ubiquitous-language skill

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

1. Propose a canonical glossary with opinionated term choices
2. Write to UBIQUITOUSLANGUAGE.md** in the working directory using the format below
3. 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**   | 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 shi

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:

1. Read the existing 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