Ubiquitous Language

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 CONTEXT.md in the working directory using the format below
5. Output a summary inline in the conversation

Output Format

CONTEXT.md is shared with the grill-me skill, so it uses that skill's structure. Write it like this:

# {Context Name}

{One or two sentence description of what this context is and why it exists.}

## Language

**Order**:
A customer's request to purchase one or more items.
_Avoid_: Purchase, transaction

**Invoice**:
A request for payment sent to a customer after delivery.
_Avoid_: Bill, payment request

**Customer**:
A person or organization that places orders.
_Avoid_: Client, buyer, account

**User**:
An authentication identity in the system.
_Avoid_: 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.
• 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 under subheadings when natural clusters emerge (e.g. by subdomain, lifecycle, or actor). If all terms belong to a single cohesive domain, a flat list under ## Language is fine — don't force groupings.
• Keep CONTEXT.md a glossary and nothing else. No implementation details, no specs, no scratch notes.
• 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

CONTEXT.md may already exist — written by an earlier run, or by grill-me during a grilling session. Extend it in place; never overwrite what's already there.

When invoked again in the same conversation:

1. Read the existing CONTEXT.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