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".
Documentation
Ubiquitous Language
Extract and formalize domain terminology from the current conversation into a consistent glossary, saved to a local file.
Process
Scan the conversation for domain-relevant nouns, verbs, and concepts
Identify problems:
Same word used for different concepts (ambiguity)
Different words used for the same concept (synonyms)
Vague or overloaded terms
Propose a canonical glossary with opinionated term choices
Write to UBIQUITOUS_LANGUAGE.md in the working directory using the format below
Output a summary inline in the conversation
Output Format
Write a UBIQUITOUS_LANGUAGE.md file with this structure:
# Ubiquitous Language## Order lifecycle| Term | Definition | Aliases to avoid || ----------- | ------------------------------------------------------- | --------------------- || **Order**
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.
Only include terms relevant for domain experts. Skip the names of modules or classes unless they have meaning in the domain language.
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.
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:
Read the existing UBIQUITOUS_LANGUAGE.md
Incorporate any new terms from subsequent discussion
Update definitions if understanding has evolved
Re-flag any new ambiguities
Rewrite the example dialogue to incorporate new terms
| 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 |
| **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**.