ubiquitous-language
SkillDocs & knowledge--- name: ubiquitous-language description: Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUSLANGUAGE.md.
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About this capability
Zorai is a persistent, multi-agent, auditable, learning execution platform where the daemon owns work, memory, approvals, tools, and long-running goals.
What this skill tells your AI
The instructions your AI receives, as published by mkurman/zorai in skills/mattpocock/ubiquitous-language/SKILL.md and read by ahel’s review.
name: ubiquitous-language description: 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". disable-model-invocation: true
tags: [mattpocock, ubiquitous-language] -------- | ------------------------------------------------------- | --------------------- | | 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.
- **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>
## 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."
</example>
## 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
Signals
- GitHub stars
- 324
- Forks
- 26
- Last commit
- Sep 2026
Advanced
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ubiquitous-language-mkurman- Source
- github.com/mkurman/zorai