ubiquitous-language

name	ubiquitous-language
description	Extract and save a DDD glossary, flag ambiguities, and propose canonical terms. Use when defining domain language or a shared vocabulary.

Ubiquitous Language

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 raw/UBIQUITOUS_LANGUAGE.md in the working directory using the format below. If content is split into sections, write each section to raw/UBIQUITOUS_LANGUAGE/{section-name}.md and document the folder structure in raw/UBIQUITOUS_LANGUAGE.md.
5. Output a summary inline in the conversation

Output Format

Write a raw/UBIQUITOUS_LANGUAGE.md file with this structure:

# 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. Pick the best term when multiple exist for the same concept. List others as aliases to avoid.
• Flag conflicts explicitly. Call out ambiguous usage in "Flagged ambiguities" with a recommendation.
• Keep definitions tight. One sentence max. Define what it IS, not what it does.
• Only include domain terms. Skip module/class names unless they have domain meaning.
• Show relationships. Use bold term names and express cardinality.
• Group terms into tables when natural clusters emerge (by subdomain, lifecycle, or actor). One table is fine if all terms are cohesive — don't force groupings.
• Write example dialogue. 3-5 exchanges between dev and domain expert demonstrating terms in action.

Example dialogue

Dev: "How do I test the sync service without Docker?"

Domain expert: "Provide the filesystem layer instead of the Docker layer. It implements the same Sandbox service interface but uses a local directory as the sandbox."

Dev: "So sync-in still creates a bundle and unpacks it?"

Domain expert: "Exactly. The sync service doesn't know which layer it's talking to. It calls exec and copyIn — the filesystem layer just runs those as local shell commands."

Re-running

When invoked again in the same conversation:

1. Read the existing raw/UBIQUITOUS_LANGUAGE.md
2. Incorporate any new terms from subsequent discussion
3. Update definitions if understanding has evolved
4. Re-flag any new ambiguities
5. Rewrite the example dialogue to incorporate new terms