Opus for high-accuracy analysis

04Cross-referencing of extracted terms with codebase identifiers

05Slack conversation harvesting via channel names or search keywords

068 GitHub stars

Casos de Uso

01Onboarding new developers by providing clear definitions of internal business logic

02Synchronizing terminology between Slack discussions and technical documentation

03Building a living glossary for Domain-Driven Design (DDD) projects

Características Principales

01Structured Markdown output with confidence markers and source citations

02Support for external reference materials including Markdown and Google Docs

03Automated domain term extraction using Claude Opus for high-accuracy analysis

04Cross-referencing of extracted terms with codebase identifiers

05Slack conversation harvesting via channel names or search keywords

068 GitHub stars

Casos de Uso

01Onboarding new developers by providing clear definitions of internal business logic

02Synchronizing terminology between Slack discussions and technical documentation

03Building a living glossary for Domain-Driven Design (DDD) projects