Terminal.skills
Skills/ubiquitous-language
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ubiquitous-language

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when: user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".

#ddd#domain-driven-design#glossary#ubiquitous-language#terminology
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed ubiquitous-language v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Review the open pull requests and summarize what needs attention"
  • "Generate a changelog from the last 20 commits on the main branch"

Information

Version
1.0.0
Author
terminal-skills
Category
Development
License
Apache-2.0

Documentation

Extract and formalize domain terminology from the current conversation into a consistent glossary, saved to a local file.

Process

  1. Scan the conversation for domain-relevant nouns, verbs, and concepts
  2. Identify problems:
    • Same word used for different concepts (ambiguity)
    • Different words used for the same concept (synonyms)
    • Vague or overloaded terms
  3. Propose a canonical glossary with opinionated term choices
  4. Write to UBIQUITOUS_LANGUAGE.md in the working directory using the format below
  5. Output a summary inline in the conversation

Output Format

Write a UBIQUITOUS_LANGUAGE.md file with this structure:

md
# Ubiquitous Language

## Order lifecycle

| Term | Definition | Aliases to avoid |
|------|-----------|-----------------| 
| **Order** | A customer's request to purchase one or more items | Purchase, transaction |
| **Invoice** | A request for payment sent to a customer after delivery | Bill, payment request |

## People

| Term | Definition | Aliases to avoid |
|------|-----------|-----------------| 
| **Customer** | A person or organization that places orders | Client, buyer, account |
| **User** | An authentication identity in the system | Login, account |

## Relationships

- An **Invoice** belongs to exactly one **Customer**
- An **Order** produces one or more **Invoices**

## Example dialogue

> **Dev:** "When a **Customer** places an **Order**, do we create the **Invoice** immediately?"
> **Domain expert:** "No — an **Invoice** is only generated once a **Fulfillment** is confirmed. A single **Order** can produce multiple **Invoices** if items ship in separate **Shipments**."
> **Dev:** "So if a **Shipment** is cancelled before dispatch, no **Invoice** exists for it?"
> **Domain expert:** "Exactly. The **Invoice** lifecycle is tied to the **Fulfillment**, not the **Order**."

## Flagged ambiguities

- "account" was used to mean both **Customer** and **User** — these are distinct concepts: a **Customer** places orders, while a **User** is an authentication identity that may or may not represent a **Customer**.

Rules

  • Be opinionated. When multiple words exist for the same concept, pick the best one and list the others as aliases to avoid.
  • Flag conflicts explicitly. If a term is used ambiguously in the conversation, call it out in the "Flagged ambiguities" section with a clear recommendation.
  • Keep definitions tight. One sentence max. Define what it IS, not what it does.
  • Show relationships. Use bold term names and express cardinality where obvious.
  • Only include domain terms. Skip generic programming concepts (array, function, endpoint) unless they have domain-specific meaning.
  • Group terms into multiple tables when natural clusters emerge (e.g. by subdomain, lifecycle, or actor). Each group gets its own heading and table. If all terms belong to a single cohesive domain, one table is fine — don't force groupings.
  • Write an example dialogue. A short conversation (3-5 exchanges) between a dev and a domain expert that demonstrates how the terms interact naturally. The dialogue should clarify boundaries between related concepts and show terms being used precisely.

Re-running

When invoked again in the same conversation:

  1. Read the existing UBIQUITOUS_LANGUAGE.md
  2. Incorporate any new terms from subsequent discussion
  3. Update definitions if understanding has evolved
  4. Mark changed entries with "(updated)" and new entries with "(new)"
  5. Re-flag any new ambiguities
  6. Rewrite the example dialogue to incorporate new terms

Post-output instruction

After writing the file, state:

I've written/updated UBIQUITOUS_LANGUAGE.md. From this point forward I will use these terms consistently. If I drift from this language or you notice a term that should be added, let me know.